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Vassy JL, Brunette CA, Yi T, Harrison A, Cardellino MP, Assimes TL, Christensen KD, Devineni P, Gaziano JM, Gong X, Hui Q, Knowles JW, Muralidhar S, Natarajan P, Pyarajan S, Sears MG, Shi Y, Sturm AC, Whitbourne SB, Sun YV, Danowski ME. Design and Pilot Results from Million Veteran Program Return Of Actionable Genetic Results (MVP-ROAR) Study. Am Heart J 2024:S0002-8703(24)00115-7. [PMID: 38762090 DOI: 10.1016/j.ahj.2024.04.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/30/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND As a mega-biobank linked to a national healthcare system, the Million Veteran Program (MVP) can directly improve the health care of participants. To determine the feasibility and outcomes of returning medically actionable genetic results to MVP participants, the program launched the MVP Return Of Actionable Results (MVP-ROAR) Study, with familial hypercholesterolemia (FH) as an exemplar actionable condition. METHODS The MVP-ROAR Study consists of a completed single-arm pilot phase and an ongoing randomized clinical trial (RCT), in which MVP participants are recontacted and invited to receive clinical confirmatory gene sequencing testing and a telegenetic counseling intervention. The primary outcome of the RCT is 6-month change in low-density lipoprotein cholesterol (LDL-C) between participants receiving results at baseline and those receiving results after 6 months. RESULTS The pilot developed processes to identify and recontact participants nationally with probable pathogenic variants in low-density lipoprotein receptor (LDLR) on the MVP genotype array, invite them to clinical confirmatory gene sequencing, and deliver a telegenetic counseling intervention. Among participants in the pilot phase, 8 (100%) had active statin prescriptions after 6 months. Results were shared with 16 first-degree family members. Six-month ΔLDL-C (low-density lipoprotein cholesterol) after the genetic counseling intervention was -37 mg/dL (95% CI: -12 to -61; p=0.03). The ongoing RCT will determine between-arm differences in this primary outcome. CONCLUSION While underscoring the importance of clinical confirmation of research results, the pilot phase of the MVP-ROAR Study marks a turning point in MVP and demonstrates the feasibility of returning genetic results to participants and their providers. The ongoing RCT will contribute to understanding how such a program might improve patient health care and outcomes.
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Affiliation(s)
- Jason L Vassy
- VA Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | | | - Thomas Yi
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | | | - Kurt D Christensen
- Harvard Medical School, Boston, MA, USA; PRecisiOn Medicine Translational Research Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute
| | | | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Xin Gong
- VA Boston Healthcare System, Boston, MA, USA
| | - Qin Hui
- Emory University Rollins School of Public Health, Atlanta, GA; VA Atlanta Healthcare System, Decatur, GA
| | | | - Sumitra Muralidhar
- Veterans Health Administration, Office of Research and Development, Washington, DC
| | - Pradeep Natarajan
- Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA
| | | | | | - Yunling Shi
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | - Yan V Sun
- Emory University Rollins School of Public Health, Atlanta, GA; VA Atlanta Healthcare System, Decatur, GA
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Gaziano TA, Gaziano JM. Can Cardiovascular Risk Assessment Be Improved in the 21st Century? JAMA 2024:2818629. [PMID: 38739381 DOI: 10.1001/jama.2024.7644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Thomas A Gaziano
- Division of Cardiology, Brigham and Women's Hospital, Boston, Massachusetts
| | - J Michael Gaziano
- Departments of Medicine, Veterans Affairs Boston Healthcare System and Brigham and Women's Hospital, Boston, Massachusetts
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Maripuri M, Dey A, Honerlaw J, Hong C, Ho YL, Tanukonda V, Chen AW, Panickan VA, Wang X, Zhang HG, Yang D, Samayamuthu MJ, Morris M, Visweswaran S, Beaulieu-Jones B, Ramoni R, Muralidhar S, Gaziano JM, Liao K, Xia Z, Brat GA, Cai T, Cho K. Characterization of Post-COVID-19 Definitions and Clinical Coding Practices: Longitudinal Study. Online J Public Health Inform 2024; 16:e53445. [PMID: 38700929 PMCID: PMC11073632 DOI: 10.2196/53445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/19/2024] [Accepted: 03/19/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Post-COVID-19 condition (colloquially known as "long COVID-19") characterized as postacute sequelae of SARS-CoV-2 has no universal clinical case definition. Recent efforts have focused on understanding long COVID-19 symptoms, and electronic health record (EHR) data provide a unique resource for understanding this condition. The introduction of the International Classification of Diseases, Tenth Revision (ICD-10) code U09.9 for "Post COVID-19 condition, unspecified" to identify patients with long COVID-19 has provided a method of evaluating this condition in EHRs; however, the accuracy of this code is unclear. OBJECTIVE This study aimed to characterize the utility and accuracy of the U09.9 code across 3 health care systems-the Veterans Health Administration, the Beth Israel Deaconess Medical Center, and the University of Pittsburgh Medical Center-against patients identified with long COVID-19 via a chart review by operationalizing the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) definitions. METHODS Patients who were COVID-19 positive with either a U07.1 ICD-10 code or positive polymerase chain reaction test within these health care systems were identified for chart review. Among this cohort, we sampled patients based on two approaches: (1) with a U09.9 code and (2) without a U09.9 code but with a new onset long COVID-19-related ICD-10 code, which allows us to assess the sensitivity of the U09.9 code. To operationalize the long COVID-19 definition based on health agency guidelines, symptoms were grouped into a "core" cluster of 11 commonly reported symptoms among patients with long COVID-19 and an extended cluster that captured all other symptoms by disease domain. Patients having ≥2 symptoms persisting for ≥60 days that were new onset after their COVID-19 infection, with ≥1 symptom in the core cluster, were labeled as having long COVID-19 per chart review. The code's performance was compared across 3 health care systems and across different time periods of the pandemic. RESULTS Overall, 900 patient charts were reviewed across 3 health care systems. The prevalence of long COVID-19 among the cohort with the U09.9 ICD-10 code based on the operationalized WHO definition was between 23.2% and 62.4% across these health care systems. We also evaluated a less stringent version of the WHO definition and the CDC definition and observed an increase in the prevalence of long COVID-19 at all 3 health care systems. CONCLUSIONS This is one of the first studies to evaluate the U09.9 code against a clinical case definition for long COVID-19, as well as the first to apply this definition to EHR data using a chart review approach on a nationwide cohort across multiple health care systems. This chart review approach can be implemented at other EHR systems to further evaluate the utility and performance of the U09.9 code.
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Affiliation(s)
- Monika Maripuri
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Andrew Dey
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | | | - Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Yuk-Lam Ho
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Vidisha Tanukonda
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Alicia W Chen
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | | | - Xuan Wang
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States
| | - Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Doris Yang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | | | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Rachel Ramoni
- Office of Research and Development, US Department of Veterans Affairs, Washington, DC, United States
| | - Sumitra Muralidhar
- Office of Research and Development, US Department of Veterans Affairs, Washington, DC, United States
| | - J Michael Gaziano
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Division of Aging, Department of Medicine, Mass General Brigham, Harvard Medical School, Boston, MA, United States
| | - Katherine Liao
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, United States
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Division of Aging, Department of Medicine, Mass General Brigham, Harvard Medical School, Boston, MA, United States
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Belloy ME, Guen YL, Stewart I, Herz J, Sherva R, Zhang R, Merritt V, Panizzon MS, Hauger RL, Gaziano JM, Logue M, Napolioni V, Greicius MD. The Role of X Chromosome in Alzheimer's Disease Genetics. medRxiv 2024:2024.04.22.24306094. [PMID: 38712163 PMCID: PMC11071554 DOI: 10.1101/2024.04.22.24306094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Importance The X chromosome has remained enigmatic in Alzheimer's disease (AD), yet it makes up 5% of the genome and carries a high proportion of genes expressed in the brain, making it particularly appealing as a potential source of unexplored genetic variation in AD. Objectives Perform the first large-scale X chromosome-wide association study (XWAS) of AD. Primary analyses are non-stratified, while secondary analyses evaluate sex-stratified effects. Design Meta-analysis of genetic association studies in case-control, family-based, population-based, and longitudinal AD-related cohorts from the US Alzheimer's Disease Genetics Consortium (ADGC) and Alzheimer's Disease Sequencing Project (ADSP), the UK Biobank (UKB), the Finnish health registry (FinnGen), and the US Million Veterans Program (MVP). Risk for AD evaluated through case-control logistic regression analyses. Data were analyzed between January 2023 and March 2024. Setting Genetic data available from high-density single-nucleotide polymorphism (SNP) microarrays and whole-genome sequencing (WGS). Summary statistics for multi-tissue expression and protein quantitative trait loci (QTL) available from published studies, enabling follow-up genetic colocalization analyses. Participants 1,629,863 eligible participants were selected from referred and volunteer samples, of which 477,596 were excluded for analysis exclusion criteria. Number of participants who declined to participate in original studies was not available. Main Outcome and Measures Risk for AD (odds ratio; OR) with 95% confidence intervals (CI). Associations were considered at X-chromosome-wide (P-value<1e-5) and genome-wide (P-value<5e-8) significance. Results Analyses included 1,152,284 non-Hispanic White European ancestry subjects (57.3% females), including 138,558 cases. 6 independent genetic loci passed X-chromosome-wide significance, with 4 showing support for causal links between the genetic signal for AD and expression of nearby genes in brain and non-brain tissues. One of these 4 loci passed conservative genome-wide significance, with its lead variant centered on an intron of SLC9A7 (OR=1.054, 95%-CI=[1.035, 1.075]) and colocalization analyses prioritizing both the SLC9A7 and nearby CHST7 genes. Conclusion and Relevance We performed the first large-scale XWAS of AD and identified the novel SLC9A7 locus. SLC9A7 regulates pH homeostasis in Golgi secretory compartments and is anticipated to have downstream effects on amyloid beta accumulation. Overall, this study significantly advances our knowledge of AD genetics and may provide novel biological drug targets.
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Affiliation(s)
- Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St.Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St.Louis, MO, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Ilaria Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Joachim Herz
- Center for Translational Neurodegeneration Research, Department of Molecular Genetics University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA
| | - Richard Sherva
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Rui Zhang
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
| | - Victoria Merritt
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - Richard L. Hauger
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Logue
- Biomedical Genetics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
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5
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Honerlaw J, Ho YL, Fontin F, Murray M, Galloway A, Heise D, Connatser K, Davies L, Gosian J, Maripuri M, Russo J, Sangar R, Tanukonda V, Zielinski E, Dubreuil M, Zimolzak AJ, Panickan VA, Cheng SC, Whitbourne SB, Gagnon DR, Cai T, Liao KP, Ramoni RB, Gaziano JM, Muralidhar S, Cho K. Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users. J Am Med Inform Assoc 2024; 31:1126-1134. [PMID: 38481028 PMCID: PMC11031216 DOI: 10.1093/jamia/ocae042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 02/21/2024] [Indexed: 04/21/2024] Open
Abstract
OBJECTIVE Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. We describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research. MATERIALS AND METHODS The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows. Phenomics experts were engaged in the development and testing of the site. RESULTS The knowledgebase stores phenotype metadata using the CIPHER standard, and definitions are accessible through complex searching. Phenotypes are contributed to the knowledgebase via webform, allowing metadata validation. Data visualization tools linking to the knowledgebase enhance user interaction with content and accelerate phenotype development. DISCUSSION The CIPHER knowledgebase was developed in the largest healthcare system in the United States and piloted with external partners. The design of the CIPHER website supports a variety of front-end tools and features to facilitate phenotype development and reuse. Health data users are encouraged to contribute their algorithms to the knowledgebase for wider dissemination to the research community, and to use the platform as a springboard for phenotyping. CONCLUSION CIPHER is a public resource for all health data users available at https://phenomics.va.ornl.gov/ which facilitates phenotype reuse, development, and dissemination of phenotyping knowledge.
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Affiliation(s)
- Jacqueline Honerlaw
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Yuk-Lam Ho
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Francesca Fontin
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Michael Murray
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Ashley Galloway
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - David Heise
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN 37830, United States
| | - Keith Connatser
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN 37830, United States
| | - Laura Davies
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN 37830, United States
| | - Jeffrey Gosian
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Monika Maripuri
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - John Russo
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Computer Science, Landmark College, Putney, VT 05346, United States
| | - Rahul Sangar
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Vidisha Tanukonda
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Atlanta Healthcare System, Decatur, GA 30033, United States
| | - Edward Zielinski
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
| | - Maureen Dubreuil
- VA Boston Healthcare System, Boston, MA 02111, United States
- Section of Rheumatology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, United States
| | - Andrew J Zimolzak
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, United States
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, United States
| | - Vidul A Panickan
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States
| | - Su-Chun Cheng
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States
| | - Stacey B Whitbourne
- VA Boston Healthcare System, Boston, MA 02111, United States
- Million Veteran Program (MVP) Coordinating Center, VA Boston, Boston, MA 02111, United States
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Department of Medicine, Harvard Medical School, Boston, MA 02115, United States
| | - David R Gagnon
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, United States
| | - Tianxi Cai
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, United States
| | - Katherine P Liao
- VA Boston Healthcare System, Boston, MA 02111, United States
- Department of Medicine, Harvard Medical School, Boston, MA 02115, United States
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States
| | - Rachel B Ramoni
- Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA 02111, United States
- Million Veteran Program (MVP) Coordinating Center, VA Boston, Boston, MA 02111, United States
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Department of Medicine, Harvard Medical School, Boston, MA 02115, United States
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
| | - Kelly Cho
- Centralized Interactive Phenomics Resource (CIPHER), Office of Research and Development, Veterans Health Administration, Washington, DC 20002, United States
- VA Boston Healthcare System, Boston, MA 02111, United States
- Million Veteran Program (MVP) Coordinating Center, VA Boston, Boston, MA 02111, United States
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States
- Department of Medicine, Harvard Medical School, Boston, MA 02115, United States
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6
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Gorman BR, Francis M, Nealon CL, Halladay CW, Duro N, Markianos K, Genovese G, Hysi PG, Choquet H, Afshari NA, Li YJ, Gaziano JM, Hung AM, Wu WC, Greenberg PB, Pyarajan S, Lass JH, Peachey NS, Iyengar SK. A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation. Commun Biol 2024; 7:418. [PMID: 38582945 PMCID: PMC10998918 DOI: 10.1038/s42003-024-06046-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 03/13/2024] [Indexed: 04/08/2024] Open
Abstract
Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.
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Affiliation(s)
- Bryan R Gorman
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Michael Francis
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Cari L Nealon
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA
| | - Christopher W Halladay
- Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, RI, USA
| | - Nalvi Duro
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Kyriacos Markianos
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Pirro G Hysi
- Department of Ophthalmology, King's College London, London, UK
- Department of Twins Research and Genetic Epidemiology, King's College London, London, UK
- UCL Great Ormond Street Hospital Institute of Child Health, King's College London, London, UK
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California (KPNC), Oakland, CA, USA
| | - Natalie A Afshari
- Shiley Eye Institute, Viterbi Family Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA
| | - Yi-Ju Li
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Center for Kidney Disease, Vanderbilt University Medical Center, Nashville, TN, USA
- VA Tennessee Valley Healthcare System, Nashville, TN, USA
| | - Wen-Chih Wu
- Cardiology Section, Medical Service, Providence VA Medical Center, Providence, RI, USA
| | - Paul B Greenberg
- Ophthalmology Section, Providence VA Medical Center, Providence, RI, USA
- Division of Ophthalmology, Alpert Medical School, Brown University, Providence, RI, USA
| | - Saiju Pyarajan
- Center for Data and Computational Sciences (C-DACS), VA Boston Healthcare System, Boston, MA, USA
| | - Jonathan H Lass
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Neal S Peachey
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
- Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
- Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
| | - Sudha K Iyengar
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, OH, USA.
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
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7
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Wang X, Liu M, Nogues IE, Chen T, Xiong X, Bonzel CL, Zhang H, Hong C, Xia Y, Dahal K, Costa L, Cui J, Gaziano JM, Kim SC, Ho YL, Cho K, Cai T, Liao KP. Heterogeneous associations between interleukin-6 receptor variants and phenotypes across ancestries and implications for therapy. Sci Rep 2024; 14:8021. [PMID: 38580710 PMCID: PMC10997791 DOI: 10.1038/s41598-024-54063-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 02/08/2024] [Indexed: 04/07/2024] Open
Abstract
The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype-phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10-3), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10-131). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype-phenotype screens in diverse populations.
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Affiliation(s)
- Xuan Wang
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Molei Liu
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Tony Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Xin Xiong
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Clara-Lea Bonzel
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Harrison Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Chuan Hong
- Department of Biostatistics, Duke University, Durham, NC, USA
| | - Yin Xia
- Department of Statistics and Data Science, Fudan University, Shanghai, China
| | - Kumar Dahal
- Department of Biostatistics, Duke University, Durham, NC, USA
| | - Lauren Costa
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
| | - Jing Cui
- Department of Biostatistics, Duke University, Durham, NC, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Seoyoung C Kim
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Tianxi Cai
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
| | - Katherine P Liao
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA.
- Rheumatology Section, VA Boston Healthcare System, Boston, USA.
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8
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Brunette CA, Yi T, Danowski ME, Cardellino M, Harrison A, Assimes TL, Knowles JW, Christensen KD, Sturm AC, Sun YV, Hui Q, Pyarajan S, Shi Y, Whitbourne SB, Gaziano JM, Muralidhar S, Vassy JL. Development and utility of a clinical research informatics application for participant recruitment and workflow management for a return of results pilot trial in familial hypercholesterolemia in the Million Veteran Program. JAMIA Open 2024; 7:ooae020. [PMID: 38464744 PMCID: PMC10923213 DOI: 10.1093/jamiaopen/ooae020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/26/2023] [Accepted: 02/14/2024] [Indexed: 03/12/2024] Open
Abstract
Objective The development of clinical research informatics tools and workflow processes associated with re-engaging biobank participants has become necessary as genomic repositories increasingly consider the return of actionable research results. Materials and Methods Here we describe the development and utility of an informatics application for participant recruitment and enrollment management for the Veterans Affairs Million Veteran Program Return Of Actionable Results Study, a randomized controlled pilot trial returning individual genetic results associated with familial hypercholesterolemia. Results The application is developed in Python-Flask and was placed into production in November 2021. The application includes modules for chart review, medication reconciliation, participant contact and biospecimen logging, survey recording, randomization, and documentation of genetic counseling and result disclosure. Three primary users, a genetic counselor and two research coordinators, and 326 Veteran participants have been integrated into the system as of February 23, 2023. The application has successfully handled 3367 task requests involving greater than 95 000 structured data points. Specifically, application users have recorded 326 chart reviews, 867 recruitment telephone calls, 158 telephone-based surveys, and 61 return of results genetic counseling sessions, among other available study tasks. Conclusion The development of usable, customizable, and secure informatics tools will become increasingly important as large genomic repositories begin to return research results at scale. Our work provides a proof-of-concept for developing and using such tools to aid in managing the return of results process within a national biobank.
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Affiliation(s)
- Charles A Brunette
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Thomas Yi
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Morgan E Danowski
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Mark Cardellino
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Alicia Harrison
- Genetic Counseling Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, United States
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Palo Alto, CA, United States
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Joshua W Knowles
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Palo Alto, CA, United States
- Family Heart Foundation, Pasadena, CA, United States
| | - Kurt D Christensen
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
- Department of Population Medicine, Harvard Medical School, Boston, MA, United States
| | | | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, United States
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Qin Hui
- Atlanta VA Health Care System, Decatur, GA, United States
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Saiju Pyarajan
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
| | - Yunling Shi
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Stacey B Whitbourne
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - J Michael Gaziano
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC, United States
| | - Jason L Vassy
- Veterans Affairs Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Harvard Medical School, Boston, MA, United States
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA, United States
- Population Precision Health, Ariadne Labs, Boston, MA, United States
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9
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O'Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. Mol Psychiatry 2024:10.1038/s41380-024-02472-1. [PMID: 38491344 DOI: 10.1038/s41380-024-02472-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 01/22/2024] [Accepted: 01/31/2024] [Indexed: 03/18/2024]
Abstract
Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed health problems, prior pharmacological treatments, and polygenic scores (PGS) has potential to inform risk stratification. We examined self-reported SB and ideation using the Columbia Suicide Severity Rating Scale (C-SSRS) among 3,942 SCZ and 5,414 BPI patients receiving care within the Veterans Health Administration (VHA). These cross-sectional data were integrated with electronic health records (EHRs), and compared across lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. PGS were constructed using available genomic data for related traits. Genome-wide association studies were performed to identify and prioritize specific loci. Only 20% of the veterans who reported SB had a corroborating ICD-9/10 EHR code. Among those without prior SB, more than 20% reported new-onset SB at follow-up. SB were associated with a range of additional clinical diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking initiation, suicide attempt, and major depressive disorder were associated with SB. The GWAS for SB yielded no significant loci. Among individuals with a diagnosed mental illness, self-reported SB were strongly associated with clinical variables across several EHR domains. Analyses point to sequelae of substance-related and psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in health records, underscoring the value of regular screening with direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY, US.
