3601
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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: 43] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [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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3602
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Levin AM, Mathias RA, Huang L, Roth LA, Daley D, Myers RA, Himes BE, Romieu I, Yang M, Eng C, Park JE, Zoratti K, Gignoux CR, Torgerson DG, Galanter JM, Huntsman S, Nguyen EA, Becker AB, Chan-Yeung M, Kozyrskyj AL, Kwok PY, Gilliland FD, Gauderman WJ, Bleecker ER, Raby BA, Meyers DA, London SJ, Martinez FD, Weiss ST, Burchard EG, Nicolae DL, Ober C, Barnes KC, Williams LK. A meta-analysis of genome-wide association studies for serum total IgE in diverse study populations. J Allergy Clin Immunol 2012; 131:1176-84. [PMID: 23146381 DOI: 10.1016/j.jaci.2012.10.002] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2012] [Revised: 09/28/2012] [Accepted: 10/02/2012] [Indexed: 01/27/2023]
Abstract
BACKGROUND IgE is both a marker and mediator of allergic inflammation. Despite reported differences in serum total IgE levels by race-ethnicity, African American and Latino subjects have not been well represented in genetic studies of total IgE. OBJECTIVE We sought to identify the genetic predictors of serum total IgE levels. METHODS We used genome-wide association data from 4292 subjects (2469 African Americans, 1564 European Americans, and 259 Latinos) in the EVE Asthma Genetics Consortium. Tests for association were performed within each cohort by race-ethnic group (ie, African American, Latino, and European American) and asthma status. The resulting P values were meta-analyzed, accounting for sample size and direction of effect. Top single nucleotide polymorphism associations from the meta-analysis were reassessed in 6 additional cohorts comprising 5767 subjects. RESULTS We identified 10 unique regions in which the combined association statistic was associated with total serum IgE levels (P<5.0×10(-6)) and the minor allele frequency was 5% or greater in 2 or more population groups. Variant rs9469220, corresponding to HLA-DQB1, was the single nucleotide polymorphism most significantly associated with serum total IgE levels when assessed in both the replication cohorts and the discovery and replication sets combined (P=.007 and 2.45×10(-7), respectively). In addition, findings from earlier genome-wide association studies were also validated in the current meta-analysis. CONCLUSION This meta-analysis independently identified a variant near HLA-DQB1 as a predictor of total serum IgE levels in multiple race-ethnic groups. This study also extends and confirms the findings of earlier genome-wide association analyses in African American and Latino subjects.
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Affiliation(s)
- Albert M Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
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3603
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Abstract
This unit provides an overview of the design and analysis of population-based case-control studies of genetic risk factors for complex disease. Considerations specific to genetic studies are emphasized. The unit reviews basic study designs differentiating case-control studies from others, presents different genetic association strategies (candidate gene, genome-wide association, and high-throughput sequencing), introduces basic methods of statistical analysis for case-control data and approaches to combining case-control studies, and discusses measures of association and impact. Admixed populations, controlling for confounding (including population stratification), consideration of multiple loci and environmental risk factors, and complementary analyses of haplotypes, genes, and pathways are briefly discussed. Readers are referred to basic texts on epidemiology for more details on general conduct of case-control studies.
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Affiliation(s)
- Dana B Hancock
- Research Triangle Institute International, Research Triangle Park, North Carolina, USA
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3604
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Auer P, Johnsen J, Johnson A, Logsdon B, Lange L, Nalls M, Zhang G, Franceschini N, Fox K, Lange E, Rich S, O’Donnell C, Jackson R, Wallace R, Chen Z, Graubert T, Wilson J, Tang H, Lettre G, Reiner A, Ganesh S, Li Y. Imputation of exome sequence variants into population- based samples and blood-cell-trait-associated loci in African Americans: NHLBI GO Exome Sequencing Project. Am J Hum Genet 2012; 91:794-808. [PMID: 23103231 DOI: 10.1016/j.ajhg.2012.08.031] [Citation(s) in RCA: 108] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2012] [Revised: 06/12/2012] [Accepted: 08/27/2012] [Indexed: 01/07/2023] Open
Abstract
Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombopoietin receptor gene (p = 1.5 × 10(-11)). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10(-13)). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325(∗)) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies.
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3605
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Asselbergs F, Guo Y, van Iperen E, Sivapalaratnam S, Tragante V, Lanktree M, Lange L, Almoguera B, Appelman Y, Barnard J, Baumert J, Beitelshees A, Bhangale T, Chen YD, Gaunt T, Gong Y, Hopewell J, Johnson T, Kleber M, Langaee T, Li M, Li Y, Liu K, McDonough C, Meijs M, Middelberg R, Musunuru K, Nelson C, O’Connell J, Padmanabhan S, Pankow J, Pankratz N, Rafelt S, Rajagopalan R, Romaine S, Schork N, Shaffer J, Shen H, Smith E, Tischfield S, van der Most P, van Vliet-Ostaptchouk J, Verweij N, Volcik K, Zhang L, Bailey K, Bailey K, Bauer F, Boer J, Braund P, Burt A, Burton P, Buxbaum S, Chen W, Cooper-DeHoff R, Cupples L, deJong J, Delles C, Duggan D, Fornage M, Furlong C, Glazer N, Gums J, Hastie C, Holmes M, Illig T, Kirkland S, Kivimaki M, Klein R, Klein B, Kooperberg C, Kottke-Marchant K, Kumari M, LaCroix A, Mallela L, Murugesan G, Ordovas J, Ouwehand W, Post W, Saxena R, Scharnagl H, Schreiner P, Shah T, Shields D, Shimbo D, Srinivasan S, Stolk R, Swerdlow D, Taylor H, Topol E, Toskala E, van Pelt J, van Setten J, Yusuf S, Whittaker J, Zwinderman A, LifeLines Cohort Study, Anand S, Balmforth A, Berenson G, et alAsselbergs F, Guo Y, van Iperen E, Sivapalaratnam S, Tragante V, Lanktree M, Lange L, Almoguera B, Appelman Y, Barnard J, Baumert J, Beitelshees A, Bhangale T, Chen YD, Gaunt T, Gong Y, Hopewell J, Johnson T, Kleber M, Langaee T, Li M, Li Y, Liu K, McDonough C, Meijs M, Middelberg R, Musunuru K, Nelson C, O’Connell J, Padmanabhan S, Pankow J, Pankratz N, Rafelt S, Rajagopalan R, Romaine S, Schork N, Shaffer J, Shen H, Smith E, Tischfield S, van der Most P, van Vliet-Ostaptchouk J, Verweij N, Volcik K, Zhang L, Bailey K, Bailey K, Bauer F, Boer J, Braund P, Burt A, Burton P, Buxbaum S, Chen W, Cooper-DeHoff R, Cupples L, deJong J, Delles C, Duggan D, Fornage M, Furlong C, Glazer N, Gums J, Hastie C, Holmes M, Illig T, Kirkland S, Kivimaki M, Klein R, Klein B, Kooperberg C, Kottke-Marchant K, Kumari M, LaCroix A, Mallela L, Murugesan G, Ordovas J, Ouwehand W, Post W, Saxena R, Scharnagl H, Schreiner P, Shah T, Shields D, Shimbo D, Srinivasan S, Stolk R, Swerdlow D, Taylor H, Topol E, Toskala E, van Pelt J, van Setten J, Yusuf S, Whittaker J, Zwinderman A, LifeLines Cohort Study, Anand S, Balmforth A, Berenson G, Bezzina C, Boehm B, Boerwinkle E, Casas J, Caulfield M, Clarke R, Connell J, Cruickshanks K, Davidson K, Day I, de Bakker P, Doevendans P, Dominiczak A, Hall A, Hartman C, Hengstenberg C, Hillege H, Hofker M, Humphries S, Jarvik G, Johnson J, Kaess B, Kathiresan S, Koenig W, Lawlor D, März W, Melander O, Mitchell B, Montgomery G, Munroe P, Murray S, Newhouse S, Onland-Moret N, Poulter N, Psaty B, Redline S, Rich S, Rotter J, Schunkert H, Sever P, Shuldiner A, Silverstein R, Stanton A, Thorand B, Trip M, Tsai M, van der Harst P, van der Schoot E, van der Schouw Y, Verschuren W, Watkins H, Wilde A, Wolffenbuttel B, Whitfield J, Hovingh G, Ballantyne C, Wijmenga C, Reilly M, Martin N, Wilson J, Rader D, Samani N, Reiner A, Hegele R, Kastelein J, Hingorani A, Talmud P, Hakonarson H, Elbers C, Keating B, Drenos F. Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci. Am J Hum Genet 2012; 91:823-38. [PMID: 23063622 PMCID: PMC3487124 DOI: 10.1016/j.ajhg.2012.08.032] [Show More Authors] [Citation(s) in RCA: 200] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2012] [Revised: 08/02/2012] [Accepted: 08/30/2012] [Indexed: 12/19/2022] Open
Abstract
Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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Affiliation(s)
- Folkert W. Asselbergs
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Yiran Guo
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Erik P.A. van Iperen
- Durrer Center for Cardiogenetic Research, 1105 AZ Amsterdam, The Netherlands
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands
| | - Suthesh Sivapalaratnam
- Department of Vascular Medicine, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Vinicius Tragante
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Matthew B. Lanktree
- Departments of Medicine and Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON N6A 3K6, Canada
| | - Leslie A. Lange
- Department of Genetics, University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Berta Almoguera
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Yolande E. Appelman
- Department of Cardiology, VU University Medical Center, 1081 HV Amsterdam, the Netherlands
| | - John Barnard
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Jens Baumert
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764 Neuherberg, Germany
| | - Amber L. Beitelshees
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Tushar R. Bhangale
- Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA 94080, USA
| | - Yii-Der Ida Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Tom R. Gaunt
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL 32603, USA
| | - Jemma C. Hopewell
- Clinical Trial Service Unit, University of Oxford, Oxford OX3 7BN, UK
| | - Toby Johnson
- Clinical Pharmacology and Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Marcus E. Kleber
- LURIC Study, Platz der alten Synagoge 1, 79098 Freiburg, Germany
- Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty of Mannheim, University of Heidelberg, Ludolf-Krehl-Strasse 7-11, 68167 Mannheim, Germany
| | - Taimour Y. Langaee
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL 32603, USA
| | - Mingyao Li
- Cardiovascular Institute, the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yun R. Li
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kiang Liu
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL 32603, USA
| | - Matthijs F.L. Meijs
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
| | - Rita P.S. Middelberg
- Genetic Epidemiology, Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane Hospital, Queensland 4029, Australia
- Department of Medicine, Prince Charles Hospital, Rode Road, Chermside, Queensland 4032, Australia
| | - Kiran Musunuru
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Jeffery R. O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Sandosh Padmanabhan
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - James S. Pankow
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Suzanne Rafelt
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Ramakrishnan Rajagopalan
- Division of Medical Genetics, Department of Medicine and the Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Simon P.R. Romaine
- Leeds Institute of Genetics, Health & Therapeutics, University of Leeds, Leeds LS2 9JT, UK
| | - Nicholas J. Schork
- The Scripps Translational Science Institute and The Scripps Research Institute, 3344 N. Torrey Pines Court, Suite 300, La Jolla, CA 92037, USA
| | - Jonathan Shaffer
- Center for Behavioral Cardiovascular Health, Department of Medicine, Columbia University, New York, NY 10032, USA
| | - Haiqing Shen
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Erin N. Smith
- Department of Pediatrics and Rady’s Children’s Hospital, University of California at San Diego School of Medicine, La Jolla, CA 9293, USA
| | - Sam E. Tischfield
- Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Peter J. van der Most
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Jana V. van Vliet-Ostaptchouk
- Molecular Genetics Laboratory, Medical Biology Division, Department of Pathology and Medical Biology, University Medical Center Groningen, Groningen University, 9700 RB Groningen, The Netherlands
- Department of Endocrinology, University Medical Center Groningen, Groningen University, 9700 RB Groningen, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
| | - 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, TX 77030, USA
| | - Li Zhang
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Kent R. Bailey
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Kristian M. Bailey
- Leeds Institute of Genetics, Health & Therapeutics, University of Leeds, Leeds LS2 9JT, UK
| | - Florianne Bauer
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Jolanda M.A. Boer
- National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
| | - Peter S. Braund
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK
| | - Amber Burt
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Paul R. Burton
- Department of Health Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK
| | - Sarah G. Buxbaum
- Jackson Heart Study and School of Health Sciences, Department of Epidemiology and Biostatistics, Jackson State University, Jackson, MS 39217, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University, 1440 Canal Street, Suite 1829, New Orleans, LA 70118, USA
