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Meeks GL, Scelza B, Asnake HM, Prall S, Patin E, Froment A, Fagny M, Quintana-Murci L, Henn BM, Gopalan S. Common DNA sequence variation influences epigenetic aging in African populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.26.608843. [PMID: 39253488 PMCID: PMC11383046 DOI: 10.1101/2024.08.26.608843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Aging is associated with genome-wide changes in DNA methylation in humans, facilitating the development of epigenetic age prediction models. However, most of these models have been trained primarily on European-ancestry individuals, and none account for the impact of methylation quantitative trait loci (meQTL). To address these gaps, we analyzed the relationships between age, genotype, and CpG methylation in 3 understudied populations: central African Baka (n = 35), southern African ‡Khomani San (n = 52), and southern African Himba (n = 51). We find that published prediction methods yield higher mean errors in these cohorts compared to European-ancestry individuals, and find that unaccounted-for DNA sequence variation may be a significant factor underlying this loss of accuracy. We leverage information about the associations between DNA genotype and CpG methylation to develop an age predictor that is minimally influenced by meQTL, and show that this model remains accurate across a broad range of genetic backgrounds. Intriguingly, we also find that the older individuals and those exhibiting relatively lower epigenetic age acceleration in our cohorts tend to carry more epigenetic age-reducing genetic variants, suggesting a novel mechanism by which heritable factors can influence longevity.
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Affiliation(s)
- Gillian L Meeks
- Integrative Genetics and Genomics Graduate Program, University of California, Davis, CA 95694, USA
| | - Brooke Scelza
- Department of Anthropology, University of California, Los Angeles, CA, 90095, USA
| | - Hana M Asnake
- Forensic Science Graduate Program, University of California, Davis, CA, 95694, USA
| | - Sean Prall
- Department of Anthropology, University of California, Los Angeles, CA, 90095, USA
| | - Etienne Patin
- Human Evolutionary Genetics Unit, CNRS UMR2000, Paris, 75015, France
| | - Alain Froment
- Institut de Recherche pour le Développement, UMR 208, Muséum National d'Histoire Naturelle, Paris, 75005, France
| | - Maud Fagny
- Human Evolutionary Genetics Unit, CNRS UMR2000, Paris, 75015, France
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, Genetique Quantitative et Evolution - Le Moulon, Gif-sur-Yvette, 91190, France
| | | | - Brenna M Henn
- Department of Anthropology, University of California Davis, Davis, CA, 95616, USA
- UC Davis Genome Center and Center for Population Biology, University of California, Davis, CA 95694, USA
| | - Shyamalika Gopalan
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, 11790, USA
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
- Center for Human Genetics, Clemson University, Greenwood, SC 29646, USA
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2
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Huang J, Kleman N, Basu S, Shriver MD, Zaidi AA. Interpreting SNP heritability in admixed populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.04.551959. [PMID: 37577588 PMCID: PMC10418213 DOI: 10.1101/2023.08.04.551959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
SNP heritabilityh s n p 2 is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability (h 2 ), being equal to it if all causal variants are known. Despite the simple intuition behindh s n p 2 , its interpretation and equivalence toh 2 is unclear, particularly in the presence of population structure and assortative mating. It is well known that population structure can lead to inflation inh ˆ s n p 2 estimates because of confounding due to linkage disequilibrium (LD) or shared environment. Here we use analytical theory and simulations to demonstrate thath s n p 2 estimates can be biased in admixed populations, even in the absence of confounding and even if all causal variants are known. This is because admixture generates LD, which contributes to the genetic variance, and therefore to heritability. Genome-wide restricted maximum likelihood (GREML) does not capture this contribution leading to under- or over-estimates ofh s n p 2 relative toh 2 , depending on the genetic architecture. In contrast, Haseman-Elston (HE) regression exaggerates the LD contribution leading to biases in the opposite direction. For the same reason, GREML and HE estimates of local ancestry heritabilityh γ 2 are also biased. We describe this bias inh ˆ s n p 2 andh ˆ γ 2 as a function of admixture history and the genetic architecture of the trait and show that it can be recovered under some conditions. We clarify the interpretation ofh ˆ s n p 2 in admixed populations and discuss its implication for genome-wide association studies and polygenic prediction.
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Affiliation(s)
- Jinguo Huang
- Bioinformatics and Genomics, Huck Institutes of the Life Sciences, Pennsylvania State University
- Department of Anthropology, Pennsylvania State University
| | - Nicole Kleman
- Department of Genetics, Cell Biology, and Development, University of Minnesota
| | - Saonli Basu
- Department of Biostatistics, University of Minnesota
| | | | - Arslan A. Zaidi
- Department of Genetics, Cell Biology, and Development, University of Minnesota
- Institute of Health Informatics, University of Minnesota
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3
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Alsup A, Nissen E, Salas LA, Molinaro AM, Reiner A, Liu S, Madsen TE, Liu L, Auer PL, Christensen BC, Wiencke JK, Kelsey KT, Koestler DC. An assessment of compositional methods for the analysis of DNA methylation-based deconvolution estimates. Epigenomics 2024; 16:1067-1080. [PMID: 39093129 DOI: 10.1080/17501911.2024.2379242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/09/2024] [Indexed: 08/04/2024] Open
Abstract
DNA methylation (DNAm)-based deconvolution estimates contain relative data, forming a composition, that standard methods (testing directly on cell proportions) are ill-suited to handle. In this study we examined the performance of an alternative method, analysis of compositions of microbiomes (ANCOM), for the analysis of DNAm-based deconvolution estimates. We performed two different simulation studies comparing ANCOM to a standard approach (two sample t-test performed directly on cell proportions) and analyzed a real-world data from the Women's Health Initiative to evaluate the applicability of ANCOM to DNAm-based deconvolution estimates. Our findings indicate that ANCOM can effectively account for the compositional nature of DNAm-based deconvolution estimates. ANCOM adequately controls the false discovery rate while maintaining statistical power comparable to that of standard methods.
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Affiliation(s)
- Alexander Alsup
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Emily Nissen
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alexander Reiner
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Simin Liu
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Tracy E Madsen
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Longjian Liu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health & Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - John K Wiencke
- Department of Neurological Surgery, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Karl T Kelsey
- Department of Emergency Medicine, Alpert Medical School of Brown University and Department of Epidemiology, Department of Pathology and Laboratory Medicine, Brown University School of Public Health, Providence, RI 02903, USA
| | - Devin C Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
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4
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Liu JM, Luo HR. Novel neutrophil biology insights underlying atypical chemokine receptor-1/Duffy antigen receptor of chemokines-associated neutropenia. Curr Opin Hematol 2024:00062752-990000000-00083. [PMID: 39045882 DOI: 10.1097/moh.0000000000000834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2024]
Abstract
PURPOSE OF REVIEW Atypical chemokine receptor-1 (ACKR1)/Duffy antigen receptor of chemokines (DARC)-associated neutropenia (ADAN; OMIM 611862), previously named benign ethnic neutropenia, and present in two-thirds of individuals identifying as Black in the USA, is associated with mild to moderate decreases in peripheral neutrophil counts that nevertheless do not lead to increased infections. Consequently, recent initiatives have sought to establish normal neutrophil count reference ranges for ADAN, considering it a normal variant rather than a clinical disorder requiring medical intervention. RECENT FINDINGS A limited number of studies elucidating the mechanism of neutropenia in ADAN has suggested that neutrophils may redistribute from peripheral blood to the tissues including the spleen: this might explain why ADAN is not associated with increased risks of infection since the total number of neutrophils in the body remains normal. In this review, we critically examine the research underlying the molecular basis of ADAN. SUMMARY Insights into the biology of neutrophils and their trafficking may inform the clinical interpretation of neutropenia in ADAN. The bulk of research suggests that ADAN does not lead to a diminished host defense as do other forms of neutropenia. However, ADAN may lead to increased proinflammatory signaling, with possible implications for senescence of the immune system and predisposition to autoimmunity and cancer.
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Affiliation(s)
- Johnson M Liu
- Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Hongbo R Luo
- Harvard Medical School and Mass General Brigham, Boston, Massachusetts, USA
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5
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Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Kripke CM, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Shakt G, Sun YV, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano JM, Madduri RK, Damrauer S, Liao KP. Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. Science 2024; 385:eadj1182. [PMID: 39024449 DOI: 10.1126/science.adj1182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 05/10/2024] [Indexed: 07/20/2024]
Abstract
One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
- Palo Alto Veterans Institute for Research (PAVIR), Palo Alto Health Care System, Palo Alto, CA 94304, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Alex Rodriguez
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Mitchell Conery
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Molei Liu
- Department of Biostatistics, Columbia University's Mailman School of Public Health, New York, NY 10032, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Youngdae Kim
- Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - David A Heise
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Lindsay Guare
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Franciel Linares
- R&D Systems Engineering, Information Technology Services Directorate, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Lauren Costa
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Ian Goethert
- Data Management and Engineering, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Ryan Tipton
- Knowledge Discovery Infrastructure, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Laura Davies
- Computing and Computational Sciences Dir PMO, PMO, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Stacey Whitbourne
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Jeremy Cohen
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN 37831, USA
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Rahul Sangar
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Michael Murray
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Daniel R Dochtermann
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Poornima Devineni
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Yunling Shi
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Tarak Nath Nandi
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | | | - Charles A Brunette
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Research Service, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37211, USA
| | - Royce Clifford
- Research Department, VA San Diego Healthcare System, San Diego, CA 92161, USA
- Department of Otolaryngology, UCSD San Diego, La Jolla, CA 92093, USA
| | - Scott Duvall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT 84148, USA
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Joel Gelernter
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Adriana Hung
- Medicine, Nephrology & Hypertension, VA Tennessee Valley Healthcare System & Vanderbilt University, Nashville, TN 37232, USA
| | - Sudha K Iyengar
- Departments of Population and Quantitative Health Sciences, Genetics and Genome Sciences, and Ophthalmology and Visual Sciences and the Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Jacob Joseph
- Medicine, Cardiology Section, VA Providence Healthcare System, Providence, RI 02908, USA
- Department of Medicine, Brown University, Providence, RI, 02908, USA
| | - Rachel Kember
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Henry Kranzler
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Colleen M Kripke
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Daniel Levey
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, OR 97239, USA
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Victoria C Merritt
- Research Department, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Cassie Overstreet
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
| | - Joseph D Deak
- Psychiatry, Yale University, New Haven, CT 06520, USA
- Psychiatry, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Divisions of Human Genetics and Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Panos Roussos
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Gabrielle Shakt
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Yan V Sun
- Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA 30322, USA
| | - Noah Tsao
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Sanan Venkatesh
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Georgios Voloudakis
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY 10468, USA
| | - Amy Justice
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT 06516, USA
- Internal Medicine, General Medicine, Yale University, New Haven, CT 06520, USA
- Health Policy, Yale School of Public Health, New Haven, CT 06520, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Georgia Tourassi
- National Center for Computational Sciences, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Saiju Pyarajan
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA 02130, USA
| | - Philip Tsao
- Medicine, Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA 94304, USA
- Department of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | | | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
| | - Alexander G Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, 37325, USA
| | - Wei Zhou
- Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Cambridge, MA 02142, USA
- Program in Medical and Population Genetics, Cambridge, MA 02142, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Benjamin F Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Kelly Cho
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - J Michael Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Ravi K Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Scott Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
- Cardiovascular Institute, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Katherine P Liao
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Medicine, Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA 02115, USA
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6
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Song M, Graubard BI, Loftfield E, Rabkin CS, Engels EA. White Blood Cell Count, Neutrophil-to-Lymphocyte Ratio, and Incident Cancer in the UK Biobank. Cancer Epidemiol Biomarkers Prev 2024; 33:821-829. [PMID: 38568024 PMCID: PMC11147725 DOI: 10.1158/1055-9965.epi-23-1145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/03/2024] [Accepted: 03/29/2024] [Indexed: 06/04/2024] Open
Abstract
BACKGROUND The peripheral white blood cell (WBC) and neutrophil-to-lymphocyte ratio (NLR) reflect levels of inflammation and adaptive immunity. They are associated with cancer prognosis, but their associations with cancer incidence are not established. METHODS We evaluated 443,540 cancer-free adults in the UK Biobank with data on total WBC and its subsets, follow-up starting one year after baseline. Cox regression was used to estimate hazard ratios (HR) per quartile of WBC or NLR for incidence of 73 cancer types. RESULTS 22,747 incident cancers were diagnosed during a median of 6.9 years of follow-up. WBC was associated with risk of cancer overall [HR, 1.05; 95% confidence interval (CI), 1.03-1.06], chronic lymphocytic leukemia/small lymphocytic leukemia (CLL/SLL, 2.79; 95% CI, 2.45-3.18), lung cancer (1.14, 95% CI, 1.08-1.20), and breast cancer (95% CI, 1.05-1.02-1.08). NLR was positively associated with cancer overall (HR, 1.03; 95% CI, 1.02-1.04, per quartile) and kidney cancer (1.16; 95% CI, 1.07-1.25), and inversely with CLL/SLL (0.38; 95% CI, 0.33-0.42). CONCLUSIONS High WBC or NLR may reflect excessive inflammatory status, promoting development of some cancers. Conversely, low NLR indicates a relative rise in lymphocytes, which could reflect an increase in circulating premalignant cells before CLL/SLL diagnosis. Peripheral WBC and NLR, in combination with other clinical information or biomarkers, may be useful tools for cancer risk stratification. IMPACT Elevated levels of WBCs or an increased NLR may indicate an overly active inflammatory response, potentially contributing to the eventual onset of certain types of cancer.