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US.
| | - Peter B Barr
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - David P Graham
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Bryan R Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Roseann E Peterson
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY, US
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD, USA
| | | | - David A Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Anna V Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Epidemiology, Human Genetics and Environmental Science, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY, USA
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Boston University School of Medicine, Boston, MA, USA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
| | | | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA, USA
- Harvard University, Boston, MA, USA
| | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - John Concato
- Yale University School of Medicine, New Haven, CT, USA
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, USA
| | - Nathan A Kimbrel
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Jean C Beckham
- Durham VA Health Care System, Durham, NC, USA
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Alan C Swann
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Thomas R Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ayman H Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY, US
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ, USA
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Philip D Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL, USA
- University of Miami School of Medicine, Miami, FL, USA
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10
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Almuwaqqat Z, Hui Q, Liu C, Zhou JJ, Voight BF, Ho YL, Posner DC, Vassy JL, Gaziano JM, Cho K, Wilson PWF, Sun YV. Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes. JAMA Netw Open 2024; 7:e243062. [PMID: 38512255 PMCID: PMC10958234 DOI: 10.1001/jamanetworkopen.2024.3062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/23/2024] [Indexed: 03/22/2024] Open
Abstract
Importance Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes. Objective To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts. Design, Setting, and Participants This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023. Exposure BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline. Main Outcomes and Measures The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI. Results Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11). Conclusions and Relevance This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.
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Affiliation(s)
- Zakaria Almuwaqqat
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Qin Hui
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia
| | - Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia
| | - Jin J. Zhou
- Department of Medicine and Biostatistics, University of California, Los Angeles
- Veterans Affairs Phoenix Healthcare System, Phoenix, Arizona
| | - Benjamin F. Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Department of Systems Pharmacology and Translational Therapeutics, Department of Genetics, University of Pennsylvania, Philadelphia\
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
| | - Daniel C. Posner
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
| | - Jason L. Vassy
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Peter W. F. Wilson
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Yan V. Sun
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, Georgia
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11
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Wang DD, Li Y, Nguyen XM, Ho YL, Hu FB, Willett WC, Wilson PW, Cho K, Gaziano JM, Djoussé L. Red Meat Intake and the Risk of Cardiovascular Diseases: A Prospective Cohort Study in the Million Veteran Program. J Nutr 2024; 154:886-895. [PMID: 38163586 DOI: 10.1016/j.tjnut.2023.12.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/22/2023] [Accepted: 12/28/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND Red meat consumption was associated with an increased risk of cardiovascular disease (CVD) in prospective cohort studies and a profile of biomarkers favoring high CVD risk in short-term controlled trials. However, several recent systematic reviews and meta-analyses concluded with no or weak evidence for limiting red meat intake. OBJECTIVES To prospectively examine the associations between red meat intake and incident CVD in an ongoing cohort study with diverse socioeconomic and racial or ethnic backgrounds. METHODS Our study included 148,506 participants [17,804 female (12.0%)] who were free of cancer, diabetes, and CVD at baseline from the Million Veteran Program. A food frequency questionnaire measured red meat intakes at baseline. Nonfatal myocardial infarction and acute ischemic stroke were identified through a high-throughput phenotyping algorithm, and fatal CVD events were identified by searching the National Death Index. RESULTS Comparing the extreme categories of intake, the multivariate-adjusted relative risks of CVD was 1.18 (95% CI: 1.01, 1.38; P-trend < 0.0001) for total red meat, 1.14 (95% CI: 0.96, 1.36; P-trend = 0.01) for unprocessed red meat, and 1.29 (95% CI: 1.04, 1.60; P-trend = 0.003) for processed red meat. We observed a more pronounced positive association between red meat intake and CVD in African American participants than in White participants (P-interaction = 0.01). Replacing 0.5 servings/d of red meat with 0.5 servings/d of nuts, whole grains, and skimmed milk was associated with 14% (RR: 0.86; 95% CI: 0.83, 0.90), 7% (RR: 0.93; 95% CI: 0.89, 0.96), and 4% (RR: 0.96; 95% CI: 0.94, 0.99) lower risks of CVD, respectively. CONCLUSIONS Red meat consumption is associated with an increased risk of CVD. Our findings support lowering red meat intake and replacing red meat with plant-based protein sources or low-fat dairy foods as a key dietary recommendation for the prevention of CVD.
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Affiliation(s)
- Dong D Wang
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; The Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Broad Institute of MIT and Harvard, Cambridge, MA, United States.
| | - Yanping Li
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States
| | - Xuan-Mai Nguyen
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States
| | - Frank B Hu
- The Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Walter C Willett
- The Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Peter Wf Wilson
- Atlanta VA Medical Center, Atlanta, GA, United States; Emory Clinical Cardiovascular Research Institute, Atlanta, GA, United States
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Luc Djoussé
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States
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12
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Orkaby AR, Lu B, Ho YL, Treu T, Galloway A, Wilson PW, Cho K, Gaziano JM, Alexander KP, Gagnon DR, Djousse L, Forman DE, Driver JA. New statin use, mortality, and first cardiovascular events in older US Veterans by frailty status. J Am Geriatr Soc 2024; 72:410-422. [PMID: 38055194 PMCID: PMC10922314 DOI: 10.1111/jgs.18700] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/27/2023] [Accepted: 10/28/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Statins are part of long-term medical regimens for many older adults. Whether frailty modifies the protective relationship between statins, mortality, and major adverse cardiovascular events (MACE) is unknown. METHODS This was a retrospective study of US Veterans ≥65, without CVD or prior statin use seen in 2002-2012, followed through 2017. A 31-item frailty index was used. The co-primary endpoint was all-cause mortality or MACE (MI, stroke/TIA, revascularization, or cardiovascular death). Cox proportional hazards models were developed to evaluate the association of statin use with outcomes; propensity score overlap weighting accounted for confounding by indication. RESULTS We identified 710,313 Veterans (mean age (SD) 75.3(6.5), 98% male, 89% white); 86,327 (12.1%) were frail. Over mean follow-up of 8 (5) years, there were 48.6 and 72.6 deaths per 1000 person-years (PY) among non-frail statin-users vs nonusers (weighted Incidence Rate Difference (wIRD)/1000 person years (PY), -24.0[95% CI, -24.5 to -23.6]), and 90.4 and 130.4 deaths per 1000PY among frail statin-users vs nonusers (wIRD/1000PY, -40.0[95% CI, -41.8 to -38.2]). There were 51.7 and 60.8 MACE per 1000PY among non-frail statin-users vs nonusers (wIRD/1000PY, -9.1[95% CI, -9.7 to -8.5]), and 88.2 and 102.0 MACE per 1000PY among frail statin-users vs nonusers (wIRD/1000PY, -13.8[95% CI, -16.2 to -11.4]). There were no significant interactions by frailty for statin users vs non-users by either mortality or MACE outcomes, p-interaction 0.770 and 0.319, respectively. Statin use was associated with lower risk of all-cause mortality (HR, 0.61 (0.60-0.61)) and MACE (HR 0.86 (0.85-0.87)). CONCLUSIONS New statin use is associated with a lower risk of mortality and MACE, independent of frailty. These findings should be confirmed in a randomized clinical trial.
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Affiliation(s)
- Ariela R. Orkaby
- New England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, 150 S Huntington St, Boston, MA 02130
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
| | - Bing Lu
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
- Department of Public Health, University of Connecticut Health Center, 263 Farmington Ave, Farmington, CT 06030
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
| | - Timothy Treu
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
| | - Ashley Galloway
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
| | - Peter W.F. Wilson
- Atlanta VA Healthcare System, 1670 Clairmont Road, Decatur, GA 30033
- Emory Clinical Cardiology Research Institute, 1462 Clifton Rd NE, 5 Floor, Atlanta, GA 30322
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
- Department of Public Health, University of Connecticut Health Center, 263 Farmington Ave, Farmington, CT 06030
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
- Department of Public Health, University of Connecticut Health Center, 263 Farmington Ave, Farmington, CT 06030
| | - Karen P. Alexander
- Division of Cardiology, Duke University Medical Center, 10 Duke Medicine Cir, Durham, NC 27710
- Duke Clinical Research Institute, Duke University, 200 Morris Street, Durham, NC 27701
| | - David R. Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
| | - Luc Djousse
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
| | - Daniel E. Forman
- Section of Geriatric Cardiology, University of Pittsburgh Medical Center, 3471 Fifth Ave, Ste 500 Pittsburgh, PA 15213
- Geriatric Research, Education, and Clinical Center, VA Pittsburgh Healthcare System, 4100 Allequippa St, Pittsburgh, PA 15240
| | - Jane A. Driver
- New England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, 150 S Huntington St, Boston, MA 02130
- Division of Aging, Brigham & Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115
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13
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Meng X, Navoly G, Giannakopoulou O, Levey DF, Koller D, Pathak GA, Koen N, Lin K, Adams MJ, Rentería ME, Feng Y, Gaziano JM, Stein DJ, Zar HJ, Campbell ML, van Heel DA, Trivedi B, Finer S, McQuillin A, Bass N, Chundru VK, Martin HC, Huang QQ, Valkovskaya M, Chu CY, Kanjira S, Kuo PH, Chen HC, Tsai SJ, Liu YL, Kendler KS, Peterson RE, Cai N, Fang Y, Sen S, Scott LJ, Burmeister M, Loos RJF, Preuss MH, Actkins KV, Davis LK, Uddin M, Wani AH, Wildman DE, Aiello AE, Ursano RJ, Kessler RC, Kanai M, Okada Y, Sakaue S, Rabinowitz JA, Maher BS, Uhl G, Eaton W, Cruz-Fuentes CS, Martinez-Levy GA, Campos AI, Millwood IY, Chen Z, Li L, Wassertheil-Smoller S, Jiang Y, Tian C, Martin NG, Mitchell BL, Byrne EM, Awasthi S, Coleman JRI, Ripke S, Sofer T, Walters RG, McIntosh AM, Polimanti R, Dunn EC, Stein MB, Gelernter J, Lewis CM, Kuchenbaecker K. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference. Nat Genet 2024; 56:222-233. [PMID: 38177345 PMCID: PMC10864182 DOI: 10.1038/s41588-023-01596-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/26/2023] [Indexed: 01/06/2024]
Abstract
Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.
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Affiliation(s)
| | | | | | - Daniel F Levey
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Dora Koller
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Gita A Pathak
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Nastassja Koen
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - J Michael Gaziano
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Heather J Zar
- SAMRC Unit on Child and Adolescent Health, Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa
| | - Megan L Campbell
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | | | - Bhavi Trivedi
- Blizard Institute, Queen Mary University of London, London, UK
| | - Sarah Finer
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | | | - Nick Bass
- Division of Psychiatry, UCL, London, UK
| | | | | | | | | | | | - Susan Kanjira
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Po-Hsiu Kuo
- Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hsi-Chung Chen
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science and Division of Psychiatry, National Yang-Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County, Taiwan
| | | | - Roseann E Peterson
- Department of Psychiatry, VCU, Richmond, VA, USA
- Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany
- Computational Health Centre, Helmholtz Munich, Neuherberg, Germany
- Department of Medicine, Technical University of Munich, Munich, Germany
| | - Yu Fang
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Srijan Sen
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Margit Burmeister
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ky'Era V Actkins
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Monica Uddin
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Agaz H Wani
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Allison E Aiello
- Robert N. Butler Columbia Aging Center, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Robert J Ursano
- Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Masahiro Kanai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - George Uhl
- Neurology and Pharmacology, University of Maryland, Maryland VA Healthcare System, Baltimore, MD, USA
| | - William Eaton
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Carlos S Cruz-Fuentes
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Gabriela A Martinez-Levy
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Adrian I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | | | - Yunxuan Jiang
- Department of Biostatistics, Emory University, Atlanta, GA, USA
- 23andMe, Inc., Mountain View, CA, USA
| | - Chao Tian
- 23andMe, Inc., Mountain View, CA, USA
| | - Nicholas G Martin
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Swapnil Awasthi
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Jonathan R I Coleman
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stephan Ripke
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Cambridge, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Renato Polimanti
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Erin C Dunn
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Murray B Stein
- Department of Psychiatry, UC San Diego School of Medicine, La Jolla, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Cathryn M Lewis
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
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14
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Imran TF, Ataklte F, Khalid M, Lopez D, Mohebali D, Bello NA, Gaziano JM, Djousse L, Arany Z, Sabe MA, French K, Poppas A, Wu W, Choudhary G. Clinical predictors of right ventricular dysfunction and association with adverse outcomes in peripartum cardiomyopathy. ESC Heart Fail 2024; 11:422-432. [PMID: 38030384 PMCID: PMC10804155 DOI: 10.1002/ehf2.14583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 10/05/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
AIMS We sought to identify factors associated with right ventricular (RV) dysfunction and elevated pulmonary artery systolic pressure (PASP) and association with adverse outcomes in peripartum cardiomyopathy (PPCM). METHODS AND RESULTS We conducted a multi-centre cohort study to identify subjects with PPCM with the following criteria: left ventricular ejection fraction (LVEF) < 40%, development of heart failure within the last month of pregnancy or 5 months of delivery, and no other identifiable cause of heart failure with reduced ejection fraction. Outcomes included a composite of (i) major adverse events (need for extracorporeal membrane oxygenation, ventricular assist device, orthotopic heart transplantation, or death) or (ii) recurrent heart failure hospitalization. RV function was obtained from echocardiogram reports. In total, 229 women (1993-2017) met criteria for PPCM. Mean age was 32.4 ± 6.8 years, 28% were of African descent, 50 (22%) had RV dysfunction, and 38 (17%) had PASP ≥ 30 mmHg. After a median follow-up of 3.4 years (interquartile range 1.0-8.8), 58 (25%) experienced the composite outcome of adverse events. African descent, family history of cardiomyopathy, LVEF, and PASP were significant predictors of RV dysfunction. Using Cox proportional hazards models, we found that women with RV dysfunction were three times more likely to experience the adverse composite outcome: hazard ratio 3.21 (95% confidence interval: 1.11-9.28), P = 0.03, in a multivariable model adjusting for age, race, body mass index, preeclampsia, hypertension, diabetes, kidney disease, and LVEF. Women with PASP ≥ 30 mmHg had a lower probability of survival free from adverse events (log-rank P = 0.04). CONCLUSIONS African descent and family history of cardiomyopathy were significant predictors of RV dysfunction. RV dysfunction and elevated PASP were significantly associated with a composite of major adverse cardiac events. This at-risk group may prompt closer monitoring or early referral for advanced therapies.
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Affiliation(s)
- Tasnim F. Imran
- Providence VA Medical CenterWarren Alpert Medical School of Brown University830 Chalkstone AveProvidenceRI02809USA
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Feven Ataklte
- Providence VA Medical CenterWarren Alpert Medical School of Brown University830 Chalkstone AveProvidenceRI02809USA
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Mahnoor Khalid
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Diana Lopez
- Brigham and Women's Hospital and the VA Boston Healthcare SystemHarvard Medical SchoolBostonMAUSA
| | | | - Natalie A. Bello
- Smidt Heart InstituteCedars Sinai Medical CenterLos AngelesCAUSA
| | - J. Michael Gaziano
- Brigham and Women's Hospital and the VA Boston Healthcare SystemHarvard Medical SchoolBostonMAUSA
| | - Luc Djousse
- Brigham and Women's Hospital and the VA Boston Healthcare SystemHarvard Medical SchoolBostonMAUSA
| | - Zolt Arany
- Cardiovascular Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Marwa A. Sabe
- Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonMAUSA
| | - Katharine French
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Athena Poppas
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Wen‐Chih Wu
- Providence VA Medical CenterWarren Alpert Medical School of Brown University830 Chalkstone AveProvidenceRI02809USA
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
| | - Gaurav Choudhary
- Providence VA Medical CenterWarren Alpert Medical School of Brown University830 Chalkstone AveProvidenceRI02809USA
- Lifespan Cardiovascular InstituteWarren Alpert Medical School of Brown UniversityProvidenceRIUSA
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15
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Scholz M, Horn K, Pott J, Wuttke M, Kühnapfel A, Nasr MK, Kirsten H, Li Y, Hoppmann A, Gorski M, Ghasemi S, Li M, Tin A, Chai JF, Cocca M, Wang J, Nutile T, Akiyama M, Åsvold BO, Bansal N, Biggs ML, Boutin T, Brenner H, Brumpton B, Burkhardt R, Cai J, Campbell A, Campbell H, Chalmers J, Chasman DI, Chee ML, Chee ML, Chen X, Cheng CY, Cifkova R, Daviglus M, Delgado G, Dittrich K, Edwards TL, Endlich K, Michael Gaziano J, Giri A, Giulianini F, Gordon SD, Gudbjartsson DF, Hallan S, Hamet P, Hartman CA, Hayward C, Heid IM, Hellwege JN, Holleczek B, Holm H, Hutri-Kähönen N, Hveem K, Isermann B, Jonas JB, Joshi PK, Kamatani Y, Kanai M, Kastarinen M, Khor CC, Kiess W, Kleber ME, Körner A, Kovacs P, Krajcoviechova A, Kramer H, Krämer BK, Kuokkanen M, Kähönen M, Lange LA, Lash JP, Lehtimäki T, Li H, Lin BM, Liu J, Loeffler M, Lyytikäinen LP, Magnusson PKE, Martin NG, Matsuda K, Milaneschi Y, Mishra PP, Mononen N, Montgomery GW, Mook-Kanamori DO, Mychaleckyj JC, März W, Nauck M, Nikus K, Nolte IM, Noordam R, Okada Y, Olafsson I, Oldehinkel AJ, Penninx BWJH, Perola M, Pirastu N, Polasek O, Porteous DJ, Poulain T, Psaty BM, Rabelink TJ, Raffield LM, Raitakari OT, Rasheed H, Reilly DF, Rice KM, Richmond A, Ridker PM, Rotter JI, Rudan I, Sabanayagam C, Salomaa V, Schneiderman N, Schöttker B, Sims M, Snieder H, Stark KJ, Stefansson K, Stocker H, Stumvoll M, Sulem P, Sveinbjornsson G, Svensson PO, Tai ES, Taylor KD, Tayo BO, Teren A, Tham YC, Thiery J, Thio CHL, Thomas LF, Tremblay J, Tönjes A, van der Most PJ, Vitart V, Völker U, Wang YX, Wang C, Wei WB, Whitfield JB, Wild SH, Wilson JF, Winkler TW, Wong TY, Woodward M, Sim X, Chu AY, Feitosa MF, Thorsteinsdottir U, Hung AM, Teumer A, Franceschini N, Parsa A, Köttgen A, Schlosser P, Pattaro C. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements. Nat Commun 2024; 15:586. [PMID: 38233393 PMCID: PMC10794254 DOI: 10.1038/s41467-024-44709-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 12/30/2023] [Indexed: 01/19/2024] Open
Abstract
X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.