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL 32603, USA
| | - L. Adrienne Cupples
- Boston University, Boston, MA 02215, USA
- The National Heart, Lung, and Blood Institute Framingham Heart Study, Framingham, MA 01702, USA
| | - Jonas S. deJong
- Heart Failure Research Center, Department of Clinical and Experimental Cardiology, Academic Medical Center, 1105 AZ Amsterdam, the Netherlands
| | - Christian Delles
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - David Duggan
- Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Myriam Fornage
- The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Clement E. Furlong
- Division of Medical Genetics, Department of Medicine and the Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | | | - John G. Gums
- Departments of Pharmacotherapy and Translational Research and Community Health and Family Medicine, University of Florida, Gainesville, FL 32607, USA
| | - Claire Hastie
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - Michael V. Holmes
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764 Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, 30625 Hannover, Germany
| | - Susan A. Kirkland
- Department of Community Health and Epidemiology and Department of Medicine, Dalhousie University, Halifax NS B3H 1V7, Canada
| | - Mika Kivimaki
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
| | - Ronald Klein
- Department of Ophthalmology & Visual Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Barbara E. Klein
- Department of Ophthalmology & Visual Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | | | - Meena Kumari
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
| | - Andrea Z. LaCroix
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Laya Mallela
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Gurunathan Murugesan
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Jose Ordovas
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA
| | - Willem H. Ouwehand
- Department of Haematology, University of Cambridge & Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Richa Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Hubert Scharnagl
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, 8036 Graz, Austria
| | - Pamela J. Schreiner
- School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Tina Shah
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
| | - Denis C. Shields
- Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Dublin 4, Ireland
| | - Daichi Shimbo
- Center for Behavioral Cardiovascular Health, Department of Medicine, Columbia University, New York, NY 10032, USA
| | - Sathanur R. Srinivasan
- Department of Epidemiology, Tulane University, 1440 Canal Street, Suite 2000, New Orleans, LA 70118 USA
| | - Ronald P. Stolk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Daniel I. Swerdlow
- Genetic Epidemiology Group, Research Department of Epidemiology and Public Health, University College London Institute of Epidemiology and Health Care, University College London, London WC1E 6BT, UK
| | - Herman A. Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39217, USA
| | - Eric J. Topol
- The Scripps Translational Science Institute and The Scripps Research Institute, 3344 N. Torrey Pines Court, Suite 300, La Jolla, CA 92037, USA
| | - Elina Toskala
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Joost L. van Pelt
- Laboratory Center, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Jessica van Setten
- Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Salim Yusuf
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, ON L8L 2X2, Canada
| | - John C. Whittaker
- GlaxoSmithKline, Stevenage SG1 2NY, UK
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - A.H. Zwinderman
- Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center, 1100DE Amsterdam, The Netherlands
| | - LifeLines Cohort Study
- LifeLines Cohort Study, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Sonia S. Anand
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, ON L8L 2X2, Canada
| | - Anthony J. Balmforth
- Leeds Institute of Genetics, Health & Therapeutics, University of Leeds, Leeds LS2 9JT, UK
| | - Gerald S. Berenson
- Department of Epidemiology, Tulane University, 1440 Canal Street, Suite 1829, New Orleans, LA 70118, USA
| | - Connie R. Bezzina
- Heart Failure Research Center, Department of Clinical and Experimental Cardiology, Academic Medical Center, 1105 AZ Amsterdam, the Netherlands
- Molecular and Experimental Cardiology Group, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Bernhard O. Boehm
- Department of Internal Medicine, Department of Medicine, University Hospital, 89069 Ulm, Germany
| | - Eric Boerwinkle
- The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Juan P. Casas
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Mark J. Caulfield
- Clinical Pharmacology and Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Robert Clarke
- Clinical Trial Service Unit, University of Oxford, Oxford OX3 7BN, UK
| | - John M. Connell
- University of Dundee, Ninewells Hospital and Medical School, Dundee DD1 9SY, UK
| | - Karen J. Cruickshanks
- Department of Ophthalmology & Visual Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Karina W. Davidson
- Departments of Medicine and Psychiatry, Columbia University, New York, NY 10027, USA
| | - Ian N.M. Day
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Paul I.W. de Bakker
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medical Genetics, Biomedical Genetics, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
| | - Pieter A. Doevendans
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
| | - Anna F. Dominiczak
- BHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - Alistair S. Hall
- Leeds Institute of Genetics, Health & Therapeutics, University of Leeds, Leeds LS2 9JT, UK
| | - Catharina A. Hartman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9700 AR Groningen, The Netherlands
| | | | - Hans L. Hillege
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
| | - Marten H. Hofker
- Molecular Genetics, Medical Biology Section, Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - Steve E. Humphries
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, 5 University Street, London WC1E 6JF, UK
| | - Gail P. Jarvik
- Division of Medical Genetics, Department of Medicine and the Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, FL 32603, USA
| | - Bernhard M. Kaess
- Klinik und Poliklinik für Innere Medizin II, University of Regensburg, 93042 Germany
| | - Sekar Kathiresan
- Broad Institute of MIT and Harvard, Cambridge, MA 02141, USA
- Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Wolfgang Koenig
- Department of Internal Medicine II–Cardiology, University of Ulm Medical Centre, 89081 Ulm, Germany
| | - Debbie A. Lawlor
- Medical Research Council Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Winfried März
- Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty of Mannheim, University of Heidelberg, Ludolf-Krehl-Strasse 7-11, 68167 Mannheim, Germany
- Synlab Academy, Gottlieb-Daimler-Straße 25, 68165 Mannheim, Germany
| | - Olle Melander
- Clinical Research Center, Malmö University Hospital, Malmö SE-205 02, Sweden
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Grant W. Montgomery
- Molecular Epidemiology, Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane Hospital, Queensland 4029, Australia
| | - Patricia B. Munroe
- Clinical Pharmacology and Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Sarah S. Murray
- The Scripps Translational Science Institute and The Scripps Research Institute, 3344 N. Torrey Pines Court, Suite 300, La Jolla, CA 92037, USA
| | - Stephen J. Newhouse
- Clinical Pharmacology and Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - N. Charlotte Onland-Moret
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, London W2 1PG, UK
| | - Bruce Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA 98195, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA 98109, USA
| | - Susan Redline
- University Hospitals, Case Medical Center and Case Western Reserve University, Cleveland, Ohio 44106, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA
| | - Jerome I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Peter Sever
- International Centre for Circulatory Health, Imperial College London, London W2 1PG, UK
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA
- Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD 21201, USA
| | - Roy L. Silverstein
- Department of Cell Biology, Lerner Research Institute, Cleveland Clinic, Case Western Reserve University, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
| | - Alice Stanton
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, D-85764 Neuherberg, Germany
| | - Mieke D. Trip
- Department of Cardiology, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen 9700 RB, The Netherlands
| | - Ellen van der Schoot
- Department of Experimental Immunology, Sanquin, 1105 AZ Amsterdam, The Netherlands
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment, 3721 MA Bilthoven, The Netherlands
| | - Hugh Watkins
- Department of Cardiovascular Medicine, The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Arthur A.M. Wilde
- Heart Failure Research Center, Department of Clinical and Experimental Cardiology, Academic Medical Center, 1105 AZ Amsterdam, the Netherlands
| | - Bruce H.R. Wolffenbuttel
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands
| | - John B. Whitfield
- Genetic Epidemiology, Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane Hospital, Queensland 4029, Australia
| | - G. Kees Hovingh
- Department of Vascular Medicine, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | | | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, the Netherlands
| | - Muredach P. Reilly
- Cardiovascular Institute, the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nicholas G. Martin
- Genetic Epidemiology, Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane Hospital, Queensland 4029, Australia
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Daniel J. Rader
- Cardiovascular Institute, the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK
- National Institute of Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Groby Road, Leicester LE3 9QP, UK
| | - Alex P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Robert A. Hegele
- Robarts Research Institute, University of Western Ontario, London, ON N6A5K8, Canada
| | - John J.P. Kastelein
- Department of Vascular Medicine, Academic Medical Center, 1105 AZ Amsterdam, The Netherlands
| | - Aroon D. Hingorani
- Research Department of Epidemiology & Public Health, University College London Institute of Epidemiology & Health Care, University College London, 1-19 Torrington Place, London WC1E 6BT, UK
| | - Philippa J. Talmud
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, 5 University Street, London WC1E 6JF, UK
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Clara C. Elbers
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Complex Genetics Section, Department of Medical Genetics, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Brendan J. Keating
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Fotios Drenos
- Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, 5 University Street, London WC1E 6JF, UK
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3606
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Traylor M, Farrall M, Holliday EG, Sudlow C, Hopewell JC, Cheng YC, Fornage M, Ikram MA, Malik R, Bevan S, Thorsteinsdottir U, Nalls MA, Longstreth WT, Wiggins KL, Yadav S, Parati EA, DeStefano AL, Worrall BB, Kittner SJ, Khan MS, Reiner AP, Helgadottir A, Achterberg S, Fernandez-Cadenas I, Abboud S, Schmidt R, Walters M, Chen WM, Ringelstein EB, O'Donnell M, Ho WK, Pera J, Lemmens R, Norrving B, Higgins P, Benn M, Sale M, Kuhlenbäumer G, Doney ASF, Vicente AM, Delavaran H, Algra A, Davies G, Oliveira SA, Palmer CNA, Deary I, Schmidt H, Pandolfo M, Montaner J, Carty C, de Bakker PIW, Kostulas K, Ferro JM, van Zuydam NR, Valdimarsson E, Nordestgaard BG, Lindgren A, Thijs V, Slowik A, Saleheen D, Paré G, Berger K, Thorleifsson G, The Australian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2 (WTCCC2), Hofman A, Mosley TH, Mitchell BD, Furie K, Clarke R, Levi C, Seshadri S, Gschwendtner A, Boncoraglio GB, Sharma P, Bis JC, Gretarsdottir S, Psaty BM, Rothwell PM, Rosand J, Meschia JF, Stefansson K, Dichgans M, Markus HS, on behalf of the International Stroke Genetics Consortium. Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): a meta-analysis of genome-wide association studies. Lancet Neurol 2012; 11:951-62. [PMID: 23041239 PMCID: PMC3490334 DOI: 10.1016/s1474-4422(12)70234-x] [Citation(s) in RCA: 376] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
BACKGROUND Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes. METHODS We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls. FINDINGS We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10(-16)) and ZFHX3 (p=2·28×10(-8)), and for large-vessel stroke at a 9p21 locus (p=3·32×10(-5)) and HDAC9 (p=2·03×10(-12)). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10(-6). However, we were unable to replicate any of these novel associations in the replication cohort. INTERPRETATION Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes. FUNDING Wellcome Trust, UK Medical Research Council (MRC), Australian National and Medical Health Research Council, National Institutes of Health (NIH) including National Heart, Lung and Blood Institute (NHLBI), the National Institute on Aging (NIA), the National Human Genome Research Institute (NHGRI), and the National Institute of Neurological Disorders and Stroke (NINDS).