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Affiliation(s)
- Minkyo Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Barry I Graubard
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Erikka Loftfield
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Charles S Rabkin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Eric A Engels
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
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7
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Kelly DL, Glassman M, Wonodi I, Vyas G, Richardson CM, Nwulia E, Wehring HJ, Oduguwa T, Mackowick M, Hipolito MMS, Peters O, Rai N, Park J, Adebayo AO, Gorelick DA, Weiner E, Liu F, Kearns AM, Adams HA, Love RC, Chen S, Olaniyan A, Ambulos N, McKoy D, Nallani MC, Lanzkron S, Mengistab M, Barr B, Davis E, Lawal R, Buchanan RW, Adebayo R. Clozapine and neutrophil response in patients of African descent: A six-month, multinational, prospective, open-label clinical trial. Schizophr Res 2024; 268:312-322. [PMID: 37633776 PMCID: PMC10891303 DOI: 10.1016/j.schres.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/04/2023] [Accepted: 08/05/2023] [Indexed: 08/28/2023]
Abstract
INTRODUCTION Clozapine is the most effective antipsychotic for treatment-resistant schizophrenia, but it is markedly underutilized, particularly in the US Black population, partly because of concern over clozapine-associated low absolute neutrophil count (ANC). People of African descent have a lower normative ANC range than the White population, which is associated with a specific "ACKR1-null" ("Duffy null") CC genotype (SNP rs2814778) on the ACKR1 gene, termed benign ethnic neutropenia (BEN). The range of ANC variability and safety of clozapine have not been established in people with BEN or examined prospectively in people of African descent. METHODS We completed a multisite, 6-month, prospective, open-label clinical trial of clozapine treatment in people of African descent with schizophrenia spectrum disorders for whom clozapine was clinically indicated, with or without the ACKR1-null genotype. We examined clozapine safety and weekly ANC during clozapine treatment and evaluated ANC variability by ACKR1-null genotype, sex, study site, and clozapine dosing using repeated measures analysis of covariance. Genotype was assayed using TaqMan® technology. RESULTS We enrolled 274 participants, of whom 227 (82.8 %) completed 6 months of clozapine treatment. There was one case of severe neutropenia (<500 cells/mm3) (0.36 %) over 1467.6 person-months of clozapine exposure. This participant recovered without sequelae after discontinuation of clozapine. Of the 249 participants with known genotypes, 199 (79.9 %) had the ACKR1-null genotype. Neutropenia (<1500 cells/mm3) occurred significantly more often in the ACKR1-null group (33 % [65/199]) than in those with the T allele (6 % (3/50); p < 0.001). Fourteen (5 %) patients discontinued due to adverse events. Rates of infection and fever were low and sialorrhea was the commonest side effect (N = 187, 68 %). CONCLUSION To our knowledge, this is the largest prospective clozapine trial in people of African descent. Severe neutropenia was rare, despite the high prevalence (80 %) of the ACKR1-null genotype. Our findings suggest that clozapine can be used safely in Black patients including those with BEN.
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Affiliation(s)
- Deanna L Kelly
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America.
| | - Matthew Glassman
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Ikwunga Wonodi
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America; Sheppard Pratt Health System, Baltimore, MD, United States of America
| | - Gopal Vyas
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America; Spring Grove Hospital Center, Catonsville, MD, United States of America
| | - Charles M Richardson
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America; Spring Grove Hospital Center, Catonsville, MD, United States of America
| | - Evaristus Nwulia
- Howard University Hospital, Washington, DC, United States of America
| | - Heidi J Wehring
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Taiwo Oduguwa
- Federal Neuropsychiatric Hospital Yaba, Lagos, Nigeria
| | - Marie Mackowick
- Clifton T. Perkins Hospital Center, Jessup, MD, United States of America
| | | | | | - Narayan Rai
- Howard University Hospital, Washington, DC, United States of America
| | - Jaeboon Park
- Clifton T. Perkins Hospital Center, Jessup, MD, United States of America
| | | | - David A Gorelick
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Elaine Weiner
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Fang Liu
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Ann Marie Kearns
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Heather A Adams
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America; Spring Grove Hospital Center, Catonsville, MD, United States of America
| | - Raymond C Love
- University of Maryland School of Pharmacy, Baltimore, MD, United States of America
| | - Shuo Chen
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | | | - Nicholas Ambulos
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Darius McKoy
- Howard University Hospital, Washington, DC, United States of America
| | - Madhulika C Nallani
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Sophie Lanzkron
- Johns Hopkins University, Baltimore, MD, United States of America
| | - Mulu Mengistab
- Howard University Hospital, Washington, DC, United States of America
| | - Brian Barr
- University of Maryland School of Medicine, Baltimore, MD, United States of America
| | - Erica Davis
- University of Maryland School of Pharmacy, Baltimore, MD, United States of America
| | - Rahman Lawal
- Federal Neuropsychiatric Hospital Yaba, Lagos, Nigeria
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States of America
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8
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Doucoure M, Zeguime A, Niangaly A, Guindo MA, Doritchamou JYA, Assadou MH, Katile A, Kanoute MB, Perou S, Ouattara A, Sanogo S, Ouologuem B, Traore S, Dao B, Dembele D, Kone M, Kamate B, Sissoko K, Sankare S, Diarra S, Dolo A, Sissoko MS, Hume JCC, Cook D, Healy SA, Gorres JP, Traoré B, Gamiel J, Duffy PE, Sagara I. Normal Clinical Laboratory Ranges by Age and Sex, and Impact on Study Screening Outcomes in Rural Mali. Am J Trop Med Hyg 2024; 110:1021-1028. [PMID: 38531104 PMCID: PMC11066370 DOI: 10.4269/ajtmh.23-0719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 01/04/2024] [Indexed: 03/28/2024] Open
Abstract
The interpretation of a laboratory test result requires an appropriate reference range established in healthy subjects, and normal ranges may vary by factors such as geographic region, sex, and age. We examined hematological and clinical chemistry parameters in healthy residents at two rural vaccine trial sites: Bancoumana and Doneguebougou in Mali, West Africa. During screening of clinical studies in 2018 and 2019, peripheral blood samples from 1,192 apparently healthy individuals age 6 months to 82 years were analyzed at a laboratory accredited by the College of American Pathologists for a complete blood count, and creatinine and/or alanine aminotransferase levels. Based on manufacturers' reference range values, which are currently used in Malian clinical laboratories, abnormal values were common in this healthy population. In fact, 30.4% of adult participants had abnormal neutrophil levels and 19.8% had abnormal hemoglobin levels. Differences by sex were observed in those who were older, but not in those younger than 10 years, for several parameters, including hemoglobin, platelet, and absolute neutrophil counts in hematology, and creatinine in biochemistry. The site-specific reference intervals we report can be used in malaria vaccine clinical trials and other interventional studies, as well as in routine clinical care, to identify abnormalities in hematological and biochemical parameters among healthy Malian trial participants.
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Affiliation(s)
- M’Bouye Doucoure
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Amatigue Zeguime
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Amadou Niangaly
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Merepen A. Guindo
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Justin Y. A. Doritchamou
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Mahamadoun H. Assadou
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Abdoulaye Katile
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Moussa B. Kanoute
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Sidiki Perou
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Adama Ouattara
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Sintry Sanogo
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Boucary Ouologuem
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Souleymane Traore
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Bakary Dao
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Drissa Dembele
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Mamady Kone
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Bourama Kamate
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Kourane Sissoko
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Seydou Sankare
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Sadio Diarra
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Amagana Dolo
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Mahamadou S. Sissoko
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Jennifer C. C. Hume
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - David Cook
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Sara A. Healy
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - J. Patrick Gorres
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Boubacar Traoré
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
| | - Jordyn Gamiel
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Patrick E. Duffy
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
| | - Issaka Sagara
- Malaria Research and Training Center, International Center for Excellence in Research–MALI, University of Sciences, Techniques and Technologies of Bamako, Mali
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9
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Mosley JD, Shelley JP, Dickson AL, Zanussi J, Daniel LL, Zheng NS, Bastarache L, Wei WQ, Shi M, Jarvik GP, Rosenthal EA, Khan A, Sherafati A, Kullo IJ, Walunas TL, Glessner J, Hakonarson H, Cox NJ, Roden DM, Frangakis SG, Vanderwerff B, Stein CM, Van Driest SL, Borinstein SC, Shu XO, Zawistowski M, Chung CP, Kawai VK. Clinical associations with a polygenic predisposition to benign lower white blood cell counts. Nat Commun 2024; 15:3384. [PMID: 38649760 PMCID: PMC11035609 DOI: 10.1038/s41467-024-47804-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 04/10/2024] [Indexed: 04/25/2024] Open
Abstract
Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is uncharacterized. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio = 0.55 per standard deviation increase in PGSWBC [95%CI, 0.30-0.94], p = 0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n = 1724, hazard ratio [HR] = 0.78 [0.69-0.88], p = 4.0 × 10-5) or immunosuppressant (n = 354, HR = 0.61 [0.38-0.99], p = 0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n = 1,466, HR = 0.62 [0.44-0.87], p = 0.006). Collectively, these findings suggest that there are genetically predisposed individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.
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Affiliation(s)
- Jonathan D Mosley
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - John P Shelley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alyson L Dickson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jacy Zanussi
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Laura L Daniel
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Neil S Zheng
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P Jarvik
- Department of Genome Sciences, University of Washington Medical Center, Seattle, WA, USA
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, USA
| | - Atlas Khan
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| | - Alborz Sherafati
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Theresa L Walunas
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Joseph Glessner
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Hakon Hakonarson
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nancy J Cox
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephan G Frangakis
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Brett Vanderwerff
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - C Michael Stein
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara L Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott C Borinstein
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Matthew Zawistowski
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Vivian K Kawai
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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10
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Hou K, Gogarten S, Kim J, Hua X, Dias JA, Sun Q, Wang Y, Tan T, Atkinson EG, Martin A, Shortt J, Hirbo J, Li Y, Pasaniuc B, Zhang H. Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations. Bioinformatics 2024; 40:btae148. [PMID: 38490256 PMCID: PMC10980565 DOI: 10.1093/bioinformatics/btae148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 02/08/2024] [Accepted: 03/13/2024] [Indexed: 03/17/2024] Open
Abstract
SUMMARY Admixed populations, with their unique and diverse genetic backgrounds, are often underrepresented in genetic studies. This oversight not only limits our understanding but also exacerbates existing health disparities. One major barrier has been the lack of efficient tools tailored for the special challenges of genetic studies of admixed populations. Here, we present admix-kit, an integrated toolkit and pipeline for genetic analyses of admixed populations. Admix-kit implements a suite of methods to facilitate genotype and phenotype simulation, association testing, genetic architecture inference, and polygenic scoring in admixed populations. AVAILABILITY AND IMPLEMENTATION Admix-kit package is open-source and available at https://github.com/KangchengHou/admix-kit. Additionally, users can use the pipeline designed for admixed genotype simulation available at https://github.com/UW-GAC/admix-kit_workflow.
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Affiliation(s)
- Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Stephanie Gogarten
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, United States
| | - Joohyun Kim
- Vanderbilt Genetics Institute and Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States
| | - Xing Hua
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States
| | - Julie-Alexia Dias
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02120, United States
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States
| | - Ying Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States
| | - Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, United States
| | - Alicia Martin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, United States
| | - Jonathan Shortt
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States
| | - Jibril Hirbo
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, United States
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, United States
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, United States
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11
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Constantinescu AE, Hughes DA, Bull CJ, Fleming K, Mitchell RE, Zheng J, Kar S, Timpson NJ, Amulic B, Vincent EE. A genome-wide association study of neutrophil count in individuals associated to an African continental ancestry group facilitates studies of malaria pathogenesis. Hum Genomics 2024; 18:26. [PMID: 38491524 PMCID: PMC10941368 DOI: 10.1186/s40246-024-00585-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 02/12/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND 'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry (N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056). RESULTS We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci (r2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null. CONCLUSION Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.
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Affiliation(s)
- Andrei-Emil Constantinescu
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- School of Translational Health Sciences, University of Bristol, Bristol, UK
| | - David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Louisiana State University, Louisiana, USA
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- School of Translational Health Sciences, University of Bristol, Bristol, UK
- Health Data Research UK, London, UK
| | - Kathryn Fleming
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Ruth E Mitchell
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases, National Health Commission, Shanghai, People's Republic of China
- Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- Early Cancer Insitute, University of Cambridge, Cambridge, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Borko Amulic
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK.
- School of Translational Health Sciences, University of Bristol, Bristol, UK.
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12
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Clay S, Alladina J, Smith NP, Visness CM, Wood RA, O'Connor GT, Cohen RT, Khurana Hershey GK, Kercsmar CM, Gruchalla RS, Gill MA, Liu AH, Kim H, Kattan M, Bacharier LB, Rastogi D, Rivera-Spoljaric K, Robison RG, Gergen PJ, Busse WW, Villani AC, Cho JL, Medoff BD, Gern JE, Jackson DJ, Ober C, Dapas M. Gene-based association study of rare variants in children of diverse ancestries implicates TNFRSF21 in the development of allergic asthma. J Allergy Clin Immunol 2024; 153:809-820. [PMID: 37944567 PMCID: PMC10939893 DOI: 10.1016/j.jaci.2023.10.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 09/25/2023] [Accepted: 10/12/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Most genetic studies of asthma and allergy have focused on common variation in individuals primarily of European ancestry. Studying the role of rare variation in quantitative phenotypes and in asthma phenotypes in populations of diverse ancestries can provide additional, important insights into the development of these traits. OBJECTIVE We sought to examine the contribution of rare variants to different asthma- or allergy-associated quantitative traits in children with diverse ancestries and explore their role in asthma phenotypes. METHODS We examined whole-genome sequencing data from children participants in longitudinal studies of asthma (n = 1035; parent-identified as 67% Black and 25% Hispanic) to identify rare variants (minor allele frequency < 0.01). We assigned variants to genes and tested for associations using an omnibus variant-set test between each of 24,902 genes and 8 asthma-associated quantitative traits. On combining our results with external data on predicted gene expression in humans and mouse knockout studies, we identified 3 candidate genes. A burden of rare variants in each gene and in a combined 3-gene score was tested for its associations with clinical phenotypes of asthma. Finally, published single-cell gene expression data in lower airway mucosal cells after allergen challenge were used to assess transcriptional responses to allergen. RESULTS Rare variants in USF1 were significantly associated with blood neutrophil count (P = 2.18 × 10-7); rare variants in TNFRSF21 with total IgE (P = 6.47 × 10-6) and PIK3R6 with eosinophil count (P = 4.10 × 10-5) reached suggestive significance. These 3 findings were supported by independent data from human and mouse studies. A burden of rare variants in TNFRSF21 and in a 3-gene score was associated with allergy-related phenotypes in cohorts of children with mild and severe asthma. Furthermore, TNFRSF21 was significantly upregulated in bronchial basal epithelial cells from adults with allergic asthma but not in adults with allergies (but not asthma) after allergen challenge. CONCLUSIONS We report novel associations between rare variants in genes and allergic and inflammatory phenotypes in children with diverse ancestries, highlighting TNFRSF21 as contributing to the development of allergic asthma.