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Affiliation(s)
- Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
| | - Katrin Horn
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Janne Pott
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Andreas Kühnapfel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - M Kamal Nasr
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Anselm Hoppmann
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
- Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
| | - Sahar Ghasemi
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Man Li
- Division of Nephrology and Hypertension, Department of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Massimiliano Cocca
- Institute for Maternal and Child Health, IRCCS 'Burlo Garofolo', Trieste, Italy
| | - Judy Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Teresa Nutile
- Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso'-CNR, Naples, Italy
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nisha Bansal
- Division of Nephrology, University of Washington, Seattle, WA, USA
- Kidney Research Institute, University of Washington, Seattle, WA, USA
| | - Mary L Biggs
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Thibaud Boutin
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Ben Brumpton
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ralph Burkhardt
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Harry Campbell
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - John Chalmers
- The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Miao Li Chee
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Renata Cifkova
- Center for Cardiovascular Prevention, Charles University in Prague, First Faculty of Medicine and Thomayer University Hospital, Prague, Czech Republic
- Department of Medicine II, Charles University in Prague, First Faculty of Medicine, Prague, Czech Republic
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Graciela Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Katalin Dittrich
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Todd L Edwards
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Karlhans Endlich
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, USA
| | - Ayush Giri
- Division of Quantitative Sciences, Department of Obstetrics & Gynecology, Vanderbilt Genetics Institute, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Iceland School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Nephrology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Pavel Hamet
- Montreal University Hospital Research Center, CHUM, Montréal, QC, Canada
- Medpharmgene, Montreal, QC, Canada
| | - Catharina A Hartman
- Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Jacklyn N Hellwege
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Nina Hutri-Kähönen
- Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Berend Isermann
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
- Beijing Institute of Ophthalmology, Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
- Privatpraxis Prof Jonas und Dr Panda-Jonas, Heidelberg, Germany
| | - Peter K Joshi
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masahiro Kanai
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | | | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Wieland Kiess
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Antje Körner
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Peter Kovacs
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Alena Krajcoviechova
- Center for Cardiovascular Prevention, Charles University in Prague, First Faculty of Medicine and Thomayer University Hospital, Prague, Czech Republic
| | - Holly Kramer
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
- Division of Nephrology and Hypertension, Loyola University Chicago, Chicago, IL, USA
| | - Bernhard K Krämer
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Mikko Kuokkanen
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado Denver-Anschutz Medical Campus, Aurora, CO, USA
| | - James P Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Hengtong Li
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Bridget M Lin
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | | | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Nina Mononen
- Department of Clinical Chemistry, Fimlab Laboratories, and The Wellbeing Services County of Pirkanmaa, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Charlottesville, VA, USA
| | - Winfried März
- Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, Graz, Austria
- Synlab Academy, Synlab Holding Deutschland GmbH, Augsburg, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Kjell Nikus
- Department of Cardiology, Heart Center, Tampere University Hospital, Tampere, Finland
- Department of Cardiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Yukinori Okada
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Albertine J Oldehinkel
- Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC/Vrije Universiteit and GGZ inGeest, Amsterdam, the Netherlands
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Nicola Pirastu
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
- Biostatistics Unit - Population and Medical Genomics Programme, Genomics Research Centre, Human Technopole Palazzo Italia, Viale Rita Levi‑Montalcini, 1, 20157, Milan, Italy
| | | | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Tanja Poulain
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- University Hospital for Children and Adolescents, Pediatric Research Unit, Medical Faculty, University Medical Center, University of Leipzig, Leipzig, Germany
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, Department of Epidemiology, Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ton J Rabelink
- Department of Internal Medicine, Section of Nephrology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory of Experimental Vascular Research, Leiden University Medical Center, Leiden, the Netherlands
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Center of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Medicine and Laboratory Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Igor Rudan
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Neil Schneiderman
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Mario Sims
- Department of Social Medicine, Population and Public Health, University of California at Riverside School of Medicine, Riverside, CA, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Klaus J Stark
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | | | | | | | - Per O Svensson
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Department of Cardiology, Södersjukhuset, Stockholm, Sweden
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Andrej Teren
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Department of Cardiology and Intensive Care Medicine, University Hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Straße 50, 33604, Bielefeld, Germany
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Joachim Thiery
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany
| | - Chris H L Thio
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Laurent F Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St.Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Johanne Tremblay
- Montreal University Hospital Research Center, CHUM, Montréal, QC, Canada
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Chaolong Wang
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah H Wild
- Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - James F Wilson
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Global Health, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Center, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Tsinghua Medicine, Tsinghua University, Beijing, China
| | - Mark Woodward
- The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
- The George Institute for Global Health, School of Public Health, Imperial College London, London, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | | | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Adriana M Hung
- Department of Veteran's Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Medical Center, Division of Nephrology & Hypertension, Nashville, TN, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afshin Parsa
- Division of Kidney, Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck), Bolzano, Italy
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Wen J, Hou J, Bonzel CL, Zhao Y, Castro VM, Gainer VS, Weisenfeld D, Cai T, Ho YL, Panickan VA, Costa L, Hong C, Gaziano JM, Liao KP, Lu J, Cho K, Cai T. LATTE: Label-efficient incident phenotyping from longitudinal electronic health records. Patterns (N Y) 2024; 5:100906. [PMID: 38264714 PMCID: PMC10801250 DOI: 10.1016/j.patter.2023.100906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 09/06/2023] [Accepted: 12/01/2023] [Indexed: 01/25/2024]
Abstract
Electronic health record (EHR) data are increasingly used to support real-world evidence studies but are limited by the lack of precise timings of clinical events. Here, we propose a label-efficient incident phenotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data. By leveraging the pre-trained semantic embeddings, LATTE selects predictive features and compresses their information into longitudinal visit embeddings through visit attention learning. LATTE models the sequential dependency between the target event and visit embeddings to derive the timings. To improve label efficiency, LATTE constructs longitudinal silver-standard labels from unlabeled patients to perform semi-supervised training. LATTE is evaluated on the onset of type 2 diabetes, heart failure, and relapses of multiple sclerosis. LATTE consistently achieves substantial improvements over benchmark methods while providing high prediction interpretability. The event timings are shown to help discover risk factors of heart failure among patients with rheumatoid arthritis.
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Affiliation(s)
- Jun Wen
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Jue Hou
- University of Minnesota, Minneapolis, MN, USA
| | - Clara-Lea Bonzel
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | | | | | - Tianrun Cai
- VA Boston Healthcare System, Boston, MA, USA
- Mass General Brigham, Boston, MA, USA
| | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Vidul A. Panickan
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | | | - J. Michael Gaziano
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Katherine P. Liao
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Junwei Lu
- VA Boston Healthcare System, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kelly Cho
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Tianxi Cai
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
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17
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Harrington KM, Quaden R, Steele L, Helmer DA, Hauser ER, Ahmed ST, Aslan M, Radhakrishnan K, Honerlaw J, Nguyen XMT, Muralidhar S, Concato J, Cho K, Gaziano JM, Whitbourne SB. The Million Veteran Program 1990-1991 Gulf War Era Survey: An Evaluation of Veteran Response, Characteristics, and Representativeness of the Gulf War Era Veteran Population. Int J Environ Res Public Health 2024; 21:72. [PMID: 38248536 PMCID: PMC10815483 DOI: 10.3390/ijerph21010072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024]
Abstract
To address gaps in understanding the pathophysiology of Gulf War Illness (GWI), the VA Million Veteran Program (MVP) developed and implemented a survey to MVP enrollees who served in the U.S. military during the 1990-1991 Persian Gulf War (GW). Eligible Veterans were invited via mail to complete a survey assessing health conditions as well as GW-specific deployment characteristics and exposures. We evaluated the representativeness of this GW-era cohort relative to the broader population by comparing demographic, military, and health characteristics between respondents and non-respondents, as well as with all GW-era Veterans who have used Veterans Health Administration (VHA) services and the full population of U.S. GW-deployed Veterans. A total of 109,976 MVP GW-era Veterans were invited to participate and 45,270 (41%) returned a completed survey. Respondents were 84% male, 72% White, 8% Hispanic, with a mean age of 61.6 years (SD = 8.5). Respondents were more likely to be older, White, married, better educated, slightly healthier, and have higher socioeconomic status than non-respondents, but reported similar medical conditions and comparable health status. Although generally similar to all GW-era Veterans using VHA services and the full population of U.S. GW Veterans, respondents included higher proportions of women and military officers, and were slightly older. In conclusion, sample characteristics of the MVP GW-era cohort can be considered generally representative of the broader GW-era Veteran population. The sample represents the largest research cohort of GW-era Veterans established to date and provides a uniquely valuable resource for conducting in-depth studies to evaluate health conditions affecting 1990-1991 GW-era Veterans.
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Affiliation(s)
- Kelly M. Harrington
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Rachel Quaden
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
| | - Lea Steele
- Veterans Health Research Program, Yudofsky Division of Neuropsychiatry, Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA;
| | - Drew A. Helmer
- Center for Innovations in Quality, Effectiveness, and Safety (IQuESt), Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA; (D.A.H.); (S.T.A.)
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elizabeth R. Hauser
- VA Cooperative Studies Program Epidemiology Center-Durham, Department of Veterans Affairs, Durham, NC 27705, USA;
- Department of Biostatistics and Bioinformatics, Duke Molecular Physiology Institute, Duke University, Durham, NC 27705, USA
| | - Sarah T. Ahmed
- Center for Innovations in Quality, Effectiveness, and Safety (IQuESt), Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA; (D.A.H.); (S.T.A.)
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT 06516, USA; (M.A.)
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06511, USA;
| | - Krishnan Radhakrishnan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT 06516, USA; (M.A.)
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD 20857, USA
| | - Jacqueline Honerlaw
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
| | - Xuan-Mai T. Nguyen
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Carle Illinois College of Medicine, University of Illinois, Champaign, IL 61820, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC 20420, USA;
| | - John Concato
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06511, USA;
- Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Kelly Cho
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - J. Michael Gaziano
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Stacey B. Whitbourne
- Million Veteran Program (MVP) Coordinating Center, VA Boston Healthcare System, Boston, MA 02130, USA; (R.Q.); (J.H.); (X.-M.T.N.); (K.C.); (J.M.G.); (S.B.W.)
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
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18
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Justice AC, Tate JP, Howland F, Gaziano JM, Kelley MJ, McMahon B, Haiman C, Wadia R, Madduri R, Danciu I, Leppert JT, Leapman MS, Thurtle D, Gnanapragasam VJ. Adaption and National Validation of a Tool for Predicting Mortality from Other Causes Among Men with Nonmetastatic Prostate Cancer. Eur Urol Oncol 2024:S2588-9311(23)00289-4. [PMID: 38171965 DOI: 10.1016/j.euo.2023.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/24/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer. OBJECTIVE To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM). DESIGN, SETTING, AND PARTICIPANTS An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups. RESULTS AND LIMITATIONS Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application. CONCLUSIONS VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation. PATIENT SUMMARY Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality.
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Affiliation(s)
- Amy C Justice
- VA Connecticut Healthcare, West Haven, CT, USA; Pain Research, Informatics, Multimorbidities, Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA; School of Public Health, Yale University, New Haven, CT, USA.
| | - Janet P Tate
- VA Connecticut Healthcare, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Frank Howland
- Wabash College Economics Department, Crawfordsville, IN, USA
| | | | - Michael J Kelley
- Durham VA Health Care System, Durham, NC, USA; Cancer Institute and Department of Medicine, Duke University, Durham, NC, USA
| | | | - Christopher Haiman
- Center for Genetic Epidemiology, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Roxanne Wadia
- Department of Anatomic Pathology and Lab Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Ravi Madduri
- Data Science Learning Division, Argonne Research Library, Lemont, IL, USA
| | - Ioana Danciu
- Oak Ridge National Laboratory, Oak Ridge, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John T Leppert
- Department of Urology, Stanford University, Stanford, CA, USA; VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Michael S Leapman
- VA Connecticut Healthcare, West Haven, CT, USA; Department of Urology, Yale School of Medicine, New Haven, CT, USA
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19
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Song RJ, Larson MG, Aparicio HJ, Gaziano JM, Wilson P, Cho K, Vasan RS, Fox MP, Djoussé L. Moderate alcohol consumption on the risk of stroke in the Million Veteran Program. BMC Public Health 2023; 23:2485. [PMID: 38087273 PMCID: PMC10714616 DOI: 10.1186/s12889-023-17377-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/29/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND There is inconsistent evidence on the association of moderate alcohol consumption and stroke risk in the general population and is not well studied among U.S. Veterans. Furthermore, it is unclear whether primarily drinking beer, wine, or liquor is associated with a difference in stroke risk. METHODS The study included 185,323 Million Veteran Program participants who self-reported alcohol consumption on the Lifestyle Survey. Moderate consumption was defined as 1-2 drinks/day and beverage preference of beer, wine or liquor was defined if ≥ 50% of total drinks consumed were from a single type of beverage. Strokes were defined using ICD-9 and ICD-10 codes from the participants' electronic health record. RESULTS The mean (sd) age of the sample was 64 (13) years and 11% were women. We observed 4,339 (94% ischemic; 6% hemorrhagic) strokes over a median follow-up of 5.2 years. In Cox models adjusted for age, sex, race, education, income, body mass index, smoking, exercise, diet, cholesterol, prevalent diabetes, prevalent hypertension, lipid-lowering medication, antihypertensive medication, and diabetes medication, moderate alcohol consumption (1-2 drinks/day) was associated with a 22% lower risk of total stroke compared with never drinking [Hazards ratio (HR) 95% confidence interval (CI): 0.78 (0.67, 0.92)]. When stratifying by stroke type, we observed a similar protective association with moderate consumption and ischemic stroke [HR (95% CI): 0.76 (0.65, 0.90)], but a non-statistically significant higher risk of hemorrhagic stroke [HR (95% CI): 1.29 (0.64, 2.61)]. We did not observe a difference in ischemic or hemorrhagic stroke risk among those who preferred beer, liquor or wine vs. no beverage preference. When stratifying by prior number of hospital visits (≤ 15, 16-33, 34-64, ≥ 65) as a proxy for health status, we observed attenuation of the protective association with greater number of visits [HR (95% CI): 0.87 (0.63, 1.19) for ≥ 65 visits vs. 0.80 (0.59, 1.08) for ≤ 15 visits]. CONCLUSIONS We observed a lower risk of ischemic stroke, but not hemorrhagic stroke with moderate alcohol consumption and did not observe substantial differences in risk by beverage preference among a sample of U.S. Veterans. Healthy user bias of moderate alcohol consumption may be driving some of the observed protective association.
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Affiliation(s)
- Rebecca J Song
- MAVERIC VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA, 02111, USA.
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, USA
- Department of Medicine, Boston University School of Medicine, Boston, USA
| | - Hugo J Aparicio
- MAVERIC VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA, 02111, USA
- Department of Neurology, Boston University School of Medicine, Boston, USA
| | - J Michael Gaziano
- MAVERIC VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA, 02111, USA
- Division of Aging, Department of Medicine, Harvard Medical School, Boston, USA
| | - Peter Wilson
- Atlanta VA Medical Center, Decatur, GA, USA
- Emory University Schools of Medicine and Public Health, Atlanta, GA, USA
| | - Kelly Cho
- MAVERIC VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA, 02111, USA
- Division of Aging, Department of Medicine, Harvard Medical School, Boston, USA
| | - Ramachandran S Vasan
- Section of Preventive Medicine, Boston University School of Medicine, Boston, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, USA
| | - Matthew P Fox
- Department of Epidemiology, Boston University School of Public Health, Boston, USA
- Department of Global Health, Boston University School of Public Health, Boston, USA
| | - Luc Djoussé
- MAVERIC VA Boston Healthcare System, Lafayette City Center, 2 Avenue de Lafayette, Boston, MA, 02111, USA
- Division of Aging, Department of Medicine, Harvard Medical School, Boston, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, USA
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20
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Barayev O, Hawley CE, Wellman H, Gerlovin H, Hsu W, Paik JM, Mandel EI, Liu CK, Djoussé L, Gaziano JM, Gagnon DR, Orkaby AR. Statins, Mortality, and Major Adverse Cardiovascular Events Among US Veterans With Chronic Kidney Disease. JAMA Netw Open 2023; 6:e2346373. [PMID: 38055276 DOI: 10.1001/jamanetworkopen.2023.46373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/07/2023] Open
Abstract
Importance There are limited data for the utility of statins for primary prevention of atherosclerotic cardiovascular disease (ASCVD) and death in adults with chronic kidney disease (CKD). Objective To evaluate the association of statin use with all-cause mortality and major adverse cardiovascular events (MACE) among US veterans older than 65 years with CKD stages 3 to 4. Design, Setting, and Participants This cohort study used a target trial emulation design for statin initiation among veterans with moderate CKD (stages 3 or 4) using nested trials with a propensity weighting approach. Linked Veterans Affairs (VA) Healthcare System, Medicare, and Medicaid data were used. This study considered veterans newly diagnosed with moderate CKD between 2005 and 2015 in the VA, with follow-up through December 31, 2017. Veterans were older than 65 years, within 5 years of CKD diagnosis, had no prior ASCVD or statin use, and had at least 1 clinical visit in the year prior to trial baseline. Eligibility criteria were assessed for each nested trial, and Cox proportional hazards models with bootstrapping were run. Analysis was conducted from July 2021 to October 2023. Exposure Statin initiation vs none. Main Outcomes and Measures Primary outcome was all-cause mortality; secondary outcome was time to first MACE (myocardial infarction, transient ischemic attack, stroke, revascularization, or mortality). Results Included in the analysis were 14 828 veterans. Mean (SD) age at CKD diagnosis was 76.9 (8.2) years, 14 616 (99%) were men, 10 539 (72%) White, and 2568 (17%) Black. After expanding to person-trials and assessing eligibility at each baseline, there were 151 243 person-trials (14 685 individuals) of nonstatin initiators and 2924 person-trials (2924 individuals) of statin initiators included. Propensity score adjustment via overlap weighting with nonparametric bootstrapping resulted in covariate balance, with mean (SD) follow-up of 3.6 (2.7) years. The hazard ratio for all-cause mortality was 0.91 (95% CI, 0.85-0.97) comparing statin initiators to noninitiators. The hazard ratio for MACE was 0.96 (95% CI, 0.91-1.02). Results remained consistent in prespecified subgroup analyses. Conclusions and Relevance In this target trial emulation of statin initiation in US veterans older than 65 years with CKD stages 3 to 4 and no prior ASCVD, statin initiation was significantly associated with a lower risk of all-cause mortality but not MACE. Results should be confirmed in a randomized clinical trial.
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Affiliation(s)
- Odeya Barayev
- Ben Gurion University of the Negev, Be'er Sheva, Israel
| | - Chelsea E Hawley
- New England Geriatric Research Education and Clinical Center, Bedford and Boston, Massachusetts
| | - Helen Wellman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
| | - Hanna Gerlovin
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
| | - Whitney Hsu
- VA Boston Healthcare System, Department of Pharmacy, Boston, Massachusetts
| | - Julie M Paik
- New England Geriatric Research Education and Clinical Center, Bedford and Boston, Massachusetts
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
- Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Ernest I Mandel
- Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Christine K Liu
- Section of Geriatrics, Department of Medicine, Stanford University School of Medicine, Stanford, California
- Geriatric Research Education and Clinical Center, Palo Alto VA Medical Center, Palo Alto, California
| | - Luc Djoussé
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - David R Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Ariela R Orkaby
- New England Geriatric Research Education and Clinical Center, Bedford and Boston, Massachusetts
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
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21
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Levey DF, Galimberti M, Deak JD, Wendt FR, Bhattacharya A, Koller D, Harrington KM, Quaden R, Johnson EC, Gupta P, Biradar M, Lam M, Cooke M, Rajagopal VM, Empke SLL, Zhou H, Nunez YZ, Kranzler HR, Edenberg HJ, Agrawal A, Smoller JW, Lencz T, Hougaard DM, Børglum AD, Demontis D, Gaziano JM, Gandal MJ, Polimanti R, Stein MB, Gelernter J. Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications. Nat Genet 2023; 55:2094-2103. [PMID: 37985822 PMCID: PMC10703690 DOI: 10.1038/s41588-023-01563-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/09/2023] [Indexed: 11/22/2023]
Abstract
As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.
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Affiliation(s)
- Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Joseph D Deak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Frank R Wendt
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
- Department of Anthropology, University of Toronto, Mississauga, Ontario, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Bhattacharya
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dora Koller
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain
| | - Kelly M Harrington
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Rachel Quaden
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Priya Gupta
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Mahantesh Biradar
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Megan Cooke
- Center for Addiction Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Veera M Rajagopal
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - Stefany L L Empke
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Yaira Z Nunez
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC and Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Howard J Edenberg
- Departments of Biochemistry and Molecular Biology and Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Todd Lencz
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - J Michael Gaziano
- Harvard Medical School, Boston, MA, USA
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael J Gandal
- Departments of Psychiatry and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- The Lifespan Brain Institute, Penn Medicine and the Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry and Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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22
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Zhou H, Kember RL, Deak JD, Xu H, Toikumo S, Yuan K, Lind PA, Farajzadeh L, Wang L, Hatoum AS, Johnson J, Lee H, Mallard TT, Xu J, Johnston KJA, Johnson EC, Nielsen TT, Galimberti M, Dao C, Levey DF, Overstreet C, Byrne EM, Gillespie NA, Gordon S, Hickie IB, Whitfield JB, Xu K, Zhao H, Huckins LM, Davis LK, Sanchez-Roige S, Madden PAF, Heath AC, Medland SE, Martin NG, Ge T, Smoller JW, Hougaard DM, Børglum AD, Demontis D, Krystal JH, Gaziano JM, Edenberg HJ, Agrawal A, Justice AC, Stein MB, Kranzler HR, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. Nat Med 2023; 29:3184-3192. [PMID: 38062264 PMCID: PMC10719093 DOI: 10.1038/s41591-023-02653-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 10/18/2023] [Indexed: 12/17/2023]
Abstract
Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA.
| | - Rachel L Kember
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Leila Farajzadeh
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Lu Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, USA
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T Mallard
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Trine Tollerup Nielsen
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cecilia Dao
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Nathan A Gillespie
- Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Laura M Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Lea K Davis
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tian Ge
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jordan W Smoller
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- National Center for PTSD, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Psychiatry and Behavioral Health Services, Yale-New Haven Hospital, New Haven, CT, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston, MA, USA
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Henry R Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.