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Affiliation(s)
- Matthew Traylor
- Stroke and Dementia Research Centre, St George's University of London, London, UK
| | - Martin Farrall
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
| | - Elizabeth G Holliday
- Centrw for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, and Center for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, NSW, Australia
| | - Cathie Sudlow
- Division of Clinical Neurosciences and Insititute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jemma C Hopewell
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
| | - Yu-Ching Cheng
- University of Maryland School of Medicine, Department of Medicine, Baltimore, MD, USA
| | - Myriam Fornage
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Department of Neurology and Department of Radiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, Netherlands
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Klinikum der Universitát München, Ludwig-Maximilians-Universität, and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Steve Bevan
- Stroke and Dementia Research Centre, St George's University of London, London, UK
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - WT Longstreth
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Sunaina Yadav
- Imperial College Cerebrovascular Research Unit (ICCRU), Imperial College London, London, UK
| | - Eugenio A Parati
- Department of Cereberovascular Disease, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Neurologico Carlo Besta, Milan, Italy
| | - Anita L DeStefano
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Bradford B Worrall
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Science, University of Virginia, Charlottesville, VA, USA
| | - Steven J Kittner
- Department of Neurology, Veterans Affairs Medical Center, Baltimore, MA, USA
- Department of Neurology, University of Maryland School of Medicine, MA, USA
| | - Muhammad Saleem Khan
- Imperial College Cerebrovascular Research Unit (ICCRU), Imperial College London, London, UK
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Anna Helgadottir
- Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Sefanja Achterberg
- Department of Neurology and Neurosurgery, Utrecht Stroke Center, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, Netherlands
| | - Israel Fernandez-Cadenas
- Neurovascular Research Laboratory, Neurology and Medicine Departments, Universitat Autònoma de Barcelona and Institute of Research Vall d'Hebrón Hospital, Barcelona, Spain
| | | | - Reinhold Schmidt
- Department of Neurology, Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Matthew Walters
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Wei-Min Chen
- deCODE Genetics, Reykjavik, Iceland
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | | | | | - Weang Kee Ho
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joanna Pera
- Department of Neurology, Jagiellonian University, Krakow, Poland
| | - Robin Lemmens
- Laboratory of Neurobiology, Vesalius Research Center, VIB, Leuven, Belgium
- Experimental Neurology and Leuven Research Institute for Neurodegenerative Diseases (LIND), University of Leuven (KU Leuven), Leuven, Belgium
- Department of Neurology, University Hospital Leuven, Leuven, Belgium
| | - Bo Norrving
- Department of Clinical Sciences Lund, Neurology, Lund University, and Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Peter Higgins
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Marianne Benn
- Department of Clinical Biochemistry and The Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, and Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michele Sale
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Virginia, Charlottesville, VA, USA
| | | | - Alexander S F Doney
- Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Astrid M Vicente
- Departamento Promoção da Saúde e Doenças Crónicas, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisbon, Portugal
| | - Hossein Delavaran
- Department of Clinical Sciences Lund, Neurology, Lund University, and Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Ale Algra
- Department of Neurology and Neurosurgery, Utrecht Stroke Center, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Gail Davies
- Department of Psychology, and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Sofia A Oliveira
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | - Colin N A Palmer
- Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Ian Deary
- Department of Psychology, and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Helena Schmidt
- Institute of Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria
| | | | - Joan Montaner
- Neurovascular Research Laboratory, Neurology and Medicine Departments, Universitat Autònoma de Barcelona and Institute of Research Vall d'Hebrón Hospital, Barcelona, Spain
| | - Cara Carty
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Paul I W de Bakker
- Department of Medical Genetics and Department of Epidemiology, University Medical Centre Utrecht, Utrecht, Netherlands
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Konstantinos Kostulas
- Department of Neurology, Karolinska Institutet at Karolinska University Hospital, Huddinge, Sweden
| | - Jose M Ferro
- Serviço de Neurologia, Centro de Estudos Egas Moniz, Hospital de Santa Maria, Lisbon, Portugal
| | - Natalie R van Zuydam
- Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | | | - Børge G Nordestgaard
- Department of Clinical Biochemistry and The Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, and Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- The Copenhagen City Heart Study, Bispebjerg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Arne Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, and Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Vincent Thijs
- Laboratory of Neurobiology, Vesalius Research Center, VIB, Leuven, Belgium
- Experimental Neurology and Leuven Research Institute for Neurodegenerative Diseases (LIND), University of Leuven (KU Leuven), Leuven, Belgium
- Department of Neurology, University Hospital Leuven, Leuven, Belgium
| | - Agnieszka Slowik
- Department of Neurology, Jagiellonian University, Krakow, Poland
| | - Danish Saleheen
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Non-Communicable Diseases, Karachi, Pakistan
- Department of Medicine, University of Pennsylvania, PA, USA
| | - Guillaume Paré
- Department of Pathology & Molecular Medicine and Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | | | - The Australian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2 (WTCCC2)
- Stroke and Dementia Research Centre, St George's University of London, London, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Centrw for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, and Center for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, NSW, Australia
- Division of Clinical Neurosciences and Insititute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
- University of Maryland School of Medicine, Department of Medicine, Baltimore, MD, USA
- University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Department of Neurology and Department of Radiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, Netherlands
- Institute for Stroke and Dementia Research, Klinikum der Universitát München, Ludwig-Maximilians-Universität, and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Imperial College Cerebrovascular Research Unit (ICCRU), Imperial College London, London, UK
- Department of Cereberovascular Disease, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Neurologico Carlo Besta, Milan, Italy
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Science, University of Virginia, Charlottesville, VA, USA
- Department of Neurology, Veterans Affairs Medical Center, Baltimore, MA, USA
- Department of Neurology, University of Maryland School of Medicine, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Neurology and Neurosurgery, Utrecht Stroke Center, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, Netherlands
- Neurovascular Research Laboratory, Neurology and Medicine Departments, Universitat Autònoma de Barcelona and Institute of Research Vall d'Hebrón Hospital, Barcelona, Spain
- Laboratory of Experimental Neurology, Brussels, Belgium
- Department of Neurology, Division of Neurogeriatrics, Medical University Graz, Graz, Austria
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Neurology, University of Münster, Münster, Germany
- National University of Ireland Galway, Galway, Ireland
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Neurology, Jagiellonian University, Krakow, Poland
- Laboratory of Neurobiology, Vesalius Research Center, VIB, Leuven, Belgium
- Experimental Neurology and Leuven Research Institute for Neurodegenerative Diseases (LIND), University of Leuven (KU Leuven), Leuven, Belgium
- Department of Neurology, University Hospital Leuven, Leuven, Belgium
- Department of Clinical Sciences Lund, Neurology, Lund University, and Department of Neurology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Biochemistry and The Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, and Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Virginia, Charlottesville, VA, USA
- Institute for Experimental Medicine, University of Kiel, Germany
- Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
- Departamento Promoção da Saúde e Doenças Crónicas, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisbon, Portugal
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Department of Psychology, and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
- Institute of Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria
- Department of Medical Genetics and Department of Epidemiology, University Medical Centre Utrecht, Utrecht, Netherlands
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Karolinska Institutet at Karolinska University Hospital, Huddinge, Sweden
- Serviço de Neurologia, Centro de Estudos Egas Moniz, Hospital de Santa Maria, Lisbon, Portugal
- Landspitali, University Hospital, Reykjavik, Iceland
- The Copenhagen City Heart Study, Bispebjerg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
- Centre for Non-Communicable Diseases, Karachi, Pakistan
- Department of Medicine, University of Pennsylvania, PA, USA
- Department of Pathology & Molecular Medicine and Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- University of Mississippi Medical Center, Jackson, MS, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Centre for Translational Neuroscience and Mental Health Research, University of Newcastle, and Hunter Medical Research Institute, New Lambton, NSW, Australia
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Department of Medicine, and Department of Health Services, University of Washington, and Group Health Research Institute, Group Health Seattle, WA, USA
- Stroke Prevention Research Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, Netherlands
| | | | - Braxton D Mitchell
- University of Maryland School of Medicine, Department of Medicine, Baltimore, MD, USA
| | - Karen Furie
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
| | - Christopher Levi
- Centre for Translational Neuroscience and Mental Health Research, University of Newcastle, and Hunter Medical Research Institute, New Lambton, NSW, Australia
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Andreas Gschwendtner
- Institute for Stroke and Dementia Research, Klinikum der Universitát München, Ludwig-Maximilians-Universität, and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Giorgio B Boncoraglio
- Department of Cereberovascular Disease, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Neurologico Carlo Besta, Milan, Italy
| | - Pankaj Sharma
- Imperial College Cerebrovascular Research Unit (ICCRU), Imperial College London, London, UK
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Bruce M Psaty
- Department of Epidemiology, Department of Medicine, and Department of Health Services, University of Washington, and Group Health Research Institute, Group Health Seattle, WA, USA
| | - Peter M Rothwell
- Stroke Prevention Research Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Jonathan Rosand
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- University of Mississippi Medical Center, Jackson, MS, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
| | | | - Kari Stefansson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universitát München, Ludwig-Maximilians-Universität, and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Hugh S Markus
- Stroke and Dementia Research Centre, St George's University of London, London, UK
| | - on behalf of the International Stroke Genetics Consortium
- Stroke and Dementia Research Centre, St George's University of London, London, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford, UK
- Centrw for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, and Center for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, NSW, Australia
- Division of Clinical Neurosciences and Insititute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK
- University of Maryland School of Medicine, Department of Medicine, Baltimore, MD, USA
- University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Department of Neurology and Department of Radiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