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Affiliation(s)
- Selene Clay
- Department of Human Genetics, University of Chicago, Chicago, Ill.
| | - Jehan Alladina
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Mass; Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
| | - Neal P Smith
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, Mass; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Mass; Massachusetts General Hospital Cancer Center, Boston, Mass
| | | | - Robert A Wood
- Pediatric Allergy and Immunology Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - George T O'Connor
- Department of Pediatrics, Boston University School of Medicine, Boston, Mass
| | - Robyn T Cohen
- Department of Pediatrics, Boston University School of Medicine, Boston, Mass
| | | | - Carolyn M Kercsmar
- Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Rebecca S Gruchalla
- Internal Medicine and Pediatrics, University of Texas Southwestern Medical Center, Dallas, Tex
| | - Michelle A Gill
- Pediatric Infectious Diseases, St. Louis Children's Hospital, St Louis, Mo
| | - Andrew H Liu
- Breathing Institute, Children's Hospital Colorado, Aurora, Colo
| | - Haejin Kim
- Allergy and Immunology, Henry Ford Health, Detroit, Mich
| | - Meyer Kattan
- Department of Pediatrics, Columbia University Medical Center, New York, NY
| | - Leonard B Bacharier
- Department of Pediatrics, Monroe Carell Jr Children's Hospital at Vanderbilt University Medical Center, Nashville, Tenn
| | - Deepa Rastogi
- Division of Pulmonology and Sleep Medicine, Children's National Hospital, Washington, DC
| | - Katherine Rivera-Spoljaric
- Department of Pediatric Allergy, Immunology, and Pulmonary Medicine, Washington University School of Medicine, St Louis, Mo
| | - Rachel G Robison
- Department of Pediatrics, Monroe Carell Jr Children's Hospital at Vanderbilt University Medical Center, Nashville, Tenn; Ann & Robert H. Lurie Children's Hospital, Chicago, Ill
| | - Peter J Gergen
- National Institute of Allergy and Infectious Diseases, Rockville, Md
| | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Alexandra-Chloe Villani
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, Mass; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Mass; Massachusetts General Hospital Cancer Center, Boston, Mass
| | - Josalyn L Cho
- Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Benjamin D Medoff
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Mass; Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
| | - James E Gern
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Daniel J Jackson
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, Ill
| | - Matthew Dapas
- Department of Human Genetics, University of Chicago, Chicago, Ill
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13
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Ha ET, Yee A, Peterson SJ, Kobayashi Y, Sacchi T, Parikh M, Brener SJ. Neutrophil-to-lymphocyte ratio and prognosis in patients undergoing percutaneous coronary intervention for acute coronary syndrome. CARDIOVASCULAR REVASCULARIZATION MEDICINE 2024; 60:29-34. [PMID: 37714727 DOI: 10.1016/j.carrev.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/08/2023] [Accepted: 09/10/2023] [Indexed: 09/17/2023]
Abstract
OBJECTIVE The purpose of this study was to characterize Acute Coronary Syndrome (ACS)-associated inflammation by investigating correlates of the neutrophil-to-lymphocyte ratio (NLR), a surrogate marker of inflammation, and its relation to 1-year mortality in a cohort of patients undergoing percutaneous coronary intervention (PCI) for ACS at a single institution. METHODS We performed a single-institution, retrospective, observational study of all-comer ACS patients who underwent PCI and were discharged home before the COVID-19 pandemic between September 23, 2011 and July 31, 2017 for who outcomes data were available. RESULTS NLRhigh group tended to be older, white patients, less likely to smoke, more likely to have a history of heart failure and cardiac arrest, higher creatinine values, lower LVEF, and higher CK-MB (a surrogate for infarct size). Linear regression model demonstrated a strong correlation between increasing NLR and white race (B = 1.103, p = 0.001, hemoglobin (B = -0.30, p < 0.001), peak CK-MB (B = 0.004, p = 0.02), LVEF (B = -0.048, p < 0.001), and serum creatinine (B = 0.47, p = 0.03). There were a total of 87 deaths at one year. NLR > 3.4 was associated with worse one-year survival post-PCI (91.4 % vs. 95.4 %, log-rank p < 0.004), which was confirmed on multivariate analysis. CONCLUSION Our data confirm the independent prognostic significance of inflammation to mortality after ACS and may provide some insight into the putative benefits of inflammation modulation.
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Affiliation(s)
- Edward T Ha
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA.
| | - Aaron Yee
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
| | - Stephen J Peterson
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
| | - Yuhei Kobayashi
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
| | - Terrence Sacchi
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
| | - Manish Parikh
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
| | - Sorin J Brener
- Department of Internal Medicine, Division of Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Weill Cornell Medical College, Brooklyn, NY, USA
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14
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Palmblad J, Sohlberg E, Nilsson CC, Lindqvist H, Deneberg S, Ratcliffe P, Meinke S, Mörtberg A, Klimkowska M, Höglund P. Clinical and immunological features in ACKR1/DARC-associated neutropenia. Blood Adv 2024; 8:571-580. [PMID: 38039514 PMCID: PMC10837479 DOI: 10.1182/bloodadvances.2023010400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 10/12/2023] [Accepted: 10/27/2023] [Indexed: 12/03/2023] Open
Abstract
ABSTRACT ACKR1/DARC-associated neutropenia (NP; ADAN; Online Mendelian Inheritance in Man 611862), caused by a variation in the ACKR1/DARC gene (rs2814778), is common in persons of African or Middle Eastern descent. In a cohort of 66 genetically confirmed subjects with ADAN, we show that absolute neutrophil counts (ANCs) may occasionally be lower than previously recognized (0.1 × 109-0.49 × 109/L for 9% of the subjects), which is similar to ANCs in severe congenital NP (SCNP). ANCs often normalized during inflammation, even mild. Individuals with ADAN (of 327 observed person-years) showed no cases of myelodysplastic syndrome (MDS), which is frequently encountered in SCNP. Unexpectedly, 22% presented with autoantibodies to neutrophils, compared with <1% in controls. Compared with healthy donors, subjects with ADAN demonstrated significantly lower human cationic antimicrobial protein-18/pro-leucin leucin-37 plasma levels; higher levels of nonclassical, proinflammatory, 6-sulfo LacNac-expressing monocytes; and differentially expressed plasma levels of 28 of the 239 analyzed cytokines related to immunity/inflammation, cell signaling, neutrophil activation, and angiogenesis. Collectively, more severe neutropenia in ADAN than previously assumed may complicate differential diagnoses compared with other SCNPs, and various (auto)immune/inflammatory reactions with a distinct profile may be a cause or consequence of this hereditary neutropenia.
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Affiliation(s)
- Jan Palmblad
- The Hematology Center, Karolinska University Hospital Huddinge and Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Ebba Sohlberg
- Center for Infectious Medicine, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Christer C. Nilsson
- The Hematology Center, Karolinska University Hospital Huddinge and Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Henric Lindqvist
- The Hematology Center, Karolinska University Hospital Huddinge and Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Deneberg
- The Hematology Center, Karolinska University Hospital Huddinge and Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Paul Ratcliffe
- Center for Hematology and Regenerative Medicine, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Clinical Immunology and Transfusion Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Stephan Meinke
- Center for Hematology and Regenerative Medicine, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Anette Mörtberg
- Department of Clinical Science, Intervention, and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Monika Klimkowska
- Department of Clinical Pathology and Cancer Diagnostics, Karolinska University Hospital and Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Petter Höglund
- Center for Hematology and Regenerative Medicine, Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden
- Medical Unit Clinical Immunology and Transfusion Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
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15
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Sun Q, Rowland BT, Chen J, Mikhaylova AV, Avery C, Peters U, Lundin J, Matise T, Buyske S, Tao R, Mathias RA, Reiner AP, Auer PL, Cox NJ, Kooperberg C, Thornton TA, Raffield LM, Li Y. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nat Commun 2024; 15:1016. [PMID: 38310129 PMCID: PMC10838303 DOI: 10.1038/s41467-024-45135-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/16/2024] [Indexed: 02/05/2024] Open
Abstract
Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
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Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bryce T Rowland
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Anna V Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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16
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Wu S, Powell V, Chintoh A, Alarabi M, Agarwal SM, Remington G. Safety of BEN guidelines in clozapine treatment: A Canadian perspective. Schizophr Res 2024; 264:451-456. [PMID: 38262312 DOI: 10.1016/j.schres.2024.01.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 11/29/2023] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
OBJECTIVE Unidentified benign ethnic neutropenia (BEN) has been recognized as a factor contributing to clozapine underutilization and discontinuation. Guidelines were implemented to accommodate BEN in Canada, and our main objective was to evaluate clozapine's safety in a sample of Canadian psychiatric patients with BEN. METHOD A retrospective chart review was conducted at the Centre for Addiction and Mental Health, Toronto, Canada. Through the clozapine clinic registry, participants were identified who (i) received clozapine using the approved BEN guidelines for hematological monitoring, and (ii) had at least one complete blood count pre- and post-clozapine initiation. RESULTS Our sample population was comprised of 41 BEN patients who were African-Caribbean (49 %), African (34 %), African-North American (12 %), Middle Eastern (2 %), and Indian-Caribbean (2 %). There was a significant reduction in hematological alerts for these patients while monitored under BEN guidelines (p < 0.001). The mean within-patient ANC value was not significantly different one year after clozapine initiation compared to the pre-clozapine baseline (p = 0.069). None of the patients discontinued clozapine for hematological reasons. CONCLUSIONS Findings demonstrated that patients monitored under the modified hematological guidelines for BEN can be safely treated with clozapine. These findings have important clinical ramifications as increased implementation of BEN guidelines may allow for broader use of clozapine.
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Affiliation(s)
- Sally Wu
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Temerty Faculty of Medicine, Institute of Medical Sciences, University of Toronto, Toronto, Canada
| | - Valerie Powell
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada
| | - Araba Chintoh
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Mohammed Alarabi
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Department of Psychiatry, King Saud University, Riyadh, Saudi Arabia
| | - Sri Mahavir Agarwal
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Temerty Faculty of Medicine, Institute of Medical Sciences, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Gary Remington
- Schizophrenia Division, Centre for Addiction and Mental Health (CAMH), Toronto, Canada; Temerty Faculty of Medicine, Institute of Medical Sciences, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Psychological Clinical Science, University of Toronto Scarborough, Toronto, ON, Canada.
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17
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Chennapragada SS, Sharma S, Dadi N, Shi R, Mansour RP. Real-world Data of Leukopenia Evaluation as Seen in a Community Academic Center. J Community Hosp Intern Med Perspect 2023; 13:126-128. [PMID: 38596546 PMCID: PMC11000836 DOI: 10.55729/2000-9666.1273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/09/2023] [Accepted: 09/14/2023] [Indexed: 04/11/2024] Open
Abstract
Leukopenia on routine laboratory testing creates a concerning situation for primary care providers due to its association with hematological malignancies. Although not all leukopenia is due to underlying cancer, it can trigger an expensive and exhausting work-up in the process of ruling it out. There is neither real-world data on the prevalent causes of leukopenia as seen in the community nor definitive guidelines on the utilization of flow-cytometry in this setting. We conducted this retrospective study at our community academic center to demonstrate the distribution of various causes of leukopenia as well as the utility of flow-cytometry. Our study demonstrates that benign reversible causes of leukopenia are most prevalent and flow-cytometry is useful only in some very specific settings. These results provide a real-world estimate for clinicians to make informed decisions while evaluating leukopenia.
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Affiliation(s)
- Suma S. Chennapragada
- Department of Hematology and Oncology, Louisiana State University Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103,
USA
| | - Shivani Sharma
- Department of Internal Medicine, Louisiana State University Health Shreveport, 1541 Kings Highway, Shreveport, LA, 71103,
USA
| | | | - Runhua Shi
- Department of Hematology and Oncology, Louisiana State University Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103,
USA
| | - Richard P. Mansour
- Department of Hematology and Oncology, Louisiana State University Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103,
USA
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18
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Tanigawa Y, Kellis M. Power of inclusion: Enhancing polygenic prediction with admixed individuals. Am J Hum Genet 2023; 110:1888-1902. [PMID: 37890495 PMCID: PMC10645553 DOI: 10.1016/j.ajhg.2023.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 09/22/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Admixed individuals offer unique opportunities for addressing limited transferability in polygenic scores (PGSs), given the substantial trans-ancestry genetic correlation in many complex traits. However, they are rarely considered in PGS training, given the challenges in representing ancestry-matched linkage-disequilibrium reference panels for admixed individuals. Here we present inclusive PGS (iPGS), which captures ancestry-shared genetic effects by finding the exact solution for penalized regression on individual-level data and is thus naturally applicable to admixed individuals. We validate our approach in a simulation study across 33 configurations with varying heritability, polygenicity, and ancestry composition in the training set. When iPGS is applied to n = 237,055 ancestry-diverse individuals in the UK Biobank, it shows the greatest improvements in Africans by 48.9% on average across 60 quantitative traits and up to 50-fold improvements for some traits (neutrophil count, R2 = 0.058) over the baseline model trained on the same number of European individuals. When we allowed iPGS to use n = 284,661 individuals, we observed an average improvement of 60.8% for African, 11.6% for South Asian, 7.3% for non-British White, 4.8% for White British, and 17.8% for the other individuals. We further developed iPGS+refit to jointly model the ancestry-shared and -dependent genetic effects when heterogeneous genetic associations were present. For neutrophil count, for example, iPGS+refit showed the highest predictive performance in the African group (R2 = 0.115), which exceeds the best predictive performance for the White British group (R2 = 0.090 in the iPGS model), even though only 1.49% of individuals used in the iPGS training are of African ancestry. Our results indicate the power of including diverse individuals for developing more equitable PGS models.