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23
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Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, Darst BF, Sheng X, Xu Y, Chou AJ, Benlloch S, Dadaev T, Brook MN, Plym A, Sahimi A, Hoffman TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Laisk T, Figuerêdo J, Muir K, Ito S, Liu X, Uchio Y, Kubo M, Kamatani Y, Lophatananon A, Wan P, Andrews C, Lori A, Choudhury PP, Schleutker J, Tammela TL, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokolorczyk D, Lubinski J, Rentsch CT, Cho K, Mcmahon BH, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder A, Stroomberg HV, Batra J, Chambers S, Horvath L, Clements JA, Tilly W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordstrom T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein S, Cook MB, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Koutros S, Beane Freeman LE, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CM, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Butler EN, Mohler JL, Taylor JA, Kogevinas M, Dierssen-Sotos T, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Pilie P, Yu Y, Bohlender RJ, Gu J, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Brenner H, Chen X, Holleczek B, Schöttker B, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJ, Carpten J, Pandha H, Michael A, Ruyck KD, Meerleer GD, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas CM, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Abraham A, Singhal S, Parliament M, Claessens F, Joniau S, den Broeck TV, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen J, Petrovics G, Casey G, Wang Y, Tettey Y, Lachance J, Tang W, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Yamoah K, Govindasami K, Chokkalingam AP, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Shittu O, Amodu O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Diop H, Gundell SM, Roobol MJ, Jenster G, van Schaik RH, Hu JJ, Sanderson M, Kachuri L, Varma R, McKean-Cowdin R, Torres M, Preuss MH, Loos RJ, Zawistowski M, Zöllner S, Lu Z, Van Den Eeden SK, Easton DF, Ambs S, Edwards TL, Mägi R, Rebbeck TR, Fritsche L, Chanock SJ, Berndt SI, Wiklund F, Nakagawa H, Witte JS, Gaziano JM, Justice AC, Mancuso N, Terao C, Eeles RA, Kote-Jarai Z, Madduri RK, Conti DV, Haiman CA. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants. Nat Genet 2023; 55:2065-2074. [PMID: 37945903 PMCID: PMC10841479 DOI: 10.1038/s41588-023-01534-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 09/15/2023] [Indexed: 11/12/2023]
Abstract
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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Affiliation(s)
- Anqi Wang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jiayi Shen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rohini Janivara
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Burcu F. Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yili Xu
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alisha J. Chou
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sara Benlloch
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology,University of Cambridge, Cambridge, UK
| | | | | | - Anna Plym
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Urology Division, Department of Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ali Sahimi
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Thomas J. Hoffman
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Atushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Genomic Medicine, National Cerebral and Cardiovascular Center Research Institute, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing,Graduate school of Frontier Sciences,The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - Masashi Fujita
- Laboratory for Cancer Genomics, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jéssica Figuerêdo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Warwick Medical School, University of Warwick, Coventry, UK
| | - Shuji Ito
- Department of Orthopaedics, Shimane University, Izumo, Shimane, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - The Biobank Japan Project
- Corresponding Author: Christopher A. Haiman, Harlyne J. Norris Cancer Research Tower, USC Norris Comprehensive Cancer Center, 1450 Biggy Street, Rm 1504, Los Angeles, CA 90033 or
| | - Yuji Uchio
- Department of Orthopaedics, Shimane University, Izumo, Shimane, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Artitaya Lophatananon
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester, UK
| | - Peggy Wan
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Caroline Andrews
- Harvard TH Chan School of Public Health and Division of Population Sciences,Dana Farber Cancer Institute, Boston, MA, USA
| | - Adriana Lori
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | | | - Johanna Schleutker
- Institute of Biomedicine, University of Turku, Turku, Finland
- Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, Turku, Finland
| | | | - Csilla Sipeky
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Anssi Auvinen
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Graham G. Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,The University of Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Robert J. MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,The University of Melbourne, Victoria, Australia
| | - Cezary Cybulski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Dominika Wokolorczyk
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jan Lubinski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Christopher T. Rentsch
- Yale School of Medicine, New Haven, CT, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kelly Cho
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | - David E. Neal
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- University of Cambridge, Department of Oncology, Addenbrooke’s Hospital, Cambridge, UK
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Jenny L. Donovan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Freddie C. Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
- Faculty of Medical Science, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Richard M. Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Borge G. Nordestgaard
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Sune F. Nielsen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Maren Weischer
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Stig E. Bojesen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Andreas Røder
- Copenhagen Prostate Cancer Center, Department of Urology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Hein V. Stroomberg
- Copenhagen Prostate Cancer Center, Department of Urology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | | | - Lisa Horvath
- Chris O’Brien Lifehouse (COBLH), Camperdown, Sydney, NSW, Australia, Sydney, Australia
- Garvan Institute of Medical Research, Sydney, Australia
| | - Judith A. Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Wayne Tilly
- Dame Roma Mitchell Cancer Research Laboratories, University of Adelaide, Adelaide, Australia
| | - Gail P. Risbridger
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
- Prostate Cancer Translational Research Program, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Henrik Gronberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Markus Aly
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, and Department of Urology, Karolinska University Hospital, Solna, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | - Robert Szulkin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- SDS Life Sciences, Stockholm, Sweden
| | - Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Tobias Nordstrom
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Sciences at Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Nora Pashayan
- University College London, Department of Applied Health Research, London, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Cambridge, UK
- Department of Applied Health Research, University College London, London, UK
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Cambridge, UK
| | - Maya Ghoussaini
- Open Targets, Wellcome Sanger Institute, Hinxton, Saffron Walden, Hinxton, UK
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Tim J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jong Y. Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Thomas A. Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Hui-Yi Lin
- School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephanie Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael B. Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH,, Bethesda, MD, USA
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Edward Giovannucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sara Lindstrom
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David J. Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kathryn L. Penney
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Constance Turman
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Catherine M. Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Phyllis J. Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ian M. Thompson
- CHRISTUS Santa Rosa Hospital – Medical Center, San Antonio, TX, USA
| | - Robert J. Hamilton
- Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Canada
- Dept. of Surgery (Urology), University of Toronto, Toronto, Canada
| | - Neil E. Fleshner
- Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | - Antonio Finelli
- Division of Urology, Princess Margaret Cancer Centre, Toronto, Canada
| | - Marie-Élise Parent
- Epidemiology and Biostatistics Unit, Centre Armand-Frappier Santé Biotechnologie, Laval, QC, Canada
| | - Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Elaine A. Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Laura E. Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Meir Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Alicja Wolk
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Niclas Håkansson
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Gerald L. Andriole
- Brady Urological Institute in National Capital Region, Johns Hopkins University, Baltimore, MD, USA
| | - Robert N. Hoover
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Mitchell J. Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Karina Dalsgaard Sørensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Michael Borre
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Urology, Aarhus University Hospital, Aarhus, Denmark
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- International Epidemiology Institute, Rockville, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - James E. Mensah
- University of Ghana Medical School, Accra, Ghana
- Korle Bu Teaching Hospital, Accra, Ghana
| | - Yong-Jie Lu
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | | | - Ninghan Feng
- Wuxi Second Hospital, Nanjing Medical University, Wuxi, Jiangzhu Province, China
| | - Xueying Mao
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | - Yudong Wu
- Department of Urology, First Affiliated Hospital, The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Shan-Chao Zhao
- Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zan Sun
- The People’s Hospital of Liaoning Proviouce, The People’s Hospital of China Medical University, Shenyang, China, Shenyang, China
| | - Stephen N. Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Daniel J. Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Catharine M.L. West
- Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | - Gill Barnett
- University of Cambridge Department of Oncology, Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | | | | | - Adam S. Kibel
- Division of Urologic Surgery, Brigham and Womens Hospital, Boston, MA, USA
| | | | - Olivier Cussenot
- GRC 5 Predictive Onco-Urology, Sorbonne Université, Paris, France
- CeRePP, Paris, France
| | | | - Florence Menegaux
- Exposome and Heredity, CESP (UMR 1018), Paris-Saclay Medical School, Paris-Saclay University, Inserm, Gustave Roussy, Villejuif, France
| | - Thérèse Truong
- Exposome and Heredity, CESP (UMR 1018), Paris-Saclay Medical School, Paris-Saclay University, Inserm, Gustave Roussy, Villejuif, France
| | - Yves Akoli Koudou
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif Cédex, France
| | - Esther M. John
- Department of Medicine, Stanford Cancer Institute,Stanford University School of Medicine, Stanford, CA, USA
| | | | - Lovise Maehle
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Sue A. Ingles
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Mariana C Stern
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Ana Vega
- Fundación Pública Galega Medicina Xenómica, Santiago De Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Spain
| | - Antonio Gómez-Caamaño
- Department of Radiation Oncology, Complexo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | - Laura Fachal
- Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Spain
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
- Fundación Pública Galega Medicina Xenómica, Santiago de Compostela, Spain
| | - Barry S. Rosenstein
- Department of Radiation Oncology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sarah L. Kerns
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Harry Ostrer
- Professor of Pathology and Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Manuel R. Teixeira
- Department of Laboratory Genetics, Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- School of Medicine and Biomedical Sciences (ICBAS), University of Porto, Porto, Portugal
| | - Paula Paulo
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
| | - Andreia Brandão
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
| | | | | | - Jeannette T. Bensen
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ebonee N. Butler
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - James L. Mohler
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Urology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
- Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Trinidad Dierssen-Sotos
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- University of Cantabria-IDIVAL, Santander, Spain
| | - Gemma Castaño-Vinyals
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Lisa Cannon-Albright
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Craig C. Teerlink
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Chad D. Huff
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Patrick Pilie
- Department of Genitourinary Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Yao Yu
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Ryan J. Bohlender
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Jian Gu
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Sara S. Strom
- The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Luc Multigner
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Pascal Blanchet
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, France
| | - Laurent Brureau
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, France
| | - Radka Kaneva
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Chavdar Slavov
- Department of Urology and Alexandrovska University Hospital, Medical University of Sofia, Sofia, Bulgaria
| | - Vanio Mitev
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Robin J. Leach
- Department of Cell Systems and Anatomy and Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eric A. Klein
- Cleveland Clinic Lerner Research Institute, Cleveland, OH, USA
- Glickman Urological & Kidney Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ann W. Hsing
- Department of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Adam B. Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Christopher J. Logothetis
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Jeri Kim
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Linda Steele
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - William B. Isaacs
- James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anselm J.M. Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Kim De Ruyck
- Ghent University, Faculty of Medicine and Health Sciences, Basic Medical Sciences, Ghent, Belgium
| | - Gert De Meerleer
- Ghent University Hospital, Department of Radiotherapy, Ghent, Belgium
| | - Piet Ost
- Ghent University Hospital, Department of Radiotherapy, Ghent, Belgium
| | - Jianfeng Xu
- Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Azad Razack
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Jasmine Lim
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Cancer Research Malaysia (CRM), Outpatient Centre, Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Lisa F. Newcomb
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Daniel W. Lin
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Jay H. Fowke
- Department of Preventive Medicine, Division of Epidemiology,The University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Benjamin A. Rybicki
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, Detroit, MI, USA
| | - Marija Gamulin
- Division of Medical Oncology, Urogenital Unit, Department of Oncology, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Davor Lessel
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tomislav Kulis
- Department of Urology, University Hospital Center Zagreb, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Nawaid Usmani
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Aswin Abraham
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Sandeep Singhal
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Matthew Parliament
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Frank Claessens
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
| | - Steven Joniau
- Department of Urology, University Hospitals Leuven, Leuven, Belgium
| | - Thomas Van den Broeck
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
- Department of Urology, University Hospitals Leuven, Leuven, Belgium
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, Servicio Galego de Saúde, SERGAS, Santiago de Compostela, Spain
- University of California San Diego, Moores Cancer Center, La Jolla, CA, USA
| | - Jose Esteban Castelao
- Genetic Oncology Unit, CHUVI Hospital, Complexo Hospitalario Universitario de Vigo, Instituto de Investigación Biomédica Galicia Sur (IISGS), Vigo (Pontevedra), Spain
| | - Maria Elena Martinez
- University of California San Diego, Moores Cancer Center, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Samantha Larkin
- Scientific Education Support, Thames Ditton, Surrey, Formerly Cancer Sciences, University of Southampton, Southampton, UK
| | - Paul A. Townsend
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | | | - William S. Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Melinda C. Aldrich
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dana C. Crawford
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Shiv Srivastava
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Jennifer Cullen
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Surgery, Center for Prostate Disease Research,Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Gyorgy Petrovics
- Department of Surgery, Center for Prostate Disease Research,Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Graham Casey
- Department of Public Health Science, Center for Public Health Genomics,University of Virginia, Charlottesville, VA, USA
| | - Ying Wang
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - Yao Tettey
- Korle Bu Teaching Hospital, Accra, Ghana
- Department of Pathology, University of Ghana, Accra, Ghana
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Wei Tang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | | | - Andrew A. Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | - Evelyn Tay
- Korle Bu Teaching Hospital, Accra, Ghana
| | | | | | - Kosj Yamoah
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | - Jacob M. Keaton
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jacklyn N. Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Nashville, TN, USA
| | - Peter E. Clark
- Atrium Health/Levine Cancer Institute, Charlotte, NC, USA
| | | | | | | | - Olufemi Ogunbiyi
- Department of Pathology, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Olayiwola Shittu
- Department of Surgery, College of Medicine, University of Ibadan and Univerity College Hospital, Ibadan, Nigeria
| | - Olukemi Amodu
- Institute of Child Health, College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Akindele O. Adebiyi
- Clinical Epidemiology Unit, Department of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oseremen I. Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Hafees O. Ajibola
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Mustapha A. Jamda
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Olabode P. Oluwole
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Maxwell Nwegbu
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | | | | | | | - Halimatou Diop
- Laboratoires Bacteriologie et Virologie, Hôpital Aristide Le Dantec, Dakar, Senegal
| | - Susan M. Gundell
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Monique J. Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Guido Jenster
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Ron H.N. van Schaik
- Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Jennifer J. Hu
- The University of Miami School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford Cancer Institute, Stanford, CA, USA
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Mina Torres
- Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew Zawistowski
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Zeyun Lu
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | | | - Douglas F. Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology,, Cambridge, UK
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Todd L. Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Timothy R. Rebbeck
- Harvard TH Chan School of Public Health and Division of Population Sciences, Dana Farber Cancer Institute, Boston, MA, USA
| | - Lars Fritsche
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Hidewaki Nakagawa
- Laboratory for Cancer Genomics, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - John S. Witte
- Department of Epidemiology and Population Health, Stanford Cancer Institute, Stanford, CA, USA
- Departments of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J. Michael Gaziano
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | - Nick Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, Shizuoka, Japan
| | - Rosalind A. Eeles
- The Institute of Cancer Research, London, UK
- Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - David V. Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Qavi AH, Zhou G, Ward RE, Carr JJ, Ellison RC, Arnett DK, Gaziano JM, Djousse L. Association of potato consumption with calcified atherosclerotic plaques in the coronary arteries: The NHLBI Family Heart Study. Nutr Metab Cardiovasc Dis 2023; 33:2413-2418. [PMID: 37580232 PMCID: PMC10808268 DOI: 10.1016/j.numecd.2023.07.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 06/27/2023] [Accepted: 07/18/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND AND AIMS While the association of potato consumption with risk factors for coronary artery disease has been inconsistent, no data are available in the literature on the influence of potato consumption on subclinical disease. Thus, we sought to examine whether baked/mashed potato consumption is associated with calcified atherosclerotic plaques in the coronary arteries. METHODS AND RESULTS In a cross-sectional design, we studied 2208 participants of the NHLBI Family Heart Study. These subjects were selected based on their elevated cardiovascular disease risk compared to the general population. Potato consumption was assessed by a semi-quantitative food frequency questionnaire. We defined prevalent CAC using an Agatston score of at least 100 and fitted generalized estimating equations to calculate prevalence odds ratios of CAC. Mean age at initial clinic visit was 58.2 years and 55% were female. Median consumption of potatoes was 2-4/week. There was no statistically significant association between frequency of potato consumption and prevalent CAC: odds ratios (95% CI) for CAC were 1.0 (reference), 0.85 (0.56-1.30), 0.85 (0.58-1.26), and 0.95 (0.60-1.53) among subjects reporting potato consumption of <1/week, 1/week, 2-4/week, and 5+/week, respectively (p for linear trend 0.83), adjusting for age, sex, BMI, smoking, exercise, diabetes, hypertension, total calories, prevalent coronary heart disease, income, education, and daily red meat intake. CONCLUSIONS We found no significant association between baked/mashed potato consumption and CAC in older adults. STUDY REGISTRATION NUMBER NCT00005136. Study registration date: 5/25/2000.
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Affiliation(s)
- Ahmed Hassaan Qavi
- Department of Cardiovascular Sciences, East Carolina University Health Medical Center and Brody School of Medicine, Greenville, NC, United States.
| | - Guohai Zhou
- Center for Clinical Investigation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Rachel E Ward
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC) and Geriatric Research, Education, and Clinical Research Center, Boston Veterans Affairs Healthcare System, Boston MA, United States
| | - John Jeffrey Carr
- Department of Radiology, Cardiovascular Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - R Curtis Ellison
- Section of Preventive Medicine & Epidemiology, Boston University School of Medicine, Boston, MA, United States
| | - Donna K Arnett
- University of South Carolina, Columbia, SC, United States
| | - J Michael Gaziano
- Division of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Center for Clinical Investigation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Luc Djousse
- Division of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States; Center for Clinical Investigation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
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25
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Nguyen XT, Ho Y, Li Y, Song RJ, Leung KH, Rahman SU, Orkaby AR, Vassy JL, Gagnon DR, Cho K, Gaziano JM, Wilson PWF. Serum Cholesterol and Impact of Age on Coronary Heart Disease Death in More Than 4 Million Veterans. J Am Heart Assoc 2023; 12:e030496. [PMID: 37889207 PMCID: PMC10727410 DOI: 10.1161/jaha.123.030496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 09/29/2023] [Indexed: 10/28/2023]
Abstract
Background The lipid hypothesis postulates that lower blood cholesterol is associated with reduced coronary heart disease (CHD) risk, which has been challenged by reports of a U-shaped relation between cholesterol and death in recent studies. We sought to examine whether the U-shaped relationship is true and to assess the impact of age on this association. Method and Results We conducted a prospective cohort study of 4 467 942 veterans aged >18 years, with baseline outpatient visits from 2002 to 2007 and follow-up to December 30, 2018, in the Veterans Health Administration electronic health record system. We observed a J-shaped relation between total cholesterol (TC) and CHD mortality after a comprehensive adjustment of confounding factors: flat for TC <180 mg/dL, and greater risk was present at higher cholesterol levels. Compared with veterans with TC between 180 and 199 mg/dL, the multiadjusted hazard ratios (HRs) for CHD death were 1.03 (95% CI, 1.02-1.04), 1.07 (95% CI, 1.06-1.09), 1.15 (95% CI, 1.13-1.18), 1.25 (95% CI, 1.22-1.28), and 1.45 (95% CI, 1.42-1.49) times greater among veterans with TC (mg/dL) of 200 to 219, 220 to 239, 140 to 259, 260 to 279 and ≥280, respectively. Similar J-shaped TC-CHD mortality patterns were observed among veterans with and without statin use at or before baseline. Conclusions The cholesterol paradox, for example, higher CHD death in patients with a low cholesterol level, was a reflection of reverse causality, especially among older participants. Our results support the lipid hypothesis that lower blood cholesterol is associated with reduced CHD. Furthermore, the hypothesis remained true when TC was low due to use of statins or other lipid-lowering medication.