- Netherlands Consortium for Healthy Ageing, Leiden, Netherlands
- Institute for Stroke and Dementia Research, Klinikum der Universitát München, Ludwig-Maximilians-Universität, and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Imperial College Cerebrovascular Research Unit (ICCRU), Imperial College London, London, UK
- Department of Cereberovascular Disease, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Neurologico Carlo Besta, Milan, Italy
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Science, University of Virginia, Charlottesville, VA, USA
- Department of Neurology, Veterans Affairs Medical Center, Baltimore, MA, USA
- Department of Neurology, University of Maryland School of Medicine, MA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Neurology and Neurosurgery, Utrecht Stroke Center, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, Netherlands
- Neurovascular Research Laboratory, Neurology and Medicine Departments, Universitat Autònoma de Barcelona and Institute of Research Vall d'Hebrón Hospital, Barcelona, Spain
- Laboratory of Experimental Neurology, Brussels, Belgium
- Department of Neurology, Division of Neurogeriatrics, Medical University Graz, Graz, Austria
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Neurology, University of Münster, Münster, Germany
- National University of Ireland Galway, Galway, Ireland
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Neurology, Jagiellonian University, Krakow, Poland
- Laboratory of Neurobiology, Vesalius Research Center, VIB, Leuven, Belgium
- Experimental Neurology and Leuven Research Institute for Neurodegenerative Diseases (LIND), University of Leuven (KU Leuven), Leuven, Belgium
- Department of Neurology, University Hospital Leuven, Leuven, Belgium
- Department of Clinical Sciences Lund, Neurology, Lund University, and Department of Neurology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Biochemistry and The Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, and Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Division of Cardiovascular Medicine, Department of Internal Medicine, University of Virginia, Charlottesville, VA, USA
- Institute for Experimental Medicine, University of Kiel, Germany
- Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
- Departamento Promoção da Saúde e Doenças Crónicas, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisbon, Portugal
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
- Department of Psychology, and Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
- Institute of Molecular Biology and Biochemistry, Medical University Graz, Graz, Austria
- Department of Medical Genetics and Department of Epidemiology, University Medical Centre Utrecht, Utrecht, Netherlands
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Karolinska Institutet at Karolinska University Hospital, Huddinge, Sweden
- Serviço de Neurologia, Centro de Estudos Egas Moniz, Hospital de Santa Maria, Lisbon, Portugal
- Landspitali, University Hospital, Reykjavik, Iceland
- The Copenhagen City Heart Study, Bispebjerg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
- Centre for Non-Communicable Diseases, Karachi, Pakistan
- Department of Medicine, University of Pennsylvania, PA, USA
- Department of Pathology & Molecular Medicine and Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, ON, Canada
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- University of Mississippi Medical Center, Jackson, MS, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Centre for Translational Neuroscience and Mental Health Research, University of Newcastle, and Hunter Medical Research Institute, New Lambton, NSW, Australia
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Department of Medicine, and Department of Health Services, University of Washington, and Group Health Research Institute, Group Health Seattle, WA, USA
- Stroke Prevention Research Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
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3607
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Liu CT, Ng MCY, Rybin D, Adeyemo A, Bielinski SJ, Boerwinkle E, Borecki I, Cade B, Chen YDI, Djousse L, Fornage M, Goodarzi MO, Grant SFA, Guo X, Harris T, Kabagambe E, Kizer JR, Liu Y, Lunetta KL, Mukamal K, Nettleton JA, Pankow JS, Patel SR, Ramos E, Rasmussen-Torvik L, Rich SS, Rotimi CN, Sarpong D, Shriner D, Sims M, Zmuda JM, Redline S, Kao WH, Siscovick D, Florez JC, Rotter JI, Dupuis J, Wilson JG, Bowden DW, Meigs JB. Transferability and fine-mapping of glucose and insulin quantitative trait loci across populations: CARe, the Candidate Gene Association Resource. Diabetologia 2012; 55:2970-84. [PMID: 22893027 PMCID: PMC3804308 DOI: 10.1007/s00125-012-2656-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2012] [Accepted: 06/14/2012] [Indexed: 01/22/2023]
Abstract
AIMS/HYPOTHESIS Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European ancestry (EuA) populations in 5,984 non-diabetic AfAs. METHODS We meta-analysed SNP associations with fasting glucose (FG) or insulin (FI) in AfAs from five cohorts in the Candidate Gene Association Resource. We: (1) calculated allele frequency differences, variations in linkage disequilibrium (LD), fixation indices (F(st)s) and integrated haplotype scores (iHSs); (2) tested EuA SNPs in AfAs; and (3) interrogated within ± 250 kb around each EuA SNP in AfAs. RESULTS Allele frequency differences ranged from 0.6% to 54%. F(st) exceeded 0.15 at 6/16 loci, indicating modest population differentiation. All iHSs were <2, suggesting no recent positive selection. For 18 SNPs, all directions of effect were the same and 95% CIs of association overlapped when comparing EuA with AfA. For 17 of 18 loci, at least one SNP was nominally associated with FG in AfAs. Four loci were significantly associated with FG (GCK, p = 5.8 × 10(-8); MTNR1B, p = 8.5 × 10(-9); and FADS1, p = 2.2 × 10(-4)) or FI (GCKR, p = 5.9 × 10(-4)). At GCK and MTNR1B the EuA and AfA SNPs represented the same signal, while at FADS1, and GCKR, the EuA and best AfA SNPs were weakly correlated (r(2) <0.2), suggesting allelic heterogeneity for association with FG at these loci. CONCLUSIONS/INTERPRETATION Few glycaemic SNPs showed strict evidence of transferability from EuA to AfAs. Four loci were significantly associated in both AfAs and those with EuA after accounting for varying LD across ancestral groups, with new signals emerging to aid fine-mapping.
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Affiliation(s)
- C.-T. Liu
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M. C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA
| | - D. Rybin
- Boston University Data Coordinating Center, Boston, MA, USA
| | - A. Adeyemo
- National Human Genome Research Institute, Bethesda, MD, USA
| | | | - E. Boerwinkle
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | - I. Borecki
- Washington University, St Louis, MO, USA
| | - B. Cade
- Brigham and Women's Hospital, Boston, MA, USA
| | | | - L. Djousse
- Brigham and Women's Hospital, Boston, MA, USA; Department
of Medicine, Harvard Medical School, Boston, MA, USA; Boston VA Healthcare
System, Boston, MA, USA
| | - M. Fornage
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | | | - S. F. A. Grant
- Children's Hospital of Philadelphia, Philadelphia, PA,
USA
| | - X. Guo
- Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - T. Harris
- National Institute on Aging, Bethesda, MD, USA
| | | | | | - Y. Liu
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA; Department of Epidemiology and Prevention, Wake Forest University,
Winston-Salem, North Carolina, USA
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA; National Heart, Lung, and Blood Institute'
Framingham Heart Study, Framingham, MA, USA
| | - K. Mukamal
- Department of Medicine, Harvard Medical School, Boston, MA,
USA
| | - J. A. Nettleton
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | | | - S. R. Patel
- Brigham and Women's Hospital, Boston, MA, USA
| | - E. Ramos
- National Human Genome Research Institute, Bethesda, MD, USA
| | | | - S. S. Rich
- University of Virginia, Charlottesville, VA, USA
| | - C. N. Rotimi
- National Human Genome Research Institute, Bethesda, MD, USA
| | - D. Sarpong
- Jackson State University, Jackson, MS, USA
| | - D. Shriner
- National Human Genome Research Institute, Bethesda, MD, USA
| | - M. Sims
- University of Mississippi Medical Center, Jackson, MS, USA
| | - J. M. Zmuda
- University of Pittsburgh, Graduate School of Public Health,
Pittsburgh, PA, USA
| | - S. Redline
- Brigham and Women's Hospital, Boston, MA, USA
| | - W. H. Kao
- Johns Hopkins University, Baltimore, MD, USA
| | | | - J. C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA, USA;
Diabetes Unit and Center for Human Genetic Research, Massachusetts General
Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad
Institute, Cambridge, MA, USA
| | - J. I. Rotter
- Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - J. Dupuis
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA; National Heart, Lung, and Blood Institute's
Framingham Heart Study, Framingham, MA, USA
| | - J. G. Wilson
- University of Mississippi Medical Center, Jackson, MS, USA
| | - D. W. Bowden
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA; Departments of Biochemistry and Internal Medicine, Wake Forest
University School of Medicine, Winston-Salem, NC, USA
| | - J. B. Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, USA;
General Medicine Division, Massachusetts General Hospital, 50 Staniford
Street, 9th Flr, Boston, MA, USA
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3608
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Genetic association analysis of complex diseases incorporating intermediate phenotype information. PLoS One 2012; 7:e46612. [PMID: 23094028 PMCID: PMC3477105 DOI: 10.1371/journal.pone.0046612] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2012] [Accepted: 09/05/2012] [Indexed: 11/19/2022] Open
Abstract
Genetic researchers often collect disease related quantitative traits in addition to disease status because they are interested in understanding the pathophysiology of disease processes. In genome-wide association (GWA) studies, these quantitative phenotypes may be relevant to disease development and serve as intermediate phenotypes or they could be behavioral or other risk factors that predict disease risk. Statistical tests combining both disease status and quantitative risk factors should be more powerful than case-control studies, as the former incorporates more information about the disease. In this paper, we proposed a modified inverse-variance weighted meta-analysis method to combine disease status and quantitative intermediate phenotype information. The simulation results showed that when an intermediate phenotype was available, the inverse-variance weighted method had more power than did a case-control study of complex diseases, especially in identifying susceptibility loci having minor effects. We further applied this modified meta-analysis to a study of imputed lung cancer genotypes with smoking data in 1154 cases and 1137 matched controls. The most significant SNPs came from the CHRNA3-CHRNA5-CHRNB4 region on chromosome 15q24–25.1, which has been replicated in many other studies. Our results confirm that this CHRNA region is associated with both lung cancer development and smoking behavior. We also detected three significant SNPs—rs1800469, rs1982072, and rs2241714—in the promoter region of the TGFB1 gene on chromosome 19 (p = 1.46×10−5, 1.18×10−5, and 6.57×10−6, respectively). The SNP rs1800469 is reported to be associated with chronic obstructive pulmonary disease and lung cancer in cigarette smokers. The present study is the first GWA study to replicate this result. Signals in the 3q26 region were also identified in the meta-analysis. We demonstrate the intermediate phenotype can potentially enhance the power of complex disease association analysis and the modified meta-analysis method is robust to incorporate intermediate phenotype or other quantitative risk factor in the analysis.
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3609
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Do R, Kathiresan S, Abecasis GR. Exome sequencing and complex disease: practical aspects of rare variant association studies. Hum Mol Genet 2012; 21:R1-9. [PMID: 22983955 PMCID: PMC3459641 DOI: 10.1093/hmg/dds387] [Citation(s) in RCA: 105] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Accepted: 09/07/2012] [Indexed: 11/13/2022] Open
Abstract
Genetic association and linkage studies can provide insights into complex disease biology, guiding the development of new diagnostic and therapeutic strategies. Over the past decade, genetic association studies have largely focused on common, easy to measure genetic variants shared between many individuals. These common variants typically have subtle functional consequence and translating the resulting association signals into biological insights can be challenging. In the last few years, exome sequencing has emerged as a cost-effective strategy for extending these studies to include rare coding variants, which often have more marked functional consequences. Here, we provide practical guidance in the design and analysis of complex trait association studies focused on rare, coding variants.