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Affiliation(s)
- Yosuke Tanigawa
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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19
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Merz LE, Hibbs SP. Invisible Infrastructure in Haematology: Neutrophil Reference Ranges and the Duffy-null Phenotype. Hemasphere 2023; 7:e972. [PMID: 37908860 PMCID: PMC10615472 DOI: 10.1097/hs9.0000000000000972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023] Open
Affiliation(s)
- Lauren E. Merz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Stephen P. Hibbs
- Wolfson Institute of Population Health, Queen Mary University of London, United Kingdom
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20
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Krecak I, Lucijanic M. Duffy-null erythrocyte phenotype and the risk of thrombotic events in essential thrombocythemia. EJHAEM 2023; 4:1186-1187. [PMID: 38024638 PMCID: PMC10660612 DOI: 10.1002/jha2.773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/05/2023] [Accepted: 08/12/2023] [Indexed: 12/01/2023]
Affiliation(s)
- Ivan Krecak
- Department of Internal MedicineGeneral Hospital of Sibenik‐Knin CountySibenikCroatia
- Faculty of MedicineUniversity of RijekaRijekaCroatia
| | - Marko Lucijanic
- Division of HematologyUniversity Hospital DubravaZagrebCroatia
- Faculty of MedicineUniversity of ZagrebZagrebCroatia
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21
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Mosley JD, Shelley JP, Dickson AL, Zanussi J, Daniel LL, Zheng NS, Bastarache L, Wei WQ, Shi M, Jarvik GP, Rosenthal EA, Khan A, Sherafati A, Kullo IJ, Walunas TL, Glessner J, Hakonarson H, Cox NJ, Roden DM, Frangakis SG, Vanderwerff B, Stein CM, Van Driest SL, Borinstein SC, Shu XO, Zawistowski M, Chung CP, Kawai VK. Clinical consequences of a polygenic predisposition to benign lower white blood cell counts: Consequences of benign WBC count genetics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.20.23294331. [PMID: 37662324 PMCID: PMC10473820 DOI: 10.1101/2023.08.20.23294331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Polygenic variation unrelated to disease contributes to interindividual variation in baseline white blood cell (WBC) counts, but its clinical significance is undefined. We investigated the clinical consequences of a genetic predisposition toward lower WBC counts among 89,559 biobank participants from tertiary care centers using a polygenic score for WBC count (PGSWBC) comprising single nucleotide polymorphisms not associated with disease. A predisposition to lower WBC counts was associated with a decreased risk of identifying pathology on a bone marrow biopsy performed for a low WBC count (odds-ratio=0.55 per standard deviation increase in PGSWBC [95%CI, 0.30 - 0.94], p=0.04), an increased risk of leukopenia (a low WBC count) when treated with a chemotherapeutic (n=1,724, hazard ratio [HR]=0.78 [0.69 - 0.88], p=4.0×10-5) or immunosuppressant (n=354, HR=0.61 [0.38 - 0.99], p=0.04). A predisposition to benign lower WBC counts was associated with an increased risk of discontinuing azathioprine treatment (n=1,466, HR=0.62 [0.44 - 0.87], p=0.006). Collectively, these findings suggest that a WBC count polygenic score identifies individuals who are susceptible to escalations or alterations in clinical care that may be harmful or of little benefit.
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Affiliation(s)
- Jonathan D. Mosley
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John P. Shelley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alyson L. Dickson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jacy Zanussi
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Laura L. Daniel
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Neil S. Zheng
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mingjian Shi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gail P. Jarvik
- Department of Genome Sciences, University of Washington Medical Center, Seattle WA, USA
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle WA, USA
| | - Elisabeth A. Rosenthal
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle WA, USA
| | - Atlas Khan
- Division of Nephrology, Dept of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY
| | - Alborz Sherafati
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester MN USA
| | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester MN USA
| | - Theresa L. Walunas
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Joe Glessner
- Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Hakon Hakonarson
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nancy J. Cox
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dan M. Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephan G. Frangakis
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Brett Vanderwerff
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - C. Michael Stein
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott C. Borinstein
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Matthew Zawistowski
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Cecilia P. Chung
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivian K. Kawai
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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22
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Ha ET, Taylor KD, Raffield LM, Briggs M, Yee A, Elemento O, Parikh M, Peterson SJ, Frishman W, Gerszten RE, Wilson JG, Kelsey K, Tahir UA, Reiner A, Auer P, Seeman T, Rich SS, Carson AP, Post WS, Rotter JI, Aronow WS. The Relationship of Duffy Gene Polymorphism, High Sensitivity C-Reactive Protein, and Long-term Outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.03.23293626. [PMID: 37609271 PMCID: PMC10441500 DOI: 10.1101/2023.08.03.23293626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Background Black adults have higher incidence of all-cause death and worse cardiovascular outcomes when compared to other populations. The Duffy chemokine receptor is not expressed in a large majority of Black adults and the clinical implications of this are unclear. Methods Here, we investigated the relationship of Duffy receptor status, high-sensitivity C-reactive protein (hs-CRP), and long-term cardiovascular outcomes in Black members of two contemporary, longitudinal cohort studies (the Jackson Heart Study and Multi-Ethnic Study of Atherosclerosis). Data on 4,307 Black participants (2,942 Duffy null and 1,365 Duffy receptor positive, as defined using Single Nucleotide Polymorphism (SNP) rs2814778) were included in this analysis. Results Duffy null was not independently associated with elevated levels of serum hs-CRP levels once conditioning for known CRP locus alleles in linkage disequilibrium with the Duffy gene. Duffy null status was not found to be independently associated with higher incidence of all-cause mortality or secondary outcomes after adjusting for possible confounders in Black participants. Conclusions These findings suggest that increased levels of hs-CRP found in Duffy null individuals is due to co-inheritance of CRP alleles known to influence circulating levels hs-CRP and that Duffy null status was not associated with worse adverse outcomes over the follow-up period in this cohort of well-balanced Black participants.
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23
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Merz LE, Li SH, Ney G, Michniacki TF, Hannibal MC, Walkovich KJ. Absolute neutrophil count nadir in healthy pediatric patients with the Duffy-null phenotype. Blood Adv 2023; 7:4182-4185. [PMID: 37285802 PMCID: PMC10407121 DOI: 10.1182/bloodadvances.2023010368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/19/2023] [Accepted: 06/03/2023] [Indexed: 06/09/2023] Open
Affiliation(s)
| | - Shih-Hon Li
- Department of Pathology, University of Michigan Medical School, Ann Arbor, MI
| | - Gina Ney
- Division of Hematology/Oncology, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI
| | - Thomas F. Michniacki
- Division of Hematology/Oncology, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI
| | - Mark C. Hannibal
- Division of Genetics, Metabolism and Genomic Medicine, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI
| | - Kelly J. Walkovich
- Division of Hematology/Oncology, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI
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24
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Moon B, Yang S, Moon H, Lee J, Park D. After cell death: the molecular machinery of efferocytosis. Exp Mol Med 2023; 55:1644-1651. [PMID: 37612408 PMCID: PMC10474042 DOI: 10.1038/s12276-023-01070-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/12/2023] [Accepted: 06/15/2023] [Indexed: 08/25/2023] Open
Abstract
Cells constituting a multicellular organism die in a variety of ways throughout life, and most of them die via apoptosis under normal conditions. The occurrence of apoptosis is especially prevalent during development and in tissues with a high cellular turnover rate, such as the thymus and bone marrow. Interestingly, although the number of apoptotic cells produced daily is known to be innumerable in a healthy adult human body, apoptotic cells are rarely observed. This absence is due to the existence of a cellular process called efferocytosis that efficiently clears apoptotic cells. Studies over the past decades have focused on how phagocytes are able to remove apoptotic cells specifically, swiftly, and continuously, resulting in defined molecular and cellular events. In this review, we will discuss the current understanding of the clearance of apoptotic cells at the molecular level.
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Affiliation(s)
- Byeongjin Moon
- School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
- Cell Mechanobiology Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
| | - Susumin Yang
- School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
- Cell Mechanobiology Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
| | - Hyunji Moon
- School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
- Cell Mechanobiology Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
| | - Juyeon Lee
- School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
- Cell Mechanobiology Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea
| | - Daeho Park
- School of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea.
- Cell Mechanobiology Laboratory, Gwangju Institute of Science and Technology, Gwangju, 61005, Korea.
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25
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Hou K, Xu Z, Ding Y, Harpak A, Pasaniuc B. Calibrated prediction intervals for polygenic scores across diverse contexts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.24.23293056. [PMID: 37546999 PMCID: PMC10402211 DOI: 10.1101/2023.07.24.23293056] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields from agriculture to personalized medicine. We analyze data from two large biobanks in the US (All of Us) and the UK (UK Biobank) to find widespread variability in PGS performance across contexts. Many contexts, including age, sex, and income, impact PGS accuracies with similar magnitudes as genetic ancestry. PGSs trained in single versus multi-ancestry cohorts show similar context-specificity in their accuracies. We introduce trait prediction intervals that are allowed to vary across contexts as a principled approach to account for context-specific PGS accuracy in genomic prediction. We model the impact of all contexts in a joint framework to enable PGS-based trait predictions that are well-calibrated (contain the trait value with 90% probability in all contexts), whereas methods that ignore context are mis-calibrated. We show that prediction intervals need to be adjusted for all considered traits ranging from 10% for diastolic blood pressure to 80% for waist circumference. Adjustment of prediction intervals depends on the dataset; for example, prediction intervals for education years need to be adjusted by 90% in All of Us versus 8% in UK Biobank. Our results provide a path forward towards utilization of PGS as a prediction tool across all individuals regardless of their contexts while highlighting the importance of comprehensive profile of context information in study design and data collection.
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Affiliation(s)
- Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ziqi Xu
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Arbel Harpak
- Department of Population Health, The University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles
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26
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Zaidi AA, Verma A, Morse C, Ritchie MD, Mathieson I. The genetic and phenotypic correlates of mtDNA copy number in a multi-ancestry cohort. HGG ADVANCES 2023; 4:100202. [PMID: 37255673 PMCID: PMC10225932 DOI: 10.1016/j.xhgg.2023.100202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/25/2023] [Indexed: 06/01/2023] Open
Abstract
Mitochondrial DNA copy number (mtCN) is often treated as a proxy for mitochondrial (dys-) function and disease risk. Pathological changes in mtCN are common symptoms of rare mitochondrial disorders, but reported associations between mtCN and common diseases vary across studies. To understand the biology of mtCN, we carried out genome- and phenome-wide association studies of mtCN in 30,666 individuals from the Penn Medicine BioBank (PMBB)-a diverse cohort of largely African and European ancestry. We estimated mtCN in peripheral blood using exome sequence data, taking cell composition into account. We replicated known genetic associations of mtCN in the PMBB and found that their effects are highly correlated between individuals of European and African ancestry. However, the heritability of mtCN was much higher among individuals of largely African ancestry ( h 2 = 0.3 ) compared with European ancestry individuals( h 2 = 0.1 ) . Admixture mapping suggests that there are undiscovered variants underlying mtCN that are differentiated in frequency between individuals with African and European ancestry. We show that mtCN is associated with many health-related phenotypes. We discovered robust associations between mtDNA copy number and diseases of metabolically active tissues, such as cardiovascular disease and liver damage, that were consistent across African and European ancestry individuals. Other associations, such as epilepsy and prostate cancer, were only discovered in either individuals with European or African ancestry but not both. We show that mtCN-phenotype associations can be sensitive to blood cell composition and environmental modifiers, explaining why such associations are inconsistent across studies. Thus, mtCN-phenotype associations must be interpreted with care.
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Affiliation(s)
- Arslan A. Zaidi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anurag Verma
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Colleen Morse
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Penn Medicine BioBank
- Center for Translational Bioinformatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marylyn D. Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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27
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Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Sun YV, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao PS, O’Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano MJ, Madduri RK, Damrauer SM, Liao KP. Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291975. [PMID: 37425708 PMCID: PMC10327290 DOI: 10.1101/2023.06.28.23291975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Genome-wide association studies (GWAS) have underrepresented individuals from non-European populations, impeding progress in characterizing the genetic architecture and consequences of health and disease traits. To address this, we present a population-stratified phenome-wide GWAS followed by a multi-population meta-analysis for 2,068 traits derived from electronic health records of 635,969 participants in the Million Veteran Program (MVP), a longitudinal cohort study of diverse U.S. Veterans genetically similar to the respective African (121,177), Admixed American (59,048), East Asian (6,702), and European (449,042) superpopulations defined by the 1000 Genomes Project. We identified 38,270 independent variants associating with one or more traits at experiment-wide P < 4.6 × 10 - 11 significance; fine-mapping 6,318 signals identified from 613 traits to single-variant resolution. Among these, a third (2,069) of the associations were found only among participants genetically similar to non-European reference populations, demonstrating the importance of expanding diversity in genetic studies. Our work provides a comprehensive atlas of phenome-wide genetic associations for future studies dissecting the architecture of complex traits in diverse populations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
- Palo Alto Veterans Institute for Research (PAVIR), Palo Alto Health Care System, Palo Alto, CA, 94304, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Alex Rodriguez
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Mitchell Conery
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Molei Liu
- Department of Biostatistics, Columbia University’s Mailman School of Public Health, New York, NY, 10032, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Youngdae Kim
- Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - David A Heise
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Lindsay Guare
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | | | - Helene Garcon
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Franciel Linares
- R&D Systems Engineering, Information Technology Services Directorate, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Lauren Costa
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Ian Goethert
- Data Management and Engineering, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Ryan Tipton
- Knowledge Discovery Infrastructure, Information Technology Services Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Laura Davies
- Computing and Computational Sciences Dir PMO, PMO, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Stacey Whitbourne
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Jeremy Cohen
- National Security Sciences Directorate, Cyber Resilience and Intelligence Division, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Rahul Sangar
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Michael Murray
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Daniel R Dochtermann
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Poornima Devineni
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Yunling Shi
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Tarak Nath Nandi
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | | | - Charles A Brunette
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Research Service, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Robert J Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37211, USA
| | - Royce Clifford
- Research Department, VA San Diego Healthcare System, San Diego, CA, 92161, USA
- Surgery, Otolaryngology, UCSD San Diego, La Jolla, California, 92093, USA
| | - Scott Duvall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, 84148, USA
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA
| | - Joel Gelernter
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Adriana Hung
- Medicine, Nephrology & Hypertension, VA Tennessee Valley Healthcare System & Vanderbilt University, Nashville, TN, 37232, USA
| | - Sudha K Iyengar
- Population and Quantitative Health Sciences, Case Western Reserve University, School of Medicine, Cleveland, OH, 44106, USA
| | - Jacob Joseph
- Medicine, Cardiology Section, VA Providence Healthcare System, Providence, RI, 02908, USA
- Department of Medicine, Brown University, Providence, RI, 02908, USA
| | - Rachel Kember
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Henry Kranzler
- Mental Illness Research, Education and Clinical Center, Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Daniel Levey
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, OR, 97239, USA
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Victoria C Merritt
- Research Department, VA San Diego Healthcare System, San Diego, CA, 92161, USA
| | - Cassie Overstreet
- Psychiatry, Human Genetics, Yale University, New Haven, CT, 06520, USA
| | - Joseph D Deak
- Psychiatry, Yale University, New Haven, CT, 06520, USA
- Psychiatry, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pediatrics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Divisions of Human Genetics and Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | | | - Panos Roussos
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Yan V Sun
- Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, 30322, USA
| | - Sanan Venkatesh
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Georgios Voloudakis
- Psychiatry, Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center; Icahn School of Medicine at Mount Sinai, Bronx, NY, 10468, USA
| | - Amy Justice
- Medicine, VA Connecticut Healthcare System West Haven, West Haven, CT, 06516, USA
- Internal Medicine, General Medicine, Yale University, New Haven, CT, 06520, USA
- Health Policy, Yale School of Public Health, New Haven, CT, 06520, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Georgia Tourassi
- National Center for Computational Sciences, Oak Ridge National Laboratory, Dept of Energy, Oak Ridge, TN, 37831, USA
| | - Saiju Pyarajan
- VA Cooperative Studies Program, VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Philip S Tsao
- Medicine, Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, 94304, USA
- Department of Medicine, Stanford University, Palo Alto, CA, 94304, USA
| | | | - Sumitra Muralidhar
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Jennifer Moser
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, 20420, USA
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, 02130, USA
| | - Alexander G Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, 37325, USA
| | - Wei Zhou
- Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, Cambridge, MA, 02142, USA
- Program in Medical and Population Genetics, Cambridge, MA, 02142, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Benjamin F Voight
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Kelly Cho
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Michael J Gaziano
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- MVP Boston Coordinating Center, VA Boston Healthcare System, Boston, MA, 02111, USA
- Department of Medicine, Division of Aging, Brigham and Women’s Hospital, Boston, MA, 02115, USA
| | - Ravi K Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, IL, 60439, USA
| | - Scott M Damrauer
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, 19104, USA
- Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Surgery, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Cardiovascular Institute, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Katherine P Liao
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, MA, 02130, USA
- Department of Medicine, Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, MA, 02115, USA
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28
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Kachuri L, Mak ACY, Hu D, Eng C, Huntsman S, Elhawary JR, Gupta N, Gabriel S, Xiao S, Keys KL, Oni-Orisan A, Rodríguez-Santana JR, LeNoir MA, Borrell LN, Zaitlen NA, Williams LK, Gignoux CR, Burchard EG, Ziv E. Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture. Nat Genet 2023; 55:952-963. [PMID: 37231098 PMCID: PMC10260401 DOI: 10.1038/s41588-023-01377-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 03/21/2023] [Indexed: 05/27/2023]
Abstract
We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Angel C Y Mak
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jennifer R Elhawary
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Shujie Xiao
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, MI, USA
| | - Kevin L Keys
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, USA
| | - Akinyemi Oni-Orisan
- Department of Clinical Pharmacy, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | | | - Luisa N Borrell
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Noah A Zaitlen
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, MI, USA
- Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Esteban González Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Elad Ziv
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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Ding Y, Hou K, Xu Z, Pimplaskar A, Petter E, Boulier K, Privé F, Vilhjálmsson BJ, Olde Loohuis LM, Pasaniuc B. Polygenic scoring accuracy varies across the genetic ancestry continuum. Nature 2023; 618:774-781. [PMID: 37198491 PMCID: PMC10284707 DOI: 10.1038/s41586-023-06079-4] [Citation(s) in RCA: 65] [Impact Index Per Article: 65.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 04/12/2023] [Indexed: 05/19/2023]
Abstract
Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use1-3. PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R2)4, ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank5 (ATLAS, n = 36,778) along with the UK Biobank6 (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries7 in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries. The decreasing trend is well captured by a continuous measure of genetic distance (GD) from the PGS training data: Pearson correlation of -0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained on individuals labelled as white British in the UKBB to individuals with European ancestries in ATLAS, individuals in the furthest GD decile have 14% lower accuracy relative to the closest decile; notably, the closest GD decile of individuals with Hispanic Latino American ancestries show similar PGS performance to the furthest GD decile of individuals with European ancestries. GD is significantly correlated with PGS estimates themselves for 82 of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestries in PGS interpretation. Our results highlight the need to move away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGSs.