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Affiliation(s)
- Xuan‐Mai T. Nguyen
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Carle Illinois College of MedicineUniversity of Illinois Urbana ChampaignChampaignILUSA
| | - Yuk‐Lam Ho
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
| | - Yanping Li
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
| | | | - Kenneth H. Leung
- Carle Illinois College of MedicineUniversity of Illinois Urbana ChampaignChampaignILUSA
| | - Saad Ur Rahman
- Carle Illinois College of MedicineUniversity of Illinois Urbana ChampaignChampaignILUSA
| | - Ariela R. Orkaby
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Division on Aging, Department of MedicineBrigham and Women’s HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Jason L. Vassy
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Division of General Internal MedicineBrigham and Women’s HospitalBostonMAUSA
| | - David R. Gagnon
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Boston University School of Public HealthBostonMAUSA
| | - Kelly Cho
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Division on Aging, Department of MedicineBrigham and Women’s HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - J. Michael Gaziano
- MAVERIC VA Boston Healthcare SystemBostonMAUSA
- Division on Aging, Department of MedicineBrigham and Women’s HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Peter W. F. Wilson
- Atlanta VA Medical CenterDecaturGAUSA
- Emory University Schools of Medicine and Public HealthAtlantaGAUSA
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26
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Hung AM, Assimon VA, Chen HC, Yu Z, Vlasschaert C, Triozzi JL, Chan H, Wheless L, Wilson O, Shah SC, Mack T, Thompson T, Matheny ME, Chandrasekar S, Mozaffari SV, Chung CP, Tsao P, Susztak K, Siew ED, Estrada K, Gaziano JM, Graham RR, Tao R, Hoek M, Robinson-Cohen C, Green EM, Bick AG. Genetic Inhibition of APOL1 Pore-Forming Function Prevents APOL1-Mediated Kidney Disease. J Am Soc Nephrol 2023; 34:1889-1899. [PMID: 37798822 PMCID: PMC10631602 DOI: 10.1681/asn.0000000000000219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/17/2023] [Indexed: 10/07/2023] Open
Abstract
SIGNIFICANCE STATEMENT African Americans are at increased risk of CKD in part due to high-risk (HR) variants in the apolipoprotein L1 ( APOL1 ) gene, termed G1/G2. A different APOL1 variant, p.N264K , reduced the risk of CKD and ESKD among carriers of APOL1 HR variants to levels comparable with individuals with APOL1 low-risk variants in an analysis of 121,492 participants of African ancestry from the Million Veteran Program (MVP). Functional genetic studies in cell models showed that APOL1 p.N264K blocked APOL1 pore-forming function and ion channel conduction and reduced toxicity of APOL1 HR mutations. Pharmacologic inhibitors that mimic this mutation blocking APOL1 -mediated pore formation may be able to prevent and/or treat APOL1 -associated kidney disease. BACKGROUND African Americans are at increased risk for nondiabetic CKD in part due to HR variants in the APOL1 gene. METHODS We tested whether a different APOL1 variant, p.N264K , modified the association between APOL1 HR genotypes (two copies of G1/G2) and CKD in a cross-sectional analysis of 121,492 participants of African ancestry from the MVP. We replicated our findings in the Vanderbilt University Biobank ( n =14,386) and National Institutes of Health All of Us ( n =14,704). Primary outcome was CKD and secondary outcome was ESKD among nondiabetic patients. Primary analysis compared APOL1 HR genotypes with and without p.N264K . Secondary analyses included APOL1 low-risk genotypes and tested for interaction. In MVP, we performed sequential logistic regression models adjusting for demographics, comorbidities, medications, and ten principal components of ancestry. Functional genomic studies expressed APOL1 HR variants with and without APOL1 p.N264K in cell models. RESULTS In the MVP cohort, 15,604 (12.8%) had two APOL1 HR variants, of which 582 (0.5%) also had APOL1 p.N264K . In MVP, 18,831 (15%) had CKD, 4177 (3%) had ESKD, and 34% had diabetes. MVP APOL1 HR, without p.N264K , was associated with increased odds of CKD (odds ratio [OR], 1.72; 95% confidence interval [CI], 1.60 to 1.85) and ESKD (OR, 3.94; 95% CI, 3.52 to 4.41). In MVP, APOL1 p.N264K mitigated the renal risk of APOL1 HR, in CKD (OR, 0.43; 95% CI, 0.28 to 0.65) and ESKD (OR, 0.19; CI 0.07 to 0.51). In the replication cohorts meta-analysis, APOL1 p.N264K mitigated the renal risk of APOL1 HR in CKD (OR, 0.40; 95% CI, 0.18 to 0.92) and ESKD (OR, 0.19; 95% CI, 0.05 to 0.79). In the mechanistic studies, APOL1 p.N264K blocked APOL1 pore-forming function and ion channel conduction and reduced toxicity of APOL1 HR variants. CONCLUSIONS APOL1 p.N264K is associated with reduced risk of CKD and ESKD among carriers of APOL1 HR to levels comparable with individuals with APOL1 low-risk genotypes.
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Affiliation(s)
- Adriana M. Hung
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Hua-Chang Chen
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Zhihong Yu
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Jefferson L. Triozzi
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Helen Chan
- Maze Therapeutics, South San Francisco, California
| | - Lee Wheless
- Department of Dermatology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Otis Wilson
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Shailja C. Shah
- VA San Diego Healthcare System and UC San Diego Health, La Jolla, California
| | - Taralynn Mack
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Trevor Thompson
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Michael E. Matheny
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | | | - Cecilia P. Chung
- Department of Rheumatology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Philip Tsao
- VA Palo Alto Health Care System, Palo Alto, California
- Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Katalin Susztak
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Edward D. Siew
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - J. Michael Gaziano
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital and Harvard School of Medicine, Boston, Massachusetts
| | | | - Ran Tao
- Nashville VA Medical Center, VA Tennessee Valley Healthcare System, Nashville, Tennessee
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Maarten Hoek
- Maze Therapeutics, South San Francisco, California
| | - Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Alexander G. Bick
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, Massachusetts
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Whitbourne SB, Moser J, Cho K, Deen J, Churby LL, Justice AC, Casas JP, Pyarajan S, Tsao PS, Gaziano JM, Muralidhar S. Leveraging the Million Veteran Program Infrastructure and Data for a Rapid Research Response to COVID-19. Fed Pract 2023; 40:S23-S28. [PMID: 38577307 PMCID: PMC10988626 DOI: 10.12788/fp.0416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Background The Veterans Health Administration Office of Research and Development (ORD) played a key role in the federal government's response to the COVID-19 pandemic. The ORD effectively leveraged existing resources to answer questions related to the SARS-CoV-2 virus and COVID-19. Observations When the COVID-19 pandemic hit in 2020, the Million Veteran Program (MVP), one of the largest genomic cohorts in the world, extended the centralized recruitment and enrollment infrastructure to develop a COVID-19 research volunteer registry to assist enrollment in the vaccine and treatment trials in which the US Department of Veterans Affairs (VA) participated. In addition, the MVP allowed for new data collection and a large genomic cohort to understand host contributions to COVID-19. This article describes ways the MVP contributed to the VA's rapid research response to COVID-19. Several host genetic factors believed to play a role in the development and severity of COVID-19 were identified. Furthermore, existing MVP partnerships with other federal agencies, particularly with the Department of Energy, were leveraged to improve understanding and management of COVID-19. Conclusions A previously established enterprise approach and research infrastructure were essential to the VA's successful and timely COVID-19 research response. This infrastructure not only supported rapid recruitment in vaccine and treatment trials, but also leveraged the unique MVP and VA electronic health record data to drive rapid scientific discovery and inform clinical operations. Extending the models that VA research applied to the federal government at large and establishing centralized resources for shared or federated data analyses across federal agencies will better equip the nation to respond to future public health crises.
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Affiliation(s)
- Stacey B. Whitbourne
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Jennifer Deen
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
| | - Lori L. Churby
- Veterans Affairs Palo Alto Healthcare System, California
| | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System, West Haven
- Yale University School of Medicine and School of Public Health, New Haven, Connecticut
| | - Juan P. Casas
- Novartis Institute for Biomedical Research, Cambridge, Massachusetts
| | - Saiju Pyarajan
- Veterans Affairs Boston Healthcare System, Massachusetts
| | - Phil S. Tsao
- Veterans Affairs Palo Alto Healthcare System, California
- Stanford University School of Medicine, Palo Alto, California
| | - J. Michael Gaziano
- Veterans Affairs Boston Healthcare System, Massachusetts
- Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC
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28
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Nogueira ACC, Barreto J, Moura FA, Luchiari B, Abuhab A, Bonilha I, Nadruz W, Gaziano JM, Gaziano T, de Carvalho LSF, Sposito AC. Comparative effectiveness and cost-effectiveness of cardioprotective glucose-lowering therapies for type 2 diabetes in Brazil: a Bayesian network model. Health Econ Rev 2023; 13:50. [PMID: 37878108 PMCID: PMC10599033 DOI: 10.1186/s13561-023-00466-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 10/16/2023] [Indexed: 10/26/2023]
Abstract
BACKGROUND The escalating prevalence of type 2 diabetes (T2DM) poses an unparalleled economic catastrophe to developing countries. Cardiovascular diseases remain the primary source of costs among individuals with T2DM, incurring expenses for medications, hospitalizations, and surgical interventions. Compelling evidence suggests that the risk of cardiovascular outcomes can be reduced by three classes of glucose-lowering therapies (GLT), including SGLT2i, GLP-1A, and pioglitazone. However, an evidence-based and cost-effective protocol is still unavailable for many countries. The objective of the current study is to compare the effectiveness and cost-effectiveness of GLT in individuals with T2DM in Brazil. METHODS We employed Bayesian Networks to calculate the incremental cost-effectiveness ratios (ICER), expressed in international dollars (Int$) per disease-adjusted life years [DALYs] averted. To determine the effectiveness of GLT, we conducted a systematic review with network meta-analysis (NMA) to provide insights for our model. Additionally, we obtained cardiovascular outcome incidence data from two real-world cohorts comprising 851 and 1337 patients in primary and secondary prevention, respectively. Our cost analysis took into account the perspective of the Brazilian public health system, and all values were converted to Int$. RESULTS In the NMA, SGLT2i [HR: 0.81 (95% CI 0.69-0.96)], GLP-1A [HR: 0.79 (95% CI 0.67-0.94)], and pioglitazone [HR: 0.73 (95% CI 0.59-0.91)] demonstrated reduced relative risks of non-fatal cardiovascular events. In the context of primary prevention, pioglitazone yielded 0.2339 DALYs averted, with an ICER of Int$7,082 (95% CI 4,521-10,770) per DALY averted when compared to standard care. SGLT2i and GLP-1A also increased effectiveness, resulting in 0.261 and 0.259 DALYs averted, respectively, but with higher ICERs of Int$12,061 (95% CI: 7,227-18,121) and Int$29,119 (95% CI: 23,811-35,367) per DALY averted. In the secondary prevention scenario, all three classes of treatments were deemed cost-effective at a maximum willingness-to-pay threshold of Int$26,700. Notably, pioglitazone consistently exhibited the highest probability of being cost-effective in both scenarios. CONCLUSIONS In Brazil, pioglitazone presented a higher probability of being cost-effective both in primary and secondary prevention, followed by SGLT2i and GLP-1A. Our findings support the use of cost-effectiveness models to build optimized and hierarchical therapeutic strategy in the management of T2DM. TRIAL REGISTRATION CRD42020194415.
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Affiliation(s)
- Ana Claudia Cavalcante Nogueira
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
- Escola Superior de Ciências da Saúde (ESCS), Brasília, Distrito Federal, Brazil
| | - Joaquim Barreto
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
| | - Filipe A Moura
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Beatriz Luchiari
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
| | - Abrão Abuhab
- Heart Institute (InCor), Do Hospital das Clínicas - FMUSP, Sao Paulo, Brazil
| | - Isabella Bonilha
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
| | - Wilson Nadruz
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
| | | | - Thomas Gaziano
- Department of Cardiovascular Medicine, Brigham & Women's Hospital, Boston, MA, USA
| | - Luiz Sergio F de Carvalho
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil
- Clarity Healthcare Intelligence, Jundiaí, SP, Brasil
| | - Andrei C Sposito
- Cardiology Division, Unicamp Medical School, São Paulo, SP, Brazil.
- Atherosclerosis and Vascular Biology Laboratory (Atherolab), State University of Campinas (Unicamp), Sao Paulo, Campinas, 13084-971, Brazil.
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29
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DuMontier C, La J, Bihn J, Corrigan J, Yildirim C, Dharne M, Hassan H, Yellapragada S, Abel GA, Gaziano JM, Do NV, Brophy M, Kim DH, Munshi NC, Fillmore NR, Driver JA. More intensive therapy as more effective treatment for frail patients with multiple myeloma [corrected]. Blood Adv 2023; 7:6275-6284. [PMID: 37582048 PMCID: PMC10589796 DOI: 10.1182/bloodadvances.2023011019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/07/2023] [Accepted: 08/07/2023] [Indexed: 08/17/2023] Open
Abstract
Although randomized controlled trial data suggest that the more intensive triplet bortezomib-lenalidomide-dexamethasone (VRd) is superior to the less intensive doublet lenalidomide-dexamethasone (Rd) in patients newly diagnosed with multiple myeloma (MM), guidelines have historically recommended Rd over VRd for patients who are frail and may not tolerate a triplet. We identified 2573 patients (median age, 69.7 years) newly diagnosed with MM who were initiated on VRd (990) or Rd (1583) in the national US Veterans Affairs health care System from 2004 to 2020. We measured frailty using the Veterans Affairs Frailty Index. To reduce imbalance in confounding, we matched patients for MM stage and 1:1 based on a propensity score. Patients who were moderate-severely frail had a higher prevalence of stage III MM and myeloma-related frailty deficits than patients who were not frail. VRd vs Rd was associated with lower mortality (hazard ratio [HR], 0.81; 95% confidence interval [CI], 0.70-0.94) in the overall matched population. Patients who were moderate-severely frail demonstrated the strongest association (HR 0.74; 95% CI, 0.56-0.97), whereas the association weakened in those who were mildly frail (HR, 0.80; 95% CI, 0.61-1.05) and nonfrail (HR, 0.86; 95% CI, 0.67-1.10). VRd vs Rd was associated with a modestly higher incidence of hospitalizations in the overall population, but this association weakened in patients who were moderate-severely frail. Our findings confirm the benefit of VRd over Rd in US veterans and further suggest that this benefit is strongest in patients with the highest levels of frailty, arguing that more intensive treatment of myeloma may be more effective treatment of frailty itself.
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Affiliation(s)
- Clark DuMontier
- New England Geriatrics Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Boston, MA
- Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Boston, MA
| | - Jennifer La
- Harvard Medical School, Boston, MA
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - John Bihn
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - June Corrigan
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - Cenk Yildirim
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - Mayuri Dharne
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - Hamza Hassan
- Chobanian and Avedisian School of Medicine, Boston University, Boston, MA
- Boston Medical Center, Boston, MA
| | - Sarvari Yellapragada
- Debakey VA Medical Center and Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX
| | - Gregory A. Abel
- Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Boston, MA
| | - J Michael Gaziano
- Division of Aging, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - Nhan V. Do
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Chobanian and Avedisian School of Medicine, Boston University, Boston, MA
| | - Mary Brophy
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Chobanian and Avedisian School of Medicine, Boston University, Boston, MA
| | - Dae H. Kim
- Harvard Medical School, Boston, MA
- Hebrew SeniorLife and Marcus Institute for Aging Research, Boston, MA
| | - Nikhil C. Munshi
- Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Boston, MA
- Veterans Affairs, Boston Healthcare System, Boston, MA
| | - Nathanael R. Fillmore
- Division of Aging, Brigham and Women’s Hospital, Boston, MA
- Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Boston, MA
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Chobanian and Avedisian School of Medicine, Boston University, Boston, MA
| | - Jane A. Driver
- New England Geriatrics Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA
- Division of Aging, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
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30
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Xiong X, Sweet SM, Liu M, Hong C, Bonzel CL, Panickan VA, Zhou D, Wang L, Costa L, Ho YL, Geva A, Mandl KD, Cheng S, Xia Z, Cho K, Gaziano JM, Liao KP, Cai T, Cai T. Knowledge-Driven Online Multimodal Automated Phenotyping System. medRxiv 2023:2023.09.29.23296239. [PMID: 37873131 PMCID: PMC10593060 DOI: 10.1101/2023.09.29.23296239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Though electronic health record (EHR) systems are a rich repository of clinical information with large potential, the use of EHR-based phenotyping algorithms is often hindered by inaccurate diagnostic records, the presence of many irrelevant features, and the requirement for a human-labeled training set. In this paper, we describe a knowledge-driven online multimodal automated phenotyping (KOMAP) system that i) generates a list of informative features by an online narrative and codified feature search engine (ONCE) and ii) enables the training of a multimodal phenotyping algorithm based on summary data. Powered by composite knowledge from multiple EHR sources, online article corpora, and a large language model, features selected by ONCE show high concordance with the state-of-the-art AI models (GPT4 and ChatGPT) and encourage large-scale phenotyping by providing a smaller but highly relevant feature set. Validation of the KOMAP system across four healthcare centers suggests that it can generate efficient phenotyping algorithms with robust performance. Compared to other methods requiring patient-level inputs and gold-standard labels, the fully online KOMAP provides a significant opportunity to enable multi-center collaboration.
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Austin-Zimmerman I, Levey DF, Giannakopoulou O, Deak JD, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse DJ, Gaziano JM, Gottlieb DJ, Polimanti R, Stein MB, Bramon E, Gelernter J. Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. Nat Commun 2023; 14:6059. [PMID: 37770476 PMCID: PMC10539313 DOI: 10.1038/s41467-023-41249-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 08/28/2023] [Indexed: 09/30/2023] Open
Abstract
Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression.
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Affiliation(s)
- Isabelle Austin-Zimmerman
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Olga Giannakopoulou
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Joseph D Deak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Spiros Denaxas
- Health Data Research UK, Institute of Health Informatics, University College London, London, NW1 2DA, UK
| | - Haritz Irizar
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Department of Genetics & Genomic Sciences and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Karoline Kuchenbaecker
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- UCL Genetics Institute, Division of Biosciences, University College London, London, WC1E 6BT, UK
| | - Andrew McQuillin
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
| | - John Concato
- School of Medicine, Yale University, New Haven, CT, 06511, USA
- Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration (FDA), Silver Spring, MD, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel J Gottlieb
- VA Boston Healthcare System, 1400 VFW Parkway (111PI), West Roxbury, MA, 02132, USA
- Division of Sleep and Circadian Disorders, Brigham & Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Departments of Psychiatry and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Elvira Bramon
- Department of Mental Health Neuroscience, Division of Psychiatry, University College London, London, W1T 7BN, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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Sun YV, Liu C, Hui Q, Zhou JJ, Gaziano JM, Wilson PW, Joseph J, Phillips LS. Correction for Collider Bias in the Genome-wide Association Study of Diabetes-Related Heart Failure due to Bidirectional Relationship between Heart Failure and Type 2 Diabetes. medRxiv 2023:2023.09.22.23295915. [PMID: 37808641 PMCID: PMC10557768 DOI: 10.1101/2023.09.22.23295915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Aims Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) across demographic groups. On the other hand, metabolic impairment, including elevated T2D incidence is a hallmark of HF pathophysiology. We investigated the bidirectional relationship between T2D and HF, and identified genetic associations with diabetes-related HF after correction for potential collider bias. Methods We performed a genome-wide association study (GWAS) of HF to identify genetic instrumental variables (GIVs) for HF, and to enable bidirectional Mendelian Randomization (MR) analysis between T2D and HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted GWAS of diabetes-related HF with correction for collider bias. Results We first identified 61 genomic loci, including 24 novel loci, significantly associated with all-cause HF in 114,275 HF cases and over 1.5 million controls of European ancestry. Combined with the summary statistics of a T2D GWAS, we obtained 59 and 82 GIVs for HF and T2D, respectively. Using a two-sample bidirectional MR approach, we estimated that T2D increased HF risk (OR 1.07, 95% CI 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to prevalent HF affecting incidence of T2D. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program, and replicated the associations in the UK Biobank study. Conclusion We identified novel HF-associated loci to enable bidirectional MR study of T2D and HF. Our MR findings support T2D as a HF risk factor and provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci. Evaluation of collider bias should be a critical component when conducting GWAS of complex disease phenotypes such as diabetes-related cardiovascular complications.
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Guardino ET, Tarko L, Wilson PWF, Gaziano JM, Cho K, Gagnon DR, Orkaby AR. Predictive value of ASCVD risk score for mortality and major adverse cardiovascular events in the year following a COVID-19 infection among US Veterans. Int J Cardiol 2023; 387:131120. [PMID: 37330018 PMCID: PMC10270727 DOI: 10.1016/j.ijcard.2023.131120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 06/13/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Morbidity and mortality following COVID-19 infection may be influenced by baseline atherosclerotic cardiovascular disease (ASCVD) risk, yet limited data are available to identify those at highest risk. We examined the association between baseline ASCVD risk with mortality and major adverse cardiovascular events (MACE) in the year following COVID-19 infection. METHODS We evaluated a nationwide retrospective cohort of US Veterans free of ASCVD who were tested for COVID-19. The primary outcome was absolute risk of all-cause mortality in the year following a COVID-19 test among those hospitalized vs. not stratified by baseline VA-ASCVD risk scores. Secondarily, risk of MACE was examined. RESULTS There were 393,683 Veterans tested for COVID-19 and 72,840 tested positive. Mean age was 57 years, 86% were male, and 68% were white. Within 30 days following infection, hospitalized Veterans with VA-ASCVD scores >20% had an absolute risk of death of 24.6% vs. 9.7% (P ≤0.0001) for those who tested positive and negative for COVID-19 respectively. In the year following infection, risk of mortality attenuated with no difference in risk after 60 days. The absolute risk of MACE was similar for Veterans who tested positive or negative for COVID-19. CONCLUSIONS Veterans without clinical ASCVD experienced an increased absolute risk of death within 30 days of a COVID-19 infection compared to Veterans with the same VA-ASCVD risk score who tested negative, but this risk attenuated after 60 days. Whether cardiovascular preventive medications can lower the risk of mortality and MACE in the acute period following COVID-19 infection should be evaluated.
