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Arigbede O, Amusa T, Buxbaum SG. Exploring the Use of Artificial Intelligence and Robotics in Prostate Cancer Management. Cureus 2023; 15:e46021. [PMID: 37900395 PMCID: PMC10602629 DOI: 10.7759/cureus.46021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 10/31/2023] Open
Abstract
Integrating artificial intelligence (AI) and robotics in prostate cancer (PCa) offers a game-changing breakthrough with far-reaching implications for diagnosis, treatment, and research. AI-driven algorithms have tremendous promise for assisting early diagnosis by analyzing invisible trends within medical imaging devices such as MRI and ultrasounds. In addition, by evaluating big datasets containing patient data, genetic attributes, and treatment outcomes, these AI algorithms offer the possibility of allowing individualized treatment regimens. This ability to personalize actions to specific patients might improve therapy efficacy while reducing side effects. Robotics can increase accuracy in less invasive surgery, revolutionize therapies like prostatectomies, and improve recovery time for patients. Robotic-assisted procedures provide clinicians with remarkable skills and flexibility, allowing clinicians to negotiate complicated anatomical structures more precisely. However, the symbiotic combination of AI and robotics has several drawbacks. Concerns about data privacy, algorithm biases, and the need to continually assess AI's diagnostic proficiency offer significant hurdles. To ensure patient privacy and data security, the ethical and regulatory aspects of integrating AI and robotics require proper attention. However, combining AI and robotics opens up a galaxy of possibilities. The joint use of AI and robotics can potentially speed up drug development procedures by filtering through massive databases, resulting in the identification of new medicinal compounds. Furthermore, combining AI and robotics might usher in an innovative era of personalized medicine, allowing healthcare providers to design therapies based on detailed patient profiles. The merging of AI and robotics in PCa care gives up unprecedented prospects. While limitations highlight the necessity for caution, the possibilities of better diagnostics, tailored therapies, and new research pathways highlight the transformational abilities of AI and robotics in determining the future of PCa management. This study explores the limitations and opportunities presented by using AI and robotics in the context of PCa.
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Affiliation(s)
- Olumide Arigbede
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, USA
- Oak Ridge Institute for Science and Education, Centers for Disease Control and Prevention, Atlanta, USA
| | - Tope Amusa
- Department of Biostatistics, Georgia State University, Atlanta, USA
| | - Sarah G Buxbaum
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, USA
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Buxbaum SG, Arigbede O, Mathis A, Close F, Darling-Reed SF. Breastfeeding among Hispanic and Black Women: Barriers and Support. J Biomed Res Environ Sci 2023; 4:1268-1273. [PMID: 37719645 PMCID: PMC10503689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
We describe barriers and supports for the practice of breastfeeding, with particular focus on Black and Hispanic women in the United States. We note that breastfeeding patterns reported by WIC agencies is highly variable across the country and within states. The global campaign to support breastfeeding, Baby Friendly Hospital Initiative, and its implementation in the US is described, as well as Healthy People goals and the mixture of policies across the US that provide incomplete support for breastfeeding mothers.
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Affiliation(s)
- Sarah G Buxbaum
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, USA
| | - Olumide Arigbede
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, USA
| | - Arlesia Mathis
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, USA
| | - Fran Close
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, USA
| | - Selina F Darling-Reed
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, USA
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Buxbaum SG, Arigbede O, Mathis A, Close F, Suther SG, Mazzio E, Saunders-Jones R, Soliman KFA, Darling-Reed SF. Disparities in Infant Nutrition: WIC Participation and Rates of Breastfeeding in Florida. Int J Environ Res Public Health 2023; 20:5988. [PMID: 37297592 PMCID: PMC10253221 DOI: 10.3390/ijerph20115988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 06/12/2023]
Abstract
Being cognizant of the pronounced health advantages of breastfeeding for both the nursing mother and her infant, the breastfeeding dyad, we examined breastfeeding rates among Floridian women who gave birth from 2012 to 2014 (N = 639,052). We investigated the associations between breastfeeding initiation and WIC-based breastfeeding support (the Special Supplemental Nutrition Program for Women, Infants, and Children), education level, and race and ethnicity. We compared the percentage of breastfeeding mothers between those in the WIC program and those who were not, and we compared breastfeeding rates across racial and ethnic groups. Consistent with previous reports, black newborns in this study were breastfed at lower rates than other racial groups, and WIC program participants were less likely to breastfeed than non-WIC program participants. However, by breaking down the data by education level and race, and ethnicity, we see a significantly increased rate of breastfeeding due to WIC participation for both Hispanic and black women with less than a high school education. Further, we assessed differences by insurance type, race, and WIC participation. In multivariable logistic regression, we showed that the WIC program has a significant positive impact on breastfeeding rates for all but white non-Hispanic mothers, independent of sociodemographic and geographic variables. We also note a trend of increasing breastfeeding rates over the study period (p-value < 0.0001), which has positive public health implications.
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Affiliation(s)
- Sarah G. Buxbaum
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A & M University, Tallahassee, FL 32307, USA
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Brown A, Wu Z, Cao H, Falzarano SM, Buxbaum SG, Rhie SK. Abstract 2060: The exploratory analysis of dysregulated transcription factor FOXC1 in pan-cancer. Cancer Res 2023. [DOI: 10.1158/1538-7445.am2023-2060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Abstract
FOXC1 is a transcription factor that is reported to play a key role in the development of cancer. For example, we showed that epigenetic dysregulation of FOXC1 is associated with meningioma progression. Moreover, we reported that FOXC1 is overexpressed in drug-resistant bladder cancer cells. To further characterize the molecular mechanisms of FOXC1 in carcinogenesis of different cancer types, we analyzed DNA-seq and RNA-seq datasets of over 30 cancer types generated from The Cancer Genome Atlas (TCGA) and Oncology Research Information Exchange network (ORIEN) consortia, using cBioportal. cBioportal is a tool that is used to visualize and analyze large-scale cancer genomic data. When we analyzed whole exome sequencing and DNA array datasets to search genetic alterations such as mutation, amplification, and deletion events that occur in the FOXC1 gene, we revealed that over 10 cancer types have genetic alterations. By analyzing RNA sequencing datasets through the cBioportal, we found that more than 10 cancer types have overexpression of FOXC1. Unlike TCGA, ORIEN has generated whole exome sequencing and RNA sequencing datasets from cancer patients who are treated. We are currently in the process of analyzing ORIEN data to determine FOXC1 alterations and its association with drug resistance in different cancer types. Moreover, we are evaluating the relationship between FOXC1 dysregulation and cancer patient survival. Overall, this analysis will denote the key role that FOXC1 plays in different cancer types and supply valuable knowledge for drug resistance.
Citation Format: Alanna Brown, Zexun Wu, Huan Cao, Sara M. Falzarano, Sarah G. Buxbaum, Suhn K. Rhie. The exploratory analysis of dysregulated transcription factor FOXC1 in pan-cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2060.
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Affiliation(s)
- Alanna Brown
- 1USC - University of Southern California, Los Angeles, CA
| | - Zexun Wu
- 1USC - University of Southern California, Los Angeles, CA
| | - Huan Cao
- 1USC - University of Southern California, Los Angeles, CA
| | | | | | - Suhn K. Rhie
- 1USC - University of Southern California, Los Angeles, CA
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Stevens C, Hightower A, Buxbaum SG, Falzarano SM, Rhie SK. Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients. Front Oncol 2023; 13:1079037. [PMID: 36937425 PMCID: PMC10018228 DOI: 10.3389/fonc.2023.1079037] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 02/10/2023] [Indexed: 03/06/2023] Open
Abstract
Prostate cancer is the second most common cancer in men in the United States, and racial disparities are greatly observed in the disease. Specifically, African American (AA) patients have 60% higher incidence and mortality rates, in addition to higher grade and stage prostate tumors, than European American (EA) patients. In order to narrow the gap between clinical outcomes for these two populations, genetic and molecular signatures contributing to this disparity have been characterized. Over the past decade, profiles of prostate tumor samples from different ethnic groups have been developed using molecular and functional assays coupled with next generation sequencing or microarrays. Comparative genome-wide analyses of genomic, epigenomic, and transcriptomic profiles from prostate tumor samples have uncovered potential race-specific mutations, copy number alterations, DNA methylation, and gene expression patterns. In this study, we reviewed over 20 published studies that examined the aforementioned molecular contributions to racial disparities in AA and EA prostate cancer patients. The reviewed genomic studies revealed mutations, deletions, amplifications, duplications, or fusion genes differentially enriched in AA patients relative to EA patients. Commonly reported genomic alterations included mutations or copy number alterations of FOXA1, KMT2D, SPOP, MYC, PTEN, TP53, ZFHX3, and the TMPRSS2-ERG fusion. The reviewed epigenomic studies identified that CpG sites near the promoters of PMEPA1, RARB, SNRPN, and TIMP3 genes were differentially methylated between AA and EA patients. Lastly, the reviewed transcriptomic studies identified genes (e.g. CCL4, CHRM3, CRYBB2, CXCR4, GALR1, GSTM3, SPINK1) and signaling pathways dysregulated between AA and EA patients. The most frequently found dysregulated pathways were involved in immune and inflammatory responses and neuroactive ligand signaling. Overall, we observed that the genomic, epigenomic, and transcriptomic alterations evaluated between AA and EA prostate cancer patients varied between studies, highlighting the impact of using different methods and sample sizes. The reported genomic, epigenomic, and transcriptomic alterations do not only uncover molecular mechanisms of tumorigenesis but also provide researchers and clinicians valuable resources to identify novel biomarkers and treatment modalities to improve the disparity of clinical outcomes between AA and EA patients.
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Affiliation(s)
- Claire Stevens
- Department of Biochemistry and Molecular Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, Los Angeles, CA, United States
- CaRE2 Program, Florida-California Health Equity Center, Los Angeles, CA, United States
| | - Alexandria Hightower
- Department of Biochemistry and Molecular Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, Los Angeles, CA, United States
- CaRE2 Program, Florida-California Health Equity Center, Los Angeles, CA, United States
| | - Sarah G. Buxbaum
- CaRE2 Program, Florida-California Health Equity Center, Los Angeles, CA, United States
- Department of Epidemiology and Biostatistics, College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, United States
| | - Sara M. Falzarano
- CaRE2 Program, Florida-California Health Equity Center, Los Angeles, CA, United States
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida College of Medicine, Gainesville, FL, United States
| | - Suhn K. Rhie
- Department of Biochemistry and Molecular Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine of USC, Los Angeles, CA, United States
- CaRE2 Program, Florida-California Health Equity Center, Los Angeles, CA, United States
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Reams RR, Odedina FT, Carpten JD, Redda K, Stern MC, Krieger JL, Aparicio J, Hensel B, Askins N, Abreu A, Adams A, Agyare E, Ali J, Allen JM, Aló R, Baezconde-Garbanati L, Brant J, Brown CP, Buxbaum SG, Cohen P, Cozen W, Ezenwa MO, Falzarano S, Fillingim RB, Flores-Rozas H, Fredenburg KM, George T, Han B, Huang Y, Hughes Halbert C, Kiros GE, Lamango NS, Lee JH, Lyon DE, Mitchell DA, Mochona B, Nieva JJ, Offringa IA, Okunieff P, Parker A, Rhie SK, Richey JM, Rogers SC, Salhia B, Schmittgen TD, Segal R, Setiawan VW, Smith U, Su LM, Suther S, Trevino J, Velazquez-Villarreal EI, Webb FJ, Wu AH, Yao Y, Wilkie DJ. Florida-California Cancer Research, Education and Engagement (CaRE 2) Health Equity Center: Structure, Innovations, and Initial Outcomes. Cancer Control 2023; 30:10732748231197878. [PMID: 37703814 PMCID: PMC10501072 DOI: 10.1177/10732748231197878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 07/21/2023] [Accepted: 08/03/2023] [Indexed: 09/15/2023] Open
Abstract
INTRODUCTION The Florida-California Cancer Research, Education, and Engagement (CaRE2) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE2 triad partnership. METHODS CaRE2 serves diverse populations in Florida and California using a "molecule to the community and back" model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. RESULTS Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE2-related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. CONCLUSION The CaRE2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.
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Affiliation(s)
- R. Renee Reams
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | | | - John D. Carpten
- Department of Translational Genomics, University of Southern California, Los Angeles, CA, USA
| | - Kinfe Redda
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Mariana C. Stern
- Departments of Population and Public Health Sciences, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Janice L. Krieger
- Department of Advertising, University of Florida, Gainesville, FL, USA
| | - Jose Aparicio
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Brooke Hensel
- Department of Behavioral Nursing Science, University of Florida, Gainesville, FL, USA
| | - Nissa Askins
- Florida State University College of Medicine, Tallahassee, FL, USA
| | - Andre Abreu
- Department of Urology, University of Southern California, Los Angeles, CA, USA
| | - Angela Adams
- Department of Pharmaceutics, University of Florida, Gainesville, FL, USA
| | - Edward Agyare
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Jamel Ali
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
- Department of Chemical and Biomedical Engineering, Florida State University, Tallahassee, FL, USA
| | - John M. Allen
- Department of Pharmacotherapy & Translational Research, University of Florida, Orlando, FL, USA
| | - Richard Aló
- College of Science and Technology, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Lourdes Baezconde-Garbanati
- Departments of Population and Public Health Sciences, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Jason Brant
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Clyde P. Brown
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Sarah G. Buxbaum
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Pinchas Cohen
- University of Southern California Leonard Davis School of Gerontology, Los Angeles, CA, USA
| | - Wendy Cozen
- Division of Hematology/Oncology, School of Medicine, University of California, Irvine, CA, USA
| | - Miriam O. Ezenwa
- Department of Behavioral Nursing Science, University of Florida, Gainesville, FL, USA
| | - Sara Falzarano
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Roger B. Fillingim
- Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, USA
| | - Hernan Flores-Rozas
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Kristianna M. Fredenburg
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Thomas George
- Department of Medicine in the College of Medicine, University of Florida, Gainesville, FL, USA
| | - Bo Han
- Departments of Surgery, University of Southern California, Los Angeles, CA, USA
| | - Yong Huang
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA
| | - Chanita Hughes Halbert
- Departments of Population and Public Health Sciences, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Gebre-Egziabher Kiros
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Nazarius S. Lamango
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Ji-Hyun Lee
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Debra E. Lyon
- Department of Behavioral Nursing Science, University of Florida, Gainesville, FL, USA
| | - Duane A. Mitchell
- Department of Neurosurgery, University of Florida, Gainesville, FL, USA
| | - Bereket Mochona
- Department of Chemistry, Florida Agricultural and Mechanical University, Tallahassee, FL USA
| | - Jorge J. Nieva
- Department of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ite A. Offringa
- Departments of Surgery, University of Southern California, Los Angeles, CA, USA
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul Okunieff
- Department of Radiation Oncology, University of Florida, Gainesville, FL, USA
| | - Alexander Parker
- College of Medicine, University of Florida, Jacksonville, FL, USA
| | - Suhn K. Rhie
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
| | - Joyce M. Richey
- Department of Clinical Physiology and Neuroscience, University of Southern California, Los Angeles, CA, USA
| | - Sherise C. Rogers
- Department of Medicine in the College of Medicine, University of Florida, Gainesville, FL, USA
| | - Bodour Salhia
- Department of Translational Genomics, University of Southern California, Los Angeles, CA, USA
| | | | - Richard Segal
- Department of Pharmaceutical Outcome and Policy, University of Florida, Gainesville, FL, USA
| | | | - Ukamaka Smith
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Li-Ming Su
- Department of Urology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Sandra Suther
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida Agricultural and Mechanical University, Tallahassee, FL, USA
| | - Jose Trevino
- Department of Surgery, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Fern J. Webb
- Department of Surgery, University of Florida, Jacksonville, FL, USA
| | - Anna H. Wu
- Department of Translational Genomics, University of Southern California, Los Angeles, CA, USA
| | - Yingwei Yao
- Department of Behavioral Nursing Science, University of Florida, Gainesville, FL, USA
| | - Diana J. Wilkie
- Department of Behavioral Nursing Science, University of Florida, Gainesville, FL, USA
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Okere AN, Trimble ML, Sanogo V, Smith U, Brown C, Buxbaum SG. The Potential Effects of Implementing an Antibiotic Stewardship Program by Integrating It with Medication Therapy Service in a Low-Income Serving Clinic - A Single-Center Experience. Innov Pharm 2022; 13:10.24926/iip.v13i3.4997. [PMID: 36627908 PMCID: PMC9815868 DOI: 10.24926/iip.v13i3.4997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Background: Bacterial antimicrobial resistance (AMR) is a leading cause of mortality worldwide. Although AMR is common in low-income communities, there is limited evidence of the effect of antibiotic stewardship programs in low-income communities in the United States. Objectives: Our goal is to assess the effects of implementing pharmacist-led ASP by integrating it with medication therapy management service (MTM) in a low-income serving clinic. We evaluated the following 1) antibiotic prescriptions per 1000 patients, 2) the frequency of clinic (office) visits 30-day post-index clinic visits for recurring infections. Methods: To achieve our goal, we conducted a pre-post, quasi-experimental intervention study using an interrupted time-series analysis to assess the following: 1) antibiotic prescriptions per 1000 patients and the 2) frequency of office visits (including telehealth) within 30-day post-index clinic visits associated with recurrent infection. Results: Our findings revealed that the long-term effect of our antibiotic stewardship program intervention was associated with 63.69% reduction in antibiotic prescriptions per 1000 patients (change in slope = -0.173, [95% CI: (-0.30, -0.05)], P < 0.007) and a reduction in the frequency of office visits within 30-day post-index clinic visits by 67.27% (change in slope = -2.043, [95% CI: (-3.84, -0.24)], P < 0.028). Conclusion: Implementing antibiotic stewardship programs is feasible for clinics serving low-income populations. It was associated with a reduction in antibiotic prescriptions and preventable clinic (office) visits within 30 days due to infection recurrence.