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Affiliation(s)
- Yi Ding
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Ziqi Xu
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Aditya Pimplaskar
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Ella Petter
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Kristin Boulier
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Florian Privé
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Institute for Precision Health, UCLA, Los Angeles, CA, USA.
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Schlottmann PG, Luna JD, Labat N, Yadarola MB, Bainttein S, Esposito E, Ibañez A, Barbaro EI, Álvarez Mendiara A, Picotti CP, Chirino Misisian A, Andreussi L, Gras J, Capalbo L, Visotto M, Dipierri JE, Alcoba E, Fernández Gabrielli L, Ávila S, Aucar ME, Martin DM, Ormaechea GJ, Inga ME, Francone AA, Charles M, Zompa T, Pérez PJ, Lotersztein V, Nuova PJ, Canonero IB, Mahroo OA, Michaelides M, Arno G, Daich Varela M. Nationwide genetic analysis of more than 600 families with inherited eye diseases in Argentina. NPJ Genom Med 2023; 8:8. [PMID: 37217489 DOI: 10.1038/s41525-023-00352-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 04/05/2023] [Indexed: 05/24/2023] Open
Abstract
This study corresponds to the first large-scale genetic analysis of inherited eye diseases (IED) in Argentina and describes the comprehensive genetic profile of a large cohort of patients. Medical records of 22 ophthalmology and genetics services throughout 13 Argentinian provinces were analyzed retrospectively. Patients with a clinical diagnosis of an ophthalmic genetic disease and a history of genetic testing were included. Medical, ophthalmological and family history was collected. A total of 773 patients from 637 families were included, with 98% having inherited retinal disease. The most common phenotype was retinitis pigmentosa (RP, 62%). Causative variants were detected in 379 (59%) patients. USH2A, RPGR, and ABCA4 were the most common disease-associated genes. USH2A was the most frequent gene associated with RP, RDH12 early-onset severe retinal dystrophy, ABCA4 Stargardt disease, PROM1 cone-rod dystrophy, and BEST1 macular dystrophy. The most frequent variants were RPGR c.1345 C > T, p.(Arg449*) and USH2A c.15089 C > A, p.(Ser5030*). The study revealed 156/448 (35%) previously unreported pathogenic/likely pathogenic variants and 8 possible founder mutations. We present the genetic landscape of IED in Argentina and the largest cohort in South America. This data will serve as a reference for future genetic studies, aid diagnosis, inform counseling, and assist in addressing the largely unmet need for clinical trials to be conducted in the region.
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Affiliation(s)
| | - José D Luna
- Centro Privado de Ojos Romagosa SA, Córdoba, Argentina
| | - Natalia Labat
- Centro Privado de Ojos Romagosa SA, Córdoba, Argentina
| | | | | | - Evangelina Esposito
- University Clinic Reina Fabiola, Córdoba, Córdoba, Argentina
- Catholic University of Cordoba, Cordoba, Argentina
| | - Agustina Ibañez
- University Clinic Reina Fabiola, Córdoba, Córdoba, Argentina
- Catholic University of Cordoba, Cordoba, Argentina
| | | | | | | | | | | | | | | | - Mauro Visotto
- Instituto Oftalmológico Trelew, Trelew, Chubut, Argentina
| | | | - Emilio Alcoba
- Hospital Materno Infantil Dr Héctor Quintana, Jujuy, Argentina
| | | | - Silvia Ávila
- Facultad de Ciencias Médicas, Universidad Nacional del Comahue, Río Negro, Argentina
| | | | | | | | - M Eugenia Inga
- Organización Medica de Investigación, Buenos Aires, Argentina
| | | | | | - Tamara Zompa
- Charles Centro Oftalmológico, Buenos Aires, Argentina
| | | | | | - Pedro J Nuova
- Ocularyb Oftalmoclinica, Yerba Buena, Tucumán, Argentina
| | | | - Omar A Mahroo
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Michel Michaelides
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Gavin Arno
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Malena Daich Varela
- Moorfields Eye Hospital, London, UK.
- UCL Institute of Ophthalmology, University College London, London, UK.
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Farida H, Triasih R, Lokida D, Mardian Y, Salim G, Wulan WN, Butar-butar DP, Sari RA, Budiman A, Hayuningsih C, Anam MS, Dipayana S, Mujahidah M, Setyati A, Aman AT, Naysilla AM, Lukman N, Diana A, Karyana M, Kline A, Neal A, Lane HC, Kosasih H, Lau CY. Epidemiologic, clinical, and serum markers may improve discrimination between bacterial and viral etiologies of childhood pneumonia. Front Med (Lausanne) 2023; 10:1140100. [PMID: 37275364 PMCID: PMC10233046 DOI: 10.3389/fmed.2023.1140100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 04/25/2023] [Indexed: 06/07/2023] Open
Abstract
Background Discrimination of bacterial and viral etiologies of childhood community-acquired pneumonia (CAP) is often challenging. Unnecessary antibiotic administration exposes patients to undue risks and may engender antimicrobial resistance. This study aimed to develop a prediction model using epidemiological, clinical and laboratory data to differentiate between bacterial and viral CAP. Methods Data from 155 children with confirmed bacterial or mixed bacterial and viral infection (N = 124) and viral infection (N = 31) were derived from a comprehensive assessment of causative pathogens [Partnerships for Enhanced Engagement in Research-Pneumonia in Pediatrics (PEER-PePPeS)] conducted in Indonesia. Epidemiologic, clinical and biomarker profiles (hematology and inflammatory markers) were compared between groups. The area under the receiver operating characteristic curve (AUROC) for varying biomarker levels was used to characterize performance and determine cut-off values for discrimination of bacterial and mixed CAP versus viral CAP. Diagnostic predictors of bacterial and mixed CAP were assessed by multivariate logistic regression. Results Diarrhea was more frequently reported in bacterial and mixed CAP, while viral infections more frequently occurred during Indonesia's rainy season. White blood cell counts (WBC), absolute neutrophil counts (ANC), neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and procalcitonin (PCT) were significantly higher in bacterial and mixed cases. After adjusting for covariates, the following were the most important predictors of bacterial or mixed CAP: rainy season (aOR 0.26; 95% CI 0.08-0.90; p = 0.033), CRP ≥5.70 mg/L (aOR 4.71; 95% CI 1.18-18.74; p = 0.028), and presence of fever (aOR 5.26; 95% CI 1.07-25.91; p = 0.041). The model assessed had a low R-squared (Nagelkerke R2 = 0.490) but good calibration (p = 0.610 for Hosmer Lemeshow test). The combination of CRP and fever had moderate predictive value with sensitivity and specificity of 62.28 and 65.52%, respectively. Conclusion Combining clinical and laboratory profiles is potentially valuable for discriminating bacterial and mixed from viral pediatric CAP and may guide antibiotic use. Further studies with a larger sample size should be performed to validate this model.
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Affiliation(s)
- Helmia Farida
- Rumah Sakit Umum Pusat Dr. Kariadi Hospital/Diponegoro University, Semarang, Indonesia
| | - Rina Triasih
- Rumah Sakit Umum Pusat Dr. Sardjito Hospital/Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Dewi Lokida
- Tangerang District General Hospital, Tangerang, Indonesia
| | - Yan Mardian
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Gustiani Salim
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Wahyu Nawang Wulan
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | | | - Rizki Amalia Sari
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Arif Budiman
- Tangerang District General Hospital, Tangerang, Indonesia
| | | | - Moh Syarofil Anam
- Rumah Sakit Umum Pusat Dr. Kariadi Hospital/Diponegoro University, Semarang, Indonesia
| | - Setya Dipayana
- Rumah Sakit Umum Pusat Dr. Kariadi Hospital/Diponegoro University, Semarang, Indonesia
| | - Mujahidah Mujahidah
- Rumah Sakit Umum Pusat Dr. Sardjito Hospital/Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Amalia Setyati
- Rumah Sakit Umum Pusat Dr. Sardjito Hospital/Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Abu Tholib Aman
- Rumah Sakit Umum Pusat Dr. Sardjito Hospital/Universitas Gadjah Mada, Yogyakarta, Indonesia
| | | | - Nurhayati Lukman
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Aly Diana
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Muhammad Karyana
- National Institute of Health Research and Development, Ministry of Health Republic of Indonesia, Jakarta, Indonesia
| | - Ahnika Kline
- National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States
| | - Aaron Neal
- National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States
| | - H. Clifford Lane
- National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States
| | - Herman Kosasih
- Indonesia Research Partnership on Infectious Disease, Jakarta, Indonesia
| | - Chuen-Yen Lau
- National Cancer Institute, Bethesda, MD, United States
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Sathe C, Accordino MK, DeStephano D, Shah M, Wright JD, Hershman DL. Social determinants of health and CDK4/6 inhibitor use and outcomes among patients with metastatic breast cancer. Breast Cancer Res Treat 2023; 200:85-92. [PMID: 37157005 DOI: 10.1007/s10549-023-06957-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 04/23/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Survival outcomes in metastatic breast cancer (MBC) have improved due to novel agents such as CDK4/6 inhibitors (CDK4/6i). Nevertheless, Black patients and patients with lower socioeconomic status (SES) continue to bear a disproportionate mortality burden. METHODS We conducted a retrospective analysis of EHR-derived data from the Flatiron Health Database (FHD). A dataset was constructed to include Black/African-American (Black/AA) and White patients with hormone receptor (HR)-positive, HER2-negative MBC. Outcomes included CDK4/6i use (overall and first-line), and rates of leukopenia, dose reduction, and time on treatment for first-line CDK4/6i. Multivariable logistic regression was used to evaluate factors associated with use and outcomes. RESULTS A total of 6802 patients with MBC were included, of which 5187 (76.3%) received CDK4/6i. Of those, 3186 (61.4%) received CDK4/6i first-line. Overall, 86.7% of patients were categorized as White and 13.3% as Black/AA; 22.4% were > 75 years old; 12.6% were treated at an academic site; 3.3% had Medicaid insurance. In addition to advanced age and poorer performance status, lower use of CDK4/6i was associated with Black/AA vs White race (72.9% vs 76.8%; OR 0.83, 95% CI 0.70-0.99, p = 0.04) and Medicaid vs commercial insurance (69.6% vs 77.4%; OR: 0.68, 95% CI 0.49-0.95, p = 0.02). Odds of CDK4/6i use were twofold higher for patients treated at an academic center (p < 0.001). Rates of CDK4/6i-induced leukopenia and dose reductions did not differ significantly by race, insurance type, or treatment site. Time on CDK4/6i was significantly lower among Medicaid patients (395 days) than patients with commercial insurance (558 days) or Medicare (643 days) (p = 0.03). CONCLUSION This analysis of real-world data suggests that Black race and lower SES are associated with decreased CDK4/6i use. However, among patients treated with CDK4/6i, subsequent toxicity outcomes are similar. Efforts to ensure access to these life-prolonging medications are warranted.