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Affiliation(s)
- Eric T Guardino
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA; Division of Aging, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA.
| | - Laura Tarko
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA
| | - Peter W F Wilson
- Atlanta VA Healthcare System, 1670 Clairmont Road, Decatur, GA 30033, USA; Emory Clinical Cardiology Research Institute, 1462 Clifton Rd NE, 5(th) Floor, Atlanta, GA 30322, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA; Division of Aging, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA
| | - David R Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA; Boston University School of Public Health, Department of Biostatistics, Boston, MA 02118, USA
| | - Ariela R Orkaby
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, 2 2 Avenue de Lafayette, Boston, MA 02111, USA; Division of Aging, Brigham & Women's Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, USA; New England GRECC (Geriatric Research, Education, and Clinical Center) VA Boston Healthcare System, 150 S Huntington St, Boston, MA 02130, USA
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King SD, Veliginti S, Brouwers MCGJ, Ren Z, Zheng W, Setiawan VW, Wilkens LR, Shu XO, Arslan AA, Freeman LEB, Bracci PM, Canzian F, Du M, Gallinger SJ, Giles GG, Goodman PJ, Haiman CA, Kogevinas M, Kooperberg C, LeMarchand L, Neale RE, Visvanathan K, White E, Albanes D, Andreotti G, Babic A, Berndt SI, Brais LK, Brennan P, Buring JE, Rabe KG, Bamlet WR, Chanock SJ, Fuchs CS, Gaziano JM, Giovannucci EL, Hackert T, Hassan MM, Katzke V, Kurtz RC, Lee IM, Malats N, Murphy N, Oberg AL, Orlow I, Porta M, Real FX, Rothman N, Sesso HD, Silverman DT, Thompson IM, Wactawski-Wende J, Wang X, Wentzensen N, Yu H, Zeleniuch-Jacquotte A, Yu K, Wolpin BM, Duell EJ, Li D, Hung RJ, Perdomo S, McCullough ML, Freedman ND, Patel AV, Peters U, Riboli E, Sund M, Tjønneland A, Zhong J, Van Den Eeden SK, Kraft P, Risch HA, Amundadottir LT, Klein AP, Stolzenberg-Solomon RZ, Antwi SO. Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization. Cancer Epidemiol Biomarkers Prev 2023; 32:1265-1269. [PMID: 37351909 PMCID: PMC10529823 DOI: 10.1158/1055-9965.epi-23-0453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/15/2023] [Accepted: 06/16/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.
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Affiliation(s)
- Sontoria D. King
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Swathi Veliginti
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| | - Martijn C. G. J. Brouwers
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Zhewen Ren
- Division of Endocrinology and Metabolic Diseases, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Veronica W. Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lynne R. Wilkens
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Alan A. Arslan
- Departments of Obstetrics and Gynecology, Population Health and Environmental Medicine, NYU Perlmutter Comprehensive Cancer Center, New York, New York, USA
| | - Laura E. Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Paige M. Bracci
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mengmeng Du
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Steven J. Gallinger
- Hepatobiliary/Pancreatic Surgical Oncology Program, University Health Network, Toronto, ON, Canada
- The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Graham G. Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Phyllis J. Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Manolis Kogevinas
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Loic LeMarchand
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Rachel E. Neale
- Population Health Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Emily White
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Gabriella Andreotti
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ana Babic
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lauren K. Brais
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Julie E. Buring
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Kari G. Rabe
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - William R. Bamlet
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Charles S. Fuchs
- Yale Cancer Center, New Haven, Connecticut, USA
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Smilow Cancer Hospital, New Haven, Connecticut, USA
| | - J. Michael Gaziano
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Boston Veteran Affairs Healthcare System, Boston, Massachusetts, USA
| | - Edward L. Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Thilo Hackert
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Manal M. Hassan
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Robert C. Kurtz
- Gastroenterology, Hepatology, and Nutrition Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - I-Min Lee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Núria Malats
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Ann L. Oberg
- Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Irene Orlow
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Miquel Porta
- Hospital del Mar Institute of Medical Research (IMIM), Universitat Autònoma de Barcelona, Spain
| | - Francisco X. Real
- Epithelial Carcinogenesis Group, Spanish National Cancer Research Centre-CNIO, Madrid, Spain
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Howard D. Sesso
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Debra T. Silverman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ian M. Thompson
- CHRISTUS Santa Rosa Hospital – Medical Center, San Antonio, Texas, USA
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, University of Buffalo, Buffalo, New York, USA
| | - Xiaoliang Wang
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Herbert Yu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Anne Zeleniuch-Jacquotte
- Departments of Population Health and Environmental Medicine, NYU Perlmutter Comprehensive Cancer Center, New York, New York, USA
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Brian M. Wolpin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Eric J. Duell
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rayjean J. Hung
- Lunenfeld-Tanenbaum Research Institute of Sinai Health System, University of Toronto, Toronto, Canada
| | - Sandra Perdomo
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | | | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Alpa V. Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Elio Riboli
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Malin Sund
- Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden
| | | | - Jun Zhong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Stephen K. Van Den Eeden
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Harvey A. Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA
| | - Laufey T. Amundadottir
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Alison P. Klein
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Rachael Z. Stolzenberg-Solomon
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Samuel O. Antwi
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Jacksonville, Florida, USA
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Robinson-Cohen C, Triozzi JL, Rowan B, He J, Chen HC, Zheng NS, Wei WQ, Wilson OD, Hellwege JN, Tsao PS, Gaziano JM, Bick A, Matheny ME, Chung CP, Lipworth L, Siew ED, Ikizler TA, Tao R, Hung AM. Genome-Wide Association Study of CKD Progression. J Am Soc Nephrol 2023; 34:1547-1559. [PMID: 37261792 PMCID: PMC10482057 DOI: 10.1681/asn.0000000000000170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 05/25/2023] [Indexed: 06/02/2023] Open
Abstract
SIGNIFICANCE STATEMENT Rapid progression of CKD is associated with poor clinical outcomes. Most previous studies looking for genetic factors associated with low eGFR have used cross-sectional data. The authors conducted a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD, focusing on longitudinal data. They identified three loci (two of them novel) associated with longitudinal eGFR decline. In addition to the known UMOD/PDILT locus, variants within BICC1 were associated with significant differences in longitudinal eGFR slope. Variants within HEATR4 also were associated with differences in eGFR decline, but only among Black/African American individuals without diabetes. These findings help characterize molecular mechanisms of eGFR decline in CKD and may inform new therapeutic approaches for progressive kidney disease. BACKGROUND Rapid progression of CKD is associated with poor clinical outcomes. Despite extensive study of the genetics of cross-sectional eGFR, only a few loci associated with eGFR decline over time have been identified. METHODS We performed a meta-analysis of genome-wide association studies of eGFR decline among 116,870 participants with CKD-defined by two outpatient eGFR measurements of <60 ml/min per 1.73 m 2 , obtained 90-365 days apart-from the Million Veteran Program and Vanderbilt University Medical Center's DNA biobank. The primary outcome was the annualized relative slope in outpatient eGFR. Analyses were stratified by ethnicity and diabetes status and meta-analyzed thereafter. RESULTS In cross-ancestry meta-analysis, the strongest association was rs77924615, near UMOD / PDILT ; each copy of the G allele was associated with a 0.30%/yr faster eGFR decline ( P = 4.9×10 -27 ). We also observed an association within BICC1 (rs11592748), where every additional minor allele was associated with a 0.13%/yr slower eGFR decline ( P = 5.6×10 -9 ). Among participants without diabetes, the strongest association was the UMOD/PDILT variant rs36060036, associated with a 0.27%/yr faster eGFR decline per copy of the C allele ( P = 1.9×10 -17 ). Among Black participants, a significantly faster eGFR decline was associated with variant rs16996674 near APOL1 (R 2 =0.29 with the G1 high-risk genotype); among Black participants with diabetes, lead variant rs11624911 near HEATR4 also was associated with a significantly faster eGFR decline. We also nominally replicated loci with known associations with eGFR decline, near PRKAG2, FGF5, and C15ORF54. CONCLUSIONS Three loci were significantly associated with longitudinal eGFR change at genome-wide significance. These findings help characterize molecular mechanisms of eGFR decline and may contribute to the development of new therapeutic approaches for progressive CKD.
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Affiliation(s)
- Cassianne Robinson-Cohen
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jefferson L Triozzi
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Bryce Rowan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Hua C Chen
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Neil S Zheng
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Otis D Wilson
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- VA Tennessee Valley Healthcare System, Clinical Sciences Research and Development, Nashville, Tennessee
| | - Jacklyn N Hellwege
- VA Tennessee Valley Healthcare System, Clinical Sciences Research and Development, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Philip S Tsao
- Department of Medicine, Division of Cardiovascular Medicine, VA Palo Alto Health Care System, Palo Alto, California
- Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital and Harvard School of Medicine, Boston, Massachusetts
| | - Alexander Bick
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Michael E Matheny
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
- Geriatrics Research Education and Clinical Care Service, VA Tennessee Valley Healthcare System, Nashville, Tennessee
| | - Cecilia P Chung
- VA Tennessee Valley Healthcare System, Clinical Sciences Research and Development, Nashville, Tennessee
- Division of Rheumatology and Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Loren Lipworth
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Edward D Siew
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - T Alp Ikizler
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Vanderbilt Center for Kidney Disease, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- VA Tennessee Valley Healthcare System, Clinical Sciences Research and Development, Nashville, Tennessee
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Li A, May SB, La J, Martens KL, Amos CI, Flowers CR, Do NV, Brophy MT, Chitalia V, Ravid K, Gaziano JM, Fillmore NR. Venous thromboembolism risk in cancer patients receiving first-line immune checkpoint inhibitor versus chemotherapy. Am J Hematol 2023; 98:1214-1222. [PMID: 37161855 PMCID: PMC10569448 DOI: 10.1002/ajh.26954] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/14/2023] [Accepted: 04/24/2023] [Indexed: 05/11/2023]
Abstract
It remains unclear if immune checkpoint inhibitor (ICI) therapy is associated with higher rate of venous thromboembolism (VTE) compared with cytotoxic chemotherapy (chemo) in patients with comparable cancer type, staging, and comorbidities. Using the national Veterans Affairs healthcare system database from 2016 to 2021, we performed a propensity score (PS)-weighted retrospective cohort study to compare the incidence of VTE in patients with selected stage III/IV cancer receiving first-line ICI versus chemo. The PS model utilized overlap weights to balance age, sex, race, treatment year, VTE history, paralysis/immobilization, prolonged hospitalization, cancer type, staging, time between diagnosis and treatment, and National Cancer Institute comorbidity index. Weighted Cox regressions with robust standard error were used to assess the hazard ratio (HR) and 95% confidence interval (CI). We found that among comparable advanced cancers, first-line ICI (n = 1823) and first-line chemo (n = 6345) had similar rates of VTE (8.49% for ICI and 8.36% for chemo at 6 months). The weighted HR was 1.06 (95% CI 0.88-1.26) for ICI versus chemo. In a subgroup analysis restricted to lung cancers, first-line ICI/chemo (n = 828), ICI monotherapy (n = 428), and chemo monotherapy (n = 4371) had similar rates of VTE (9.60% for ICI/chemo, 10.04% for ICI, and 8.91% for chemo at 6 months). The weighted HR was 1.05 (95% CI 0.77-1.42) for ICI versus chemo, and 1.08 (95% CI 0.83-1.42) for ICI/chemo versus chemo. In conclusion, ICI as a systemic therapy has a similarly elevated risk as cytotoxic chemo for VTE occurrence in cancer patients. This finding can inform future prospective studies exploring thromboprophylaxis strategies.
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Affiliation(s)
- Ang Li
- Section of Hematology-Oncology, Baylor College of Medicine, Houston, TX
| | - Sarah B May
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, TX
| | - Jennifer La
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Harvard Medical School, Boston, MA
| | - Kylee L Martens
- Division of Hematology-Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR
| | - Christopher I Amos
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, TX
- Section of Epidemiology and Population Science, Baylor College of Medicine, Houston, TX
| | - Christopher R Flowers
- Department of Lymphoma-Myeloma, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Nhan V Do
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - Mary T Brophy
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - Vipul Chitalia
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - Katya Ravid
- Boston University Chobanian & Avedisian School of Medicine, Boston, MA
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Harvard Medical School, Boston, MA
| | - Nathanael R Fillmore
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Harvard Medical School, Boston, MA
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Guardino ET, Li Y, Nguyen XM, Wilson PWF, Gaziano JM, Cho K, Benjamin EJ, Djoussé L. Dietary ω-3 fatty acids and the incidence of atrial fibrillation in the Million Veteran Program. Am J Clin Nutr 2023; 118:406-411. [PMID: 37353210 PMCID: PMC10447488 DOI: 10.1016/j.ajcnut.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/22/2023] [Accepted: 06/01/2023] [Indexed: 06/25/2023] Open
Abstract
BACKGROUND Although recent large randomized clinical trials have reported an increased risk of atrial fibrillation (AF) with marine ω-3 fatty acid supplements, it is unclear whether dietary marine ω-3 fatty acids assessed through food frequency questionnaires are associated with AF risk. OBJECTIVES We sought to test the hypothesis that dietary eicosapentaenoic acid/docosahexaenoic acid/docosapentaecnoic acid (EPA/DHA/DPA) is associated with a higher risk of AF in a large prospective cohort of US Veterans. METHODS We analyzed data from Million Veteran Program participants who completed self-reported food frequency questionnaires. We used multivariable Cox regression to estimate the HRs of AF across quintiles of ω-3 fatty acid consumption and a cubic spline analysis to assess the dose-response relations between ω-3 fatty acids and AF. RESULTS Of the 301,294 veterans studied, the median intake of ω-3 fatty acids (EPA/DHA/DPA) was 219 mg/d (IQR: 144-575), and the mean age was 64.9 y (SD: 12.0); 91% were men, and 84% were White. Consumption of EPA/DHA/DPA exhibited a nonlinear inverse relation with incident AF characterized by an initial decline to 11% at 750 mg/d of marine ω-3 fatty acid intake followed by a plateau. CONCLUSIONS Contrary to our hypothesis, dietary EPA/DHA/DPA was not associated with a higher risk of AF but was inversely related to AF risk in a nonlinear manner.
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Affiliation(s)
- Eric T Guardino
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Division of Aging, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, United States.
| | - Yanping Li
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States
| | - Xuan-Mai Nguyen
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States
| | - Peter W F Wilson
- Atlanta VA Healthcare System, Decatur, GA, United States; Emory Clinical Cardiology Research Institute, Atlanta, GA, United States
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Division of Aging, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States
| | - Emelia J Benjamin
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine/Boston Medical Center, Boston, MA, United States; Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States
| | - Luc Djoussé
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, United States; Division of Aging, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, United States; Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States
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Wu Z, Petrick JL, Florio AA, Guillemette C, Beane Freeman LE, Buring JE, Bradwin G, Caron P, Chen Y, Eliassen AH, Engel LS, Freedman ND, Gaziano JM, Giovannuci EL, Hofmann JN, Huang WY, Kirsh VA, Kitahara CM, Koshiol J, Lee IM, Liao LM, Newton CC, Palmer JR, Purdue MP, Rohan TE, Rosenberg L, Sesso HD, Sinha R, Stampfer MJ, Um CY, Van Den Eeden SK, Visvanathan K, Wactawski-Wende J, Zeleniuch-Jacquotte A, Zhang X, Graubard BI, Campbell PT, McGlynn KA. Endogenous sex steroid hormones and risk of liver cancer among US men: Results from the Liver Cancer Pooling Project. JHEP Rep 2023; 5:100742. [PMID: 37425211 PMCID: PMC10326694 DOI: 10.1016/j.jhepr.2023.100742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/28/2023] [Accepted: 03/03/2023] [Indexed: 07/11/2023] Open
Abstract
Background & Aims Incidence rates of liver cancer in most populations are two to three times higher among men than women. The higher rates among men have led to the suggestion that androgens are related to increased risk whereas oestrogens are related to decreased risk. This hypothesis was investigated in the present study via a nested case-control analysis of pre-diagnostic sex steroid hormone levels among men in five US cohorts. Methods Concentrations of sex steroid hormones and sex hormone-binding globulin were quantitated using gas chromatography-mass spectrometry and a competitive electrochemiluminescence immunoassay, respectively. Multivariable conditional logistic regression was used to calculate odds ratios (ORs) and 95% CIs for associations between hormones and liver cancer among 275 men who subsequently developed liver cancer and 768 comparison men. Results Higher concentrations of total testosterone (OR per one-unit increase in log2 = 1.77, 95% CI = 1.38-2.29), dihydrotestosterone (OR = 1.76, 95% CI = 1.21-2.57), oestrone (OR = 1.74, 95% CI = 1.08-2.79), total oestradiol (OR = 1.58, 95% CI=1.22-20.05), and sex hormone-binding globulin (OR = 1.63, 95% CI = 1.27-2.11) were associated with increased risk. Higher concentrations of dehydroepiandrosterone (DHEA), however, were associated with a 53% decreased risk (OR = 0.47, 95% CI = 0.33-0.68). Conclusions Higher concentrations of both androgens (testosterone, dihydrotestosterone) and their aromatised oestrogenic metabolites (oestrone, oestradiol) were observed among men who subsequently developed liver cancer compared with men who did not. As DHEA is an adrenal precursor of both androgens and oestrogens, these results may suggest that a lower capacity to convert DHEA to androgens, and their subsequent conversion to oestrogens, confers a lower risk of liver cancer, whereas a greater capacity to convert DHEA confers a greater risk. Impact and implications This study does not fully support the current hormone hypothesis as both androgen and oestrogen levels were associated with increased risk of liver cancer among men. The study also found that higher DHEA levels were associated with lower risk, thus suggesting the hypothesis that greater capacity to convert DHEA could be associated with increased liver cancer risk among men.
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Affiliation(s)
- Zeni Wu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Andrea A. Florio
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Chantal Guillemette
- Pharmacogenomics Laboratory, Centre Hospitalier Universitaire de Québec-(CHU de Québec) Research Center–Université Laval, Québec, QC, Canada
- Faculty of Pharmacy and Cancer Research Center, Laval University, Québec, QC, Canada
| | - Laura E. Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Julie E. Buring
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Gary Bradwin
- Clinical and Epidemiologic Research Laboratory, Department of Laboratory Medicine, Boston Children’s Hospital, Boston, MA, USA
| | - Patrick Caron
- Pharmacogenomics Laboratory, Centre Hospitalier Universitaire de Québec-(CHU de Québec) Research Center–Université Laval, Québec, QC, Canada
| | - Yu Chen
- Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - A. Heather Eliassen
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Lawrence S. Engel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - J. Michael Gaziano
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Edward L. Giovannuci
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jonathan N. Hofmann
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Victoria A. Kirsh
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Cari M. Kitahara
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Jill Koshiol
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - I-Min Lee
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Linda M. Liao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Julie R. Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Mark P. Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Thomas E. Rohan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, NY, USA
| | - Lynn Rosenberg
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Howard D. Sesso
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Rashmi Sinha
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Meir J. Stampfer
- Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Caroline Y. Um
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | | | - Kala Visvanathan
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA
| | | | - Xuehong Zhang
- Department of Nutrition, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Barry I. Graubard
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Katherine A. McGlynn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
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Ross JM, Sugimoto JD, Timmons A, Adams J, Deardoff K, Korpak A, Liu C, Moore K, Wilson D, Bedimo R, Chang KM, Cho K, Crothers K, Garshick E, Gaziano JM, Holodniy M, Hunt CM, Isaacs SN, Le E, Jones BE, Shah JA, Smith NL, Lee JS. Early Outcomes of SARS-CoV-2 Infection in a Multisite Prospective Cohort of Inpatient Veterans. Open Forum Infect Dis 2023; 10:ofad330. [PMID: 37484899 PMCID: PMC10358428 DOI: 10.1093/ofid/ofad330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/23/2023] [Indexed: 07/25/2023] Open
Abstract
Background Over 870 000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have occurred among Veterans Health Administration users, and 24 000 have resulted in death. We examined early outcomes of SARS-CoV-2 infection in hospitalized veterans. Methods In an ongoing, prospective cohort study, we enrolled veterans age ≥18 tested for SARS-CoV-2 and hospitalized at 15 Department of Veterans Affairs medical centers between February 2021 and June 2022. We estimated adjusted odds ratios (aORs), adjusted incidence rate ratios (aIRRs), and adjusted hazard ratios (aHRs) for maximum illness severity within 30 days of study entry (defined using the 4-category VA Severity Index for coronavirus disease 2019 [COVID-19]), as well as length of hospitalization and rehospitalization within 60 days, in relationship with demographic characteristics, Charlson comorbidity index (CCI), COVID-19 vaccination, and calendar period of enrollment. Results The 542 participants included 329 (61%) who completed a primary vaccine series (with or without booster; "vaccinated"), 292 (54%) enrolled as SARS-CoV-2-positive, and 503 (93%) men, with a mean age of 64.4 years. High CCI scores (≥5) occurred in 61 (44%) vaccinated and 29 (19%) unvaccinated SARS-CoV-2-positive participants. Severe illness or death occurred in 29 (21%; 6% died) vaccinated and 31 (20%; 2% died) unvaccinated SARS-CoV-2-positive participants. SARS-CoV-2-positive inpatients per unit increase in CCI had greater multivariable-adjusted odds of severe illness (aOR, 1.21; 95% CI, 1.01-1.45), more hospitalization days (aIRR, 1.06; 95% CI, 1.03-1.10), and rehospitalization (aHR, 1.07; 95% CI, 1.01-1.12). Conclusions In a cohort of hospitalized US veterans with SARS-CoV-2 infection, those with a higher CCI had more severe COVID-19 illness, more hospital days, and rehospitalization, after adjusting for vaccination status, age, sex, and calendar period.