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Affiliation(s)
- Ron Do
- Center for Human Genetic Research and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA and
| | - Sekar Kathiresan
- Center for Human Genetic Research and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA and
| | - Gonçalo R. Abecasis
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
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3610
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Yang J, Loos RJF, Powell JE, Medland SE, Speliotes EK, Chasman DI, Rose LM, Thorleifsson G, Steinthorsdottir V, Mägi R, Waite L, Smith AV, Yerges-Armstrong LM, Monda KL, Hadley D, Mahajan A, Li G, Kapur K, Vitart V, Huffman JE, Wang SR, Palmer C, Esko T, Fischer K, Zhao JH, Demirkan A, Isaacs A, Feitosa MF, Luan J, Heard-Costa NL, White C, Jackson AU, Preuss M, Ziegler A, Eriksson J, Kutalik Z, Frau F, Nolte IM, Van Vliet-Ostaptchouk JV, Hottenga JJ, Jacobs KB, Verweij N, Goel A, Medina-Gomez C, Estrada K, Bragg-Gresham JL, Sanna S, Sidore C, Tyrer J, Teumer A, Prokopenko I, Mangino M, Lindgren CM, Assimes TL, Shuldiner AR, Hui J, Beilby JP, McArdle WL, Hall P, Haritunians T, Zgaga L, Kolcic I, Polasek O, Zemunik T, Oostra BA, Junttila MJ, Grönberg H, Schreiber S, Peters A, Hicks AA, Stephens J, Foad NS, Laitinen J, Pouta A, Kaakinen M, Willemsen G, Vink JM, Wild SH, Navis G, Asselbergs FW, Homuth G, John U, Iribarren C, Harris T, Launer L, Gudnason V, O'Connell JR, Boerwinkle E, Cadby G, Palmer LJ, James AL, Musk AW, Ingelsson E, Psaty BM, Beckmann JS, Waeber G, Vollenweider P, Hayward C, Wright AF, Rudan I, et alYang J, Loos RJF, Powell JE, Medland SE, Speliotes EK, Chasman DI, Rose LM, Thorleifsson G, Steinthorsdottir V, Mägi R, Waite L, Smith AV, Yerges-Armstrong LM, Monda KL, Hadley D, Mahajan A, Li G, Kapur K, Vitart V, Huffman JE, Wang SR, Palmer C, Esko T, Fischer K, Zhao JH, Demirkan A, Isaacs A, Feitosa MF, Luan J, Heard-Costa NL, White C, Jackson AU, Preuss M, Ziegler A, Eriksson J, Kutalik Z, Frau F, Nolte IM, Van Vliet-Ostaptchouk JV, Hottenga JJ, Jacobs KB, Verweij N, Goel A, Medina-Gomez C, Estrada K, Bragg-Gresham JL, Sanna S, Sidore C, Tyrer J, Teumer A, Prokopenko I, Mangino M, Lindgren CM, Assimes TL, Shuldiner AR, Hui J, Beilby JP, McArdle WL, Hall P, Haritunians T, Zgaga L, Kolcic I, Polasek O, Zemunik T, Oostra BA, Junttila MJ, Grönberg H, Schreiber S, Peters A, Hicks AA, Stephens J, Foad NS, Laitinen J, Pouta A, Kaakinen M, Willemsen G, Vink JM, Wild SH, Navis G, Asselbergs FW, Homuth G, John U, Iribarren C, Harris T, Launer L, Gudnason V, O'Connell JR, Boerwinkle E, Cadby G, Palmer LJ, James AL, Musk AW, Ingelsson E, Psaty BM, Beckmann JS, Waeber G, Vollenweider P, Hayward C, Wright AF, Rudan I, Groop LC, Metspalu A, Khaw KT, van Duijn CM, Borecki IB, Province MA, Wareham NJ, Tardif JC, Huikuri HV, Cupples LA, Atwood LD, Fox CS, Boehnke M, Collins FS, Mohlke KL, Erdmann J, Schunkert H, Hengstenberg C, Stark K, Lorentzon M, Ohlsson C, Cusi D, Staessen JA, Van der Klauw MM, Pramstaller PP, Kathiresan S, Jolley JD, Ripatti S, Jarvelin MR, de Geus EJC, Boomsma DI, Penninx B, Wilson JF, Campbell H, Chanock SJ, van der Harst P, Hamsten A, Watkins H, Hofman A, Witteman JC, Zillikens MC, Uitterlinden AG, Rivadeneira F, Zillikens MC, Kiemeney LA, Vermeulen SH, Abecasis GR, Schlessinger D, Schipf S, Stumvoll M, Tönjes A, Spector TD, North KE, Lettre G, McCarthy MI, Berndt SI, Heath AC, Madden PAF, Nyholt DR, Montgomery GW, Martin NG, McKnight B, Strachan DP, Hill WG, Snieder H, Ridker PM, Thorsteinsdottir U, Stefansson K, Frayling TM, Hirschhorn JN, Goddard ME, Visscher PM. FTO genotype is associated with phenotypic variability of body mass index. Nature 2012; 490:267-72. [PMID: 22982992 PMCID: PMC3564953 DOI: 10.1038/nature11401] [Show More Authors] [Citation(s) in RCA: 326] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2012] [Accepted: 07/06/2012] [Indexed: 12/21/2022]
Abstract
There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
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Affiliation(s)
- Jian Yang
- University of Queensland Diamantina Institute, The University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4102, Australia
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3611
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Mishra A, Yazar S, Hewitt AW, Mountain JA, Ang W, Pennell CE, Martin NG, Montgomery GW, Hammond CJ, Young TL, Macgregor S, Mackey DA. Genetic variants near PDGFRA are associated with corneal curvature in Australians. Invest Ophthalmol Vis Sci 2012; 53:7131-6. [PMID: 22969067 DOI: 10.1167/iovs.12-10489] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
PURPOSE Irregularity in the corneal curvature (CC) is highly associated with various eye disorders such as keratoconus and myopia. The sample had limited power to find genomewide significant (5 × 10(-8)) hits but good power for replication. Thus, an attempt was made to test whether alleles in the FRAP1 and PDGFRA genes, recently found to be associated with CC in Asian populations, also influence CC in Australians of North European ancestry. Results of initial genomewide association studies (GWAS) for CC in Australians were also reported. METHODS Two population-based cohorts of 1788 Australian twins and their families, as well as 1013 individuals from a birth cohort from Western Australia, were genotyped using genomewide arrays. Following separate individual analysis and quality control, the results from each cohort underwent meta-analysis. RESULTS Meta-analysis revealed significant replication of association between rs2114039 and corneal curvature (P = 0.0045). The SNP rs2114039 near PDGFRA has been previously implicated in Asians. No SNP at the FRAP1 locus was found to be associated in our Australian samples. No SNP surpassed the genomewide significance threshold of 5 × 10(-8). The SNP with strongest association was rs2444240 (P = 3.658 × 10(-7)), which is 31 kb upstream to the TRIM29 gene. CONCLUSIONS A significant role of the PDGFRA gene in determining corneal curvature in the Australian population was confirmed in this study, also highlighting the putative association of the TRIM29 locus with CC.
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Affiliation(s)
- Aniket Mishra
- Queensland Institute of Medical Research, Brisbane, Australia.
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3612
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Njiaju UO, Gamazon ER, Gorsic LK, Delaney SM, Wheeler HE, Im HK, Dolan ME. Whole-genome studies identify solute carrier transporters in cellular susceptibility to paclitaxel. Pharmacogenet Genomics 2012; 22:498-507. [PMID: 22437668 DOI: 10.1097/fpc.0b013e328352f436] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE The clinical use of paclitaxel is limited by variable responses and the potential for significant toxicity. To date, studies of associations between variants in candidate genes and paclitaxel effects have yielded conflicting results. We aimed to evaluate the relationships between global gene expression and paclitaxel sensitivity. METHODS We utilized well-genotyped lymphoblastoid cell lines derived from the International HapMap Project to evaluate the relationships between cellular susceptibility to paclitaxel and global gene expression. Cells were exposed to varying concentrations of paclitaxel to evaluate paclitaxel-induced cytotoxicity and apoptosis. Among the top genes, we identified solute carrier (SLC) genes associated with paclitaxel sensitivity and narrowed down the list to those that had single nucleotide polymorphisms associated with both the expression level of the SLC gene and also with paclitaxel sensitivity. We performed an independent validation in an independent set of cell lines and also conducted functional studies using RNA interference. RESULTS Of all genes associated with paclitaxel-induced cytotoxicity at P less than 0.05 (1713 genes), there was a significant enrichment in SLC genes (31 genes). A subset of SLC genes, namely SLC31A2, SLC43A1, SLC35A5, and SLC41A2, was associated with paclitaxel sensitivity and had regulating single nucleotide polymorphisms that were also associated with paclitaxel-induced cytotoxicity. Multivariate modeling demonstrated that those four SLC genes together explained 20% of the observed variability in paclitaxel susceptibility. Using RNA interference, we demonstrated increased paclitaxel susceptibility with knockdown of three SLC genes, SLC31A2, SLC35A5, and SLC41A2. CONCLUSION Our findings are novel and lend further support to the role of transporters, specifically solute carriers, in mediating cellular susceptibility to paclitaxel.
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Affiliation(s)
- Uchenna O Njiaju
- Section of Hematology/Oncology, Department of Medicine, University of Chicago Comprehensive Cancer, Chicago, Illinois, USA
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3613
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Manjarrez-Orduño N, Marasco E, Chung SA, Katz MS, Kiridly JF, Simpfendorfer KR, Freudenberg J, Ballard DH, Nashi E, Hopkins TJ, Cunninghame Graham DS, Lee AT, Coenen MJH, Franke B, Swinkels DW, Graham RR, Kimberly RP, Gaffney PM, Vyse TJ, Behrens TW, Criswell LA, Diamond B, Gregersen PK. CSK regulatory polymorphism is associated with systemic lupus erythematosus and influences B-cell signaling and activation. Nat Genet 2012; 44:1227-30. [PMID: 23042117 PMCID: PMC3715052 DOI: 10.1038/ng.2439] [Citation(s) in RCA: 90] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2012] [Accepted: 09/11/2012] [Indexed: 12/11/2022]
Abstract
C-src tyrosine kinase, Csk, physically interacts with the intracellular phosphatase Lyp (PTPN22) and can modify the activation state of downstream Src kinases, such as Lyn, in lymphocytes. We identified an association of Csk with systemic lupus erythematosus (SLE) and refined its location to an intronic polymorphism rs34933034 (OR 1.32, p = 1.04 × 10−9). The risk allele is associated with increased CSK expression and augments inhibitory phosphorylation of Lyn. In carriers of the risk allele, B cell receptor (BCR)-mediated activation of mature B cells, as well as plasma IgM, are increased. Moreover, the fraction of transitional B cells is doubled in the cord blood of carriers of the risk allele compared to non-risk haplotypes due to an expansion of the late transitional cells, a stage targeted by selection mechanisms. This suggests that the Lyp-Csk complex increases susceptibility to lupus at multiple maturation and activation points of B cells.
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Affiliation(s)
- Nataly Manjarrez-Orduño
- Center for Autoimmune and Musculoskeletal Disorders, The Feinstein Institute for Medical Research, North Shore-Long Island Jewish, Manhasset, New York, USA
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3614
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Wei P, Tang H, Li D. Insights into pancreatic cancer etiology from pathway analysis of genome-wide association study data. PLoS One 2012; 7:e46887. [PMID: 23056513 PMCID: PMC3464266 DOI: 10.1371/journal.pone.0046887] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2012] [Accepted: 09/06/2012] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS) data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry. METHODS Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM) test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01) using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). RESULTS Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025) and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002), and the olfactory transduction pathway (P = 0.0001). LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10(-5)): ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways) to be the most significant pathway for pancreatic cancer risk in this study population. CONCLUSION These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.
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Affiliation(s)
- Peng Wei
- Division of Biostatistics and Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Hongwei Tang
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America
- * E-mail:
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3615
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Wilk JB, Shrine NRG, Loehr LR, Zhao JH, Manichaikul A, Lopez LM, Smith AV, Heckbert SR, Smolonska J, Tang W, Loth DW, Curjuric I, Hui J, Cho MH, Latourelle JC, Henry AP, Aldrich M, Bakke P, Beaty TH, Bentley AR, Borecki IB, Brusselle GG, Burkart KM, Chen TH, Couper D, Crapo JD, Davies G, Dupuis J, Franceschini N, Gulsvik A, Hancock DB, Harris TB, Hofman A, Imboden M, James AL, Khaw KT, Lahousse L, Launer LJ, Litonjua A, Liu Y, Lohman KK, Lomas DA, Lumley T, Marciante KD, McArdle WL, Meibohm B, Morrison AC, Musk AW, Myers RH, North KE, Postma DS, Psaty BM, Rich SS, Rivadeneira F, Rochat T, Rotter JI, Soler Artigas M, Starr JM, Uitterlinden AG, Wareham NJ, Wijmenga C, Zanen P, Province MA, Silverman EK, Deary IJ, Palmer LJ, Cassano PA, Gudnason V, Barr RG, Loos RJF, Strachan DP, London SJ, Boezen HM, Probst-Hensch N, Gharib SA, Hall IP, O'Connor GT, Tobin MD, Stricker BH. Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction. Am J Respir Crit Care Med 2012; 186:622-32. [PMID: 22837378 PMCID: PMC3480517 DOI: 10.1164/rccm.201202-0366oc] [Citation(s) in RCA: 142] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Accepted: 07/04/2012] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Genome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known. OBJECTIVES Perform meta-analyses of GWAS for airflow obstruction, a key pathophysiologic characteristic of COPD assessed by spirometry, in population-based cohorts examining all participants, ever smokers, never smokers, asthma-free participants, and more severe cases. METHODS Fifteen cohorts were studied for discovery (3,368 affected; 29,507 unaffected), and a population-based family study and a meta-analysis of case-control studies were used for replication and regional follow-up (3,837 cases; 4,479 control subjects). Airflow obstruction was defined as FEV(1) and its ratio to FVC (FEV(1)/FVC) both less than their respective lower limits of normal as determined by published reference equations. MEASUREMENTS AND MAIN RESULTS The discovery meta-analyses identified one region on chromosome 15q25.1 meeting genome-wide significance in ever smokers that includes AGPHD1, IREB2, and CHRNA5/CHRNA3 genes. The region was also modestly associated among never smokers. Gene expression studies confirmed the presence of CHRNA5/3 in lung, airway smooth muscle, and bronchial epithelial cells. A single-nucleotide polymorphism in HTR4, a gene previously related to FEV(1)/FVC, achieved genome-wide statistical significance in combined meta-analysis. Top single-nucleotide polymorphisms in ADAM19, RARB, PPAP2B, and ADAMTS19 were nominally replicated in the COPD meta-analysis. CONCLUSIONS These results suggest an important role for the CHRNA5/3 region as a genetic risk factor for airflow obstruction that may be independent of smoking and implicate the HTR4 gene in the etiology of airflow obstruction.