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Affiliation(s)
- Claire Sathe
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA.
| | - Melissa K Accordino
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - David DeStephano
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Mansi Shah
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Jason D Wright
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Dawn L Hershman
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
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Jiang MZ, Aguet F, Ardlie K, Chen J, Cornell E, Cruz D, Durda P, Gabriel SB, Gerszten RE, Guo X, Johnson CW, Kasela S, Lange LA, Lappalainen T, Liu Y, Reiner AP, Smith J, Sofer T, Taylor KD, Tracy RP, VanDenBerg DJ, Wilson JG, Rich SS, Rotter JI, Love MI, Raffield LM, Li Y. Canonical correlation analysis for multi-omics: Application to cross-cohort analysis. PLoS Genet 2023; 19:e1010517. [PMID: 37216410 PMCID: PMC10237647 DOI: 10.1371/journal.pgen.1010517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 06/02/2023] [Accepted: 05/01/2023] [Indexed: 05/24/2023] Open
Abstract
Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.
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Affiliation(s)
- Min-Zhi Jiang
- Department of Applied Physical Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - François Aguet
- Illumina Artificial Intelligence Laboratory, Illumina, Inc., San Diego, California, United States of America
| | - Kristin Ardlie
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Elaine Cornell
- Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, Vermont, United States of America
| | - Dan Cruz
- Department of Medicine, Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - Stacey B. Gabriel
- The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Robert E. Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Craig W. Johnson
- Department of Biostatistics, University of Washington at Seattle, Seattle, Washington, United States of America
| | - Silva Kasela
- New York Genome Center, New York, New York, United States of America
| | - Leslie A. Lange
- Department of Epidemiology, Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, Lifecourse Epidemiology of Adiposity & Diabetes Center, Aurora, Colorado, United States of America
| | - Tuuli Lappalainen
- New York Genome Center, New York, New York, United States of America
| | - Yongmei Liu
- Department of Medicine, Cardiology and Neurology, Duke University Medical Center, Durham, North Carolina, United States of America
| | - Alex P. Reiner
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Josh Smith
- Northwest Genomic Center, University of Washington, Seattle, Washington, United States of America
| | - Tamar Sofer
- Department of Biostatistics, Harvard Medical School, Medicine-Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Kent D. Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont, Colchester, Vermont, United States of America
| | - David J. VanDenBerg
- Department of Preventive Medicine, University of Southern California, Los Angeles, California, United States of America
| | - James G. Wilson
- Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jerome I. Rotter
- Department of Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, University of California at Los Angeles, Torrance, California, United States of America
| | - Michael I. Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Nissen E, Reiner A, Liu S, Wallace RB, Molinaro AM, Salas LA, Christensen BC, Wiencke JK, Koestler DC, Kelsey KT. Assessment of immune cell profiles among post-menopausal women in the Women's Health Initiative using DNA methylation-based methods. Clin Epigenetics 2023; 15:69. [PMID: 37118842 PMCID: PMC10141818 DOI: 10.1186/s13148-023-01488-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 04/19/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND Over the past decade, DNA methylation (DNAm)-based deconvolution methods that leverage cell-specific DNAm markers of immune cell types have been developed to provide accurate estimates of the proportions of leukocytes in peripheral blood. Immune cell phenotyping using DNAm markers, termed immunomethylomics or methylation cytometry, offers a solution for determining the body's immune cell landscape that does not require fresh blood and is scalable to large sample sizes. Despite significant advances in DNAm-based deconvolution, references at the population level are needed for clinical and research interpretation of these additional immune layers. Here we aim to provide some references for immune populations in a group of multi-ethnic post-menopausal American women. RESULTS We applied DNAm-based deconvolution to a large sample of post-menopausal women enrolled in the Women's Health Initiative (baseline, N = 58) or the ancillary Long Life Study (WHI-LLS, N = 1237) to determine the reference ranges of 58 immune parameters, including proportions and absolute counts for 19 leukocyte subsets and 20 derived cell ratios. Participants were 50-94 years old at the time of blood draw, and N = 898 (69.3%) self-identified as White. Using linear regression models, we observed significant associations between age at blood draw and absolute counts and proportions of naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ memory, neutrophils, and natural killer cells. We also assessed the same immune profiles in a subset of paired longitudinal samples collected 14-18 years apart across N = 52 participants. Our results demonstrate high inter-individual variability in rates of change of leukocyte subsets over this time. And, when conducting paired t tests to test the difference in counts and proportions between the baseline visit and LLS visit, there were significant changes in naïve B, memory CD4+, naïve CD4+, naïve CD8+, memory CD8+ cells and neutrophils, similar to the results seen when analyzing the association with age in the entire cohort. CONCLUSIONS Here, we show that derived cell counts largely reflect the immune profile associated with proportions and that these novel methods replicate the known immune profiles associated with age. Further, we demonstrate the value this methylation cytometry approach can add as a potential application in epidemiological studies.
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Affiliation(s)
- Emily Nissen
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, USA
| | - Alexander Reiner
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Simin Liu
- Departments of Epidemiology, Medicine, and Surgery, Brown University, Providence, RI, USA
| | - Robert B Wallace
- Departments of Epidemiology and Internal Medicine, School of Public Health, University of Iowa, Iowa City, IA, USA
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
| | - Brock C Christensen
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Molecular and Systems Biology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
- Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, NH, USA
| | - John K Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Devin C Koestler
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, USA
| | - Karl T Kelsey
- Departments of Epidemiology and Pathology and Laboratory Medicine, Brown University, 70 Ship St, Providence, RI, 02903, USA.
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35
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Fioredda F, Skokowa J, Tamary H, Spanoudakis M, Farruggia P, Almeida A, Guardo D, Höglund P, Newburger PE, Palmblad J, Touw IP, Zeidler C, Warren AJ, Dale DC, Welte K, Dufour C, Papadaki HA. The European Guidelines on Diagnosis and Management of Neutropenia in Adults and Children: A Consensus Between the European Hematology Association and the EuNet-INNOCHRON COST Action. Hemasphere 2023; 7:e872. [PMID: 37008163 PMCID: PMC10065839 DOI: 10.1097/hs9.0000000000000872] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/09/2023] [Indexed: 04/03/2023] Open
Abstract
Neutropenia, as an isolated blood cell deficiency, is a feature of a wide spectrum of acquired or congenital, benign or premalignant disorders with a predisposition to develop myelodysplastic neoplasms/acute myeloid leukemia that may arise at any age. In recent years, advances in diagnostic methodologies, particularly in the field of genomics, have revealed novel genes and mechanisms responsible for etiology and disease evolution and opened new perspectives for tailored treatment. Despite the research and diagnostic advances in the field, real world evidence, arising from international neutropenia patient registries and scientific networks, has shown that the diagnosis and management of neutropenic patients is mostly based on the physicians' experience and local practices. Therefore, experts participating in the European Network for the Innovative Diagnosis and Treatment of Chronic Neutropenias have collaborated under the auspices of the European Hematology Association to produce recommendations for the diagnosis and management of patients across the whole spectrum of chronic neutropenias. In the present article, we describe evidence- and consensus-based guidelines for the definition and classification, diagnosis, and follow-up of patients with chronic neutropenias including special entities such as pregnancy and the neonatal period. We particularly emphasize the importance of combining the clinical findings with classical and novel laboratory testing, and advanced germline and/or somatic mutational analyses, for the characterization, risk stratification, and monitoring of the entire spectrum of neutropenia patients. We believe that the wide clinical use of these practical recommendations will be particularly beneficial for patients, families, and treating physicians.
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Affiliation(s)
| | - Julia Skokowa
- Department of Oncology, Hematology, Immunology, Rheumatology, and Clinical Immunology, University Hospital Tübingen, Germany
| | - Hannah Tamary
- The Rina Zaizov Hematology/Oncology Division, Schneider Children’s Medical Center of Israel, Petah Tikva, Israel
- Sackler School of Medicine, Tel Aviv University, Israel
| | - Michail Spanoudakis
- Department of Hematology, Warrington and Halton Teaching Hospitals NHS foundation Trust, Warrington, United Kingdom
| | - Piero Farruggia
- Pediatric Onco-Hematology, ARNAS Civico Di Cristina Benfratelli Hospital, Palermo, Italy
| | - Antonio Almeida
- Department of Hematology, Hospital da Luz Lisboa, Portugal
- Faculdade de Medicina, Universidade Católica Portuguesa, Lisbon, Portugal
| | - Daniela Guardo
- Unit of Hematology, IRCCS Istituto Giannina Gaslini, Genova, Italy
| | - Petter Höglund
- Clinical Immunology and Transfusion Medicine Clinic, Karolinska University Hospital, Stockholm, Sweden
- Center for Hematology and Regenerative Medicine (HERM), Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
- Department of Hematology, Karolinska University Hospital, Stockholm, Sweden
| | | | - Jan Palmblad
- Center for Hematology and Regenerative Medicine (HERM), Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden
- Department of Hematology, Karolinska University Hospital, Stockholm, Sweden
| | - Ivo P. Touw
- Department of Hematology and Erasmus MC Cancer Institute, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Cornelia Zeidler
- Department of Oncology, Hematology, Immunology and Bone Marrow Transplantation, Hannover Medical School, Hannover, Germany
| | - Alan J. Warren
- Department of Hematology, University of Cambridge, United Kingdom
- Cambridge Institute for Medical Research, University of Cambridge, United Kingdom
- Wellcome Trust–Medical Research Council Stem Cell Institute, University of Cambridge, United Kingdom
| | | | - Karl Welte
- University Children’s Hospital Tübingen, Germany
| | - Carlo Dufour
- Unit of Hematology, IRCCS Istituto Giannina Gaslini, Genova, Italy
| | - Helen A. Papadaki
- Hemopoiesis Research Laboratory, School of Medicine, University of Crete, Heraklion, Greece
- Department of Hematology, University Hospital of Heraklion, Crete, Greece
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36
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Hou K, Ding Y, Xu Z, Wu Y, Bhattacharya A, Mester R, Belbin GM, Buyske S, Conti DV, Darst BF, Fornage M, Gignoux C, Guo X, Haiman C, Kenny EE, Kim M, Kooperberg C, Lange L, Manichaikul A, North KE, Peters U, Rasmussen-Torvik LJ, Rich SS, Rotter JI, Wheeler HE, Wojcik GL, Zhou Y, Sankararaman S, Pasaniuc B. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals. Nat Genet 2023; 55:549-558. [PMID: 36941441 PMCID: PMC11120833 DOI: 10.1038/s41588-023-01338-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 02/16/2023] [Indexed: 03/23/2023]
Abstract
Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (radmix) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis radmix = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies.
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Affiliation(s)
- Kangcheng Hou
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
| | - Yi Ding
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
| | - Ziqi Xu
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Yue Wu
- Department of Computer Science, UCLA, Los Angeles, CA, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Rachel Mester
- Graduate Program in Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Gillian M Belbin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - David V Conti
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Burcu F Darst
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Myriam Fornage
- Brown Foundation Institute for Molecular Medicine, The University of Texas Health Science Center, Houston, TX, USA
| | - Chris Gignoux
- Division of Biomedical Informatics and Personalized Medicine, University of Colorado, Denver, CO, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Christopher Haiman
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, 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
| | - Michelle Kim
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Charles Kooperberg
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Leslie Lange
- Department of Medicine, University of Colorado, Aurora, CO, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Kari E North
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ulrike Peters
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Heather E Wheeler
- Department of Biology, Loyola University Chicago, Chicago, IL, USA
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Ying Zhou
- Division of Public Health Science, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sriram Sankararaman
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA
- Department of Computer Science, UCLA, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
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37
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Crawford KS, Volkman BF. Prospects for targeting ACKR1 in cancer and other diseases. Front Immunol 2023; 14:1111960. [PMID: 37006247 PMCID: PMC10050359 DOI: 10.3389/fimmu.2023.1111960] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/03/2023] [Indexed: 03/17/2023] Open
Abstract
The chemokine network is comprised of a family of signal proteins that encode messages for cells displaying chemokine G-protein coupled receptors (GPCRs). The diversity of effects on cellular functions, particularly directed migration of different cell types to sites of inflammation, is enabled by different combinations of chemokines activating signal transduction cascades on cells displaying a combination of receptors. These signals can contribute to autoimmune disease or be hijacked in cancer to stimulate cancer progression and metastatic migration. Thus far, three chemokine receptor-targeting drugs have been approved for clinical use: Maraviroc for HIV, Plerixafor for hematopoietic stem cell mobilization, and Mogalizumab for cutaneous T-cell lymphoma. Numerous compounds have been developed to inhibit specific chemokine GPCRs, but the complexity of the chemokine network has precluded more widespread clinical implementation, particularly as anti-neoplastic and anti-metastatic agents. Drugs that block a single signaling axis may be rendered ineffective or cause adverse reactions because each chemokine and receptor often have multiple context-specific functions. The chemokine network is tightly regulated at multiple levels, including by atypical chemokine receptors (ACKRs) that control chemokine gradients independently of G-proteins. ACKRs have numerous functions linked to chemokine immobilization, movement through and within cells, and recruitment of alternate effectors like β-arrestins. Atypical chemokine receptor 1 (ACKR1), previously known as the Duffy antigen receptor for chemokines (DARC), is a key regulator that binds chemokines involved in inflammatory responses and cancer proliferation, angiogenesis, and metastasis. Understanding more about ACKR1 in different diseases and populations may contribute to the development of therapeutic strategies targeting the chemokine network.
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Affiliation(s)
- Kyler S. Crawford
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, United States
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38
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Pincez T, Lo KS, D'Orengiani ALPHD, Garrett ME, Brugnara C, Ashley-Koch AE, Telen MJ, Galacteros F, Joly P, Bartolucci P, Lettre G. Variation and impact of polygenic hematologic traits in monogenic sickle cell disease. Haematologica 2023; 108:870-881. [PMID: 36226494 PMCID: PMC9973495 DOI: 10.3324/haematol.2022.281180] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Indexed: 11/09/2022] Open
Abstract
Several of the complications observed in sickle cell disease (SCD) are influenced by variation in hematologic traits (HT), such as fetal hemoglobin (HbF) level and neutrophil count. Previous large-scale genome-wide association studies carried out in largely healthy individuals have identified thousands of variants associated with HT, which have then been used to develop multi-ancestry polygenic trait scores (PTS). Here, we tested whether these PTS associate with HT in SCD patients and if they can improve statistical models associated with SCD-related complications. In 2,056 SCD patients, we found that the PTS predicted less HT variance than in non-SCD individuals of African ancestry. This was particularly striking at the Duffy/DARC locus, where we observed an epistatic interaction between the SCD genotype and the Duffy null variant (rs2814778) that led to a two-fold weaker effect on neutrophil count. PTS for these HT which are measured as part of routine practice were not associated with complications in SCD. In contrast, we found that a simple PTS for HbF that includes only six variants explained a large fraction of the phenotypic variation (20.5-27.1%), associated with acute chest syndrome and stroke risk, and improved the statistical modeling of the vaso-occlusive crisis rate. Using Mendelian randomization, we found that increasing HbF by 4.8% reduces stroke risk by 39% (P=0.0006). Taken together, our results highlight the importance of validating PTS in large diseased populations before proposing their implementation in the context of precision medicine initiatives.