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Affiliation(s)
- Arinze Nkemdirim Okere
- Florida Agricultural and Mechanical University, College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health,Corresponding author: Arinze Nkemdirim Okere, PharmD, MS, MBA, BCPS, BCCP Professor and Director Cardiovascular Disease and Stroke Prevention Program Florida Agricultural and Mechanical University College of Pharmacy and Pharmaceutical Sciences Institute of Public Health 1415 S Martin Luther King Jr Blvd, Tallahassee, FL 32307
| | | | | | - Ukamaka Smith
- Florida Agricultural and Mechanical University, College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health
| | - Clyde Brown
- Florida Agricultural and Mechanical University, College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health
| | - Sarah G. Buxbaum
- Florida Agricultural and Mechanical University, College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health
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Andrew PO, Bhuiyan A, Mawson A, Buxbaum SG, Sung JH, Shahbazi M. HIV/AIDS Knowledge of Undergraduate Students at a Historically Black College and University. Diseases 2018; 6:E98. [PMID: 30384469 PMCID: PMC6313487 DOI: 10.3390/diseases6040098] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Revised: 10/18/2018] [Accepted: 10/22/2018] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE This study among 400 undergraduate students enrolled at Jackson State University (JSU) study aimed to assess knowledge about HIV and AIDS among African-American undergraduate students attending a historically black college and university. A cross-sectional survey was conducted. Data were collected using a validated, self-administered, and standardized questionnaire on knowledge regarding risks for HIV and AIDS. Three hundred and eighty-six students (96.5%) had good knowledge about HIV and AIDS, although some participants had misconceptions about the modes of HIV infection transmission. There were no significant gender differences for HIV and AIDS knowledge among the participants (χ² = 3.05; P = 0.08). In general we concluded that JSU undergraduate students had adequate knowledge about HIV transmission modes and AIDS, although some participants had misconceptions about the routes of HIV infection transmission. Hence, this study calls for strengthening HIV and AIDS awareness education among undergraduate students.
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Affiliation(s)
| | - Azad Bhuiyan
- Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39213, USA.
| | - Anthony Mawson
- Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39213, USA.
| | - Sarah G Buxbaum
- Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39213, USA.
| | - Jung Hye Sung
- Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39213, USA.
| | - Mohammad Shahbazi
- Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39213, USA.
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Bennett B, Sharma M, Bennett R, Mawson AR, Buxbaum SG, Sung JH. Using Social Cognitive Theory to Predict Medication Compliance Behavior in Patients with Depression in Southern United States in 2016 in a Cross-Sectional Study. J Caring Sci 2018; 7:1-8. [PMID: 29637050 PMCID: PMC5889792 DOI: 10.15171/jcs.2018.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 11/02/2017] [Indexed: 11/09/2022] Open
Abstract
Introduction: Depression is a major public health issue. One of the concerns in depression research and practice pertains to non-compliance to prescribed medications. The purpose of the study was to predict compliance with medication use for patients with depression using social cognitive theory (SCT). Based on this study it was envisaged that recommendations for interventions to enhance compliance for medication use could be developed for patients with depression. Methods: The study was conducted using cross sectional design (n=148) in southern United States with a convenience sample of clinic-based depression patients with a 37-item valid and reliable questionnaire. Sample size was calculated to be 148 using G*Power (five predictors with a 0.80 power at the 0.05 alpha level and an estimated effect size of 0.10 with an inflation by 10% for missing data). Social cognitive theory constructs of expectations, self-efficacy and self-efficacy in overcoming barriers, self-control, and environment were reified. Data were analyzed using multiple linear regression and multiple logistic regression analyses. Results: Self-control for taking medication for depression (P=0.04), expectations for taking medication for depression (P=0.025), age (P<0.0001) and race (P=0.04) were significantly related to intent for taking medication for depression (Adjusted R2 = 0.183). In race, Blacks had lower intent to take medication for depression. Conclusion: Social cognitive theory is weakly predictive with low explained variance for taking medication for depression. It needs to be bolstered by newer theories like integrative model or multi-theory model of health behavior change for designing educational interventions aimed at enhancing compliance to medication for depression.
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Affiliation(s)
- Britney Bennett
- Epidemiologist, STD/HIV Office, Mississippi State Department of Health, Jackson, Mississippi
| | - Manoj Sharma
- Department of Behavioral & Environmental Health, School of Public Health, Jackson State University, Jackson, Mississippi
| | - Russell Bennett
- Department of Health Policy & Management, Jackson State University, Jackson, Mississippi
| | - Anthony R Mawson
- Department of Epidemiology & Biostatistics, Jackson State University, Jackson, Mississippi
| | - Sarah G Buxbaum
- Department of Epidemiology & Biostatistics, Jackson State University, Jackson, Mississippi
| | - Jung Hye Sung
- Department of Epidemiology & Biostatistics, Jackson State University, Jackson, Mississippi
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10
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Shanta Bridges L, Sharma M, Lee JHS, Bennett R, Buxbaum SG, Reese-Smith J. Using the PRECEDE-PROCEED model for an online peer-to-peer suicide prevention and awareness for depression (SPAD) intervention among African American college students: experimental study. Health Promot Perspect 2018; 8:15-24. [PMID: 29423358 PMCID: PMC5797304 DOI: 10.15171/hpp.2018.02] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Accepted: 12/30/2017] [Indexed: 11/29/2022] Open
Abstract
Background: Suicide rates are high among African American students because they are at a greater risk of depression. A commonly used suicide prevention approach is the gatekeeper training. However, gatekeeper training is neither evidence-based nor has it been identified as culturally-appropriate for African American college students. Therefore, the purpose of this study was to develop and evaluate an online peer-to-peer PRECEDE-PROCEED model based depression awareness and suicide prevention program that was culturally appropriate for African American college students. Methods: The setting was a predominantly Black institution in southern USA. A pre-experimental repeated measures one group design was used to measure changes in peer educators’ (n = 29) predisposing factors regarding knowledge, skills and attitudes pertaining to depression, reinforcing factors or receiving support from peers, healthcare professionals and teachers to help someone with depression, enabling factors or sureness of finding organizations to help someone with depression, and behavior for helping someone with depression at pretest, posttest and 1-month follow-up. A posttest only one group design was also used to measure effect on predisposing factors and behavior of students (n = 300) trained by peer educators. Results: There were statistically significant improvements in attitudes related to depression as disease (P = 0.003; η2 = 0.39), attitudes about managing depression (P = 0.0001; η2 = 0.30), skills(P = 0.0001; η2 = 0.41), reinforcing factors (P = 0.018; η2 = 0.13), enabling factors (P = 0.0001;η2 = 0.31), and behavior (P = 0.016; η2 = 0.14). Changes in knowledge about depression and attitudes about helping people with depression were not statistically significant over time for peer educators. The peer-to-peer training was not completely effective in transferring corresponding changes for students trained by peers. Conclusion: The program was effective for peer educators but peers could not significantly influence other students in all domains. This study provides a starting point toward evidencebased approaches for health promotion interventionists addressing depression awareness and suicide prevention among African American college students.
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Affiliation(s)
- Ledetra Shanta Bridges
- Behavioral & Environmental Health, School of Public Health, Jackson State University, Jackson, MS 39213, USA
| | - Manoj Sharma
- Behavioral & Environmental Health, School of Public Health, Jackson State University, Jackson, MS 39213, USA
| | - Jung Hye Sung Lee
- Epidemiology & Biostatistics, School of Public Health, Jackson State University, Jackson, MS 39213, USA
| | - Russell Bennett
- Health Policy & Management, School of Public Health, Jackson State University, Jackson, MS 39213, USA
| | - Sarah G Buxbaum
- Health Policy & Management, School of Public Health, Jackson State University, Jackson, MS 39213, USA
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11
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Divers J, Palmer ND, Langefeld CD, Brown WM, Lu L, Hicks PJ, Smith SC, Xu J, Terry JG, Register TC, Wagenknecht LE, Parks JS, Ma L, Chan GC, Buxbaum SG, Correa A, Musani S, Wilson JG, Taylor HA, Bowden DW, Carr JJ, Freedman BI. Genome-wide association study of coronary artery calcified atherosclerotic plaque in African Americans with type 2 diabetes. BMC Genet 2017; 18:105. [PMID: 29221444 PMCID: PMC5723099 DOI: 10.1186/s12863-017-0572-9] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 11/23/2017] [Indexed: 11/26/2022] Open
Abstract
Background Coronary artery calcified atherosclerotic plaque (CAC) predicts cardiovascular disease (CVD). Despite exposure to more severe conventional CVD risk factors, African Americans (AAs) are less likely to develop CAC, and when they do, have markedly lower levels than European Americans. Genetic factors likely contribute to the observed ethnic differences. To identify genes associated with CAC in AAs with type 2 diabetes (T2D), a genome-wide association study (GWAS) was performed using the Illumina 5 M chip in 691 African American-Diabetes Heart Study participants (AA-DHS), with replication in 205 Jackson Heart Study (JHS) participants with T2D. Genetic association tests were performed on the genotyped and 1000 Genomes-imputed markers separately for each study, and combined in a meta-analysis. Results Single nucleotide polymorphisms (SNPs), rs11353135 (2q22.1), rs16879003 (6p22.3), rs5014012, rs58071836 and rs10244825 (all on chromosome 7), rs10918777 (9q31.2), rs13331874 (16p13.3) and rs4459623 (18q12.1) were associated with presence and/or quantity of CAC in the AA-DHS and JHS, with meta-analysis p-values ≤8.0 × 10−7. The strongest result in AA-DHS alone was rs6491315 in the 13q32.1 region (parameter estimate (SE) = −1.14 (0.20); p-value = 9.1 × 10−9). This GWAS peak replicated a previously reported AA-DHS CAC admixture signal (rs7492028, LOD score 2.8). Conclusions Genetic association between SNPs on chromosomes 2, 6, 7, 9, 16 and 18 and CAC were detected in AAs with T2D from AA-DHS and replicated in the JHS. These data support a role for genetic variation on these chromosomes as contributors to CAC in AAs with T2D, as well as to variation in CAC between populations of African and European ancestry. Electronic supplementary material The online version of this article (10.1186/s12863-017-0572-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jasmin Divers
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157-1053, USA.
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157-1053, USA
| | - W Mark Brown
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157-1053, USA
| | - Lingyi Lu
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157-1053, USA
| | - Pamela J Hicks
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - S Carrie Smith
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jianzhao Xu
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - James G Terry
- Department of Radiology and Vanderbilt Center for Translation and Clinical Cardiovascular Research (VTRACC), Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Thomas C Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Department of Epidemiology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John S Parks
- Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lijun Ma
- Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Gary C Chan
- Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Sarah G Buxbaum
- School of Public Health Initiative, Jackson State University, Jackson, MS, USA
| | | | | | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Herman A Taylor
- Morehouse School of Medicine, Morehouse College, Atlanta, Georgia
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John Jeffrey Carr
- Department of Radiology and Vanderbilt Center for Translation and Clinical Cardiovascular Research (VTRACC), Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Barry I Freedman
- Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
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12
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Appel SJ, Buxbaum SG. Group Conference Call Diabetes Educational Support Sessions: A Pilot Study. J Natl Black Nurses Assoc 2016; 27:32-38. [PMID: 29932594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The aim of this study was to determine the acceptability of group-conference-call diabetes educational support sessions for rural dwelling southern African-American women and to describe the impact on diabetes distress. Pre- post-test design was utilized to determine any change in scores on questionnaires. Qualitative techniques were utilized to determine the acceptability of the conference callformat. Participants recruited (N = 3) manifested either dysglycemia or frank type 2 diabetes. Diabetes distress and knowledge tools, demographics, baseline laboratory data, and measures of body habitus were obtained. An adapted version of the American Association of Diabetes Educator's Association diabetes education curriculum was used to provide the classes. The conference call intervention was found to be convenient, informative, and it removed the hassle of needing to be in one location to receive education. Diabetes distress was reduced (p = 0.005) in the sub-scale related regimen management. Offering alternatives to in-person diabetes education classes has the potential to reduce levels of opportunity costs and include a larger number of individuals living chaotic lives due to the demands of chronic illness and extended family needs.
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13
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Evans DS, Avery CL, Nalls MA, Li G, Barnard J, Smith EN, Tanaka T, Butler AM, Buxbaum SG, Alonso A, Arking DE, Berenson GS, Bis JC, Buyske S, Carty CL, Chen W, Chung MK, Cummings SR, Deo R, Eaton CB, Fox ER, Heckbert SR, Heiss G, Hindorff LA, Hsueh WC, Isaacs A, Jamshidi Y, Kerr KF, Liu F, Liu Y, Lohman KK, Magnani JW, Maher JF, Mehra R, Meng YA, Musani SK, Newton-Cheh C, North KE, Psaty BM, Redline S, Rotter JI, Schnabel RB, Schork NJ, Shohet RV, Singleton AB, Smith JD, Soliman EZ, Srinivasan SR, Taylor HA, Van Wagoner DR, Wilson JG, Young T, Zhang ZM, Zonderman AB, Evans MK, Ferrucci L, Murray SS, Tranah GJ, Whitsel EA, Reiner AP, Sotoodehnia N. Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans. Hum Mol Genet 2016; 25:4350-4368. [PMID: 27577874 PMCID: PMC5291202 DOI: 10.1093/hmg/ddw284] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 08/03/2016] [Accepted: 08/19/2016] [Indexed: 12/14/2022] Open
Abstract
The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10-14) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10-4). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10-8) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10-9). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10-7), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved.
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Affiliation(s)
- Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA .