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Affiliation(s)
- Jemma B Wilk
- Division of Aging, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA 02120, USA.
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3616
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Genome-wide association studies of asthma in population-based cohorts confirm known and suggested loci and identify an additional association near HLA. PLoS One 2012; 7:e44008. [PMID: 23028483 PMCID: PMC3461045 DOI: 10.1371/journal.pone.0044008] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2012] [Accepted: 07/27/2012] [Indexed: 01/03/2023] Open
Abstract
RATIONALE Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. OBJECTIVES To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. METHODS The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5 x 10(-8)) and three variants reported as suggestive (P<5× 10(-7)). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. MAIN RESULTS We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4 × 10(-9)). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (P(Stage1+Stage2) = 1.1x10(-9)), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (P(Stage1+Stage2) = 1.1x10(-8)), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. CONCLUSIONS Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.
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3617
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Graff M, North KE, Mohlke KL, Lange LA, Luo J, Harris KM, Young KL, Richardson AS, Lange EM, Gordon-Larsen P. Estimation of genetic effects on BMI during adolescence in an ethnically diverse cohort: The National Longitudinal Study of Adolescent Health. Nutr Diabetes 2012; 2:e47. [PMID: 23168566 PMCID: PMC3461356 DOI: 10.1038/nutd.2012.20] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Accepted: 08/18/2012] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE The contribution of genetic variants to body mass index (BMI) during adolescence across multiethnic samples is largely unknown. We selected genetic loci associated with BMI or obesity in European-descent samples and examined them in a multiethnic adolescent sample. DESIGN AND SAMPLE In 5103 European American (EA), 1748 African American (AfA), 1304 Hispanic American (HA) and 439 Asian American (AsA) participants of the National Longitudinal Study of Adolescent Health (Add Health; ages 12-21 years, 47.5% male), we assessed the association between 41 established obesity-related single-nucleotide polymorphisms (SNPs) with BMI using additive genetic models, stratified by race/ethnicity, and in a pooled meta-analysis sample. We also compared the magnitude of effect for BMI-SNP associations in EA and AfA adolescents to comparable effect estimates from 11 861 EA and AfA adults in the Atherosclerosis Risk in Communities study (ages 45-64 years, 43.2% male). RESULTS Thirty-five of 41 BMI-SNP associations were directionally consistent with published studies in European populations, 18 achieved nominal significance (P<0.05; effect sizes from 0.19 to 0.71 kg m(-2) increase in BMI per effect allele), while 4 (FTO, TMEM18, TFAP2B, MC4R) remained significant after Bonferroni correction (P<0.0015). Of 41 BMI-SNP associations in AfA, HA and AsA adolescents, nine, three and five, respectively, were directionally consistent and nominally significant. In the pooled meta-analysis, 36 of 41 effect estimates were directionally consistent and 21 of 36 were nominally significant. In EA adolescents, BMI effect estimates were larger (P<0.05) for variants near TMEM18, PTER and MC4R and smaller for variants near MTIF3 and NRXN3 compared with EA adults. CONCLUSION Our findings suggest that obesity susceptibility loci may have a comparatively stronger role during adolescence than during adulthood, with variation across race/ethnic subpopulation.
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Affiliation(s)
- M Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - K E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - K L Mohlke
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - L A Lange
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - J Luo
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - K M Harris
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Sociology, University of North Carolina, Chapel Hill, NC, USA
| | - K L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - A S Richardson
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
| | - E M Lange
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - P Gordon-Larsen
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
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3618
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Carey RM, Schoeffel CD, Gildea JJ, Jones JE, McGrath HE, Gordon LN, Park MJ, Sobota RS, Underwood PC, Williams J, Sun B, Raby B, Lasky-Su J, Hopkins PN, Adler GK, Williams SM, Jose PA, Felder RA. Salt sensitivity of blood pressure is associated with polymorphisms in the sodium-bicarbonate cotransporter. Hypertension 2012; 60:1359-66. [PMID: 22987918 DOI: 10.1161/hypertensionaha.112.196071] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Previous studies have demonstrated that single nucleotide polymorphisms (SNPs) of the sodium-bicarbonate co-transporter gene (SLC4A5) are associated with hypertension. We tested the hypothesis that SNPs in SLC4A5 are associated with salt sensitivity of blood pressure in 185 whites consuming an isocaloric constant diet with a randomized order of 7 days of low Na(+) (10 mmol/d) and 7 days of high Na(+) (300 mmol/d) intake. Salt sensitivity was defined as a ≥ 7-mm Hg increase in mean arterial pressure during a randomized transition between high and low Na(+) diet. A total of 35 polymorphisms in 17 candidate genes were assayed, 25 of which were tested for association. Association analyses with salt sensitivity revealed 3 variants that associated with salt sensitivity, 2 in SLC4A5 (P<0.001) and 1 in GRK4 (P=0.020). Of these, 2 SNPs in SLC4A5 (rs7571842 and rs10177833) demonstrated highly significant results and large effects sizes, using logistic regression. These 2 SNPs had P values of 1.0 × 10(-4) and 3.1 × 10(-4) with odds ratios of 0.221 and 0.221 in unadjusted regression models, respectively, with the G allele at both sites conferring protection. These SNPs remained significant after adjusting for body mass index and age (P=8.9 × 10(-5) and 2.6 × 10(-4) and odds ratios 0.210 and 0.286, respectively). Furthermore, the association of these SNPs with salt sensitivity was replicated in a second hypertensive population. Meta-analysis demonstrated significant associations of both SNPs with salt sensitivity (rs7571842 [P=1.2 × 10(-5)]; rs1017783 [P=1.1 × 10(-4)]). In conclusion, SLC4A5 variants are strongly associated with salt sensitivity of blood pressure in 2 separate white populations.
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Affiliation(s)
- Robert M Carey
- Department of Medicine, University of Virginia Health System, Charlottesville, VA 22908-1414, USA.
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3619
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Yokoyama JS, Lam ET, Ruhe AL, Erdman CA, Robertson KR, Webb AA, Williams DC, Chang ML, Hytönen MK, Lohi H, Hamilton SP, Neff MW. Variation in genes related to cochlear biology is strongly associated with adult-onset deafness in border collies. PLoS Genet 2012; 8:e1002898. [PMID: 23028339 PMCID: PMC3441646 DOI: 10.1371/journal.pgen.1002898] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Accepted: 06/29/2012] [Indexed: 01/22/2023] Open
Abstract
Domestic dogs can suffer from hearing losses that can have profound impacts on working ability and quality of life. We have identified a type of adult-onset hearing loss in Border Collies that appears to have a genetic cause, with an earlier age of onset (3–5 years) than typically expected for aging dogs (8–10 years). Studying this complex trait within pure breeds of dog may greatly increase our ability to identify genomic regions associated with risk of hearing impairment in dogs and in humans. We performed a genome-wide association study (GWAS) to detect loci underlying adult-onset deafness in a sample of 20 affected and 28 control Border Collies. We identified a region on canine chromosome 6 that demonstrates extended support for association surrounding SNP Chr6.25819273 (p-value = 1.09×10−13). To further localize disease-associated variants, targeted next-generation sequencing (NGS) of one affected and two unaffected dogs was performed. Through additional validation based on targeted genotyping of additional cases (n = 23 total) and controls (n = 101 total) and an independent replication cohort of 16 cases and 265 controls, we identified variants in USP31 that were strongly associated with adult-onset deafness in Border Collies, suggesting the involvement of the NF-κB pathway. We found additional support for involvement of RBBP6, which is critical for cochlear development. These findings highlight the utility of GWAS–guided fine-mapping of genetic loci using targeted NGS to study hereditary disorders of the domestic dog that may be analogous to human disorders. The domestic dog offers a unique opportunity to study complex disorders similar to those seen in humans, but within the context of the much simpler genetic backgrounds of pure breeds, which represent closed populations. We performed a whole-genome search for genetic risk factors of adult-onset deafness in the Border Collie, a breed of herding dog that relies on acute hearing to perceive and respond to commands while working. Adult-onset deafness in Border Collies typically begins in early adulthood and is similar to age-related hearing loss in humans. This earlier onset has particular impact on the utility of working Border Collies and the livelihoods of their owners, and it appears to have a genetic cause. We identified three genetic variants that were strongly associated with adult-onset deafness in a sample of 405 Border Collies. These variants are located in two genes that have previously been linked to deafness, one involved in ear development and another that appears to mitigate tissue damage in the ear. These results provide new insight regarding genetic risk factors for age-related hearing loss in both dogs and humans.
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Affiliation(s)
- Jennifer S. Yokoyama
- Department of Psychiatry and Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Ernest T. Lam
- Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Alison L. Ruhe
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, Arizona, United States of America
- Veterinary Genetics Laboratory, University of California Davis, Davis, California, United States of America
| | - Carolyn A. Erdman
- Department of Psychiatry and Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Kathryn R. Robertson
- Veterinary Genetics Laboratory, University of California Davis, Davis, California, United States of America
| | - Aubrey A. Webb
- CullenWebb Animal Neurology and Ophthalmology Centre, Riverview, New Brunswick, Canada
- Department of Clinical Neuroscience, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - D. Colette Williams
- School of Veterinary Medicine, University of California Davis, Davis, California, United States of America
| | - Melanie L. Chang
- Department of Anthropology, University of Oregon, Eugene, Oregon, United States of America
| | - Marjo K. Hytönen
- Department of Veterinary Biosciences and Research Programs Unit, Molecular Medicine, University of Helsinki and Folkhälsan Research Center, Helsinki, Finland
| | - Hannes Lohi
- Department of Veterinary Biosciences and Research Programs Unit, Molecular Medicine, University of Helsinki and Folkhälsan Research Center, Helsinki, Finland
| | - Steven P. Hamilton
- Department of Psychiatry and Institute for Human Genetics, University of California San Francisco, San Francisco, California, United States of America
| | - Mark W. Neff
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, Arizona, United States of America
- The Van Andel Research Institute, Grand Rapids, Michigan, United States of America
- * E-mail:
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3620
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Meesters C, Leber M, Herold C, Angisch M, Mattheisen M, Drichel D, Lacour A, Becker T. Quick, "imputation-free" meta-analysis with proxy-SNPs. BMC Bioinformatics 2012; 13:231. [PMID: 22971100 PMCID: PMC3472171 DOI: 10.1186/1471-2105-13-231] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2012] [Accepted: 09/07/2012] [Indexed: 01/08/2023] Open
Abstract
Background Meta-analysis (MA) is widely used to pool genome-wide association studies (GWASes) in order to a) increase the power to detect strong or weak genotype effects or b) as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software), however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming. Results Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127. Conclusions YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy-SNPs for missing markers to avoid unnecessary power loss. MA with YAMAS can be readily conducted as YAMAS provides a generic parser for heterogeneous tabulated file formats within the GWAS field and avoids cumbersome setups. In this way, it supplements the meta-analysis process.