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Affiliation(s)
- Thomas Pincez
- Montreal Heart Institute, Montreal, Quebec, Canada; Department of Pediatrics, Division of Pediatric Hematology-Oncology, Charles-Bruneau Cancer Center, CHU Sainte-Justine, Universite de Montreal, Montreal, Quebec
| | - Ken Sin Lo
- Montreal Heart Institute, Montreal, Quebec
| | | | - Melanie E Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC
| | - Carlo Brugnara
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, MA
| | | | - Marilyn J Telen
- Department of Medicine, Division of Hematology, Duke University Medical Center, Durham, NC
| | - Frederic Galacteros
- Red Cell Genetic Disease Unit, Hopital Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris Est, IMRB - U955 - Equipe no 2, Creteil
| | - Philippe Joly
- Unite Fonctionnelle 34445 'Biochimie des Pathologies Erythrocytaires', Laboratoire de Biochimie et Biologie Moleculaire Grand-Est, Groupement Hospitalier Est, Hospices Civils de Lyon, Bron, France; Laboratoire Inter-Universitaire de Biologie de la Motricite (LIBM) EA7424, Equipe 'Biologie Vasculaire et du Globule Rouge', Universite Claude Bernard Lyon 1, Comite d'Universites et d'Etablissements (COMUE), Lyon
| | - Pablo Bartolucci
- Red Cell Genetic Disease Unit, Hopital Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris Est, IMRB - U955 - Equipe no 2, Creteil
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, Quebec, Canada; Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec.
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39
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Bagheri M, Chung CP, Dickson AL, Van Driest SL, Borinstein SC, Mosley JD. White blood cell ranges and frequency of neutropenia by Duffy genotype status. Blood Adv 2023; 7:406-409. [PMID: 35895516 PMCID: PMC9979714 DOI: 10.1182/bloodadvances.2022007680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 07/07/2022] [Accepted: 07/08/2022] [Indexed: 02/02/2023] Open
Affiliation(s)
- Minoo Bagheri
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Cecilia P. Chung
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Alyson L. Dickson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
| | - Scott C. Borinstein
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
| | - Jonathan D. Mosley
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
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40
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Lesegretain A, Brunner A, King AJ, Laadem A, Fell G, Fathi AT. Comparison of demographics, disease characteristics, and outcomes between Black and White patients with myelodysplastic syndromes: A population-based study. Leuk Res 2023; 125:107006. [PMID: 36580877 DOI: 10.1016/j.leukres.2022.107006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 12/27/2022]
Abstract
Racial disparities in cancer care and outcomes have been well documented in various malignancies, with Black patients having the highest death rate and shortest survival of any racial/ethnic group in the United States (US) for most cancers. However, there have been limited studies on racial/ethnic disparities in myelodysplastic syndromes (MDS). Our study characterized and compared differences in baseline demographics, clinical characteristics, socioeconomic factors, and overall survival (OS) between Black and White patients with MDS in the US. We used the Surveillance, Epidemiology, and End Results (SEER) Program and included 37,562 patients (Black, 8.1 %; White, 91.9 %) diagnosed between 2001 and 2013. We observed significant differences in baseline characteristics between cohorts. In a univariate analysis, Black race was associated with longer survival (hazard ratio [HR]: 0.83; 95 % confidence interval [CI], 0.79-0.86; p < 0.001). The association between race and survival was attenuated but remained significant in various models to adjust for differences in baseline characteristics (HR in multivariable analysis, 0.92; 95 % CI, 0.87-0.96); p < 0.001). Subgroup analysis by histology revealed differences in the association between race and OS. Refractory anemia (RA), RA with ring sideroblasts, and MDS-not otherwise specified, a category in SEER representing a poorly defined MDS subset for 52 % of cases in our study, favored Black patients. RA with excess blasts favored White patients. The overall finding that Black race is associated with better OS outcomes, when compared with White patients, needs to be interpreted with caution and nuanced by histology. Additional research to explore these associations is warranted.
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Affiliation(s)
- Arnaud Lesegretain
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA; Daiichi Sankyo, 211 Mt Airy Rd, Basking Ridge, NJ 07920, USA.
| | - Andrew Brunner
- Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
| | - Andrew J King
- Department of Health Care Policy, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.
| | | | - Geoffrey Fell
- Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, USA.
| | - Amir T Fathi
- Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
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41
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Elgart M, Goodman MO, Isasi C, Chen H, Morrison AC, de Vries PS, Xu H, Manichaikul AW, Guo X, Franceschini N, Psaty BM, Rich SS, Rotter JI, Lloyd-Jones DM, Fornage M, Correa A, Heard-Costa NL, Vasan RS, Hernandez R, Kaplan RC, Redline S, Sofer T. Correlations between complex human phenotypes vary by genetic background, gender, and environment. Cell Rep Med 2022; 3:100844. [PMID: 36513073 PMCID: PMC9797952 DOI: 10.1016/j.xcrm.2022.100844] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 07/11/2022] [Accepted: 11/09/2022] [Indexed: 12/15/2022]
Abstract
We develop a closed-form Haseman-Elston estimator for genetic and environmental correlation coefficients between complex phenotypes, which we term HEc, that is as precise as GCTA yet ∼20× faster. We estimate genetic and environmental correlations between over 7,000 phenotype pairs in subgroups from the Trans-Omics in Precision Medicine (TOPMed) program. We demonstrate substantial differences in both heritabilities and genetic correlations for multiple phenotypes and phenotype pairs between individuals of self-reported Black, Hispanic/Latino, and White backgrounds. We similarly observe differences in many of the genetic and environmental correlations between genders. To estimate the contribution of genetics to the observed phenotypic correlation, we introduce "fractional genetic correlation" as the fraction of phenotypic correlation explained by genetics. Finally, we quantify the enrichment of correlations between phenotypic domains, each of which is comprised of multiple phenotypes. Altogether, we demonstrate that the observed correlations between complex human phenotypes depend on the genetic background of the individuals, their gender, and their environment.
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Affiliation(s)
- Michael Elgart
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
| | - Matthew O Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Carmen Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA; Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Huichun Xu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Xiuqing Guo
- 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
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, 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
| | | | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA; Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Adolfo Correa
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nancy L Heard-Costa
- Boston University and National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Ramachandran S Vasan
- Boston University and National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA; Preventive Medicine & Epidemiology, and Cardiovascular Medicine, Medicine, Boston University School of Medicine, and Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Ryan Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA; Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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Harvey S, Wolter-Warmerdam K, Hickey F, Daniels D, DomBourian M, Ambruso DR, McKinney C. Blood counts in children with Down syndrome. Pediatr Blood Cancer 2022; 69:e30002. [PMID: 36151966 DOI: 10.1002/pbc.30002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/23/2022] [Accepted: 08/29/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Children with Down syndrome (DS) are more likely to have hematologic and immunologic abnormalities compared to their typically developing peers, but normal ranges have not been defined. The goal of this study was to create references for complete blood counts (CBCs) in patients with DS. METHODS A retrospective investigation of 355 (male = 196, 55.2%; mean age = 6.49 years, SD = 5.07) healthy pediatric patients with DS who received a CBC between 2011 and 2017 as part of their medical care at a single, large, pediatric teaching hospital. Control data on 770 healthy patients without DS were included. Descriptive statistics were performed on demographic and clinical characteristics. Kruskal-Wallis H tests, nested analysis-of-variance tests, and t-tests were run to determine the significant associations. RESULTS Age-related normative curves for healthy children with DS outlining 2.5th, 25th, 50th, 75th, and 97.5th percentiles are provided for total white blood count, hemoglobin concentration, hematocrit, mean corpuscular volume, and platelet, absolute neutrophil, absolute lymphocyte, eosinophil, monocyte, and basophil counts. Statistical differences were found between children with and without DS receiving care at the same hospital based on matched age/sex groups. CONCLUSIONS This study demonstrates that patients with DS have different reference ranges for multiple blood counts compared to those without DS, creating a new resource for pediatricians to refer to when evaluating CBCs in this population.
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Affiliation(s)
- Susan Harvey
- Center of Cancer and Blood Disorders, Children's Hospital Colorado, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA.,Department of Pediatrics, Children's National, Washington, District of Columbia, USA
| | | | - Francis Hickey
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA.,Sie Center for Down Syndrome, Children's Hospital Colorado, Aurora, Colorado, USA
| | - Dee Daniels
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA.,Sie Center for Down Syndrome, Children's Hospital Colorado, Aurora, Colorado, USA
| | - Melkon DomBourian
- Department of Pathology, Children's Hospital Colorado, Aurora, Colorado, USA.,Department of Pathology, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Daniel R Ambruso
- Center of Cancer and Blood Disorders, Children's Hospital Colorado, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Christopher McKinney
- Center of Cancer and Blood Disorders, Children's Hospital Colorado, Aurora, Colorado, USA.,Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA
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43
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Chung CP, Karakoc G, Liu G, Gamboa JL, Mosley JD, Cox NJ, Stein CM, Kawai V. Ancestry, ACKR1 and leucopenia in patients with systemic lupus erythematosus. Lupus Sci Med 2022; 9:e000790. [PMID: 36376015 PMCID: PMC9664301 DOI: 10.1136/lupus-2022-000790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 10/14/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE SLE is more prevalent in populations of African (AA) than European ancestry (EA) and leucopenia is common. A homozygous variant in ACKR1 (rs2814778-CC) is associated with lower white cell counts; the variant is common in AA but not EA populations. We hypothesised that in SLE: (1) leucopenia is more frequent in patients of AA than EA, and (2) the ACKR1-CC genotype accounts for the higher frequency of leucopenia in AA patients. METHODS We performed a retrospective cohort study in patients with SLE at a tertiary care system. Ancestry was defined by genetic principal components. We compared the rate of leucopenia, thrombocytopenia and anaemia between (a) EA and AA patients, and (b) ACKR1-CT/TT and CC genotype in AA patients. RESULTS The cohort included 574 patients of EA and 190 of AA; ACKR1-CC genotype was common in AA (70%) but not EA (0%) patients. Rates of leucopenia for ancestry and genotype were AA 60.0% vs EA 36.8 % (p=1.9E-08); CC 67.7% vs CT/TT 42.1% (p=9.8E-04). The rate of leucopenia did not differ by ancestry comparing EA patients versus AA with CT/TT genotype (p=0.59). Thrombocytopenia (22.2% vs 13.2%, p=0.004) and anaemia (88.4% vs 66.2%, p=3.7E-09) were more frequent in AA patients but were not associated with ACKR1 genotype (p=0.82 and p=0.84, respectively). CONCLUSIONS SLE of AA had higher rates of anaemia, leucopenia, and thrombocytopenia than those of EA; only the difference in leucopenia was explained by ACKR1-CC genotype. This genotype could affect clinical practice.
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Affiliation(s)
- Cecilia P Chung
- Division of Rheumatology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Tennessee Valley Healthcare System - Nashville Campus, Nashville, Tennessee, USA
| | - Gul Karakoc
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ge Liu
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jorge L Gamboa
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jonathan D Mosley
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - C Michael Stein
- Division of Rheumatology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Vivian Kawai
- Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Ghosh P, Campos VJ, Vo DT, Guccione C, Goheen-Holland V, Tindle C, Mazzini GS, He Y, Alexandrov LB, Lippman SM, Gurski RR, Das S, Yadlapati R, Curtius K, Sahoo D. AI-assisted discovery of an ethnicity-influenced driver of cell transformation in esophageal and gastroesophageal junction adenocarcinomas. JCI Insight 2022; 7:e161334. [PMID: 36134663 PMCID: PMC9675486 DOI: 10.1172/jci.insight.161334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/10/2022] [Indexed: 11/17/2022] Open
Abstract
Although Barrett's metaplasia of the esophagus (BE) is the only known precursor lesion to esophageal adenocarcinomas (EACs), drivers of cellular transformation in BE remain incompletely understood. We use an artificial intelligence-guided network approach to study EAC initiation and progression. Key predictions are subsequently validated in a human organoid model, in patient-derived biopsy specimens of BE, a case-control study of genomics of BE progression, and in a cross-sectional study of 113 patients with BE and EACs. Our model classified healthy esophagus from BE and BE from EACs in several publicly available gene expression data sets (n = 932 samples). The model confirmed that all EACs must originate from BE and pinpointed a CXCL8/IL8↔neutrophil immune microenvironment as a driver of cellular transformation in EACs and gastroesophageal junction adenocarcinomas. This driver is prominent in White individuals but is notably absent in African Americans (AAs). Network-derived gene signatures, independent signatures of neutrophil processes, CXCL8/IL8 expression, and an absolute neutrophil count (ANC) are associated with risk of progression. SNPs associated with changes in ANC by ethnicity (e.g., benign ethnic neutropenia [BEN]) modify that risk. Findings define a racially influenced immunological basis for cell transformation and suggest that BEN in AAs may be a deterrent to BE→EAC progression.