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Guo Li
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Barnard
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Erin N Smith
- Department of Pediatrics and Rady Children's Hospital, University of California at San Diego, School of Medicine, La Jolla, CA, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Anne M Butler
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Sarah G Buxbaum
- Center of Excellence in Minority Health and Health Disparities, Jackson State University, Jackson, MS, USA
- Department of Epidemiology and Biostatistics, Jackson State University School of Public Health (Initiative), Jackson, MS, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gerald S Berenson
- Department of Medicine and Cardiology, Tulane University, New Orleans, LA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Steven Buyske
- Department of Statistics and Biostatistics and Department of Genetics, Rutgers University, Piscataway, NJ, USA
| | - Cara L Carty
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Mina K Chung
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA
| | - Steven R Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Rajat Deo
- Division of Cardiovascular Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles B Eaton
- Departments of Family Medicine and Epidemiology, Alpert Medical School, Brown University, Providence, RI, USA
| | - Ervin R Fox
- Department of Medicine, Division of Cardiovascular Disease, University of Mississippi Medical Center, Jackson, MS, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Gerardo Heiss
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Lucia A Hindorff
- National Institutes of Health, National Human Genome Research Institute, Office of Population Genomics, Bethesda, MD, USA
| | - Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, USA
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), Dept. of Biochemistry, Maastricht University, Maastricht, the Netherlands
| | - Yalda Jamshidi
- Cardiogenetics Lab, Institute of Cardiovascular and Cell Sciences, St George's University of London, UK
| | - Kathleen F Kerr
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Felix Liu
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA
| | - Kurt K Lohman
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA
| | - Jared W Magnani
- Department of Medicine, Division of Cardiology, University of Pittsburgh Medical Center Heart and Vascular Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joseph F Maher
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Reena Mehra
- Program for Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yan A Meng
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Solomon K Musani
- Cardiovascular Research Center and Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston,MA, USA
| | - Christopher Newton-Cheh
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
- Department of Medicine, Division of Sleep Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Departments of Medicine and Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jerome I Rotter
- University Heart Center Hamburg and German Center for Cardiovascular Research, Hamburg, Germany
| | | | - Nicholas J Schork
- Center for Cardiovascular Research, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Ralph V Shohet
- Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jonathan D Smith
- Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elsayed Z Soliman
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Herman A Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - David R Van Wagoner
- Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James G Wilson
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Taylor Young
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Zhu-Ming Zhang
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Alan B Zonderman
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Michele K Evans
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Sarah S Murray
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Gregory J Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Membership of the CHARGE QRS Consortium is provided in the acknowledgements and
| | - Alex P Reiner
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nona Sotoodehnia
- Department of Epidemiology, University of Washington, Seattle, WA, USA .
- Division of Cardiology, University of Washington, Seattle, WA, USA
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14
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Cade BE, Gottlieb DJ, Lauderdale DS, Bennett DA, Buchman AS, Buxbaum SG, De Jager PL, Evans DS, Fülöp T, Gharib SA, Johnson WC, Kim H, Larkin EK, Lee SK, Lim AS, Punjabi NM, Shin C, Stone KL, Tranah GJ, Weng J, Yaffe K, Zee PC, Patel SR, Zhu X, Redline S, Saxena R. Common variants in DRD2 are associated with sleep duration: the CARe consortium. Hum Mol Genet 2016; 25:167-79. [PMID: 26464489 PMCID: PMC4690488 DOI: 10.1093/hmg/ddv434] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 10/09/2015] [Indexed: 12/20/2022] Open
Abstract
Sleep duration is implicated in the etiologies of chronic diseases and premature mortality. However, the genetic basis for sleep duration is poorly defined. We sought to identify novel genetic components influencing sleep duration in a multi-ethnic sample. Meta-analyses were conducted of genetic associations with self-reported, habitual sleep duration from seven Candidate Gene Association Resource (CARe) cohorts of over 25 000 individuals of African, Asian, European and Hispanic American ancestry. All individuals were genotyped for ∼50 000 SNPs from 2000 candidate heart, lung, blood and sleep genes. African-Americans had additional genome-wide genotypes. Four cohorts provided replication. A SNP (rs17601612) in the dopamine D2 receptor gene (DRD2) was significantly associated with sleep duration (P = 9.8 × 10(-7)). Conditional analysis identified a second DRD2 signal with opposite effects on sleep duration. In exploratory analysis, suggestive association was observed for rs17601612 with polysomnographically determined sleep latency (P = 0.002). The lead DRD2 signal was recently identified in a schizophrenia GWAS, and a genetic risk score of 11 additional schizophrenia GWAS loci genotyped on the IBC array was also associated with longer sleep duration (P = 0.03). These findings support a role for DRD2 in influencing sleep duration. Our work motivates future pharmocogenetics research on alerting agents such as caffeine and modafinil that interact with the dopaminergic pathway and further investigation of genetic overlap between sleep and neuro-psychiatric traits.
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Affiliation(s)
- Brian E Cade
- Division of Sleep and Circadian Disorders and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA,
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA, VA Boston Healthcare System, Boston, MA 02132, USA
| | - Diane S Lauderdale
- Department of Health Studies, The University of Chicago, Chicago, IL 60637, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Aron S Buchman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Sarah G Buxbaum
- School of Public Health, Jackson State University, Jackson, MS 39217, USA
| | - Philip L De Jager
- Department of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Tibor Fülöp
- Department of Internal Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Division of Pulmonary and Critical Care Medicine and
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Hyun Kim
- Institute of Human Genomic Study, Korea University Ansan Medical Center, Ansan 425-707, Republic of Korea
| | - Emma K Larkin
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Seung Ku Lee
- Institute of Human Genomic Study, Korea University Ansan Medical Center, Ansan 425-707, Republic of Korea
| | - Andrew S Lim
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Naresh M Punjabi
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Chol Shin
- Institute of Human Genomic Study, Korea University Ansan Medical Center, Ansan 425-707, Republic of Korea, Division of Pulmonary, Sleep and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Ansan 425-707, Republic of Korea
| | - Katie L Stone
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Gregory J Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Jia Weng
- Division of Sleep and Circadian Disorders and
| | - Kristine Yaffe
- Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA 94107, USA, San Francisco VA Medical Center, San Francisco, CA 94121, USA
| | - Phyllis C Zee
- Department of Neurology and Sleep Medicine Center, Northwestern University, Chicago, IL 60611, USA
| | - Sanjay R Patel
- Division of Sleep and Circadian Disorders and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA, Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA, Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Richa Saxena
- Division of Sleep and Circadian Disorders and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA, Center for Human Genetic Research and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, MA 02114, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
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15
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Swerdlow DI, Preiss D, Kuchenbaecker KB, Holmes MV, Engmann JEL, Shah T, Sofat R, Stender S, Johnson PCD, Scott RA, Leusink M, Verweij N, Sharp SJ, Guo Y, Giambartolomei C, Chung C, Peasey A, Amuzu A, Li K, Palmen J, Howard P, Cooper JA, Drenos F, Li YR, Lowe G, Gallacher J, Stewart MCW, Tzoulaki I, Buxbaum SG, van der A DL, Forouhi NG, Onland-Moret NC, van der Schouw YT, Schnabel RB, Hubacek JA, Kubinova R, Baceviciene M, Tamosiunas A, Pajak A, Topor-Madry R, Stepaniak U, Malyutina S, Baldassarre D, Sennblad B, Tremoli E, de Faire U, Veglia F, Ford I, Jukema JW, Westendorp RGJ, de Borst GJ, de Jong PA, Algra A, Spiering W, Maitland-van der Zee AH, Klungel OH, de Boer A, Doevendans PA, Eaton CB, Robinson JG, Duggan D, Kjekshus J, Downs JR, Gotto AM, Keech AC, Marchioli R, Tognoni G, Sever PS, Poulter NR, Waters DD, Pedersen TR, Amarenco P, Nakamura H, McMurray JJV, Lewsey JD, Chasman DI, Ridker PM, Maggioni AP, Tavazzi L, Ray KK, Seshasai SRK, Manson JE, Price JF, Whincup PH, Morris RW, Lawlor DA, Smith GD, Ben-Shlomo Y, Schreiner PJ, Fornage M, Siscovick DS, Cushman M, Kumari M, Wareham NJ, Verschuren WMM, Redline S, Patel SR, Whittaker JC, Hamsten A, Delaney JA, Dale C, Gaunt TR, Wong A, Kuh D, Hardy R, Kathiresan S, Castillo BA, van der Harst P, Brunner EJ, Tybjaerg-Hansen A, Marmot MG, Krauss RM, Tsai M, Coresh J, Hoogeveen RC, Psaty BM, Lange LA, Hakonarson H, Dudbridge F, Humphries SE, Talmud PJ, Kivimäki M, Timpson NJ, Langenberg C, Asselbergs FW, Voevoda M, Bobak M, Pikhart H, Wilson JG, Reiner AP, Keating BJ, Hingorani AD, Sattar N. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials. Lancet 2015; 385:351-61. [PMID: 25262344 PMCID: PMC4322187 DOI: 10.1016/s0140-6736(14)61183-1] [Citation(s) in RCA: 462] [Impact Index Per Article: 51.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING The funding sources are cited at the end of the paper.
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Affiliation(s)
- Daniel I Swerdlow
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK.
| | - David Preiss
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.
| | - Karoline B Kuchenbaecker
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Department of Surgery, Division of Transplantation, and Clinical Epidemiology Unit, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael V Holmes
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK
| | - Jorgen E L Engmann
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK
| | - Tina Shah
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK
| | - Reecha Sofat
- UCL Department of Medicine, University College London, London, UK
| | - Stefan Stender
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Paul C D Johnson
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Maarten Leusink
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Niek Verweij
- University of Groningen, University Medical Centre Groningen, Department of Cardiology, Groningen, Netherlands
| | - Stephen J Sharp
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Christina Chung
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Anne Peasey
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | | | - KaWah Li
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Jutta Palmen
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Philip Howard
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Jackie A Cooper
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Yun R Li
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Gordon Lowe
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - John Gallacher
- Department of Primary Care and Public Health, Cardiff University Medical School, Cardiff University, Cardiff, UK
| | - Marlene C W Stewart
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | | | - Daphne L van der A
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Nita G Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Yvonne T van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Renate B Schnabel
- University Heart Center Hamburg, Department of General and Interventional Cardiology, Hamburg, Germany
| | - Jaroslav A Hubacek
- Centre for Experimental Medicine, Institute of Clinical and Experimental Medicine, Prague, Czech Republic
| | | | | | | | - Andrzej Pajak
- Department of Epidemiology and Population Studies, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Krakow, Poland
| | - Roman Topor-Madry
- Department of Epidemiology and Population Studies, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Krakow, Poland
| | - Urszula Stepaniak
- Department of Epidemiology and Population Studies, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Krakow, Poland
| | - Sofia Malyutina
- Institute of Internal and Preventive Medicine, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia
| | - Damiano Baldassarre
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy; Centro Cardiologico Monzino IRCCS Milan, Milan, Italy
| | - Bengt Sennblad
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden; Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
| | - Elena Tremoli
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy; Centro Cardiologico Monzino IRCCS Milan, Milan, Italy
| | - Ulf de Faire
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Rudi G J Westendorp
- Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Gert Jan de Borst
- Department of Vascular Surgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Ale Algra
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands; Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Wilko Spiering
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, Netherlands
| | - Anke H Maitland-van der Zee
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Olaf H Klungel
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Anthonius de Boer
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands
| | - Pieter A Doevendans
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | | | | | - David Duggan
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | - John Kjekshus
- Department of Cardiology, Oslo University Hospital Rikshospitalet, University of Oslo, Oslo, Norway
| | - John R Downs
- Department of Medicine, University of Texas Health Science Centre, San Antonio, TX, USA; VERDICT, South Texas Veterans Health Care System, San Antonio, TX, USA
| | | | - Anthony C Keech
- NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia
| | - Roberto Marchioli
- Hematology and Oncology Therapeutic Delivery Unit, Quintiles, Milan, Italy
| | - Gianni Tognoni
- Department of Clinical Pharmacology and Epidemiology, Consorzio Mario NegriSud, Santa Maria Imbaro, Chieti, Italy
| | - Peter S Sever
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Neil R Poulter
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - David D Waters
- Department of Medicine, University of California, San Francisco, CA, USA
| | - Terje R Pedersen
- Centre for Preventative Medicine, Oslo University Hospital Rikshospitalet, University of Oslo, Oslo, Norway
| | | | | | - John J V McMurray
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - James D Lewsey
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | | | | | | | - Luigi Tavazzi
- Maria Cecilia Hospital, GVM Care and Research, E.S. Health Science Foundation, Cotignola (RA), Italy
| | - Kausik K Ray
- Cardiac and Cell Sciences Research Institute, London, UK
| | | | | | - Jackie F Price
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Richard W Morris
- UCL Department of Primary Care and Population Health, University College London, London, UK
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Yoav Ben-Shlomo
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | | | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - David S Siscovick
- Cardiovascular Health Research Unit of the Department of Medicine, Department of Epidemiology, and Department of Health Services, University of Washington, Seattle, WA, USA
| | - Mary Cushman
- Departments of Medicine and Pathology, University of Vermont, Colchester, VT, USA
| | - Meena Kumari
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Nick J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | | | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Joseph A Delaney
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Caroline Dale
- Department of Non-Communicable Disease Epidemiology, London, UK
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Andrew Wong
- MRCUnit for Lifelong Health and Ageing, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Diana Kuh
- MRCUnit for Lifelong Health and Ageing, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Rebecca Hardy
- MRCUnit for Lifelong Health and Ageing, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Sekar Kathiresan
- Cardiology Division, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Berta A Castillo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Pim van der Harst
- University of Groningen, University Medical Centre Groningen, Department of Cardiology, Groningen, Netherlands
| | - Eric J Brunner
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Anne Tybjaerg-Hansen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Michael G Marmot
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA USA
| | | | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ronald C Hoogeveen
- Baylor College of Medicine, Department of Medicine, Division of Atherosclerosis and Vascular Medicine, Houston, TX, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit of the Department of Medicine, Department of Epidemiology, and Department of Health Services, University of Washington, Seattle, WA, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, NC, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Steve E Humphries
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Philippa J Talmud
- Centre for Cardiovascular Genetics, University College London, London, UK
| | - Mika Kivimäki
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK; School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Folkert W Asselbergs
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK; Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands; Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Netherlands
| | - Mikhail Voevoda
- Institute of Internal and Preventive Medicine, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia; Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia
| | - Martin Bobak
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Hynek Pikhart
- UCL Research Department of Epidemiology and Public Health, University College London, London, UK
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Brendan J Keating
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Aroon D Hingorani
- UCL Institute of Cardiovascular Science and Farr Institute, University College London, London, UK
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
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16
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Holmes MV, Dale CE, Zuccolo L, Silverwood RJ, Guo Y, Ye Z, Prieto-Merino D, Dehghan A, Trompet S, Wong A, Cavadino A, Drogan D, Padmanabhan S, Li S, Yesupriya A, Leusink M, Sundstrom J, Hubacek JA, Pikhart H, Swerdlow DI, Panayiotou AG, Borinskaya SA, Finan C, Shah S, Kuchenbaecker KB, Shah T, Engmann J, Folkersen L, Eriksson P, Ricceri F, Melander O, Sacerdote C, Gamble DM, Rayaprolu S, Ross OA, McLachlan S, Vikhireva O, Sluijs I, Scott RA, Adamkova V, Flicker L, Bockxmeer FMV, Power C, Marques-Vidal P, Meade T, Marmot MG, Ferro JM, Paulos-Pinheiro S, Humphries SE, Talmud PJ, Mateo Leach I, Verweij N, Linneberg A, Skaaby T, Doevendans PA, Cramer MJ, van der Harst P, Klungel OH, Dowling NF, Dominiczak AF, Kumari M, Nicolaides AN, Weikert C, Boeing H, Ebrahim S, Gaunt TR, Price JF, Lannfelt L, Peasey A, Kubinova R, Pajak A, Malyutina S, Voevoda MI, Tamosiunas A, Maitland-van der Zee AH, Norman PE, Hankey GJ, Bergmann MM, Hofman A, Franco OH, Cooper J, Palmen J, Spiering W, de Jong PA, Kuh D, Hardy R, Uitterlinden AG, Ikram MA, Ford I, Hyppönen E, Almeida OP, Wareham NJ, Khaw KT, Hamsten A, Husemoen LLN, Tjønneland A, Tolstrup JS, Rimm E, Beulens JWJ, Verschuren WMM, Onland-Moret NC, Hofker MH, Wannamethee SG, Whincup PH, Morris R, Vicente AM, Watkins H, Farrall M, Jukema JW, Meschia J, Cupples LA, Sharp SJ, Fornage M, Kooperberg C, LaCroix AZ, Dai JY, Lanktree MB, Siscovick DS, Jorgenson E, Spring B, Coresh J, Li YR, Buxbaum SG, Schreiner PJ, Ellison RC, Tsai MY, Patel SR, Redline S, Johnson AD, Hoogeveen RC, Hakonarson H, Rotter JI, Boerwinkle E, de Bakker PIW, Kivimaki M, Asselbergs FW, Sattar N, Lawlor DA, Whittaker J, Davey Smith G, Mukamal K, Psaty BM, Wilson JG, Lange LA, Hamidovic A, Hingorani AD, Nordestgaard BG, Bobak M, Leon DA, Langenberg C, Palmer TM, Reiner AP, Keating BJ, Dudbridge F, Casas JP. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. BMJ 2014; 349:g4164. [PMID: 25011450 PMCID: PMC4091648 DOI: 10.1136/bmj.g4164] [Citation(s) in RCA: 452] [Impact Index Per Article: 45.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/21/2014] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease. DESIGN Mendelian randomisation meta-analysis of 56 epidemiological studies. PARTICIPANTS 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers. MAIN OUTCOME MEASURES Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption. RESULTS Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)). CONCLUSIONS Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.