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3621
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Chasman DI, Fuchsberger C, Pattaro C, Teumer A, Böger CA, Endlich K, Olden M, Chen MH, Tin A, Taliun D, Li M, Gao X, Gorski M, Yang Q, Hundertmark C, Foster MC, O'Seaghdha CM, Glazer N, Isaacs A, Liu CT, Smith AV, O'Connell JR, Struchalin M, Tanaka T, Li G, Johnson AD, Gierman HJ, Feitosa MF, Hwang SJ, Atkinson EJ, Lohman K, Cornelis MC, Johansson A, Tönjes A, Dehghan A, Lambert JC, Holliday EG, Sorice R, Kutalik Z, Lehtimäki T, Esko T, Deshmukh H, Ulivi S, Chu AY, Murgia F, Trompet S, Imboden M, Coassin S, Pistis G, Harris TB, Launer LJ, Aspelund T, Eiriksdottir G, Mitchell BD, Boerwinkle E, Schmidt H, Cavalieri M, Rao M, Hu F, Demirkan A, Oostra BA, de Andrade M, Turner ST, Ding J, Andrews JS, Freedman BI, Giulianini F, Koenig W, Illig T, Meisinger C, Gieger C, Zgaga L, Zemunik T, Boban M, Minelli C, Wheeler HE, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Nöthlings U, Jacobs G, Biffar R, Ernst F, Homuth G, Kroemer HK, Nauck M, Stracke S, Völker U, Völzke H, Kovacs P, Stumvoll M, Mägi R, Hofman A, et alChasman DI, Fuchsberger C, Pattaro C, Teumer A, Böger CA, Endlich K, Olden M, Chen MH, Tin A, Taliun D, Li M, Gao X, Gorski M, Yang Q, Hundertmark C, Foster MC, O'Seaghdha CM, Glazer N, Isaacs A, Liu CT, Smith AV, O'Connell JR, Struchalin M, Tanaka T, Li G, Johnson AD, Gierman HJ, Feitosa MF, Hwang SJ, Atkinson EJ, Lohman K, Cornelis MC, Johansson A, Tönjes A, Dehghan A, Lambert JC, Holliday EG, Sorice R, Kutalik Z, Lehtimäki T, Esko T, Deshmukh H, Ulivi S, Chu AY, Murgia F, Trompet S, Imboden M, Coassin S, Pistis G, Harris TB, Launer LJ, Aspelund T, Eiriksdottir G, Mitchell BD, Boerwinkle E, Schmidt H, Cavalieri M, Rao M, Hu F, Demirkan A, Oostra BA, de Andrade M, Turner ST, Ding J, Andrews JS, Freedman BI, Giulianini F, Koenig W, Illig T, Meisinger C, Gieger C, Zgaga L, Zemunik T, Boban M, Minelli C, Wheeler HE, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Nöthlings U, Jacobs G, Biffar R, Ernst F, Homuth G, Kroemer HK, Nauck M, Stracke S, Völker U, Völzke H, Kovacs P, Stumvoll M, Mägi R, Hofman A, Uitterlinden AG, Rivadeneira F, Aulchenko YS, Polasek O, Hastie N, Vitart V, Helmer C, Wang JJ, Stengel B, Ruggiero D, Bergmann S, Kähönen M, Viikari J, Nikopensius T, Province M, Ketkar S, Colhoun H, Doney A, Robino A, Krämer BK, Portas L, Ford I, Buckley BM, Adam M, Thun GA, Paulweber B, Haun M, Sala C, Mitchell P, Ciullo M, Kim SK, Vollenweider P, Raitakari O, Metspalu A, Palmer C, Gasparini P, Pirastu M, Jukema JW, Probst-Hensch NM, Kronenberg F, Toniolo D, Gudnason V, Shuldiner AR, Coresh J, Schmidt R, Ferrucci L, Siscovick DS, van Duijn CM, Borecki IB, Kardia SLR, Liu Y, Curhan GC, Rudan I, Gyllensten U, Wilson JF, Franke A, Pramstaller PP, Rettig R, Prokopenko I, Witteman J, Hayward C, Ridker PM, Parsa A, Bochud M, Heid IM, Kao WHL, Fox CS, Köttgen A. Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function. Hum Mol Genet 2012; 21:5329-43. [PMID: 22962313 DOI: 10.1093/hmg/dds369] [Show More Authors] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
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Affiliation(s)
- Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA
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3622
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Reiner AP, Beleza S, Franceschini N, Auer PL, Robinson JG, Kooperberg C, Peters U, Tang H. Genome-wide association and population genetic analysis of C-reactive protein in African American and Hispanic American women. Am J Hum Genet 2012; 91:502-12. [PMID: 22939635 DOI: 10.1016/j.ajhg.2012.07.023] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2012] [Revised: 07/08/2012] [Accepted: 07/26/2012] [Indexed: 11/29/2022] Open
Abstract
C-reactive protein (CRP) is a systemic inflammation marker that predicts future cardiovascular risk. CRP levels are higher in African Americans and Hispanic Americans than in European Americans, but the genetic determinants of CRP in these admixed United States minority populations are largely unknown. We performed genome-wide association studies (GWASs) of 8,280 African American (AA) and 3,548 Hispanic American (HA) postmenopausal women from the Women's Health Initiative SNP Health Association Resource. We discovered and validated a CRP-associated variant of triggering receptors expressed by myeloid cells 2 (TREM2) in chromosomal region 6p21 (p = 10(-10)). The TREM2 variant associated with higher CRP is common in Africa but rare in other ancestral populations. In AA women, the CRP region in 1q23 contained a strong admixture association signal (p = 10(-17)), which appears to be related to several independent CRP-associated alleles; the strongest of these is present only in African ancestral populations and is associated with higher CRP. Of the other genomic loci previously associated with CRP through GWASs of European populations, most loci (LEPR, IL1RN, IL6R, GCKR, NLRP3, HNF1A, HNF4A, and APOC1) showed consistent patterns of association with CRP in AA and HA women. In summary, we have identified a common TREM2 variant associated with CRP in United States minority populations. The genetic architecture underlying the CRP phenotype in AA women is complex and involves genetic variants shared across populations, as well as variants specific to populations of African descent.
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Affiliation(s)
- Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
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3623
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Foroud T, Koller DL, Lai D, Sauerbeck L, Anderson C, Ko N, Deka R, Mosley TH, Fornage M, Woo D, Moomaw CJ, Hornung R, Huston J, Meissner I, Bailey-Wilson JE, Langefeld C, Rouleau G, Connolly ES, Worrall BB, Kleindorfer D, Flaherty ML, Martini S, Mackey J, De Los Rios La Rosa F, Brown RD, Broderick JP. Genome-wide association study of intracranial aneurysms confirms role of Anril and SOX17 in disease risk. Stroke 2012; 43:2846-52. [PMID: 22961961 DOI: 10.1161/strokeaha.112.656397] [Citation(s) in RCA: 94] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Genomewide association studies have identified novel genetic factors that contribute to intracranial aneurysm (IA) susceptibility. We sought to confirm previously reported loci, to identify novel risk factors, and to evaluate the contribution of these factors to familial and sporadic IA. METHOD We utilized 2 complementary samples, one recruited on the basis of a dense family history of IA (discovery sample 1: 388 IA cases and 397 controls) and the other without regard to family history (discovery sample 2: 1095 IA cases and 1286 controls). Imputation was used to generate a common set of single nucleotide polymorphisms (SNP) across samples, and a logistic regression model was used to test for association in each sample. Results from each sample were then combined in a metaanalysis. RESULTS There was only modest overlap in the association results obtained in the 2 samples. In neither sample did results reach genomewide significance. However, the metaanalysis yielded genomewide significance for SNP on chromosome 9p (CDKN2BAS; rs6475606; P=3.6×10(-8)) and provided further evidence to support the previously reported association of IA with SNP in SOX17 on chromosome 8q (rs1072737; P=8.7×10(-5)). Analyses suggest that the effect of smoking acts multiplicatively with the SNP genotype, and smoking has a greater effect on risk than SNP genotype. CONCLUSIONS In addition to replicating several previously reported loci, we provide further evidence that the association on chromosome 9p is attributable to variants in CDKN2BAS (also known as ANRIL, an antisense noncoding RNA).
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Affiliation(s)
- Tatiana Foroud
- Indiana University School of Medicine, 410 W. 10 Street, Indianapolis, IN 46202, USA.
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3624
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Common variation at 6q16 within HACE1 and LIN28B influences susceptibility to neuroblastoma. Nat Genet 2012; 44:1126-30. [PMID: 22941191 PMCID: PMC3459292 DOI: 10.1038/ng.2387] [Citation(s) in RCA: 222] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Accepted: 07/24/2012] [Indexed: 12/13/2022]
Abstract
Neuroblastoma is a cancer of the sympathetic nervous system that accounts for approximately 10% of all pediatric oncology deaths. Here, we report a genome-wide association study of 2,817 neuroblastoma cases and 7,473 controls. We identified two new associations at 6q16, the first within HACE1 (rs4336470; combined P=2.7×10(-11); odds ratio 1.26, 95% confidence interval (CI) 1.18-1.35) and the second within LIN28B (rs17065417; combined P=1.2×10(-8); odds ratio 1.38, 95% CI 1.23-1.54). Expression of LIN28B and let-7 miRNA correlated with rs17065417 genotype in neuroblastoma cell lines, and we observed significant growth inhibition upon depletion of LIN28B, specifically in neuroblastoma cells that were homozygous for the risk allele. Low HACE1 and high LIN28B expression in diagnostic primary neuroblastomas were associated with worse overall survival (P=0.008 and 0.014, respectively). Taken together, these data show that common variants in HACE1 and LIN28B influence neuroblastoma susceptibility and indicate that both genes likely have a role in disease progression.
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3625
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Hamilton G, Harris SE, Davies G, Liewald DC, Tenesa A, Payton A, Horan MA, Ollier WER, Pendleton N, Starr JM, Porteous D, Deary IJ. The role of ECE1 variants in cognitive ability in old age and Alzheimer's disease risk. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:696-709. [PMID: 22693153 DOI: 10.1002/ajmg.b.32073] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2011] [Accepted: 05/23/2012] [Indexed: 12/13/2022]
Abstract
The β-amyloid peptide may play a central role in Alzheimer's disease (AD) pathogenesis. We have evaluated variants in seven Aβ-degrading genes (ACE, ECE1, ECE2, IDE, MME, PLAU, and TF) for association with AD risk in the Genetic and Environmental Risk in Alzheimer's Disease Consortium 1 (GERAD1) cohort, and with three cognitive phenotypes in the Lothian Birth Cohort 1936 (LBC1936), using 128 and 121 SNPs, respectively. In GERAD1, we identified a significant association between a four-SNP intragenic ECE1 haplotype and risk of AD in individuals that carried at least one APOE ε4 allele (P = 0.00035, odds ratio = 1.61). In LBC1936, we identified a significant association between a different two-SNP ECE1 intragenic haplotype and non-verbal reasoning in individuals lacking the APOE ε4 allele (P = 0.00036, β = -0.19). Both results showed a trend towards significance after permutation (0.05 < P < 0.10). A follow-up cognitive genetic study evaluated the association of ECE1 SNPs in three additional cohorts of non-demented older people. Meta-analysis of the four cohorts identified the significant association (Z < 0.05) of SNPs in the ECE-1b promoter with non-verbal reasoning scores, particularly in individuals lacking the APOE ε4 allele. Our genetic findings are not wholly consistent. Nonetheless, the AD associated intronic haplotype is linked to the 338A variant of known ECE1b promoter variant, 338C>A (rs213045). We observed significantly less expression from the 338A variant in two human neuroblastoma cell lines and speculate that this promoter may be subject to tissue-specific regulation.