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Affiliation(s)
- Jennifer M Ross
- VA Puget Sound Health Care System, Seattle, Washington, USA
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA
| | | | - Andrew Timmons
- VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Jonathan Adams
- VA Puget Sound Health Care System, Seattle, Washington, USA
| | | | - Anna Korpak
- VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Cindy Liu
- VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Kathryn Moore
- VA Puget Sound Health Care System, Seattle, Washington, USA
| | - Deanna Wilson
- VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Roger Bedimo
- VA North Texas Health Care System, Dallas, Texas, USA
- Department of Medicine, University of Texas—Southwestern Medical Center, Dallas, Texas, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kelly Cho
- VA Boston Health Care System, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Kristina Crothers
- VA Puget Sound Health Care System, Seattle, Washington, USA
- Division of Pulmonary and Critical Care, University of Washington, Seattle, Washington, USA
| | - Eric Garshick
- VA Boston Health Care System, Boston, Massachusetts, USA
- Chobanian & Avedisian School of Medicine, Boston University, Boston, Massachusetts, USA
| | - J Michael Gaziano
- VA Boston Health Care System, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Mark Holodniy
- VA Palo Alto Health Care System, Palo Alto, California, USA
- Department of Medicine—Infectious Diseases, Stanford University, Palo Alto, California, USA
| | - Christine M Hunt
- VA Durham Health Care System, Durham, North Carolina, USA
- Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA
| | - Stuart N Isaacs
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Elizabeth Le
- VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Barbara E Jones
- VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Javeed A Shah
- VA Puget Sound Health Care System, Seattle, Washington, USA
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA
| | - Nicholas L Smith
- VA Puget Sound Health Care System, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, California, USA
- Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine, and, by courtesy, Department of Epidemiology and Population Health, Stanford University, Palo Alto, California, USA
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Chen F, Madduri RK, Rodriguez AA, Darst BF, Chou A, Sheng X, Wang A, Shen J, Saunders EJ, Rhie SK, Bensen JT, Ingles SA, Kittles RA, Strom SS, Rybicki BA, Nemesure B, Isaacs WB, Stanford JL, Zheng W, Sanderson M, John EM, Park JY, Xu J, Wang Y, Berndt SI, Huff CD, Yeboah ED, Tettey Y, Lachance J, Tang W, Rentsch CT, Cho K, Mcmahon BH, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Sellers TA, Yamoah K, Murphy AB, Crawford DC, Patel AV, Bush WS, Aldrich MC, Cussenot O, Petrovics G, Cullen J, Neslund-Dudas CM, Stern MC, Kote-Jarai Z, Govindasami K, Cook MB, Chokkalingam AP, Hsing AW, Goodman PJ, Hoffmann TJ, Drake BF, Hu JJ, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Idowu MO, Popoola O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Mensah JE, Diop H, Van Den Eeden SK, Blanchet P, Fowke JH, Casey G, Hennis AJ, Lubwama A, Thompson IM, Leach R, Easton DF, Preuss MH, Loos RJ, Gundell SM, Wan P, Mohler JL, Fontham ET, Smith GJ, Taylor JA, Srivastava S, Eeles RA, Carpten JD, Kibel AS, Multigner L, Parent MÉ, Menegaux F, Cancel-Tassin G, Klein EA, Andrews C, Rebbeck TR, Brureau L, Ambs S, Edwards TL, Watya S, Chanock SJ, Witte JS, Blot WJ, Michael Gaziano J, Justice AC, Conti DV, Haiman CA. Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry. Eur Urol 2023; 84:13-21. [PMID: 36872133 PMCID: PMC10424812 DOI: 10.1016/j.eururo.2023.01.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 12/14/2022] [Accepted: 01/24/2023] [Indexed: 03/06/2023]
Abstract
BACKGROUND Genetic factors play an important role in prostate cancer (PCa) susceptibility. OBJECTIVE To discover common genetic variants contributing to the risk of PCa in men of African ancestry. DESIGN, SETTING, AND PARTICIPANTS We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness. RESULTS AND LIMITATIONS Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4). CONCLUSIONS This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry. PATIENT SUMMARY In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.
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Affiliation(s)
- Fei Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Burcu F Darst
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Alisha Chou
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xin Sheng
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Anqi Wang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jiayi Shen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Suhn K Rhie
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jeannette T Bensen
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sue A Ingles
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rick A Kittles
- Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - Sara S Strom
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Benjamin A Rybicki
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - William B Isaacs
- James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Esther M John
- Department of Medicine, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Jong Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Jianfeng Xu
- Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Ying Wang
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Chad D Huff
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | | | - Yao Tettey
- Department of Pathology, University of Ghana, Accra, Ghana; Korle Bu Teaching Hospital, Accra, Ghana
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Wei Tang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Christopher T Rentsch
- Yale School of Medicine, New Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Kelly Cho
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Jamaica Plain, MA, USA
| | - Benjamin H Mcmahon
- Theoretical Biology Division, Los Alamos National Lab, Los Alamos, NM, USA
| | | | - Andrew A Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | - Evelyn Tay
- Korle Bu Teaching Hospital, Accra, Ghana
| | | | | | - Thomas A Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kosj Yamoah
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA; Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Adam B Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Dana C Crawford
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Alpa V Patel
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Melinda C Aldrich
- Division of Epidemiology, Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Olivier Cussenot
- Department of Urology and Predictive Onco-Urology Group, Sorbonne Université, GRC 5 Predictive Onco-Urology, APHP-Sorbonne Université, Paris, France; CeRePP, Tenon Hospital, Paris, France
| | - Gyorgy Petrovics
- Department of Surgery, Center for Prostate Disease Research, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Jennifer Cullen
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA; Department of Surgery, Center for Prostate Disease Research, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | | | - Mariana C Stern
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Michael B Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | | | - Ann W Hsing
- Department of Medicine, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Phyllis J Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Thomas J Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Bettina F Drake
- Division of Public Health Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Jennifer J Hu
- The University of Miami School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Jacob M Keaton
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jacklyn N Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Nashville, TN, USA
| | - Peter E Clark
- Atrium Health/Levine Cancer Institute, Charlotte, NC, USA
| | | | | | | | - Olufemi Ogunbiyi
- College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Michael O Idowu
- College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Olufemi Popoola
- College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Akindele O Adebiyi
- College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Oseremen I Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Hafees O Ajibola
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Mustapha A Jamda
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Olabode P Oluwole
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Maxwell Nwegbu
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | | | | | | | | | - Halimatou Diop
- Laboratoires Bacteriologie et Virologie, Hôpital Aristide Le Dantec, Dakar, Senegal
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA
| | - Pascal Blanchet
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, Guadeloupe, France
| | - Jay H Fowke
- Department of Preventive Medicine, Division of Epidemiology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Graham Casey
- Department of Public Health Science, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Anselm J Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | | | - Ian M Thompson
- CHRISTUS Santa Rosa Medical Center Hospital, San Antonio, TX, USA
| | - Robin Leach
- Department of Urology, Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Susan M Gundell
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peggy Wan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - James L Mohler
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Urology, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Elizabeth T Fontham
- School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, USA
| | - Gary J Smith
- Department of Urology, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA; Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Shiv Srivastava
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Rosaline A Eeles
- The Institute of Cancer Research, London, UK; Royal Marsden NHS Foundation Trust, London, UK
| | - John D Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Adam S Kibel
- Department of Urology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Luc Multigner
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Marie-Élise Parent
- Epidemiology and Biostatistics Unit, Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique, Laval, QC, Canada
| | - Florence Menegaux
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif Cédex, France; Paris-Sud University, Villejuif Cédex, France
| | - Geraldine Cancel-Tassin
- Department of Urology and Predictive Onco-Urology Group, Sorbonne Université, GRC 5 Predictive Onco-Urology, APHP-Sorbonne Université, Paris, France; CeRePP, Tenon Hospital, Paris, France
| | - Eric A Klein
- Cleveland Clinic Lerner Research Institute, Cleveland, OH, USA
| | - Caroline Andrews
- Harvard TH Chan School of Public Health and Division of Population Sciences, Dana Farber Cancer Institute, Boston, MA, USA; Glickman Urological & Kidney Institute, Cleveland, OH, USA
| | - Timothy R Rebbeck
- Harvard TH Chan School of Public Health and Division of Population Sciences, Dana Farber Cancer Institute, Boston, MA, USA
| | - Laurent Brureau
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, Guadeloupe, France
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; International Epidemiology Institute, Rockville, MD, USA
| | - J Michael Gaziano
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - David V Conti
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Lui AJ, Pagadala MS, Zhong AY, Lynch J, Karunamuni R, Lee KM, Plym A, Rose BS, Carter H, Kibel AS, DuVall SL, Gaziano JM, Panizzon MS, Hauger RL, Seibert TM. Agent Orange exposure and prostate cancer risk in the Million Veteran Program. medRxiv 2023:2023.06.14.23291413. [PMID: 37398205 PMCID: PMC10312838 DOI: 10.1101/2023.06.14.23291413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Purpose Exposure to Agent Orange, a known carcinogen, might increase risk of prostate cancer (PCa). We sought to investigate the association of Agent Orange exposure and PCa risk when accounting for race/ethnicity, family history, and genetic risk in a diverse population of US Vietnam War veterans. Methods & Materials This study utilized the Million Veteran Program (MVP), a national, population-based cohort study of United States military veterans conducted 2011-2021 with 590,750 male participants available for analysis. Agent Orange exposure was obtained using records from the Department of Veterans Affairs (VA) using the US government definition of Agent Orange exposure: active service in Vietnam while Agent Orange was in use. Only veterans who were on active duty (anywhere in the world) during the Vietnam War were included in this analysis (211,180 participants). Genetic risk was assessed via a previously validated polygenic hazard score calculated from genotype data. Age at diagnosis of any PCa, diagnosis of metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. Results Exposure to Agent Orange was associated with increased PCa diagnosis (HR 1.04, 95% CI 1.01-1.06, p=0.003), primarily among Non-Hispanic White men (HR 1.09, 95% CI 1.06- 1.12, p<0.001). When accounting for race/ethnicity and family history, Agent Orange exposure remained an independent risk factor for PCa diagnosis (HR 1.06, 95% CI 1.04-1.09, p<0.05). Univariable associations of Agent Orange exposure with PCa metastasis (HR 1.08, 95% CI 0.99-1.17) and PCa death (HR 1.02, 95% CI 0.84-1.22) did not reach significance on multivariable analysis. Similar results were found when accounting for polygenic hazard score. Conclusions Among US Vietnam War veterans, Agent Orange exposure is an independent risk factor for PCa diagnosis, though associations with PCa metastasis or death are unclear when accounting for race/ethnicity, family history, and/or polygenic risk.
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Li A, La J, May SB, Guffey D, da Costa WL, Amos CI, Bandyo R, Milner EM, Kurian KM, Chen DC, Do NV, Granada C, Riaz N, Brophy MT, Chitalia V, Gaziano JM, Garcia DA, Carrier M, Flowers CR, Zakai NA, Fillmore NR. Derivation and Validation of a Clinical Risk Assessment Model for Cancer-Associated Thrombosis in Two Unique US Health Care Systems. J Clin Oncol 2023; 41:2926-2938. [PMID: 36626707 PMCID: PMC10431461 DOI: 10.1200/jco.22.01542] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/25/2022] [Accepted: 12/01/2022] [Indexed: 01/12/2023] Open
Abstract
PURPOSE Venous thromboembolism (VTE), especially pulmonary embolism (PE) and lower extremity deep vein thrombosis (LE-DVT), is a serious and potentially preventable complication for patients with cancer undergoing systemic therapy. METHODS Using retrospective data from patients diagnosed with incident cancer from 2011-2020, we derived a parsimonious risk assessment model (RAM) using least absolute shrinkage and selection operator regression from the Harris Health System (HHS, n = 9,769) and externally validated it using the Veterans Affairs (VA) health care system (n = 79,517). Bootstrapped c statistics and calibration curves were used to assess external model discrimination and fit. Dichotomized risk strata using integer scores were created and compared against the Khorana score (KS). RESULTS Incident VTE and PE/LE-DVT at 6 months occurred in 590 (6.2%) and 437 (4.6%) patients in HHS and 4,027 (5.1%) and 3,331 (4.2%) patients in the VA health care system. Assessed at the time of systemic therapy initiation, the new RAM included components of the KS with the modified cancer subtype, cancer staging, systemic therapy class, history of VTE, history of paralysis/immobility, recent hospitalization, and Asian/Pacific Islander race. The c statistic was 0.71 in HHS and 0.68 in the VA health care system (compared with 0.65 and 0.60, respectively, for KS). Furthermore, the new RAM appropriately reclassified 28% of patients and increased the proportion of VTEs in the high-risk group from 37% to 68% in the validation data set. CONCLUSION The novel RAM stratified patients with cancer into a high-risk group with 8%-10% cumulative incidence of VTE and 7% PE/LE-DVT at 6 months (v 3% and 2%, respectively, in the low-risk group). The model had improved performance over the original KS and doubled the number of VTE events in the high-risk stratum. We encourage additional external validation from prospective studies.[Media: see text].
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Affiliation(s)
- Ang Li
- Section of Hematology-Oncology, Baylor College of Medicine, Houston, TX
| | - Jennifer La
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
| | - Sarah B. May
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, TX
| | - Danielle Guffey
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, TX
| | - Wilson L. da Costa
- Section of Epidemiology and Population Science, Baylor College of Medicine, Houston, TX
| | - Christopher I. Amos
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, TX
- Section of Epidemiology and Population Science, Baylor College of Medicine, Houston, TX
| | | | | | | | - Daniel C.R. Chen
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Section of General Internal Medicine, Boston University School of Medicine, Boston, MA
| | - Nhan V. Do
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Section of General Internal Medicine, Boston University School of Medicine, Boston, MA
| | - Carolina Granada
- Section of Hematology-Oncology, Baylor College of Medicine, Houston, TX
| | - Nimrah Riaz
- Section of Hematology-Oncology, Baylor College of Medicine, Houston, TX
| | - Mary T. Brophy
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Section of Hematology & Medical Oncology, Boston University School of Medicine, Boston, MA
| | - Vipul Chitalia
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Renal Section, Department of Medicine, Boston University School of Medicine, Boston, MA
- Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of Aging, Brigham and Women's Hospital, Boston, MA
| | - David A. Garcia
- Division of Hematology, University of Washington School of Medicine, Seattle, WA
| | - Marc Carrier
- Department of Medicine, Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Christopher R. Flowers
- Division of Cancer Medicine, Department of Lymphoma-Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Neil A. Zakai
- Departments of Medicine and Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT
| | - Nathanael R. Fillmore
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA
- Section of Hematology & Medical Oncology, Boston University School of Medicine, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
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Vassy JL, Posner DC, Ho YL, Gagnon DR, Galloway A, Tanukonda V, Houghton SC, Madduri RK, McMahon BH, Tsao PS, Damrauer SM, O’Donnell CJ, Assimes TL, Casas JP, Gaziano JM, Pencina MJ, Sun YV, Cho K, Wilson PW. Cardiovascular Disease Risk Assessment Using Traditional Risk Factors and Polygenic Risk Scores in the Million Veteran Program. JAMA Cardiol 2023; 8:564-574. [PMID: 37133828 PMCID: PMC10157509 DOI: 10.1001/jamacardio.2023.0857] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 03/09/2023] [Indexed: 05/04/2023]
Abstract
Importance Primary prevention of atherosclerotic cardiovascular disease (ASCVD) relies on risk stratification. Genome-wide polygenic risk scores (PRSs) are proposed to improve ASCVD risk estimation. Objective To determine whether genome-wide PRSs for coronary artery disease (CAD) and acute ischemic stroke improve ASCVD risk estimation with traditional clinical risk factors in an ancestrally diverse midlife population. Design, Setting, and Participants This was a prognostic analysis of incident events in a retrospectively defined longitudinal cohort conducted from January 1, 2011, to December 31, 2018. Included in the study were adults free of ASCVD and statin naive at baseline from the Million Veteran Program (MVP), a mega biobank with genetic, survey, and electronic health record data from a large US health care system. Data were analyzed from March 15, 2021, to January 5, 2023. Exposures PRSs for CAD and ischemic stroke derived from cohorts of largely European descent and risk factors, including age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein (HDL) cholesterol, smoking, and diabetes status. Main Outcomes and Measures Incident nonfatal myocardial infarction (MI), ischemic stroke, ASCVD death, and composite ASCVD events. Results A total of 79 151 participants (mean [SD] age, 57.8 [13.7] years; 68 503 male [86.5%]) were included in the study. The cohort included participants from the following harmonized genetic ancestry and race and ethnicity categories: 18 505 non-Hispanic Black (23.4%), 6785 Hispanic (8.6%), and 53 861 non-Hispanic White (68.0%) with a median (5th-95th percentile) follow-up of 4.3 (0.7-6.9) years. From 2011 to 2018, 3186 MIs (4.0%), 1933 ischemic strokes (2.4%), 867 ASCVD deaths (1.1%), and 5485 composite ASCVD events (6.9%) were observed. CAD PRS was associated with incident MI in non-Hispanic Black (hazard ratio [HR], 1.10; 95% CI, 1.02-1.19), Hispanic (HR, 1.26; 95% CI, 1.09-1.46), and non-Hispanic White (HR, 1.23; 95% CI, 1.18-1.29) participants. Stroke PRS was associated with incident stroke in non-Hispanic White participants (HR, 1.15; 95% CI, 1.08-1.21). A combined CAD plus stroke PRS was associated with ASCVD deaths among non-Hispanic Black (HR, 1.19; 95% CI, 1.03-1.17) and non-Hispanic (HR, 1.11; 95% CI, 1.03-1.21) participants. The combined PRS was also associated with composite ASCVD across all ancestry groups but greater among non-Hispanic White (HR, 1.20; 95% CI, 1.16-1.24) than non-Hispanic Black (HR, 1.11; 95% CI, 1.05-1.17) and Hispanic (HR, 1.12; 95% CI, 1.00-1.25) participants. Net reclassification improvement from adding PRS to a traditional risk model was modest for the intermediate risk group for composite CVD among men (5-year risk >3.75%, 0.38%; 95% CI, 0.07%-0.68%), among women, (6.79%; 95% CI, 3.01%-10.58%), for age older than 55 years (0.25%; 95% CI, 0.03%-0.47%), and for ages 40 to 55 years (1.61%; 95% CI, -0.07% to 3.30%). Conclusions and Relevance Study results suggest that PRSs derived predominantly in European samples were statistically significantly associated with ASCVD in the multiancestry midlife and older-age MVP cohort. Overall, modest improvement in discrimination metrics were observed with addition of PRSs to traditional risk factors with greater magnitude in women and younger age groups.