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Affiliation(s)
- Michael V Holmes
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK Department of Surgery, Penn Transplant Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Caroline E Dale
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit (IEU) at the Universty of Bristol, Oakfield House, Bristol BS8 2BN, UK
| | - Richard J Silverwood
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, USA BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Zheng Ye
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - David Prieto-Merino
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, the Netherlands
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Alana Cavadino
- Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
| | - Dagmar Drogan
- German Institute of Human Nutrition Potsdam-Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - Shanshan Li
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Ajay Yesupriya
- Office of Public Health Genomics, Office of Epidemiology, Surveillance, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
| | - Maarten Leusink
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Johan Sundstrom
- Department of Medical Sciences, Uppsala University, Uppsala University Hospital, SE-751 85 Uppsala, Sweden
| | - Jaroslav A Hubacek
- Center for Experimental Medicine, Institute for Clinical and Experimental Medicine, Videnska 1958/9, Prague 4, 14021, Czech Republic
| | - Hynek Pikhart
- Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
| | - Daniel I Swerdlow
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Andrie G Panayiotou
- Cyprus International Institute for Environmental and Public Health in association with the Harvard School of Public Health, Cyprus University of Technology, 3603 Limassol, Cyprus
| | | | - Chris Finan
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Sonia Shah
- UCL Genetics Institute, Department of Genetics Environment and Evolution, London, WC1E 6BT, UK
| | - Karoline B Kuchenbaecker
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Tina Shah
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Jorgen Engmann
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Lasse Folkersen
- Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Per Eriksson
- Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Fulvio Ricceri
- Unit of Cancer Epidemiology, San Giovanni Battista Hospital and Center for Cancer Prevention (CPO-Piemonte), 10129, Torino, Italy
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, San Giovanni Battista Hospital and Center for Cancer Prevention (CPO-Piemonte), 10129, Torino, Italy
| | - Dale M Gamble
- Mayo Clinic Department of Neurology, Jacksonville, FL 32224, USA
| | - Sruti Rayaprolu
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
| | - Stela McLachlan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Olga Vikhireva
- Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
| | - Ivonne Sluijs
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Vera Adamkova
- Department of Preventive Cardiology, Institute for Clinical and Experimental Medicine, Prague 4, 14021, Czech Republic
| | - Leon Flicker
- Western Australian Centre for Health & Ageing, Centre for Medical Research, University of Western Australia, Perth, Australia
| | - Frank M van Bockxmeer
- Department of Clinical Biochemistry, Royal Perth Hospital and School of Surgery, the University of Western Australia
| | - Christine Power
- Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK
| | - Pedro Marques-Vidal
- Department of Internal Medicine, Internal Medicine, CHUV, Lausanne, Switzerland
| | - Tom Meade
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Michael G Marmot
- UCL Institute of Health Equity, Department of Epidemiology & Public Health, London WC1E 7HB, UK
| | - Jose M Ferro
- Instituto Medicina Molecular, Faculdade de Medicina Universidade de Lisboa, 1649-028 Lisbon, Portugal Servico Neurologia, Hospital de Santa Maria, 1649-035 Lisbon, Portugal
| | - Sofia Paulos-Pinheiro
- Instituto Nacional de Saude Doutor Ricardo Jorge, 1649-016 Lisbon, Portugal Faculdade Ciencias Universidade Lisboa, 1749-016 Lisbon, Portugal
| | - Steve E Humphries
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Philippa J Talmud
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Irene Mateo Leach
- Department of Cardiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Allan Linneberg
- Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup University Hospital, Glostrup, Denmark
| | - Tea Skaaby
- Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup University Hospital, Glostrup, Denmark
| | - Pieter A Doevendans
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maarten J Cramer
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, Groningen, The Netherlands Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands
| | - Olaf H Klungel
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Nicole F Dowling
- Office of Public Health Genomics, Office of Epidemiology, Surveillance, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
| | - Anna F Dominiczak
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - Meena Kumari
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Andrew N Nicolaides
- Vascular Screening and Diagnostic Centre, Ayios Dometios, Nicosia, Cyprus Deparment of Vascular Surgery, Imperial College, London, SW7 2BX, UK Cyprus Cardiovascular Disease Educational and Research trust, Nicosia, Cyprus
| | - Cornelia Weikert
- German Institute of Human Nutrition Potsdam-Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Heiner Boeing
- German Institute of Human Nutrition Potsdam-Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Shah Ebrahim
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU) at the Universty of Bristol, Oakfield House, Bristol BS8 2BN, UK
| | - Jackie F Price
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Lars Lannfelt
- Department of Public Health & Caring Sciences, Uppsala University, Uppsala University Hospital, SE-75185 Uppsala, Sweden
| | - Anne Peasey
- Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
| | - Ruzena Kubinova
- Centre for Health Monitoring, National Institute of Public Health, 100 42 Prague, Czech Republic
| | - Andrzej Pajak
- Department of Epidemiology and Population Studies, Institute of Public Health, Jagiellonian University Medical College, 31-531 Krakow, Poland
| | - Sofia Malyutina
- Institute of Internal and Preventative Medicine, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia, 630089 Dept of Internal Medicine, Novosibirsk State Medical University, Novosibirsk, Russia, 630091
| | - Mikhail I Voevoda
- Institute of Internal and Preventative Medicine, Siberian Branch of Russian Academy of Medical Sciences, Novosibirsk, Russia, 630089 Faculty of Medicine, Novosibirsk State University, Novosibirsk, Russia, 630090
| | - Abdonas Tamosiunas
- Department of Population Studies, Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas LT-50161, Lithuania
| | - Anke H Maitland-van der Zee
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Paul E Norman
- School of Surgery, University of Western Australia, Perth, Australia
| | - Graeme J Hankey
- Department of Neurology, Sir Charles Gairdner Hospital, Perth, Australia School of Medicine and Pharmacology, The University of Western Australia, Nedlands, Perth, Australia
| | - Manuela M Bergmann
- German Institute of Human Nutrition Potsdam-Rehbrücke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jackie Cooper
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK WC1E 6JF
| | - Jutta Palmen
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, UK
| | - Wilko Spiering
- Department of Vascular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | | | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Elina Hyppönen
- Centre for Paediatric Epidemiology and Biostatistics, UCL Institute of Child Health, London, UK School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide SA 5000, Australia South Australian Health and Medical Research Institute, Adelaide SA5000, Australia
| | - Osvaldo P Almeida
- Western Australian Centre for Health & Ageing, Centre for Medical Research, University of Western Australia, Perth, Australia School of Psychiatry & Clinical Neurosciences (M573), University of Western Australia, Perth 6009, Australia Department of Psychiatry, Royal Perth Hospital, Perth, Australia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Kay-Tee Khaw
- Department of Primary Care and Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Anders Hamsten
- Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Stockholm, Sweden Center for Molecular Medicine, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Lise Lotte N Husemoen
- Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup University Hospital, Glostrup, Denmark
| | - Anne Tjønneland
- Danish Cancer Society, Strandboulevarden, Copenhagen, Denmark
| | - Janne S Tolstrup
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Eric Rimm
- Department of Epidemiology and Department of Nutrition, Harvard School of Public Health, Boston, MA, USA Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Joline W J Beulens
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands
| | - W M Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - N Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands
| | - Marten H Hofker
- Dept Pathology and Medical Biology, Medical Biology division, Molecular Genetics, University Medical Center Groningen and Groningen University, Groningen, The Netherlands
| | | | - Peter H Whincup
- Population Health Research Institute, St George's, University of London, London, UK
| | - Richard Morris
- Department of Primary Care & Population Health, UCL, London, UK
| | - Astrid M Vicente
- Instituto Nacional de Saude Doutor Ricardo Jorge, 1649-016 Lisbon, Portugal Instituto Gulbenkian Ciencia, P-2780-156 Oeiras, Portugal Biofig - Center for Biodiversity, Functional and Integrative Genomics, Campus da FCUL, 1749-016 Lisboa, Portugal
| | - Hugh Watkins
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
| | - Martin Farrall
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, the Netherlands
| | - James Meschia
- Mayo Clinic Department of Neurology, Jacksonville, FL 32224, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA National Heart, Lung, and Blood Institute's The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Stephen J Sharp
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Texas, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Andrea Z LaCroix
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - James Y Dai
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Matthew B Lanktree
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada L8S4L8
| | | | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Bonnie Spring
- Northwestern University, Feinberg School of Medicine, Department of Preventive Medicine, Chicago, IL, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yun R Li
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, USA
| | - Sarah G Buxbaum
- School of Health Sciences, Jackson State University, Jackson, MS, USA
| | - Pamela J Schreiner
- School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - R Curtis Ellison
- Preventive Medicine and Epidemiology, Evans Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, USA
| | - Sanjay R Patel
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; Harvard Medical School, Boston USA Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital; Harvard Medical School, Boston USA
| | - Andrew D Johnson
- National Heart, Lung, and Blood Institute's The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Ron C Hoogeveen
- Baylor College of Medicine, Department of Medicine, Division of Atherosclerosis & Vascular Medicine, Houston, Texas 77030, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, Calif, USA
| | - Eric Boerwinkle
- Division of Epidemiology, School of Public Health, University of Texas Health Science Center at Houston, Texas, USA
| | - Paul I W de Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit (IEU) at the Universty of Bristol, Oakfield House, Bristol BS8 2BN, UK
| | - John Whittaker
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK Genetics, R&D, GlaxoSmithKline, Stevenage, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU) at the Universty of Bristol, Oakfield House, Bristol BS8 2BN, UK
| | - Kenneth Mukamal
- Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA,USA Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, North Carolina 27514, USA
| | - Ajna Hamidovic
- College of Pharmacy, The University of New Mexico, Albuquerque, NM, USA
| | - Aroon D Hingorani
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK
| | - Børge G Nordestgaard
- The Copenhagen General Population Study, Herlev Hospital, Copenhagen, Denmark Faculty of Health Sciences, Copenhagen University Hospital, University of Copenhagen,Copenhagen, Denmark Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Denmark
| | - Martin Bobak
- Department of Epidemiology and Public Health, University College London, London, WC1E 6BT, UK
| | - David A Leon
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Tom M Palmer
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Brendan J Keating
- Department of Surgery, Penn Transplant Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104, USA Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, USA
| | - Frank Dudbridge
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Juan P Casas
- Genetic Epidemiology Group, Institute of Cardiovascular Science, Department of Epidemiology and Public Health, University College London, UK Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
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17
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Bidulescu A, Choudhry S, Musani SK, Buxbaum SG, Liu J, Rotimi CN, Wilson JG, Taylor HA, Gibbons GH. Associations of adiponectin with individual European ancestry in African Americans: the Jackson Heart Study. Front Genet 2014; 5:22. [PMID: 24575123 PMCID: PMC3918651 DOI: 10.3389/fgene.2014.00022] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2013] [Accepted: 01/21/2014] [Indexed: 12/23/2022] Open
Abstract
Background: Compared with European Americans, African Americans (AAs) exhibit lower levels of the cardio-metabolically protective adiponectin even after accounting for adiposity measures. Because few studies have examined in AA the association between adiponectin and genetic admixture, a dense panel of ancestry informative markers (AIMs) was used to estimate the individual proportions of European ancestry (PEA) for the AAs enrolled in a large community-based cohort, the Jackson Heart Study (JHS). We tested the hypothesis that plasma adiponectin and PEA are directly associated and assessed the interaction with a series of cardio-metabolic risk factors. Methods: Plasma specimens from 1439 JHS participants were analyzed by ELISA for adiponectin levels. Using pseudo-ancestral population genotype data from the HapMap Consortium, PEA was estimated with a panel of up to 1447 genome-wide preselected AIMs by a maximum likelihood approach. Interaction assessment, stepwise linear and cubic multivariable-adjusted regression models were used to analyze the cross-sectional association between adiponectin and PEA. Results: Among the study participants (62% women; mean age 48 ± 12 years), the median (interquartile range) of PEA was 15.8 (9.3)%. Body mass index (BMI) (p = 0.04) and insulin resistance (p = 0.0001) modified the association between adiponectin and PEA. Adiponectin was directly and linearly associated with PEA (β = 0.62 ± 0.28, p = 0.03) among non-obese (n = 673) and insulin sensitive participants (n = 1141; β = 0.74 ± 0.23, p = 0.001), but not among those obese or with insulin resistance. No threshold point effect was detected for non-obese participants. Conclusions: In a large AA population, the individual proportion of European ancestry was linearly and directly associated with plasma adiponectin among non-obese and non insulin-resistant participants, pointing to the interaction of genetic and metabolic factors influencing adiponectin levels.