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Affiliation(s)
- Pradipta Ghosh
- Department of Cellular and Molecular Medicine
- Department of Medicine
- HUMANOID Center of Research Excellence, and
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
| | - Vinicius J. Campos
- Department of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | | | - Caitlin Guccione
- Division of Biomedical Informatics, UCSD, La Jolla, California, USA
| | - Vanae Goheen-Holland
- Department of Cellular and Molecular Medicine
- HUMANOID Center of Research Excellence, and
| | - Courtney Tindle
- Department of Cellular and Molecular Medicine
- HUMANOID Center of Research Excellence, and
| | - Guilherme S. Mazzini
- Department of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Postgraduate Program in Medicine, Surgical Scienceas, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Yudou He
- Department of Cellular and Molecular Medicine
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
| | - Ludmil B. Alexandrov
- Department of Cellular and Molecular Medicine
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
| | - Scott M. Lippman
- Department of Medicine
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
| | - Richard R. Gurski
- Department of Gastrointestinal Surgery, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Postgraduate Program in Medicine, Surgical Scienceas, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
- Medical School of Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Soumita Das
- HUMANOID Center of Research Excellence, and
- Department of Pathology and
| | | | - Kit Curtius
- Department of Medicine
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
- Division of Biomedical Informatics, UCSD, La Jolla, California, USA
| | - Debashis Sahoo
- Moores Comprehensive Cancer Center, UCSD, La Jolla, California, USA
- Department of Pediatrics and
- Department of Computer Science and Engineering, Jacob’s School of Engineering, UCSD, California, La Jolla, USA
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Yassin MA, Soliman AT, Hmissi SM, Abdulla MA, Itani M, Alamami AA, Aldapt MB, Suliman AM, Ibrahim EA, Mohamed MF, Rozi W, Mohamed SF, Chandra P, Nashwan AJ. Prevalence of neutropenia among adult Arabs in Qatar: Relation to other hematological parameters and anthropometric data. Medicine (Baltimore) 2022; 101:e30431. [PMID: 36086749 PMCID: PMC10980397 DOI: 10.1097/md.0000000000030431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 07/27/2022] [Indexed: 11/26/2022] Open
Abstract
Neutropenia ranges from a normal variant to life-threatening acquired and congenital disorders. This study aims at providing baseline information regarding the prevalence and spectrum of neutropenia in the Arab blood donors who are living in Qatar. This retrospective cohort study was conducted to review the data of healthy Arab individuals (≥18 years) who donated blood between January 1, 2015 to May 15, 2019. A complete blood count was performed using automated analyzers. The prevalence of neutropenia was 10.7%. The prevalence in females was 32% and in males, it was 6%. Absolute neutrophil count (ANC) below 1 × 109/L was detected in 10% of Arab females and 1.8 % of Arab males. In females, the neutropenic group had significantly lower hemoglobin (Hb) levels and higher red cell distribution width, and lower total white blood cells and lymphocyte counts (P < .001) compared to the group with ANC > 1.5 × 109/L. Significant correlations were found between the ANC and Hb (r = 0.33, P < .05) and ANC and total white blood cells (r = 0.45, P < .01). The prevalence of neutropenia is considerably high in Arab adult females compared to other ethnic groups. Besides the genetic constitution of Arabs, the lower Hb and higher red cell distribution width in females suggest that iron deficiency could contribute to the development of neutropenia.
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Affiliation(s)
- Mohamed A. Yassin
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Ashraf T. Soliman
- Division of Endocrinology, Department of Pediatrics, Hamad General Hospital (HGH), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Saloua M. Hmissi
- Blood Transfusion Center, Hamad Medical Corporation (HMC), Doha, Qatar
| | - Mohammad A.J. Abdulla
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Maya Itani
- Department of Dietetics and Nutrition, Hamad Medical Corporation (HMC), Doha, Qatar
| | - Ans A. Alamami
- Department of Critical Care Medicine, Hamad General Hospital (HGH), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Mahmood B. Aldapt
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Aasir M. Suliman
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Ezzeddin A. Ibrahim
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | | | - Waail Rozi
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Shehab F. Mohamed
- Department of Medical Oncology/Hematology, National Centre for Cancer Care and Research (NCCCR), Hamad Medical Corporation (HMC), Doha, Qatar
| | - Prem Chandra
- Medical Research Center, Hamad Medical Corporation (HMC), Doha, Qatar
| | - Abdulqadir J. Nashwan
- Department of Nursing, Hazm Mebaireek General Hospital (HMGH), Hamad Medical Corporation (HMC), Doha, Qatar
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Johnson R, Ding Y, Venkateswaran V, Bhattacharya A, Boulier K, Chiu A, Knyazev S, Schwarz T, Freund M, Zhan L, Burch KS, Caggiano C, Hill B, Rakocz N, Balliu B, Denny CT, Sul JH, Zaitlen N, Arboleda VA, Halperin E, Sankararaman S, Butte MJ, Lajonchere C, Geschwind DH, Pasaniuc B. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative. Genome Med 2022; 14:104. [PMID: 36085083 PMCID: PMC9461263 DOI: 10.1186/s13073-022-01106-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 08/03/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative-an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736). METHODS We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture. We assess the relationship between genetically inferred ancestry (GIA) and >1500 EHR-derived phenotypes (phecodes). Finally, we demonstrate the utility of genetic data linked with EHR to perform ancestry-specific and multi-ancestry genome and phenome-wide scans across a broad set of disease phenotypes. RESULTS We identify 5 continental-scale GIA clusters including European American (EA), African American (AA), Hispanic Latino American (HL), South Asian American (SAA) and East Asian American (EAA) individuals and 7 subcontinental GIA clusters within the EAA GIA corresponding to Chinese American, Vietnamese American, and Japanese American individuals. Although we broadly find that self-identified race/ethnicity (SIRE) is highly correlated with GIA, we still observe marked differences between the two, emphasizing that the populations defined by these two criteria are not analogous. We find a total of 259 significant associations between continental GIA and phecodes even after accounting for individuals' SIRE, demonstrating that for some phenotypes, GIA provides information not already captured by SIRE. GWAS identifies significant associations for liver disease in the 22q13.31 locus across the HL and EAA GIA groups (HL p-value=2.32×10-16, EAA p-value=6.73×10-11). A subsequent PheWAS at the top SNP reveals significant associations with neurologic and neoplastic phenotypes specifically within the HL GIA group. CONCLUSIONS Overall, our results explore the interplay between SIRE and GIA within a disease context and underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping linked with EHR-based phenotyping.
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Affiliation(s)
- Ruth Johnson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Yi Ding
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Vidhya Venkateswaran
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Oral Biology, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kristin Boulier
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Medicine, Division of Cardiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Alec Chiu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sergey Knyazev
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tommer Schwarz
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Malika Freund
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA
| | - Lingyu Zhan
- Molecular Biology Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kathryn S Burch
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Christa Caggiano
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Brian Hill
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Nadav Rakocz
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Brunilda Balliu
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Christopher T Denny
- Division of Hematology/Oncology, Department of Pediatrics, Gwynne Hazen Cherry Memorial Laboratories, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Noah Zaitlen
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Valerie A Arboleda
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Eran Halperin
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Manish J Butte
- Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Clara Lajonchere
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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Absolute neutrophil count by Duffy status among healthy Black and African American adults. Blood Adv 2022; 7:317-320. [PMID: 35994632 PMCID: PMC9881043 DOI: 10.1182/bloodadvances.2022007679] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 08/08/2022] [Accepted: 08/08/2022] [Indexed: 02/01/2023] Open
Abstract
Many people of African ancestry have lower absolute neutrophil counts (ANCs) without increased risk for infection. This is associated with the Duffy-null phenotype (nonexpression of the Duffy antigen on red blood cells), which is commonly found in those of African descent. Currently, there are no studies that compare the ANC of individuals with Duffy-null phenotype to those with Duffy non-null phenotypes within a self-identified Black population. The aim of this study was to assess the impact of Duffy status on ANCs based on complete blood counts with differential and Duffy testing in a healthy population of self-identified Black individuals at a single primary care center. This study found that 66.7% (80 of 120) of Black individuals have the Duffy-null phenotype and that there is a significant difference in ANCs between Duffy-null and Duffy non-null individuals (median, 2820 cells per μL vs 5005 cells per μL; P < .001). Additionally, 19 of 80 (23.8%) Duffy-null individuals had an ANC of <2000 cells per μL compared with no (0) Duffy non-null individuals. The Duffy-null phenotype is clinically insignificant; however, inappropriate reference ranges can propagate systemic racism. Therefore, we advocate for the development of Duffy-null-specific ANC reference ranges as well as replacing the term benign ethnic neutropenia with Duffy-nullassociated neutrophil count.
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48
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Dickson AL, Daniel LL, Jackson E, Zanussi J, Yang W, Plummer WD, Dupont WD, Wei WQ, Nepal P, Hung AM, Cox NJ, Van Driest SL, Feng Q, Yang JJ, Stein CM, Mosley JD, Chung CP. Race, Genotype, and Azathioprine Discontinuation : A Cohort Study. Ann Intern Med 2022; 175:1092-1099. [PMID: 35724382 PMCID: PMC9378477 DOI: 10.7326/m21-4675] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Thiopurines are an important class of immunosuppressants despite their risk for hematopoietic toxicity and narrow therapeutic indices. Benign neutropenia related to an ACKR1 variant (rs2814778-CC) is common among persons of African ancestries. OBJECTIVE To test whether rs2814778-CC was associated with azathioprine discontinuation attributed to hematopoietic toxicity and lower thiopurine dosing. DESIGN Retrospective cohort study. SETTING Two tertiary care centers. PATIENTS Thiopurine users with White or Black race. MEASUREMENTS Azathioprine discontinuation attributed to hematopoietic toxicity. Secondary outcomes included weight-adjusted final dose, leukocyte count, and change in leukocyte count. RESULTS The rate of azathioprine discontinuation attributed to hematopoietic toxicity was 3.92 per 100 person-years among patients with the CC genotype (n = 101) and 1.34 per 100 person-years among those with the TT or TC genotype (n = 1365) (hazard ratio [HR] from competing-risk model, 2.92 [95% CI, 1.57 to 5.41]). The risk remained significant after adjustment for race (HR, 2.61 [CI, 1.01 to 6.71]). The risk associated with race alone (HR, 2.13 [CI, 1.21 to 3.75]) was abrogated by adjustment for genotype (HR, 1.13 [CI, 0.48 to 2.69]). Lower last leukocyte count and lower dosing were significant among patients with the CC genotype. Lower dosing was validated in an external cohort of 94 children of African ancestries prescribed the thiopurine 6-mercaptopurine (6-MP) for acute lymphoblastic leukemia. The CC genotype was independently associated with lower 6-MP dose intensity relative to the target daily dose of 75 mg/m2 (median, 0.83 [IQR, 0.70 to 0.94] for the CC genotype vs. 0.94 [IQR, 0.72 to 1.13] for the TT or TC genotype; P = 0.013). LIMITATIONS Unmeasured confounding; data limited to tertiary centers. CONCLUSION Patients with the CC genotype had higher risk for azathioprine discontinuation attributed to hematopoietic toxicity and lower thiopurine doses. Genotype was associated with those risks, even after adjustment for race. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- Alyson L Dickson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Laura L Daniel
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Elise Jackson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Jacy Zanussi
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Wenjian Yang
- Pharmacy and Pharmaceutical Sciences Department, St. Jude Children's Research Hospital, Memphis, Tennessee (W.Y., J.J.Y.)
| | - W Dale Plummer
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee (W.D.P., W.D.D.)
| | - William D Dupont
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee (W.D.P., W.D.D.)
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee (W.W.)
| | - Puran Nepal
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Adriana M Hung
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Nancy J Cox
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Sara L Van Driest
- Departments of Medicine and Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee (S.L.V.)
| | - QiPing Feng
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Jun J Yang
- Pharmacy and Pharmaceutical Sciences Department, St. Jude Children's Research Hospital, Memphis, Tennessee (W.Y., J.J.Y.)
| | - C Michael Stein
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
| | - Jonathan D Mosley
- Departments of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee (J.D.M.)
| | - Cecilia P Chung
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee (A.L.D., L.L.D., E.J., J.Z., P.N., A.M.H., N.J.C., Q.F., C.M.S., C.P.C.)
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49
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Watson JA, Uyoga S, Wanjiku P, Makale J, Nyutu GM, Mturi N, George EC, Woodrow CJ, Day NPJ, Bejon P, Opoka RO, Dondorp AM, John CC, Maitland K, Williams TN, White NJ. Improving the diagnosis of severe malaria in African children using platelet counts and plasma PfHRP2 concentrations. Sci Transl Med 2022; 14:eabn5040. [PMID: 35857826 PMCID: PMC7613613 DOI: 10.1126/scitranslmed.abn5040] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Severe malaria caused by Plasmodium falciparum is difficult to diagnose accurately in children in high-transmission settings. Using data from 2649 pediatric and adult patients enrolled in four studies of severe illness in three countries (Bangladesh, Kenya, and Uganda), we fitted Bayesian latent class models using two diagnostic markers: the platelet count and the plasma concentration of P. falciparum histidine-rich protein 2 (PfHRP2). In severely ill patients with clinical features consistent with severe malaria, the combination of a platelet count of ≤150,000/μl and a plasma PfHRP2 concentration of ≥1000 ng/ml had an estimated sensitivity of 74% and specificity of 93% in identifying severe falciparum malaria. Compared with misdiagnosed children, pediatric patients with true severe malaria had higher parasite densities, lower hematocrits, lower rates of invasive bacterial disease, and a lower prevalence of both sickle cell trait and sickle cell anemia. We estimate that one-third of the children enrolled into clinical studies of severe malaria in high-transmission settings in Africa had another cause of their severe illness.
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Affiliation(s)
- James A. Watson
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK,Corresponding author.
| | - Sophie Uyoga
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Perpetual Wanjiku
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Johnstone Makale
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Gideon M. Nyutu
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Neema Mturi
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Elizabeth C. George
- Medical Research Council Clinical Trials Unit, University College London, London, UK
| | - Charles J. Woodrow
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nicholas P. J. Day
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Philip Bejon
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK,KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya
| | - Robert O. Opoka
- Makerere University, Department of Paediatrics and Child Health, Kampala, Uganda
| | - Arjen M. Dondorp
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chandy C. John
- Department of Pediatrics, Indiana University, Indiana, IN, USA
| | - Kathryn Maitland
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya,Institute of Global Health Innovation, Department of Surgery and Cancer, Imperial College, London, UK
| | - Thomas N. Williams
- KEMRI Wellcome Trust Research Programme, Centre for Geographic Medicine Research, Coast, Kilifi 80108, Kenya,Institute of Global Health Innovation, Department of Surgery and Cancer, Imperial College, London, UK
| | - Nicholas J. White
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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50
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Mitr R, Pollack JR. RE: Lower Exome Sequencing Coverage of Ancestrally African Patients in the Cancer Genome Atlas. J Natl Cancer Inst 2022; 114:1728. [PMID: 35801943 PMCID: PMC9745426 DOI: 10.1093/jnci/djac132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/28/2022] [Indexed: 01/11/2023] Open
Affiliation(s)
- Rhea Mitr
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jonathan R Pollack
- Correspondence to: Jonathan R. Pollack, MD, PhD, Department of Pathology, Stanford University School of Medicine, 269 Campus Dr, CCSR-3245A, Stanford, CA, USA (e-mail: )
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