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Affiliation(s)
- Jason L. Vassy
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Daniel C. Posner
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - Yuk-Lam Ho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - David R. Gagnon
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Ashley Galloway
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | | | | | - Ravi K. Madduri
- Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois
- University of Chicago Consortium for Advanced Science and Engineering, The University of Chicago, Chicago, Illinois
| | - Benjamin H. McMahon
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico
| | - Philip S. Tsao
- Palo Alto VA Healthcare System, Palo Alto, California
- Stanford Cardiovascular Institute, Stanford University, Stanford, California
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | | - Themistocles L. Assimes
- Palo Alto VA Healthcare System, Palo Alto, California
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California
- Stanford Cardiovascular Institute, Stanford University, Stanford, California
| | - Juan P. Casas
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - J. Michael Gaziano
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Michael J. Pencina
- Department of Biostatistics, Duke University Medical Center, Durham, North Carolina
| | - Yan V. Sun
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Kelly Cho
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
| | - Peter W.F. Wilson
- Veterans Affairs Atlanta Healthcare System, Decatur, Georgia
- Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
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Martens KL, Li A, La J, May SB, Swinnerton KN, Tosi H, Elbers DC, Do NV, Brophy MT, Gaziano JM, Lotfollahzadeh S, Chitalia V, Ravid K, Fillmore NR. Epidemiology of Cancer-Associated Venous Thromboembolism in Patients With Solid and Hematologic Neoplasms in the Veterans Affairs Health Care System. JAMA Netw Open 2023; 6:e2317945. [PMID: 37306999 PMCID: PMC10261992 DOI: 10.1001/jamanetworkopen.2023.17945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 04/16/2023] [Indexed: 06/13/2023] Open
Abstract
Importance Identifying changes in epidemiologic patterns of the incidence and risk of cancer-associated thrombosis (CAT), particularly with evolving cancer-directed therapy, is essential for risk stratification. Objective To assess the incidence of CAT over time and to determine pertinent patient-specific, cancer-specific, and treatment-specific factors associated with its risk. Design, Setting, and Participants This longitudinal, retrospective cohort study was conducted from 2006 to 2021. Duration of follow-up was from the date of diagnosis until first venous thromboembolism (VTE) event, death, loss of follow-up (defined as a 90-day gap without clinical encounters), or administrative censoring on April 1, 2022. The study took place within the US Department of Veterans Affairs national health care system. Patients with newly diagnosed invasive solid tumors and hematologic neoplasms were included in the study. Data were analyzed from December 2022 to February 2023. Exposure Newly diagnosed invasive solid tumors and hematologic neoplasms. Main Outcomes Incidence of VTE was assessed using a combination of International Classification of Diseases, Ninth Revision, Clinical Modification and International Statistical Classification of Diseases, Tenth Revision, Clinical Modification and natural language processing confirmed outcomes. Cumulative incidence competing risk functions were used to estimate incidence of CAT. Multivariable Cox regression models were built to assess the association of baseline variables with CAT. Pertinent patient variables included demographics, region, rurality, area deprivation index, National Cancer Institute comorbidity index, cancer type, staging, first-line systemic treatment within 3 months (time-varying covariate), and other factors that could be associated with the risk of VTE. Results A total of 434 203 patients (420 244 men [96.8%]; median [IQR] age, 67 [62-74] years; 7414 Asian or Pacific Islander patients [1.7%]; 20 193 Hispanic patients [4.7%]; 89 371 non-Hispanic Black patients [20.6%]; 313 157 non-Hispanic White patients [72.1%]) met the inclusion criteria. Overall incidence of CAT at 12 months was 4.5%, with yearly trends ranging stably from 4.2% to 4.7%. The risk of VTE was associated with cancer type and stage. In addition to confirming well-known risk distribution among patients with solid tumors, a higher risk of VTE was observed among patients with aggressive lymphoid neoplasms compared with patients with indolent lymphoid or myeloid hematologic neoplasms. Compared with no treatment, patients receiving first-line chemotherapy (hazard ratio [HR], 1.44; 95% CI, 1.40-1.49) and immune checkpoint inhibitors (HR, 1.49; 95% CI, 1.22-1.82) had a higher adjusted relative risk than patients receiving targeted therapy (HR, 1.21; 95% CI, 1.13-1.30) or endocrine therapy (HR, 1.20; 95% CI, 1.12-1.28). Finally, adjusted VTE risk was significantly higher among Non-Hispanic Black patients (HR, 1.23; 95% CI, 1.19-1.27) and significantly lower in Asian or Pacific Islander patients (HR, 0.84; 95% CI, 0.76-0.93) compared with Non-Hispanic White patients. Conclusions and Relevance In this cohort study of patients with cancer, a high incidence of VTE was observed, with yearly trends that remained stable over the 16-year study period. Both novel and known factors associated with the risk of CAT were identified, providing valuable and applicable insights in this current treatment landscape.
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Affiliation(s)
- Kylee L Martens
- Division of Hematology & Medical Oncology, Oregon Health & Science University, Portland
| | - Ang Li
- Section of Hematology-Oncology, Baylor College of Medicine, Houston, Texas
| | - Jennifer La
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Sarah B May
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Institute for Clinical & Translational Research, Baylor College of Medicine, Houston, Texas
| | - Kaitlin N Swinnerton
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
| | - Hannah Tosi
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
| | - Danne C Elbers
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Nhan V Do
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Boston University School of Medicine, Boston, Massachusetts
| | - Mary T Brophy
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Boston University School of Medicine, Boston, Massachusetts
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | | | - Vipul Chitalia
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Boston University School of Medicine, Boston, Massachusetts
| | - Katya Ravid
- Boston University School of Medicine, Boston, Massachusetts
| | - Nathanael R Fillmore
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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Whitbourne SB, Li Y, Brewer JV, Deen J, Gutierrez C, Murphy SA, Lord E, Yan J, Nguyen XMT, Tsao PS, Gaziano JM, Muralidhar S. Overview of Efforts to Increase Women Enrollment in the Veterans Affairs Million Veteran Program. Health Equity 2023; 7:324-332. [PMID: 37284530 PMCID: PMC10240313 DOI: 10.1089/heq.2023.0006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2023] [Indexed: 06/08/2023] Open
Abstract
Background Ensuring enhanced delivery of care to women Veterans is a top Veterans Affairs (VA) priority; however, women are historically underrepresented in research that informs evidence-based health care. A primary barrier to women's participation is the inability to engage with research in person due to a number of documented challenges. The VA Million Veteran Program (MVP) is committed to increasing access for women Veterans to participate in research, thereby better understanding conditions specific to this population and how disease manifests differently in women compared to men. The goal of this work is to describe the results of the MVP Women's Campaign, an effort designed to increase outreach to and awareness of remote enrollment options for women Veterans. Materials and Methods The MVP Women's Campaign launched two phases between March 2021 and April 2022: the Multimedia Phase leveraged a variety of strategic multichannel communication tactics and the Email Phase focused on direct email communication to women Veterans. The effect of the Multimedia Phase was determined using t-tests and chi-square tests, as well as logistic regression models to compare demographic subgroups. The Email Phase was evaluated using comparisons of the enrollment rate across demographic groups through a multivariate adjusted logistic regression model. Results Overall, 4694 women Veterans enrolled during the MVP Women's Campaign (54% during the Multimedia Phase and 46% during the Email Phase). For the Multimedia Phase, the percentage of older women online enrollees increased, along with women from the southwest and western regions of the United States. Differences for women Veteran online enrollment across different ethnicity and race groups were not observed. During the Email Phase, the enrollment rate increased with age. Compared to White women Veterans, Blacks, Asians, and Native Americans were significantly less likely to enroll while Veterans with multiple races were more likely to enroll. Conclusion The MVP Women's Campaign is the first large-scale outreach effort focusing on recruitment of women Veterans into MVP. The combination of print and digital outreach tactics and direct email recruitment resulted in over a fivefold increase in women Veteran enrollees during a 7-month period. Attention to messaging and communication channels, combined with a better understanding of effective recruitment methods for certain Veteran populations, allows MVP the opportunity to advance health and health care not only for women Veterans, but beyond. Lessons learned will be applied to increase other populations in MVP such as Blacks, Hispanics, Asians, Native Americans, younger Veterans, and Veterans with certain health conditions.
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Affiliation(s)
- Stacey B. Whitbourne
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Yanping Li
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Jessica V.V. Brewer
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Jennifer Deen
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia, USA
| | - Claudia Gutierrez
- Million Veteran Program Coordinating Center, VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Sybil A. Murphy
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Emily Lord
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Joseph Yan
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Xuan-Mai T. Nguyen
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
- Carle Illinois College of Medicine, University of Illinois, Champaign, Illinois, USA
| | - Philip S. Tsao
- Million Veteran Program Coordinating Center, VA Palo Alto Health Care System, Palo Alto, California, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, USA
| | - J. Michael Gaziano
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia, USA
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Gan Z, Zhou D, Rush E, Panickan VA, Ho YL, Ostrouchov G, Xu Z, Shen S, Xiong X, Greco KF, Hong C, Bonzel CL, Wen J, Costa L, Cai T, Begoli E, Xia Z, Gaziano JM, Liao KP, Cho K, Cai T, Lu J. ARCH: Large-scale Knowledge Graph via Aggregated Narrative Codified Health Records Analysis. medRxiv 2023:2023.05.14.23289955. [PMID: 37293026 PMCID: PMC10246054 DOI: 10.1101/2023.05.14.23289955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Objective Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes, covering hundreds of thousands of clinical concepts available for research and clinical care. The complex, massive, heterogeneous, and noisy nature of EHR data imposes significant challenges for feature representation, information extraction, and uncertainty quantification. To address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods The ARCH algorithm first derives embedding vectors from a co-occurrence matrix of all EHR concepts and then generates cosine similarities along with associated p -values to measure the strength of relatedness between clinical features with statistical certainty quantification. In the final step, ARCH performs a sparse embedding regression to remove indirect linkage between entity pairs. We validated the clinical utility of the ARCH knowledge graph, generated from 12.5 million patients in the Veterans Affairs (VA) healthcare system, through downstream tasks including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer's disease patients. Results ARCH produces high-quality clinical embeddings and KG for over 60,000 EHR concepts, as visualized in the R-shiny powered web-API (https://celehs.hms.harvard.edu/ARCH/). The ARCH embeddings attained an average area under the ROC curve (AUC) of 0.926 and 0.861 for detecting pairs of similar EHR concepts when the concepts are mapped to codified data and to NLP data; and 0.810 (codified) and 0.843 (NLP) for detecting related pairs. Based on the p -values computed by ARCH, the sensitivity of detecting similar and related entity pairs are 0.906 and 0.888 under false discovery rate (FDR) control of 5%. For detecting drug side effects, the cosine similarity based on the ARCH semantic representations achieved an AUC of 0.723 while the AUC improved to 0.826 after few-shot training via minimizing the loss function on the training data set. Incorporating NLP data substantially improved the ability to detect side effects in the EHR. For example, based on unsupervised ARCH embeddings, the power of detecting drug-side effects pairs when using codified data only was 0.15, much lower than the power of 0.51 when using both codified and NLP concepts. Compared to existing large-scale representation learning methods including PubmedBERT, BioBERT and SAPBERT, ARCH attains the most robust performance and substantially higher accuracy in detecting these relationships. Incorporating ARCH selected features in weakly supervised phenotyping algorithms can improve the robustness of algorithm performance, especially for diseases that benefit from NLP features as supporting evidence. For example, the phenotyping algorithm for depression attained an AUC of 0.927 when using ARCH selected features but only 0.857 when using codified features selected via the KESER network[1]. In addition, embeddings and knowledge graphs generated from the ARCH network were able to cluster AD patients into two subgroups, where the fast progression subgroup had a much higher mortality rate. Conclusions The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.
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Affiliation(s)
| | - Doudou Zhou
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Everett Rush
- Oak Ridge National Laboratory, Oak Ridge, TN USA
| | - Vidul A Panickan
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | | | - Zhiwei Xu
- University of Michigan, Ann Arbor, MI, USA
| | - Shuting Shen
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xin Xiong
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Clara-Lea Bonzel
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Jun Wen
- Harvard Medical School, Boston, MA, USA
| | | | - Tianrun Cai
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Oak Ridge, TN USA
| | - Zongqi Xia
- University of Pittsburgh, Pittsburgh, USA
| | - J Michael Gaziano
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Katherine P Liao
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Kelly Cho
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
| | - Tianxi Cai
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Junwei Lu
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
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Peachey N, Gorman B, Francis M, Nealon C, Halladay C, Duro N, Markianos K, Genovese G, Hysi P, Choquet H, Afshari N, Li YJ, Gaziano JM, Hung A, Wu WC, Greenberg P, Pyarajan S, Lass J, Iyengar S. Multi-ancestry GWAS of Fuchs corneal dystrophy highlights roles of laminins, collagen, and endothelial cell regulation. Res Sq 2023:rs.3.rs-2762003. [PMID: 37205546 PMCID: PMC10187421 DOI: 10.21203/rs.3.rs-2762003/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular pathophysiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program (MVP) and meta-analyzed with the previous largest FECD GWAS, finding twelve significant loci (eight novel). We further confirmed the TCF4 locus in admixed African and Hispanic/Latino ancestries, and found an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and co-localization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California
| | | | | | | | | | | | | | - Saiju Pyarajan
- Center for Data and Computational Sciences, Veterans Affairs Boston Healthcare System
| | - Jonathan Lass
- Case Western Reserve University and University Hospitals Case Medical Center
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La J, DuMontier C, Hassan H, Abdallah M, Edwards C, Verma K, Ferri G, Dharne M, Yildirim C, Corrigan J, Gaziano JM, Do NV, Brophy MT, Driver JA, Munshi NC, Fillmore NR. Validation of algorithms to select patients with multiple myeloma and patients initiating myeloma treatment in the national Veterans Affairs Healthcare System. Pharmacoepidemiol Drug Saf 2023; 32:558-566. [PMID: 36458420 PMCID: PMC10448707 DOI: 10.1002/pds.5579] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 11/13/2022] [Accepted: 11/23/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND We aimed to evaluate and compare the performance of multiple myeloma (MM) selection algorithms for use in Veterans Affairs (VA) research. METHODS Using the VA Corporate Data Warehouse (CDW), the VA Cancer Registry (VACR), and VA pharmacy data, we randomly selected 500 patients from 01/01/1999 to 06/01/2021 who had (1) either one MM diagnostic code OR were listed in the VACR as having MM AND (2) at least one MM treatment code. A team reviewed oncology notes for each veteran to annotate details regarding MM diagnosis and initial treatment within VA. We evaluated inter-annotator agreement and compared the performance of four published algorithms (two developed and validated external to VA data and two used in VA data). RESULTS A total of 859 patients were reviewed to obtain 500 patients who were annotated as having MM and initiating MM treatment in VA. Agreement was high among annotators for all variables: MM diagnosis (98.3% agreement, Kappa = 0.93); initial treatment in VA (91.8% agreement; Kappa = 0.77); and initial treatment classification (87.6% agreement; Kappa = 0.86). VA Algorithms were more specific and had higher PPVs than non-VA algorithms for both MM diagnosis and initial treatment in VA. We developed the "VA Recommended Algorithm," which had the highest PPV among all algorithms in identifying patients diagnosed with MM (PPV = 0.98, 95% CI = 0.95-0.99) and in identifying patients who initiated their MM treatment in VA (PPV = 0.93, 95% CI = 0.90-0.96). CONCLUSION Our VA Recommended Algorithm optimizes sensitivity and PPV for cohort selection and treatment classification.
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Affiliation(s)
- Jennifer La
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Clark DuMontier
- New England Geriatrics Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts, USA
- Division of Aging, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Hamza Hassan
- Boston University School of Medicine, Boston, Massachusetts, USA
- Boston Medical Center, Boston, Massachusetts, USA
| | - Maya Abdallah
- Boston University School of Medicine, Boston, Massachusetts, USA
- Boston Medical Center, Boston, Massachusetts, USA
| | - Camille Edwards
- Boston University School of Medicine, Boston, Massachusetts, USA
- Boston Medical Center, Boston, Massachusetts, USA
| | - Karina Verma
- Boston University School of Medicine, Boston, Massachusetts, USA
- Boston Medical Center, Boston, Massachusetts, USA
| | - Grace Ferri
- Boston University School of Medicine, Boston, Massachusetts, USA
- Boston Medical Center, Boston, Massachusetts, USA
| | - Mayuri Dharne
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Cenk Yildirim
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
| | - June Corrigan
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- Division of Aging, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Nhan V Do
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Boston University School of Medicine, Boston, Massachusetts, USA
| | - Mary T Brophy
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Boston University School of Medicine, Boston, Massachusetts, USA
| | - Jane A Driver
- New England Geriatrics Research, Education and Clinical Center, VA Boston Healthcare System, Boston, Massachusetts, USA
- Division of Aging, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Nikhil C Munshi
- VA Boston CSP Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Nathanael R Fillmore
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts, USA
- VA Boston CSP Center, Boston, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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49
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Bigdeli TB, Barr PB, Rajeevan N, Graham DP, Li Y, Meyers JL, Gorman BR, Peterson RE, Sayward F, Radhakrishnan K, Natarajan S, Nielsen DA, Wilkinson AV, Malhotra AK, Zhao H, Brophy M, Shi Y, O’Leary TJ, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, DeLisi LE, Kimbrel NA, Beckham JC, Swann AC, Kosten TR, Fanous AH, Aslan M, Harvey PD. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. medRxiv 2023:2023.03.06.23286866. [PMID: 36945597 PMCID: PMC10029042 DOI: 10.1101/2023.03.06.23286866] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Objective Persons diagnosed with schizophrenia (SCZ) or bipolar I disorder (BPI) are at high risk for self-injurious behavior, suicidal ideation, and suicidal behaviors (SB). Characterizing associations between diagnosed mental and physical health problems, prior pharmacological treatments, and aggregate genetic factors has potential to inform risk stratification and mitigation strategies. Methods In this study of 3,942 SCZ and 5,414 BPI patients receiving VA care, self-reported SB and ideation were assessed using the Columbia Suicide Severity Rating Scale (C-SSRS). These cross-sectional data were integrated with electronic health records (EHR), and compared by lifetime diagnoses, treatment histories, follow-up screenings, and mortality data. Polygenic scores (PGS) for traits related to psychiatric disorders, substance use, and cognition were constructed using available genomic data, and exploratory genome-wide association studies were performed to identify and prioritize specific loci. Results Only 20% of veterans who self-reported SB had a corroborating ICD-9/10 code in their EHR; and among those who denied prior behaviors, more than 20% reported new-onset SB at follow-up. SB were associated with a range of psychiatric and non-psychiatric diagnoses, and with treatment with specific classes of psychotropic medications (e.g., antidepressants, antipsychotics, etc.). PGS for externalizing behaviors, smoking, suicide attempt, and major depressive disorder were also associated with attempt and ideation. Conclusions Among individuals with a diagnosed mental illness, a GWAS for SB did not yield any significant loci. Self-reported SB were strongly associated with clinical variables across several EHR domains. Overall, clinical and polygenic analyses point to sequelae of substance-use related behaviors and other psychiatric comorbidities as strong correlates of prior and subsequent SB. Nonetheless, past SB was frequently not documented in clinical settings, underscoring the value of regular screening based on direct, in-person assessments, especially among high-risk individuals.
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Affiliation(s)
- Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - David P. Graham
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Bryan R. Gorman
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Krishnan Radhakrishnan
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | | | - David A. Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Anna V. Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX
- National Mental Health and Substance Use Policy Laboratory, Substance Abuse and Mental Health Services Administration, Rockville, MD
| | - Anil K. Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Boston University School of Medicine, Boston, MA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Timothy J. O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J. Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research and Information Center (MAVERIC), Jamaica Plain, MA
- Harvard University, Boston, MA
| | | | | | - Grant D. Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - John Concato
- Yale University School of Medicine, New Haven, CT
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD
| | - Larry J. Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY
- James J. Peters Veterans Affairs Medical Center, Bronx, NY
| | - Lynn E. DeLisi
- Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Alan C. Swann
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
- Departments of Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Ayman H. Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry, University of Arizona College of Medicine Phoenix, Phoenix, AZ
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
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50
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Honerlaw J, Ho YL, Fontin F, Gosian J, Maripuri M, Murray M, Sangar R, Galloway A, Zimolzak AJ, Whitbourne SB, Casas JP, Ramoni RB, Gagnon DR, Cai T, Liao KP, Gaziano JM, Muralidhar S, Cho K. Framework of the Centralized Interactive Phenomics Resource (CIPHER) standard for electronic health data-based phenomics knowledgebase. J Am Med Inform Assoc 2023; 30:958-964. [PMID: 36882092 PMCID: PMC10114031 DOI: 10.1093/jamia/ocad030] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/14/2023] [Accepted: 02/23/2023] [Indexed: 03/09/2023] Open
Abstract
The development of phenotypes using electronic health records is a resource-intensive process. Therefore, the cataloging of phenotype algorithm metadata for reuse is critical to accelerate clinical research. The Department of Veterans Affairs (VA) has developed a standard for phenotype metadata collection which is currently used in the VA phenomics knowledgebase library, CIPHER (Centralized Interactive Phenomics Resource), to capture over 5000 phenotypes. The CIPHER standard improves upon existing phenotype library metadata collection by capturing the context of algorithm development, phenotyping method used, and approach to validation. While the standard was iteratively developed with VA phenomics experts, it is applicable to the capture of phenotypes across healthcare systems. We describe the framework of the CIPHER standard for phenotype metadata collection, the rationale for its development, and its current application to the largest healthcare system in the United States.
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Affiliation(s)
- Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Francesca Fontin
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Jeffrey Gosian
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Monika Maripuri
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Michael Murray
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Rahul Sangar
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Ashley Galloway
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Andrew J Zimolzak
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, USA.,Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Stacey B Whitbourne
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Rachel B Ramoni
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia, USA
| | - David R Gagnon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, USA
| | - Tianxi Cai
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Katherine P Liao
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.,Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
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