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Affiliation(s)
- Aurelian Bidulescu
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health - Bloomington Bloomington, IN, USA
| | - Shweta Choudhry
- Department of Urology, University of California San Francisco, CA, USA
| | - Solomon K Musani
- Jackson Heart Study, University of Mississippi Medical Center Jackson, MS, USA
| | - Sarah G Buxbaum
- Department of Health Sciences, Jackson State University Jackson, MS, USA
| | - Jiankang Liu
- Jackson Heart Study, University of Mississippi Medical Center Jackson, MS, USA
| | - Charles N Rotimi
- National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA
| | - James G Wilson
- Jackson Heart Study, University of Mississippi Medical Center Jackson, MS, USA
| | - Herman A Taylor
- Jackson Heart Study, University of Mississippi Medical Center Jackson, MS, USA
| | - Gary H Gibbons
- National Heart Lung and Blood Institute, National Institutes of Health Bethesda, MD, USA
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18
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Yaghootkar H, Lamina C, Scott RA, Dastani Z, Hivert MF, Warren LL, Stancáková A, Buxbaum SG, Lyytikäinen LP, Henneman P, Wu Y, Cheung CY, Pankow JS, Jackson AU, Gustafsson S, Zhao JH, Ballantyne CM, Xie W, Bergman RN, Boehnke M, el Bouazzaoui F, Collins FS, Dunn SH, Dupuis J, Forouhi NG, Gillson C, Hattersley AT, Hong J, Kähönen M, Kuusisto J, Kedenko L, Kronenberg F, Doria A, Assimes TL, Ferrannini E, Hansen T, Hao K, Häring H, Knowles JW, Lindgren CM, Nolan JJ, Paananen J, Pedersen O, Quertermous T, Smith U, Lehtimäki T, Liu CT, Loos RJ, McCarthy MI, Morris AD, Vasan RS, Spector TD, Teslovich TM, Tuomilehto J, van Dijk KW, Viikari JS, Zhu N, Langenberg C, Ingelsson E, Semple RK, Sinaiko AR, Palmer CN, Walker M, Lam KS, Paulweber B, Mohlke KL, van Duijn C, Raitakari OT, Bidulescu A, Wareham NJ, Laakso M, Waterworth DM, Lawlor DA, Meigs JB, Richards JB, Frayling TM. Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes. Diabetes 2013; 62:3589-98. [PMID: 23835345 PMCID: PMC3781444 DOI: 10.2337/db13-0128] [Citation(s) in RCA: 101] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
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Affiliation(s)
- Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
| | - Claudia Lamina
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K
| | - Zari Dastani
- Department of Epidemiology, Biostatistics and Occupational Health, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
| | - Marie-France Hivert
- Department of Medicine, Université de Sherbrooke, Sherbrooke, Quebec, Canada
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
| | - Liling L. Warren
- Quantitative Sciences, GlaxoSmithKline, Research Triangle Park, North Carolina
| | | | - Sarah G. Buxbaum
- School of Health Sciences, Jackson State University, Jackson, Mississippi
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Chloe Y.Y. Cheung
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - Anne U. Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K
| | - Christie M. Ballantyne
- Baylor College of Medicine and Methodist DeBakey Heart and Vascular Center, Houston, Texas
| | - Weijia Xie
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan
| | - Fatiha el Bouazzaoui
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Francis S. Collins
- Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Sandra H. Dunn
- School of Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Nita G. Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K
| | | | - Andrew T. Hattersley
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
- Genetics of Diabetes, University of Exeter Medical School, Exeter, U.K
| | - Jaeyoung Hong
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere, Finland
| | | | - Lyudmyla Kedenko
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Alessandro Doria
- Section on Genetics and Epidemiology, Joslin Diabetes Center, Boston, Massachusetts
| | - Themistocles L. Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, California
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California
| | - Ele Ferrannini
- Department of Internal Medicine, University of Pisa, Pisa, Italy
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York
| | - Hans Häring
- Division of Endocrinology, Diabetology, Nephrology, Vascular Medicine and Clinical Chemistry, Department of Internal Medicine, University of Tübingen, Tübingen, Germany
| | - Joshua W. Knowles
- Department of Medicine, Stanford University School of Medicine, Stanford, California
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California
| | | | | | | | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
- Hagedorn Research Institute, Copenhagen, Denmark
- Institute of Biomedical Science, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
| | - Thomas Quertermous
- Department of Medicine, Stanford University School of Medicine, Stanford, California
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, California
| | - Ulf Smith
- Department of Molecular and Clinical Medicine, The Lundberg Laboratory for Diabetes Research, Sahlgrenska Academy, Gothenburg, Sweden
| | | | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Ruth J.F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K
- Department of Preventive Medicine, Mount Sinai School of Medicine, The Charles Bronfman Institute for Personalized Medicine, Institute of Child Health and Development, New York, New York
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, U.K
| | - Andrew D. Morris
- Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Ramachandran S. Vasan
- Boston University School of Medicine, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Tim D. Spector
- Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | - Tanya M. Teslovich
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
- King Abdulaziz University, Jeddah, Saudi Arabia
- Red RECAVA Grupo RD06/0014/0015, Hospital Universitario La Paz, Madrid, Spain
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jorma S. Viikari
- Department of Medicine, Turku University Hospital, Turku, Finland
- Department of Medicine, University of Turku, Turku, Finland
| | - Na Zhu
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | | | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Robert K. Semple
- The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, U.K
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Cambridge, U.K
| | - Alan R. Sinaiko
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota
| | - Colin N.A. Palmer
- Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, U.K
| | - Mark Walker
- Institute of Cellular Medicine, The Medical School, Newcastle University, Newcastle, U.K
| | - Karen S.L. Lam
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- Research Centre of Heart, Brain, Hormone and Healthy Aging, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Bernhard Paulweber
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Aurelian Bidulescu
- Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia
- Department of Community Health and Preventive Medicine, Morehouse School of Medicine, Atlanta, Georgia
| | - Nick J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K
| | | | | | - Debbie A. Lawlor
- Department of Social Medicine, University of Bristol, Bristol, U.K
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
| | - J. Brent Richards
- Twin Research and Genetic Epidemiology, King’s College London, London, U.K
- Department of Medicine, Human Genetics, Epidemiology and Biostatistics, McGill University, Montreal, Canada
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, U.K
- Corresponding author: Timothy M. Frayling,
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Lynch HT, Buxbaum SG, Snyder CL, Stacey M, Shaw TG, Lynch PM. The impact of family information services on genetic testing uptake among relatives in Lynch syndrome families. J Clin Oncol 2013. [DOI: 10.1200/jco.2013.31.15_suppl.1573] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
1573 Background: A mismatch repair (MMR) pathogenic mutation in an index patient provides a basis for predictive mutation testing in at-risk members of Lynch syndrome (LS) families. Mutation carriers warrant aggressive surveillance. As importantly, non-carriers can safely follow general population screening guidelines. However, penetration of predictive testing has been disappointing in first-degree relatives (FDR), and has been even more limited in second- and more distant-degree relatives, even though the benefits can be as great as in FDRs. Family Information Services (FISs), involve an in-person session in which expert providers and counselors meet with multiple family members in a convenient geographical location. Education and counseling are intended to lead to testing for the family MMR mutation, followed by appropriate surveillance. Methods: LS families with a known MMR mutation (n=97) were targeted for this study. Selection for FIS was based on family size and convenient geographic location. Twenty-eight were offered an FIS and 69 received standard care (mailed educational material and invitation for testing). Data were collected on testing rates. Results: In at-risk patients that did receive FIS, 20.4% (std dev = 11.4%, 95% CI: 16.0 to 24.8%, range: 3 to 57.5%) were DNA tested, whereas in families that did not receive FIS, 12.9% (std dev = 10.8%, 95% CI: 10.2 to 15.5%, range: 0 to 43.5%) were DNA tested. The difference in proportions tested between the FIS and non-FIS families was statistically significant (p=0.003) and was more pronounced in family members whose relationship to the proband was beyond first-degree (p<0.0001). Of those individuals that attended an FIS, 81.1% were tested. Conclusions: Genetic counseling in the FIS setting facilitates uptake of predictive mutational testing in FDRs and in more distant at-risk relatives. However, the FIS is time-consuming and labor intensive; more efficient means of disseminating LS risk information and the benefits of predictive testing in more distant relatives are needed. A cost-effectiveness analysis as well as a randomized study that controls for participation bias must be done.
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20
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Oelsner EC, Pottinger TD, Burkart KM, Allison M, Buxbaum SG, Hansel NN, Kumar R, Larkin EK, Lange LA, Loehr LR, London SJ, O'Connor GT, Papanicolaou G, Petrini MF, Rabinowitz D, Raghavan S, Redline S, Thyagarajan B, Tracy RP, Wilk JB, White WB, Rich SS, Barr RG. Adhesion molecules, endothelin-1 and lung function in seven population-based cohorts. Biomarkers 2013; 18:196-203. [PMID: 23557128 DOI: 10.3109/1354750x.2012.762805] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
CONTEXT Endothelial function is abnormal in chronic obstructive pulmonary disease (COPD); whether endothelial dysfunction causes COPD is unknown. OBJECTIVE Test associations of endothelial biomarkers with FEV1 using instrumental variables. METHODS Among 26 907 participants with spirometry, ICAM-1, P-selectin, E-selectin and endothelin-1 were measured in subsets. RESULTS ICAM-1 and P-selectin were inversely associated with FEV1 among European-Americans (-29 mL and -34 mL per standard deviation of log-transformed biomarker, p < 0.001), as was endothelin-1 among African-Americans (-22 mL, p = 0.008). Genetically-estimated ICAM-1 and P-selectin were not significantly associated with FEV1. The instrumental variable for endothelin-1 was non-informative. CONCLUSION Although ICAM-1, P-selectin and endothelin-1 were inversely associated with FEV1, associations for ICAM-1 and P-selectin do not appear causal.
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Affiliation(s)
- E C Oelsner
- Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
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21
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Elbers CC, Guo Y, Tragante V, van Iperen EPA, Lanktree MB, Castillo BA, Chen F, Yanek LR, Wojczynski MK, Li YR, Ferwerda B, Ballantyne CM, Buxbaum SG, Chen YDI, Chen WM, Cupples LA, Cushman M, Duan Y, Duggan D, Evans MK, Fernandes JK, Fornage M, Garcia M, Garvey WT, Glazer N, Gomez F, Harris TB, Halder I, Howard VJ, Keller MF, Kamboh MI, Kooperberg C, Kritchevsky SB, LaCroix A, Liu K, Liu Y, Musunuru K, Newman AB, Onland-Moret NC, Ordovas J, Peter I, Post W, Redline S, Reis SE, Saxena R, Schreiner PJ, Volcik KA, Wang X, Yusuf S, Zonderland AB, Anand SS, Becker DM, Psaty B, Rader DJ, Reiner AP, Rich SS, Rotter JI, Sale MM, Tsai MY, Borecki IB, Hegele RA, Kathiresan S, Nalls MA, Taylor HA, Hakonarson H, Sivapalaratnam S, Asselbergs FW, Drenos F, Wilson JG, Keating BJ. Gene-centric meta-analysis of lipid traits in African, East Asian and Hispanic populations. PLoS One 2012; 7:e50198. [PMID: 23236364 PMCID: PMC3517599 DOI: 10.1371/journal.pone.0050198] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2012] [Accepted: 10/22/2012] [Indexed: 11/18/2022] Open
Abstract
Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10(-7) and p = 1.5×10(-6) respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10(-12)). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.
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Affiliation(s)
- Clara C. Elbers
- Department of Genetics, University of Pennsylvania, School of Medicine, Philadelphia, Pennsylvania, United States of America
- Department of Medical Genetics, Biomedical Genetics, University Medical Center, Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- BGI-Shenzhen, Shenzhen, People's Republic of China
| | - Vinicius Tragante
- Department of Medical Genetics, Biomedical Genetics, University Medical Center, Utrecht, The Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Erik P. A. van Iperen
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Matthew B. Lanktree
- Departments of Medicine and Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Berta Almoguera Castillo
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Fang Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Lisa R. Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Mary K. Wojczynski
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Yun R. Li
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | - Bart Ferwerda
- Department of Genetics, University of Pennsylvania, School of Medicine, Philadelphia, Pennsylvania, United States of America
| | | | - Sarah G. Buxbaum
- Jackson Heart Study, Jackson State University, Jackson, Mississippi, United States of America
- School of Health Sciences, Department of Epidemiology and Biostatistics, Jackson State University, Jackson, Mississippi, United States of America
| | - Yii-Der Ida Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
| | - L. Adrienne Cupples
- Boston University, Boston, Massachusetts, United States of America
- The National Heart, Lung, Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Mary Cushman
- Department of Medicine, Thrombosis and Hemostasis Program, University of Vermont, Burlington, Vermont, United States of America
| | - Yanan Duan
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - David Duggan
- Translational Genomics Research Institute, Phoenix, Arizona, United States of America
| | - Michele K. Evans
- Health Disparities Unit, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Jyotika K. Fernandes
- Division of Endocrinology, Diabetes and Medical Genetics, College of Medicine, Medical University of South Carolina, Charleston, SC United States of America
| | - Myriam Fornage
- The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Melissa Garcia
- Laboratory for Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - W. Timothy Garvey
- Department of Nutrition Sciences, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Nicole Glazer
- Boston University, Boston, Massachusetts, United States of America
| | - Felicia Gomez
- Department of Genetics, University of Pennsylvania, School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Tamara B. Harris
- Laboratory for Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Indrani Halder
- Heart and Vascular Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Virginia J. Howard
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Margaux F. Keller
- Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - M. Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Stephen B. Kritchevsky
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America
- Sticht Center on Aging, Wake Forest University, Winston-Salem, North Carolina, United States of America
| | - Andrea LaCroix
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Kiang Liu
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina, United States of America
| | - Kiran Musunuru
- Broad Institute, Cambridge, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Anne B. Newman
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - N. Charlotte Onland-Moret
- Department of Medical Genetics, Biomedical Genetics, University Medical Center, Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jose Ordovas
- JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts, United States of America
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Wendy Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Susan Redline
- Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Steven E. Reis
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Richa Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Pamela J. Schreiner
- School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Kelly A. Volcik
- Division of Epidemiology, Human Genetics and Environmental Sciences, Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Xingbin Wang
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Salim Yusuf
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Alan B. Zonderland
- Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Sonia S. Anand
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Diane M. Becker
- GeneSTAR Research Program, Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Bruce Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
| | - Daniel J. Rader
- Cardiovascular Institute, the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jerome I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Michèle M. Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Ingrid B. Borecki
- Division of Statistical Genomics and Department of Genetics Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Robert A. Hegele
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Sekar Kathiresan
- Broad Institute, Cambridge, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Michael A. Nalls
- Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Herman A. Taylor
- Jackson State University, Tougaloo College, and the University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
| | | | - Folkert W. Asselbergs
- Department of Medical Genetics, Biomedical Genetics, University Medical Center, Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Brendan J. Keating
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
- * E-mail:
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Deo R, Nalls MA, Avery CL, Smith JG, Evans DS, Keller MF, Butler AM, Buxbaum SG, Li G, Miguel Quibrera P, Smith EN, Tanaka T, Akylbekova EL, Alonso A, Arking DE, Benjamin EJ, Berenson GS, Bis JC, Chen LY, Chen W, Cummings SR, Ellinor PT, Evans MK, Ferrucci L, Fox ER, Heckbert SR, Heiss G, Hsueh WC, Kerr KF, Limacher MC, Liu Y, Lubitz SA, Magnani JW, Mehra R, Marcus GM, Murray SS, Newman AB, Njajou O, North KE, Paltoo DN, Psaty BM, Redline SS, Reiner AP, Robinson JG, Rotter JI, Samdarshi TE, Schnabel RB, Schork NJ, Singleton AB, Siscovick D, Soliman EZ, Sotoodehnia N, Srinivasan SR, Taylor HA, Trevisan M, Zhang Z, Zonderman AB, Newton-Cheh C, Whitsel EA. Common genetic variation near the connexin-43 gene is associated with resting heart rate in African Americans: a genome-wide association study of 13,372 participants. Heart Rhythm 2012. [PMID: 23183192 DOI: 10.1016/j.hrthm.2012.11.014] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Genome-wide association studies have identified several genetic loci associated with variation in resting heart rate in European and Asian populations. No study has evaluated genetic variants associated with heart rate in African Americans. OBJECTIVE To identify novel genetic variants associated with resting heart rate in African Americans. METHODS Ten cohort studies participating in the Candidate-gene Association Resource and Continental Origins and Genetic Epidemiology Network consortia performed genome-wide genotyping of single nucleotide polymorphisms (SNPs) and imputed 2,954,965 SNPs using HapMap YRI and CEU panels in 13,372 participants of African ancestry. Each study measured the RR interval (ms) from 10-second resting 12-lead electrocardiograms and estimated RR-SNP associations using covariate-adjusted linear regression. Random-effects meta-analysis was used to combine cohort-specific measures of association and identify genome-wide significant loci (P≤2.5×10(-8)). RESULTS Fourteen SNPs on chromosome 6q22 exceeded the genome-wide significance threshold. The most significant association was for rs9320841 (+13 ms per minor allele; P = 4.98×10(-15)). This SNP was approximately 350 kb downstream of GJA1, a locus previously identified as harboring SNPs associated with heart rate in Europeans. Adjustment for rs9320841 also attenuated the association between the remaining 13 SNPs in this region and heart rate. In addition, SNPs in MYH6, which have been identified in European genome-wide association study, were associated with similar changes in the resting heart rate as this population of African Americans. CONCLUSIONS An intergenic region downstream of GJA1 (the gene encoding connexin 43, the major protein of the human myocardial gap junction) and an intragenic region within MYH6 are associated with variation in resting heart rate in African Americans as well as in populations of European and Asian origin.
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Affiliation(s)
- R Deo
- Division of Cardiology, Electrophysiology Section, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
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23
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Smith JG, Avery CL, Evans DS, Nalls MA, Meng YA, Smith EN, Palmer C, Tanaka T, Mehra R, Butler AM, Young T, Buxbaum SG, Kerr KF, Berenson GS, Schnabel RB, Li G, Ellinor PT, Magnani JW, Chen W, Bis JC, Curb JD, Hsueh WC, Rotter JI, Liu Y, Newman AB, Limacher MC, North KE, Reiner AP, Quibrera PM, Schork NJ, Singleton AB, Psaty BM, Soliman EZ, Solomon AJ, Srinivasan SR, Alonso A, Wallace R, Redline S, Zhang ZM, Post WS, Zonderman AB, Taylor HA, Murray SS, Ferrucci L, Arking DE, Evans MK, Fox ER, Sotoodehnia N, Heckbert SR, Whitsel EA, Newton-Cheh C. Impact of ancestry and common genetic variants on QT interval in African Americans. ACTA ACUST UNITED AC 2012; 5:647-55. [PMID: 23166209 DOI: 10.1161/circgenetics.112.962787] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Ethnic differences in cardiac arrhythmia incidence have been reported, with a particularly high incidence of sudden cardiac death and low incidence of atrial fibrillation in individuals of African ancestry. We tested the hypotheses that African ancestry and common genetic variants are associated with prolonged duration of cardiac repolarization, a central pathophysiological determinant of arrhythmia, as measured by the electrocardiographic QT interval. METHODS AND RESULTS First, individual estimates of African and European ancestry were inferred from genome-wide single-nucleotide polymorphism (SNP) data in 7 population-based cohorts of African Americans (n=12,097) and regressed on measured QT interval from ECGs. Second, imputation was performed for 2.8 million SNPs, and a genome-wide association study of QT interval was performed in 10 cohorts (n=13,105). There was no evidence of association between genetic ancestry and QT interval (P=0.94). Genome-wide significant associations (P<2.5 × 10(-8)) were identified with SNPs at 2 loci, upstream of the genes NOS1AP (rs12143842, P=2 × 10(-15)) and ATP1B1 (rs1320976, P=2 × 10(-10)). The most significant SNP in NOS1AP was the same as the strongest SNP previously associated with QT interval in individuals of European ancestry. Low probability values (P<10(-5)) were observed for SNPs at several other loci previously identified in genome-wide association studies in individuals of European ancestry, including KCNQ1, KCNH2, LITAF, and PLN. CONCLUSIONS We observed no difference in duration of cardiac repolarization with global genetic indices of African American ancestry. In addition, our genome-wide association study extends the association of polymorphisms at several loci associated with repolarization in individuals of European ancestry to include individuals of African ancestry.
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Affiliation(s)
- J Gustav Smith
- Department of Cardiology, Lund University, Skåne University Hospital, Sweden.
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Patel SR, Goodloe R, De G, Kowgier M, Weng J, Buxbaum SG, Cade B, Fulop T, Gharib SA, Gottlieb DJ, Hillman D, Larkin EK, Lauderdale DS, Li L, Mukherjee S, Palmer L, Zee P, Zhu X, Redline S. Association of genetic loci with sleep apnea in European Americans and African-Americans: the Candidate Gene Association Resource (CARe). PLoS One 2012; 7:e48836. [PMID: 23155414 PMCID: PMC3498243 DOI: 10.1371/journal.pone.0048836] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2012] [Accepted: 10/01/2012] [Indexed: 01/02/2023] Open
Abstract
Although obstructive sleep apnea (OSA) is known to have a strong familial basis, no genetic polymorphisms influencing apnea risk have been identified in cross-cohort analyses. We utilized the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe) to identify sleep apnea susceptibility loci. Using a panel of 46,449 polymorphisms from roughly 2,100 candidate genes on a customized Illumina iSelect chip, we tested for association with the apnea hypopnea index (AHI) as well as moderate to severe OSA (AHI≥15) in 3,551 participants of the Cleveland Family Study and two cohorts participating in the Sleep Heart Health Study. Among 647 African-Americans, rs11126184 in the pleckstrin (PLEK) gene was associated with OSA while rs7030789 in the lysophosphatidic acid receptor 1 (LPAR1) gene was associated with AHI using a chip-wide significance threshold of p-value<2×10−6. Among 2,904 individuals of European ancestry, rs1409986 in the prostaglandin E2 receptor (PTGER3) gene was significantly associated with OSA. Consistency of effects between rs7030789 and rs1409986 in LPAR1 and PTGER3 and apnea phenotypes were observed in independent clinic-based cohorts. Novel genetic loci for apnea phenotypes were identified through the use of customized gene chips and meta-analyses of cohort data with replication in clinic-based samples. The identified SNPs all lie in genes associated with inflammation suggesting inflammation may play a role in OSA pathogenesis.
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Affiliation(s)
- Sanjay R Patel
- Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
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25
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Butler AM, Yin X, Evans DS, Nalls MA, Smith EN, Tanaka T, Li G, Buxbaum SG, Whitsel EA, Alonso A, Arking DE, Benjamin EJ, Berenson GS, Bis JC, Chen W, Deo R, Ellinor PT, Heckbert SR, Heiss G, Hsueh WC, Keating BJ, Kerr KF, Li Y, Limacher MC, Liu Y, Lubitz SA, Marciante KD, Mehra R, Meng YA, Newman AB, Newton-Cheh C, North KE, Palmer CD, Psaty BM, Quibrera PM, Redline S, Reiner AP, Rotter JI, Schnabel RB, Schork NJ, Singleton AB, Smith JG, Soliman EZ, Srinivasan SR, Zhang ZM, Zonderman AB, Ferrucci L, Murray SS, Evans MK, Sotoodehnia N, Magnani JW, Avery CL. Novel loci associated with PR interval in a genome-wide association study of 10 African American cohorts. ACTA ACUST UNITED AC 2012; 5:639-46. [PMID: 23139255 DOI: 10.1161/circgenetics.112.963991] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The PR interval, as measured by the resting, standard 12-lead ECG, reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at 9 loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans. METHODS AND RESULTS We present results from the largest genome-wide association study to date of PR in 13 415 adults of African descent from 10 cohorts. We tested for association between PR (ms) and ≈2.8 million genotyped and imputed single-nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (λ range: 0.9-1.1), although not after genomic control correction was applied to the overall meta-analysis (λ: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0 × 10(-8)), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained 2 additional independent secondary signals influencing PR (P<5.0 × 10(-8)). CONCLUSIONS This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European, and Asian descent.
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Affiliation(s)
- Anne M Butler
- Department of Epidemiology, University of North Carolina, Chapel Hill, 27514, USA.
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26
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Dastani Z, Hivert MF, Timpson N, Perry JRB, Yuan X, Scott RA, Henneman P, Heid IM, Kizer JR, Lyytikäinen LP, Fuchsberger C, Tanaka T, Morris AP, Small K, Isaacs A, Beekman M, Coassin S, Lohman K, Qi L, Kanoni S, Pankow JS, Uh HW, Wu Y, Bidulescu A, Rasmussen-Torvik LJ, Greenwood CMT, Ladouceur M, Grimsby J, Manning AK, Liu CT, Kooner J, Mooser VE, Vollenweider P, Kapur KA, Chambers J, Wareham NJ, Langenberg C, Frants R, Willems-vanDijk K, Oostra BA, Willems SM, Lamina C, Winkler TW, Psaty BM, Tracy RP, Brody J, Chen I, Viikari J, Kähönen M, Pramstaller PP, Evans DM, St. Pourcain B, Sattar N, Wood AR, Bandinelli S, Carlson OD, Egan JM, Böhringer S, van Heemst D, Kedenko L, Kristiansson K, Nuotio ML, Loo BM, Harris T, Garcia M, Kanaya A, Haun M, Klopp N, Wichmann HE, Deloukas P, Katsareli E, Couper DJ, Duncan BB, Kloppenburg M, Adair LS, Borja JB, Wilson JG, Musani S, Guo X, Johnson T, Semple R, Teslovich TM, Allison MA, Redline S, Buxbaum SG, Mohlke KL, Meulenbelt I, Ballantyne CM, Dedoussis GV, Hu FB, Liu Y, Paulweber B, Spector TD, Slagboom PE, Ferrucci L, Jula A, Perola M, Raitakari O, Florez JC, Salomaa V, Eriksson JG, Frayling TM, Hicks AA, Lehtimäki T, Smith GD, Siscovick DS, Kronenberg F, van Duijn C, Loos RJF, Waterworth DM, Meigs JB, Dupuis J, Richards JB. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS Genet 2012; 8:e1002607. [PMID: 22479202 PMCID: PMC3315470 DOI: 10.1371/journal.pgen.1002607] [Citation(s) in RCA: 356] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Accepted: 02/03/2012] [Indexed: 12/16/2022] Open
Abstract
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
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Affiliation(s)
- Zari Dastani
- Department of Epidemiology, Biostatistics, and Occupational Health, Jewish General Hospital, Lady Davis Institute, McGill University, Montreal, Canada
| | - Marie-France Hivert
- Department of Medicine, Université de Sherbrooke, Sherbrooke, Canada
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Nicholas Timpson
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - John R. B. Perry
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Xin Yuan
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Iris M. Heid
- Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Regensburg, Germany
| | - Jorge R. Kizer
- Departments of Medicine and Public Health, Weill Cornell Medical College, New York, New York, United States of America
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Christian Fuchsberger
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kerrin Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Leiden, The Netherlands
| | - Marian Beekman
- Section of Molecular Epidemiology, Leiden University Medical Center and The Netherlands Genomics Initiative, The Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Stefan Coassin
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Kurt Lohman
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Lu Qi
- Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Hae-Won Uh
- Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Aurelian Bidulescu
- Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Celia M. T. Greenwood
- Lady Davis Institute for Medical Research, Department of Oncology, McGill University, Montreal, Canada
| | - Martin Ladouceur
- Department of Human Genetics McGill University, Montreal, Canada
| | - Jonna Grimsby
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jaspal Kooner
- Cardiology, Ealing Hospital National Health Service (NHS) Trust, London, United Kingdom
| | - Vincent E. Mooser
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - Peter Vollenweider
- Department of Internal Medicine, University of Lausanne, Lausanne, Switzerland
| | - Karen A. Kapur
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - John Chambers
- Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Rune Frants
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ko Willems-vanDijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ben A. Oostra
- Centre for Medical Systems Biology, Leiden, The Netherlands
- Deptartment of Clinical Genetics and Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sara M. Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Claudia Lamina
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Thomas W. Winkler
- Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Regensburg, Germany
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
| | - Russell P. Tracy
- Departments of Pathology and Biochemistry, University of Vermont, Burlington, Vermont, United States of America
| | - Jennifer Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Ida Chen
- Medical Genetics Research Institute, Cedars Sinai Medical Center, Los Angeles, California, United States of America
| | - Jorma Viikari
- Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, Italy
- Department of Neurology, General Central Hospital, Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - David M. Evans
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Beate St. Pourcain
- School of Social and community medicine, University of Bristol, Bristol, United Kingdom
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Andrew R. Wood
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | | | - Olga D. Carlson
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, United States of America
| | - Josephine M. Egan
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, United States of America
| | - Stefan Böhringer
- Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Diana van Heemst
- Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Lyudmyla Kedenko
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Kati Kristiansson
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Marja-Liisa Nuotio
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Britt-Marie Loo
- Population Studies Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Tamara Harris
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Melissa Garcia
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Alka Kanaya
- Division of General Internal Medicine, Women's Health Clinical Research Center, University of California San Francisco, San Francisco, California, United States of America
| | - Margot Haun
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Norman Klopp
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Großhadern, Munich, Germany
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | | | - David J. Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Bruce B. Duncan
- School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Margreet Kloppenburg
- Department of Rheumatology and Department of Clinical Epidemiology, Leiden, The Netherlands
| | - Linda S. Adair
- Department of Nutrition, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Judith B. Borja
- Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines
| | | | | | | | | | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Solomon Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Xiuqing Guo
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Toby Johnson
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- University Institute of Social and Preventative Medicine, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Robert Semple
- Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tanya M. Teslovich
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Matthew A. Allison
- Department of Family and Preventive Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Susan Redline
- Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Sarah G. Buxbaum
- Jackson Heart Study Coordinating Center, Jackson State University, Jackson, Mississippi, United States of America
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Ingrid Meulenbelt
- Section of Molecular Epidemiology, Leiden University Medical Center and The Netherlands Genomics Initiative, The Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Christie M. Ballantyne
- Baylor College of Medicine and Methodist DeBakey Heart and Vascular Center, Houston, Texas, United States of America
| | | | - Frank B. Hu
- Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Yongmei Liu
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Bernhard Paulweber
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - P. Eline Slagboom
- Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Antti Jula
- Population Studies Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Markus Perola
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and the Department of Clinical Physiology, Turku University Hospital, Turku, Finland
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Veikko Salomaa
- Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Johan G. Eriksson
- Diabetes Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
- Vaasa Central Hospital, Vaasa, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Timothy M. Frayling
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, Italy
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - George Davey Smith
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | | | - Florian Kronenberg
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Cornelia van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Leiden, The Netherlands
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Dawn M. Waterworth
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - J. Brent Richards
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Departments of Medicine, Human Genetics, Epidemiology, and Biostatistics, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Canada
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Hinch AG, Tandon A, Patterson N, Song Y, Rohland N, Palmer CD, Chen GK, Wang K, Buxbaum SG, Akylbekova EL, Aldrich MC, Ambrosone CB, Amos C, Bandera EV, Berndt SI, Bernstein L, Blot WJ, Bock CH, Boerwinkle E, Cai Q, Caporaso N, Casey G, Cupples LA, Deming SL, Diver WR, Divers J, Fornage M, Gillanders EM, Glessner J, Harris CC, Hu JJ, Ingles SA, Isaacs W, John EM, Kao WHL, Keating B, Kittles RA, Kolonel LN, Larkin E, Le Marchand L, McNeill LH, Millikan RC, Murphy A, Musani S, Neslund-Dudas C, Nyante S, Papanicolaou GJ, Press MF, Psaty BM, Reiner AP, Rich SS, Rodriguez-Gil JL, Rotter JI, Rybicki BA, Schwartz AG, Signorello LB, Spitz M, Strom SS, Thun MJ, Tucker MA, Wang Z, Wiencke JK, Witte JS, Wrensch M, Wu X, Yamamura Y, Zanetti KA, Zheng W, Ziegler RG, Zhu X, Redline S, Hirschhorn JN, Henderson BE, Taylor HA, Price AL, Hakonarson H, Chanock SJ, Haiman CA, Wilson JG, Reich D, Myers SR. The landscape of recombination in African Americans. Nature 2011; 476:170-5. [PMID: 21775986 PMCID: PMC3154982 DOI: 10.1038/nature10336] [Citation(s) in RCA: 230] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2011] [Accepted: 06/27/2011] [Indexed: 01/14/2023]
Abstract
Recombination, together with mutation, gives rise to genetic variation in populations. Here we leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P value < 10(-245)). We identify a 17-base-pair DNA sequence motif that is enriched in these hotspots, and is an excellent match to the predicted binding target of PRDM9 alleles common in West Africans and rare in Europeans. Sites of this motif are predicted to be risk loci for disease-causing genomic rearrangements in individuals carrying these alleles. More generally, this map provides a resource for research in human genetic variation and evolution.
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Affiliation(s)
- Anjali G Hinch
- Wellcome Trust Centre for Human Genetics, Oxford University, Roosevelt Drive, Oxford OX3 7BN, UK
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Hamidovic A, Kasberger JL, Young TR, Goodloe RJ, Redline S, Buxbaum SG, Benowitz NL, Bergen AW, Butler KR, Franceschini N, Gharib SA, Hitsman B, Levy D, Meng Y, Papanicolaou GJ, Preis SR, Spring B, Styn MA, Tong EK, White WB, Wiggins KL, Jorgenson E. Genetic variability of smoking persistence in African Americans. Cancer Prev Res (Phila) 2011; 4:729-34. [PMID: 21436384 DOI: 10.1158/1940-6207.capr-10-0362] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
To date, most genetic association analyses of smoking behaviors have been conducted in populations of European ancestry and many of these studies focused on the phenotype that measures smoking quantity, that is, cigarettes per day. Additional association studies in diverse populations with different linkage disequilibrium patterns and an alternate phenotype, such as total tobacco exposure which accounts for intermittent periods of smoking cessation within a larger smoking period as measured in large cardiovascular risk studies, can aid the search for variants relevant to smoking behavior. For these reasons, we undertook an association analysis by using a genotyping array that includes 2,100 genes to analyze smoking persistence in unrelated African American participants from the Atherosclerosis Risk in Communities study. A locus located approximately 4 kb downstream from the 3'-UTR of the brain-derived neurotrophic factor (BDNF) significantly influenced smoking persistence. In addition, independent variants rs12915366 and rs12914385 in the cluster of genes encoding nicotinic acetylcholine receptor subunits (CHRNA5-CHRNA3-CHRNB4) on 15q25.1 were also associated with the phenotype in this sample of African American subjects. To our knowledge, this is the first study to more extensively evaluate the genome in the African American population, as a limited number of previous studies of smoking behavior in this population included evaluations of only single genomic regions.
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Affiliation(s)
- Ajna Hamidovic
- Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA.
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Jeff JM, Brown-Gentry K, Buxbaum SG, Sarpong DF, Taylor HA, George AL, Roden DM, Crawford DC. SCN5A variation is associated with electrocardiographic traits in the Jackson Heart Study. ACTA ACUST UNITED AC 2011; 4:139-44. [PMID: 21325150 DOI: 10.1161/circgenetics.110.958124] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Understanding variation in the normal electric activity of the heart, assessed by the ECG, may provide a starting point for studies of susceptibility to serious arrhythmias such as sudden cardiac death during myocardial infarction or drug therapy. Recent genetic association studies of one ECG trait, the QT interval, have identified common variation in European-descent populations, but little is known about the genetic determinants of ECG traits in populations of African descent. METHODS AND RESULTS To identify genetic risk factors, we have undertaken a candidate gene study of ECG traits in collaboration with the Jackson Heart Study, a longitudinal study of 5301 blacks ascertained from the Jackson, Mississippi, area. Nine quantitative ECG traits were evaluated: P, PR, QRS, QT, and QTc durations, heart rate, and P, QRS, and T axes. We genotyped 72 variations in the predominant sodium channel gene expressed in heart, SCN5A, encoding the Na(v)1.5 voltage-gated sodium channel in 4558 subjects. Both rare and common variants in this gene have previously been associated with inherited arrhythmia syndromes and variable conduction. Adjusting for age, sex, and European ancestry, we performed tests of association in 3054 unrelated participants and identified 14 significant associations (P<1.0×10(-4)), of which 13 are independent, based on linkage disequilibrium. These variants explain up to 2% of the variation in ECG traits in the Jackson Heart Study. CONCLUSIONS These results suggest that SCN5A variation contributes to ECG trait distributions in blacks, and these same variations may be risk or protective factors associated with susceptibility to arrhythmias.
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Affiliation(s)
- Janina M Jeff
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232-0700, USA
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Bidulescu A, Din-Dzietham R, Coverson DL, Chen Z, Meng YX, Buxbaum SG, Gibbons GH, Welch VL. Interaction of sleep quality and psychosocial stress on obesity in African Americans: the Cardiovascular Health Epidemiology Study (CHES). BMC Public Health 2010; 10:581. [PMID: 20920190 PMCID: PMC2955012 DOI: 10.1186/1471-2458-10-581] [Citation(s) in RCA: 77] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2010] [Accepted: 09/28/2010] [Indexed: 01/05/2023] Open
Abstract
Background Compared with whites, sleep disturbance and sleep deprivation appear more prevalent in African Americans (AA). Long-term sleep deprivation may increase the risk of obesity through multiple metabolic and endocrine alterations. Previous studies have reported contradictory results on the association between habitual sleep duration and obesity. Accordingly, we aimed to assess whether sleep quality and duration are inversely associated with body mass index (BMI) and obesity and test whether these associations are modified by psychosocial stress, known to influence sleep quality. Methods A sample of 1,515 AA residents of metropolitan Atlanta, aged 30-65 years, was recruited by a random-digit-dialing method in 2007-08. The outcome obesity was defined by BMI (kg/m2) continuously and categorically (BMI ≥ 30 versus BMI < 30). Global sleep quality (GSQ) score was computed as the sum of response values for the seven components of the Pittsburgh Sleep Quality Index (PSQI) scale. GSQ score was defined as a continuous variable (range 0-21) and as tertiles. The general perceived stress (GPS), derived from the validated Cohen scale, was categorized into tertiles to test the interaction. Chi-square tests, correlation coefficients and weighted multiple linear and logistic regression were used to assess the associations of GSQ, GPS and obesity. Results The mean (standard deviation) age was 47.5 (17.0) years, and 1,096 (72%) were women. GSQ score categorized into tertiles was associated with BMI. Among women, after multivariable adjustment that included age, gender, physical activity, smoking status, education, total family income, financial stress and history of hypertension, hypercholesterolemia, diabetes and myocardial infarction, obesity was associated with sleep quality as assessed by GSQ continuous score, [odds ratio, OR (95% C.I.): 1.08 (1.03 - 1.12)], and with a worse sleep disturbance subcomponent score [OR (95% C.I.): 1.48 (1.16 - 1.89)]. Among all participants, stress modified the association between obesity and sleep quality; there was an increased likelihood of obesity in the medium stress category, OR (95% C.I.): 1.09 (1.02 - 1.17). Conclusion Sleep quality was associated with obesity in women. The association of sleep quality with obesity was modified by perceived stress. Our results indicate the need for simultaneous assessment of sleep and stress.
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Sumner AE, Harman JL, Buxbaum SG, Miller BV, Tambay AV, Wyatt SB, Taylor HA, Rotimi CN, Sarpong DF. The triglyceride/high-density lipoprotein cholesterol ratio fails to predict insulin resistance in African-American women: an analysis of Jackson Heart Study. Metab Syndr Relat Disord 2010; 8:511-4. [PMID: 20715971 DOI: 10.1089/met.2010.0028] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Compared to whites, insulin-resistant African Americans have worse outcomes. Screening programs that could identify insulin resistance early enough for intervention to affect outcome often rely on triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels. Racial differences in TG and HDL-C may compromise the efficacy of these programs in African Americans. A recommendation currently exists to use the TG/HDL-C ratio ≥2.0 to predict insulin resistance in African Americans. The validity of this recommendation needs examination. Therefore, our aim was to determine the ability of TG/HDL-C ratio to predict insulin resistance in African Americans. METHODS In 1,903 African Americans [895 men, 1,008 women, age 55 ± 12 years, mean ± standard deviation (SD), range 35-80 years, body mass index (BMI) 31.0 ± 6.4 kg/m(2), range 18.5-55 kg/m(2)] participating in the Jackson Heart Study, a population-based study of African Americans, Jackson, Mississippi tricounty region, insulin resistance was defined by the upper quartile (≥4.43) of homeostasis model assessment of insulin resistance (HOMA-IR). An area under the receiver operating characteristic curve (AUC-ROC) of >0.70 was required for prediction of insulin resistance by TG/HDL-C. The optimal test cutoff was determined by the Youden index. RESULTS HOMA-IR was similar in men and women (3.40 ± 2.03 vs. 3.80 ± 2.46, P = 0.60). Women had lower TG (94 ± 49 vs. 109 ± 65 mg/dL P < 0.001) and TG/HDL-C (1.9 ± 1.4 vs. 2.7 ± 2.1, P < 0.001). For men, AUC-ROC for prediction of insulin resistance by TG/HDL-C was: 0.77 ± 0.01, mean ± standard error (SE), with an optimal cutoff of ≥2.5. For women, the AUC-ROC was 0.66 ± 0.01, rendering an optimal cutoff indefinable. When women were divided in two groups according to age, 35-50 years and 51-80 years, the results did not change. CONCLUSIONS In African-American men, the recommended TG/HDL-C threshold of 2.0 should be adjusted upward to 2.5. In African-American women, TG/HDL-C cannot identify insulin resistance. The Jackson Heart Study can help determine the efficacy of screening programs in African-Americans.
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Affiliation(s)
- Anne E Sumner
- Clinical Endocrinology Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, Maryland 0892-1612, USA.
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Keebler ME, Deo RC, Surti A, Konieczkowski D, Guiducci C, Burtt N, Buxbaum SG, Sarpong DF, Steffes MW, Wilson JG, Taylor HA, Kathiresan S. Fine-mapping in African Americans of 8 recently discovered genetic loci for plasma lipids: the Jackson Heart Study. ACTA ACUST UNITED AC 2010; 3:358-64. [PMID: 20570916 DOI: 10.1161/circgenetics.109.914267] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
BACKGROUND Genome-wide association studies in cohorts of European descent have identified novel genomic regions as associated with lipids, but their relevance in African Americans remains unclear. METHODS AND RESULTS We genotyped 8 index single nucleotide polymorphisms (SNPs) and 488 tagging SNPs across 8 novel lipid loci in the Jackson Heart Study, a community-based cohort of 4605 African Americans. For each trait, we calculated residuals adjusted for age, sex, and global ancestry and performed multivariable linear regression to detect genotype-phenotype association with adjustment for local ancestry. To explore admixture effects, we conducted stratified analyses in individuals with a high probability of 2 African ancestral alleles or at least 1 European allele at each locus. We confirmed 2 index SNPs as associated with lipid traits in African Americans, with suggestive association for 3 more. However, the effect sizes for 4 of the 5 associated SNPs were larger in the European local ancestry subgroup compared with the African local ancestry subgroup, suggesting that the replication is driven by European ancestry segments. Through fine-mapping, we discovered 3 new SNPs with significant associations, 2 with consistent effect on triglyceride levels across ancestral groups: rs636523 near DOCK7/ANGPTL3 and rs780093 in GCKR. African linkage disequilibrium patterns did not assist in narrowing association signals. CONCLUSIONS We confirm that 5 genetic regions associated with lipid traits in European-derived populations are relevant in African Americans. To further evaluate these loci, fine-mapping in larger African American cohorts and/or resequencing will be required.
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Abstract
BACKGROUND To examine the association of increased plasma leptin concentration with prevalent stroke and coronary heart disease (CHD) and to examine the genetic contributions of leptin to this association in the Jackson Heart Study cohort. METHODS A cohort of 5170 participants aged 21-84 years who underwent Exam I during 2000-2004 was analysed. Odds ratios (OR) of prevalent stroke and CHD were calculated using a logistic regression model adjusted for age, smoking, hypertension and waist circumference (WC). Variance component analysis was used to partition the phenotypic variance of leptin into the polygenic and environmental components. RESULTS The prevalence of stroke and CHD was 4.04% and 5.85% in women, and 4.88% and 8.92% in men, respectively. Body mass index (BMI) and WC were highly correlated with leptin both in men and women. In multivariate analysis stratified by sex, leptin was significantly associated with stroke (OR = 1.97, 95% CI = 1.21-3.21) in women after adjustment for age, smoking, systolic blood pressure, BMI and WC (P = 0.0079). No significant association was observed in men. Heritability of sex-, age-adjusted log-transformed leptin for this cohort was 38.0% and 37.8% after further adjustment for WC and hypertension, respectively. In addition, a sibship effect was also found to be significant and explained 12.2% of the total variance of leptin (P = 0.007). CONCLUSION There is a significant association of leptin with stroke in women, which is partly influenced by the genetic factor. The findings suggest that leptinemia is an independent risk factor for stroke in African American women.
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Affiliation(s)
- Jiankang Liu
- Jackson Heart Study, Jackson State University, University of Mississippi Medical Center, Jackson, Mississippi 39216-4505, USA.
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Akylbekova EL, Crow RS, Johnson WD, Buxbaum SG, Njemanze S, Fox E, Sarpong DF, Taylor HA, Newton-Cheh C. Clinical correlates and heritability of QT interval duration in blacks: the Jackson Heart Study. Circ Arrhythm Electrophysiol 2009; 2:427-32. [PMID: 19808499 DOI: 10.1161/circep.109.858894] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Electrocardiographic QT interval prolongation is a risk factor for sudden cardiac death and drug-induced arrhythmia. The clinical correlates and heritability of QT interval duration in blacks have not been well studied despite their higher risk for sudden cardiac death compared with non-Hispanic whites. We sought to investigate potential correlates of the QT interval and estimate its heritability in the Jackson Heart Study. METHODS AND RESULTS The Jackson Heart Study comprises a sample of blacks residing in Jackson, Miss, of whom 5302 individuals with data at the baseline examination were available for study. Jackson Heart Study participants on QT-altering medications, with bundle-branch block, paced rhythm, atrial fibrillation/flutter, or other arrhythmias were excluded, resulting in a sample of 4660 individuals eligible for analyses. The relation between QT and potential covariates was tested using multivariable stepwise linear regression. Heritability was estimated using Sequential Oligogenic Linkage Analysis Routine in a subset of 1297 Jackson Heart Study participants in 292 families; the remaining sample included unrelated individuals. In stepwise multivariable linear regression analysis, covariates significantly associated with QT interval duration included R-R interval, sex, QRS duration, age, serum potassium, hypertension, body mass index, coronary heart disease, diuretic use, and Sokolow-Lyon voltage (P < or = 0.01 for all). The heritability of QT interval duration in the age-, sex-, and R-R interval-adjusted model and in the fully adjusted model was 0.41 (SE, 0.07) and 0.40 (SE, 0.07; P < 10(-11) for both), respectively. CONCLUSIONS There is substantial heritability of adjusted QT interval in blacks, supporting the need for further investigation to identify its genetic determinants.
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Nalls MA, Wilson JG, Patterson NJ, Tandon A, Zmuda JM, Huntsman S, Garcia M, Hu D, Li R, Beamer BA, Patel KV, Akylbekova EL, Files JC, Hardy CL, Buxbaum SG, Taylor HA, Reich D, Harris TB, Ziv E. Admixture Mapping of White Cell Count: Genetic Locus Responsible for Lower White Blood Cell Count in the Health ABC and Jackson Heart Studies. Am J Hum Genet 2008. [DOI: 10.1016/j.ajhg.2008.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Nalls MA, Wilson JG, Patterson NJ, Tandon A, Zmuda JM, Huntsman S, Garcia M, Hu D, Li R, Beamer BA, Patel KV, Akylbekova EL, Files JC, Hardy CL, Buxbaum SG, Taylor HA, Reich D, Harris TB, Ziv E. Admixture mapping of white cell count: genetic locus responsible for lower white blood cell count in the Health ABC and Jackson Heart studies. Am J Hum Genet 2008; 82:81-7. [PMID: 18179887 DOI: 10.1016/j.ajhg.2007.09.003] [Citation(s) in RCA: 128] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2007] [Revised: 08/31/2007] [Accepted: 09/11/2007] [Indexed: 01/22/2023] Open
Abstract
White blood cell count (WBC) is an important clinical marker that varies among different ethnic groups. African Americans are known to have a lower WBC than European Americans. We surveyed the entire genome for loci underlying this difference in WBC by using admixture mapping. We analyzed data from African American participants in the Health, Aging, and Body Composition Study and the Jackson Heart Study. Participants of both studies were genotyped across >or= 1322 single nucleotide polymorphisms that were pre-selected to be informative for African versus European ancestry and span the entire genome. We used these markers to estimate genetic ancestry in each chromosomal region and then tested the association between WBC and genetic ancestry at each locus. We found a locus on chromosome 1q strongly associated with WBC (p < 10(-12)). The strongest association was with a marker known to affect the expression of the Duffy blood group antigen. Participants who had both copies of the common West African allele had a mean WBC of 4.9 (SD 1.3); participants who had both common European alleles had a mean WBC of 7.1 (SD 1.3). This variant explained approximately 20% of population variation in WBC. We used admixture mapping, a novel method for conducting genetic-association studies, to find a region that was significantly associated with WBC on chromosome 1q. Additional studies are needed to determine the biological mechanism for this effect and its clinical implications.
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Tang Y, Buxbaum SG, Waldman I, Anderson GM, Zabetian CP, Köhnke MD, Cubells JF. A single nucleotide polymorphism at DBH, possibly associated with attention-deficit/hyperactivity disorder, associates with lower plasma dopamine beta-hydroxylase activity and is in linkage disequilibrium with two putative functional single nucleotide polymorphisms. Biol Psychiatry 2006; 60:1034-8. [PMID: 16616730 DOI: 10.1016/j.biopsych.2006.02.017] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2005] [Revised: 07/26/2005] [Accepted: 02/10/2006] [Indexed: 11/30/2022]
Abstract
BACKGROUND The DBH gene regulates plasma dopamine beta-hydroxylase activity (pDbetaH). Two single nucleotide polymorphisms (SNPs), -1021C-->T (rs1611115; SNP1) and +1603C-->T (rs6271; SNP3), independently influence pDbetaH. Another SNP, commonly known as DBH Taq1A (rs2519152; SNP2) is associated with attention-deficit/hyperactivity disorder (ADHD) in some (but not all) studies. We tested whether 1) SNP2 associates with pDbetaH; and 2) whether linkage disequilibrium (LD) between SNP2 and the other SNPs explains that association. METHODS Plasma dopamine beta-hydroxylase activity and genotypes at the SNPs were determined in Caucasian subjects (n = 418). Associations to pDbetaH were examined using analyses of variance (ANOVAs) and LD among the SNPs using estimation maximization. RESULTS 1) Each polymorphism analyzed alone associated with pDbetaH; 2) SNP2 was in strong LD with SNP1 and SNP3, respectively, but there was no significant LD between SNP1 and SNP3; and 3) analyzed jointly, each SNP contributed significantly and uniquely to plasma DbetaH activity. CONCLUSIONS 1) SNP2 associates with pDbetaH; 2) SNP2 shows LD with SNP1 and SNP3; 3) most of the association between SNP2 and pDbetaH simply reflects that LD; however, 4) SNP2 also appears to exert a small independent effect on pDbetaH, suggesting that SNP2, or another variant in LD with it, uniquely influences pDbetaH.
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Affiliation(s)
- Yilang Tang
- Department of Psychiatry, Yale University School of Medicine and VA Connecticut Healthcare System, New Haven, Connecticut, USA
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Abstract
Several programs are currently available for the detection of genotyping error that may or may not be Mendelianly inconsistent. However, no systematic study exists that evaluates their performance under varying pedigree structures and sizes, marker spacing, and allele frequencies. Our simulation study compares four multipoint methods: Merlin, Mendel4, SimWalk2, and Sibmed. We look at empirical thresholds, power, and false-positive rates on 7 small pedigree structures that included sibships with and without genotyped parents, and a three-generation pedigree, using 11 microsatellite markers with 3 different map spacings. Simulated data includes 5,000 replicates of each pedigree structure and marker map, with random genotyping errors in about 4% of the middle marker's genotypes. We found that the default thresholds used by these programs provide low power (47-72%). Power is improved more by adding genotyped siblings than by using more closely spaced markers. Some mistyping methods are sensitive to the frequencies of the observed alleles. Siblings of mistyped individuals have elevated false-positive rates, as do markers close to the mistyped marker. We conclude that thresholds should be decided based on the pedigree and marker data and that greater focus should be placed on modeling genotyping error when computing likelihoods, rather than on detecting and eliminating genotyping errors.
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Affiliation(s)
- Nandita Mukhopadhyay
- Department of Human Genetic, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
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Shibamura H, Olson JM, van Vlijmen-Van Keulen C, Buxbaum SG, Dudek DM, Tromp G, Ogata T, Skunca M, Sakalihasan N, Pals G, Limet R, MacKean GL, Defawe O, Verloes A, Arthur C, Lossing AG, Burnett M, Sueda T, Kuivaniemi H. Genome scan for familial abdominal aortic aneurysm using sex and family history as covariates suggests genetic heterogeneity and identifies linkage to chromosome 19q13. Circulation 2004; 109:2103-8. [PMID: 15096456 DOI: 10.1161/01.cir.0000127857.77161.a1] [Citation(s) in RCA: 108] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Abdominal aortic aneurysm (AAA) is a relatively common disease, with 1% to 2% of the population harboring aneurysms. Genetic risk factors are likely to contribute to the development of AAAs, although no such risk factors have been identified. METHODS AND RESULTS We performed a whole-genome scan of AAA using affected-relative-pair (ARP) linkage analysis that includes covariates to allow for genetic heterogeneity. We found strong evidence of linkage (logarithm of odds [LOD] score=4.64) to a region near marker D19S433 at 51.88 centimorgans (cM) on chromosome 19 with 36 families (75 ARPs) when including sex and the number of affected first-degree relatives of the proband (N(aff)) as covariates. We then genotyped 83 additional families for the same markers and typed additional markers for all families and obtained a LOD score of 4.75 (P=0.00014) with sex, N(aff), and their interaction as covariates near marker D19S416 (58.69 cM). We also identified a region on chromosome 4 with a LOD score of 3.73 (P=0.0012) near marker D4S1644 using the same covariate model as for chromosome 19. CONCLUSIONS Our results provide evidence for genetic heterogeneity and the presence of susceptibility loci for AAA on chromosomes 19q13 and 4q31.
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Affiliation(s)
- Hidenori Shibamura
- Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Mich 48201, USA
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Palmer LJ, Buxbaum SG, Larkin EK, Patel SR, Elston RC, Tishler PV, Redline S. Whole genome scan for obstructive sleep apnea and obesity in African-American families. Am J Respir Crit Care Med 2004; 169:1314-21. [PMID: 15070816 DOI: 10.1164/rccm.200304-493oc] [Citation(s) in RCA: 93] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common, chronic disease associated with obesity. OSA and obesity are both prevalent in African Americans, who are also at increased risk for secondary complications. To identify susceptibility loci for OSA, we undertook a 9-centimorgans genome scan in 59 African-American pedigrees ascertained on the basis of either an affected individual with laboratory-confirmed disease or a proband who was a neighborhood control subject. Variance component linkage analysis was performed for the quantitative phenotypes apnea-hypopnea index (AHI) and body mass index. A candidate region on chromosome 8q (logarithm of odds [LOD] = 1.29, p = 0.006) gave the only evidence for linkage to the AHI. Body mass index was linked to multiple regions, most significantly to markers on chromosome 4q (LOD = 2.63, p = 0.0006) and 8q (LOD = 2.56, p = 0.0007). Evidence of linkage to the AHI was only slightly reduced after adjustment for body mass index. After adjustment for the AHI, some of the primary linkages to body mass index were greatly reduced whereas others remained suggestive. Our results suggest that there are both shared and unshared genetic factors underlying susceptibility to OSA and obesity, and that the genetic determinants of obesity in this population may be modulated by apnea severity.
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MESH Headings
- Adolescent
- Adult
- Black or African American/genetics
- Aged
- Body Mass Index
- Chromosome Mapping
- Chromosomes, Human, Pair 12/genetics
- Chromosomes, Human, Pair 2/genetics
- Chromosomes, Human, Pair 5/genetics
- Chromosomes, Human, Pair 8/genetics
- Cohort Studies
- Family Health
- Female
- Genetic Linkage/genetics
- Genetic Predisposition to Disease/genetics
- Genome, Human
- Humans
- Lod Score
- Male
- Middle Aged
- Obesity/genetics
- Pedigree
- Phenotype
- Polysomnography
- Sex Factors
- Sleep Apnea, Obstructive/genetics
- Statistics as Topic
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Affiliation(s)
- Lyle J Palmer
- Western Australian Institute for Medical Research, Centre for Medical Research, University of Western Australia, Perth, Australia.
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Zabetian CP, Buxbaum SG, Elston RC, Köhnke MD, Anderson GM, Gelernter J, Cubells JF. The structure of linkage disequilibrium at the DBH locus strongly influences the magnitude of association between diallelic markers and plasma dopamine beta-hydroxylase activity. Am J Hum Genet 2003; 72:1389-400. [PMID: 12730829 PMCID: PMC1180300 DOI: 10.1086/375499] [Citation(s) in RCA: 72] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2002] [Accepted: 03/14/2003] [Indexed: 11/03/2022] Open
Abstract
There is currently a great deal of interest in using linkage disequilibrium (LD) mapping to locate both disease and quantitative-trait loci on a genomewide scale. Recent findings suggest that much of the human genome is organized in discrete "blocks" of low haplotype diversity, but the utility of such blocks in identifying genes influencing complex traits is not yet known and must ultimately be tested empirically through use of real data. We recently identified a putative functional polymorphism (-1021C-->T) in the 5' upstream region of the DBH gene that accounted for 35%-52% of the total phenotypic variance in plasma dopamine beta-hydroxylase (DBH) activity in samples from three distinct populations. In the present study, we genotyped 11 diallelic markers at the DBH locus surrounding -1021C-->T in 386 unrelated individuals of European origin. We identified a single 10-kb block containing -1021C-->T, in which four haplotypes comprised 93% of the observed chromosomes. Only markers within the block were highly associated with phenotype (P< or =2.2 x 10(-10)), with one exception. In general, association with phenotype was strongly correlated with the degree of LD between each marker and -1021C-->T. Of four LD measures assessed, d(2) was the best predictor of this relationship. Had one attempted to map quantitative-trait loci for plasma DBH activity on a genomewide basis without prior knowledge of candidate regions and not included (by chance) markers within this haplotype block, the DBH locus might have been missed entirely. These results provide a direct example of the potential value of constructing a haplotype map of the human genome prior to embarking on large-scale association studies.
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Affiliation(s)
- Cyrus P. Zabetian
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - Sarah G. Buxbaum
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - Robert C. Elston
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - Michael D. Köhnke
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - George M. Anderson
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - Joel Gelernter
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
| | - Joseph F. Cubells
- Department of Psychiatry and Child Study Center, Yale University School of Medicine, New Haven, CT; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH; and University Hospital of Psychiatry and Psychotherapy, Tübingen University Hospital, Tübingen, Germany
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Palmer LJ, Buxbaum SG, Larkin E, Patel SR, Elston RC, Tishler PV, Redline S. A whole-genome scan for obstructive sleep apnea and obesity. Am J Hum Genet 2003; 72:340-50. [PMID: 12506338 PMCID: PMC379227 DOI: 10.1086/346064] [Citation(s) in RCA: 128] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2002] [Accepted: 10/29/2002] [Indexed: 01/22/2023] Open
Abstract
Obstructive sleep apnea (OSA) is a common, chronic, complex disease associated with serious cardiovascular and neuropsychological sequelae and with substantial social and economic costs. Along with male gender, obesity is the most characteristic feature of OSA in adults. To identify susceptibility loci for OSA, we undertook a 9-cM genome scan in 66 white pedigrees (n=349 subjects) ascertained on the basis of either an affected individual with laboratory-confirmed OSA or a proband who was a neighborhood control individual. Multipoint variance-component linkage analysis was performed for the OSA-associated quantitative phenotypes apnea-hypopnea index (AHI) and body mass index (BMI). Candidate regions on chromosomes 1p (LOD score 1.39), 2p (LOD score 1.64), 12p (LOD score 1.43), and 19p (LOD score 1.40) gave the most evidence for linkage to AHI. BMI was also linked to multiple regions, most significantly to markers on chromosomes 2p (LOD score 3.08), 7p (LOD score 2.53), and 12p (LOD score 3.41). Extended modeling indicated that the evidence for linkage to AHI was effectively removed after adjustment for BMI, with the exception of the candidate regions on chromosomes 2p (adjusted LOD score 1.33) and 19p (adjusted LOD score 1.45). After adjustment for AHI, the primary linkages to BMI remained suggestive but were roughly halved. Our results suggest that there are both shared and unshared genetic factors underlying susceptibility to OSA and obesity and that the interrelationship of OSA and obesity in white individuals may be partially explained by a common causal pathway involving one or more genes regulating both AHI and BMI levels.
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Affiliation(s)
- Lyle J Palmer
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
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Abstract
Predicting phenotype from genotype is difficult when the phenotype is affected by a gene with numerous weakly penetrant alleles that differ only in the pattern of their single nucleotide polymorphisms (SNPs). While it is probable that SNP interactions affect phenotype, to our knowledge no one has determined the most effective way of evaluating whether SNPs interact and of modeling the interaction. Therefore, to explore this issue, we investigate here three methods of modeling SNP interaction using data from Genetic Analysis Workshop 12. Since major gene 5 (MG5) has sequence information and explains 37% of the variation in quantitative trait 5 (Q5), we focus on using SNPs within MG5 to predict Q5 among individuals who married into the pedigree. As a preliminary screening step, we reduced the number of SNPs from 269 to 34 based on their association with Q5. In our first models we assumed that SNPs affected Q5 in a simple additive manner. These models explained 34% and 15% of the variation in Q5 in women and men, respectively. Our second model was a linear model, which used individual SNPs and simple interaction terms as predictors. These models explained 36% and 16% of the variation in Q5 levels for women and men, respectively. Our last model was a "hit"-based model which was motivated by the hypothesis that disequilibrium between SNPs may reflect the fact that SNPs affect phenotype by acting in concert with other SNPs within their "disequilibrium set." Thus, the number of hits within the disequilibrium sets were used as predictors. These models explained 35% and 19% of the variation in Q5 for women and men, respectively. Our results suggest that phenotype can be predicted from complex patterns of weakly penetrant SNPs using relatively simple models. We concluded that SNP interaction either was not included in the simulation model, or had only a weak impact on Q5 levels.
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Affiliation(s)
- B A Fijal
- Department of Epidemiology and Biostatistics, Case Western Reserve University, 2500 MetroHealth Drive, Cleveland, OH 44109, USA
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Buxbaum SG, Elston RC, Tishler PV, Redline S. Genetics of the apnea hypopnea index in Caucasians and African Americans: I. Segregation analysis. Genet Epidemiol 2002; 22:243-53. [PMID: 11921084 DOI: 10.1002/gepi.0170] [Citation(s) in RCA: 92] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Differences in age of presentation and anatomic risk factors for obstructive sleep apnea (OSA) in Caucasians and African Americans suggest possible racial differences in the genetic underpinnings of the disorder. In this study, we assess transmission patterns in a Caucasian sample consisting of 177 families (N = 1,195) and in an African American sample consisting of 125 families (N = 720) for two variables: 1) apnea hypopnea index (AHI) log transformed and adjusted for age, and 2) AHI log transformed and adjusted for age and body mass index (BMI). We allowed for residual familial correlations and sex-specific means in all models. Analysis of the Caucasian sample showed transmission patterns consistent with that of a major gene that were stronger in the age-adjusted variable than in the age- and BMI-adjusted variable. However, in the African American families, adjusting for BMI in addition to age gave stronger evidence for segregation of a codominant gene with an allele frequency of 0.14, accounting for 35% of the total variance. These results provide support for an underlying genetic basis for OSA that in African Americans is independent of the contribution of BMI.
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Affiliation(s)
- Sarah G Buxbaum
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44109-1998, USA.
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Zabetian CP, Anderson GM, Buxbaum SG, Elston RC, Ichinose H, Nagatsu T, Kim KS, Kim CH, Malison RT, Gelernter J, Cubells JF. A quantitative-trait analysis of human plasma-dopamine beta-hydroxylase activity: evidence for a major functional polymorphism at the DBH locus. Am J Hum Genet 2001; 68:515-22. [PMID: 11170900 PMCID: PMC1235285 DOI: 10.1086/318198] [Citation(s) in RCA: 217] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2000] [Accepted: 12/07/2000] [Indexed: 11/03/2022] Open
Abstract
Dopamine-beta-hydroxylase (D beta H) catalyzes the conversion of dopamine to norepinephrine and is released from sympathetic neurons into the circulation. Plasma-D beta H activity varies widely between individuals, and a subgroup of the population has very low activity levels. Mounting evidence suggests that the DBH structural gene is itself the major quantitative-trait locus (QTL) for plasma-D beta H activity, and a single unidentified polymorphism may account for a majority of the variation in activity levels. Through use of both sequencing-based mutational analysis of extreme phenotypes and genotype/phenotype correlations in samples from African American, European American (EA), and Japanese populations, we have identified a novel polymorphism (--1021C-->T), in the 5' flanking region of the DBH gene, that accounts for 35%--52% of the variation in plasma-D beta H activity in these populations. In EAs, homozygosity at the T allele predicted the very low D beta H-activity trait, and activity values in heterozygotes formed an intermediate distribution, indicating codominant inheritance. Our findings demonstrate that --1021C-->T is a major genetic marker for plasma-D beta H activity and provide new tools for investigation of the role of both D beta H and the DBH gene in human disease.
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Affiliation(s)
- Cyrus P. Zabetian
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - George M. Anderson
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Sarah G. Buxbaum
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Robert C. Elston
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Hiroshi Ichinose
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Toshiharu Nagatsu
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Kwang-Soo Kim
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Chun-Hyung Kim
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Robert T. Malison
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Joel Gelernter
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
| | - Joseph F. Cubells
- Department of Psychiatry and Child Study Center, Yale University, and Connecticut Mental Health Center, New Haven; Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland; Institute for Comprehensive Medical Sciences, Fujita Health University, Toyoake, Japan; and Molecular Neurobiology Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA
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