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Affiliation(s)
- Gillian Hamilton
- Medical Genetics, Molecular Medicine Centre, University of Edinburgh, Edinburgh, UK.
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3626
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Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, Mägi R, Strawbridge RJ, Rehnberg E, Gustafsson S, Kanoni S, Rasmussen-Torvik LJ, Yengo L, Lecoeur C, Shungin D, Sanna S, Sidore C, Johnson PCD, Jukema JW, Johnson T, Mahajan A, Verweij N, Thorleifsson G, Hottenga JJ, Shah S, Smith AV, Sennblad B, Gieger C, Salo P, Perola M, Timpson NJ, Evans DM, Pourcain BS, Wu Y, Andrews JS, Hui J, Bielak LF, Zhao W, Horikoshi M, Navarro P, Isaacs A, O'Connell JR, Stirrups K, Vitart V, Hayward C, Esko T, Mihailov E, Fraser RM, Fall T, Voight BF, Raychaudhuri S, Chen H, Lindgren CM, Morris AP, Rayner NW, Robertson N, Rybin D, Liu CT, Beckmann JS, Willems SM, Chines PS, Jackson AU, Kang HM, Stringham HM, Song K, Tanaka T, Peden JF, Goel A, Hicks AA, An P, Müller-Nurasyid M, Franco-Cereceda A, Folkersen L, Marullo L, Jansen H, Oldehinkel AJ, Bruinenberg M, Pankow JS, North KE, Forouhi NG, Loos RJF, Edkins S, Varga TV, Hallmans G, Oksa H, Antonella M, Nagaraja R, Trompet S, Ford I, Bakker SJL, Kong A, Kumari M, Gigante B, Herder C, Munroe PB, Caulfield M, Antti J, Mangino M, Small K, Miljkovic I, et alScott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, Mägi R, Strawbridge RJ, Rehnberg E, Gustafsson S, Kanoni S, Rasmussen-Torvik LJ, Yengo L, Lecoeur C, Shungin D, Sanna S, Sidore C, Johnson PCD, Jukema JW, Johnson T, Mahajan A, Verweij N, Thorleifsson G, Hottenga JJ, Shah S, Smith AV, Sennblad B, Gieger C, Salo P, Perola M, Timpson NJ, Evans DM, Pourcain BS, Wu Y, Andrews JS, Hui J, Bielak LF, Zhao W, Horikoshi M, Navarro P, Isaacs A, O'Connell JR, Stirrups K, Vitart V, Hayward C, Esko T, Mihailov E, Fraser RM, Fall T, Voight BF, Raychaudhuri S, Chen H, Lindgren CM, Morris AP, Rayner NW, Robertson N, Rybin D, Liu CT, Beckmann JS, Willems SM, Chines PS, Jackson AU, Kang HM, Stringham HM, Song K, Tanaka T, Peden JF, Goel A, Hicks AA, An P, Müller-Nurasyid M, Franco-Cereceda A, Folkersen L, Marullo L, Jansen H, Oldehinkel AJ, Bruinenberg M, Pankow JS, North KE, Forouhi NG, Loos RJF, Edkins S, Varga TV, Hallmans G, Oksa H, Antonella M, Nagaraja R, Trompet S, Ford I, Bakker SJL, Kong A, Kumari M, Gigante B, Herder C, Munroe PB, Caulfield M, Antti J, Mangino M, Small K, Miljkovic I, Liu Y, Atalay M, Kiess W, James AL, Rivadeneira F, Uitterlinden AG, Palmer CNA, Doney ASF, Willemsen G, Smit JH, Campbell S, Polasek O, Bonnycastle LL, Hercberg S, Dimitriou M, Bolton JL, Fowkes GR, Kovacs P, Lindström J, Zemunik T, Bandinelli S, Wild SH, Basart HV, Rathmann W, Grallert H, Maerz W, Kleber ME, Boehm BO, Peters A, Pramstaller PP, Province MA, Borecki IB, Hastie ND, Rudan I, Campbell H, Watkins H, Farrall M, Stumvoll M, Ferrucci L, Waterworth DM, Bergman RN, Collins FS, Tuomilehto J, Watanabe RM, de Geus EJC, Penninx BW, Hofman A, Oostra BA, Psaty BM, Vollenweider P, Wilson JF, Wright AF, Hovingh GK, Metspalu A, Uusitupa M, Magnusson PKE, Kyvik KO, Kaprio J, Price JF, Dedoussis GV, Deloukas P, Meneton P, Lind L, Boehnke M, Shuldiner AR, van Duijn CM, Morris AD, Toenjes A, Peyser PA, Beilby JP, Körner A, Kuusisto J, Laakso M, Bornstein SR, Schwarz PEH, Lakka TA, Rauramaa R, Adair LS, Smith GD, Spector TD, Illig T, de Faire U, Hamsten A, Gudnason V, Kivimaki M, Hingorani A, Keinanen-Kiukaanniemi SM, Saaristo TE, Boomsma DI, Stefansson K, van der Harst P, Dupuis J, Pedersen NL, Sattar N, Harris TB, Cucca F, Ripatti S, Salomaa V, Mohlke KL, Balkau B, Froguel P, Pouta A, Jarvelin MR, Wareham NJ, Bouatia-Naji N, McCarthy MI, Franks PW, Meigs JB, Teslovich TM, Florez JC, Langenberg C, Ingelsson E, Prokopenko I, Barroso I. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 2012; 44:991-1005. [PMID: 22885924 PMCID: PMC3433394 DOI: 10.1038/ng.2385] [Show More Authors] [Citation(s) in RCA: 654] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2012] [Accepted: 07/20/2012] [Indexed: 12/16/2022]
Abstract
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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Affiliation(s)
- Robert A Scott
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
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3627
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Luciano M, Huffman JE, Arias-Vásquez A, Vinkhuyzen AAE, Middeldorp CM, Giegling I, Payton A, Davies G, Zgaga L, Janzing J, Ke X, Galesloot T, Hartmann AM, Ollier W, Tenesa A, Hayward C, Verhagen M, Montgomery GW, Hottenga JJ, Konte B, Starr JM, Vitart V, Vos PE, Madden PAF, Willemsen G, Konnerth H, Horan MA, Porteous DJ, Campbell H, Vermeulen SH, Heath AC, Wright A, Polasek O, Kovacevic SB, Hastie ND, Franke B, Boomsma DI, Martin NG, Rujescu D, Wilson JF, Buitelaar J, Pendleton N, Rudan I, Deary IJ. Genome-wide association uncovers shared genetic effects among personality traits and mood states. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:684-95. [PMID: 22628180 PMCID: PMC3795298 DOI: 10.1002/ajmg.b.32072] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2012] [Accepted: 05/03/2012] [Indexed: 12/27/2022]
Abstract
Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (~2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546-1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta-analysis of the cohort results was performed, with follow-up associations of the top SNPs and genes investigated in independent cohorts (n = 527-6,032). Suggestive association (P = 8 × 10(-8)) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10(-6)) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene-based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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3628
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Sandholm N, Salem RM, McKnight AJ, Brennan EP, Forsblom C, Isakova T, McKay GJ, Williams WW, Sadlier DM, Mäkinen VP, Swan EJ, Palmer C, Boright AP, Ahlqvist E, Deshmukh HA, Keller BJ, Huang H, Ahola AJ, Fagerholm E, Gordin D, Harjutsalo V, He B, Heikkilä O, Hietala K, Kytö J, Lahermo P, Lehto M, Lithovius R, Österholm AM, Parkkonen M, Pitkäniemi J, Rosengård-Bärlund M, Saraheimo M, Sarti C, Söderlund J, Soro-Paavonen A, Syreeni A, Thorn LM, Tikkanen H, Tolonen N, Tryggvason K, Tuomilehto J, Wadén J, Gill GV, Prior S, Guiducci C, Mirel DB, Taylor A, Hosseini SM, DCCT/EDIC Research Group, Parving HH, Rossing P, Tarnow L, Ladenvall C, Alhenc-Gelas F, Lefebvre P, Rigalleau V, Roussel R, Tregouet DA, Maestroni A, Maestroni S, Falhammar H, Gu T, Möllsten A, Cimponeriu D, Ioana M, Mota M, Mota E, Serafinceanu C, Stavarachi M, Hanson RL, Nelson RG, Kretzler M, Colhoun HM, Panduru NM, Gu HF, Brismar K, Zerbini G, Hadjadj S, Marre M, Groop L, Lajer M, Bull SB, Waggott D, Paterson AD, Savage DA, Bain SC, Martin F, Hirschhorn JN, Godson C, Florez JC, Groop PH, Maxwell AP. New susceptibility loci associated with kidney disease in type 1 diabetes. PLoS Genet 2012; 8:e1002921. [PMID: 23028342 PMCID: PMC3447939 DOI: 10.1371/journal.pgen.1002921] [Citation(s) in RCA: 186] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2012] [Accepted: 07/12/2012] [Indexed: 12/12/2022] Open
Abstract
Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 × 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 × 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 × 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.
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Affiliation(s)
- Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland
| | - Rany M. Salem
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Endocrine Research Unit, Department of Endocrinology, Children's Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Amy Jayne McKnight
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
| | - Eoin P. Brennan
- Diabetes Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
- Mater Misericordiae Hospital, Dublin, Ireland
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Tamara Isakova
- Division of Nephrology and Hypertension, University of Miami, Miami, Florida, United States of America
| | - Gareth J. McKay
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
| | - Winfred W. Williams
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Denise M. Sadlier
- Diabetes Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
- Mater Misericordiae Hospital, Dublin, Ireland
| | - Ville-Petteri Mäkinen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Institute of Clinical Medicine, Department of Internal Medicine, Biocenter Oulu and Clinical Research Center, University of Oulu, Oulu, Finland
| | - Elizabeth J. Swan
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
| | - Cameron Palmer
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Endocrine Research Unit, Department of Endocrinology, Children's Hospital, Boston, Massachusetts, United States of America
| | | | - Emma Ahlqvist
- Department of Clinical Sciences, Diabetes, and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Harshal A. Deshmukh
- Wellcome Trust Centre for Molecular Medicine, University of Dundee, Dundee, Scotland, United Kingdom
| | - Benjamin J. Keller
- Computer Science, Eastern Michigan University, Ypsilanti, Michigan, United States of America
| | - Huateng Huang
- Division of Nephrology, Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Aila J. Ahola
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Emma Fagerholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Daniel Gordin
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Bing He
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Outi Heikkilä
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Kustaa Hietala
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Kytö
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Päivi Lahermo
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Markku Lehto
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Raija Lithovius
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Anne-May Österholm
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Maija Parkkonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Pitkäniemi
- Hjelt Institute, Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Milla Rosengård-Bärlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Markku Saraheimo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Cinzia Sarti
- Hjelt Institute, Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jenny Söderlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Aino Soro-Paavonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Lena M. Thorn
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Heikki Tikkanen
- Unit for Sports and Exercise Medicine, Institute of Clinical Medicine, University of Helsinki, Finland
| | - Nina Tolonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Karl Tryggvason
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
- South Ostrobothnia Central Hospital, Seinäjoki, Finland
- Red RECAVA Grupo RD06/0014/0015, Hospital Universitario La Paz, Madrid, Spain
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
| | - Johan Wadén
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Geoffrey V. Gill
- Diabetes Endocrine Unit, Clinical Sciences Centre, Aintree University Hospital, University of Liverpool, Liverpool, United Kingdom
| | - Sarah Prior
- Institute of Life Sciences, Swansea University, Swansea, United Kingdom
| | - Candace Guiducci
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Daniel B. Mirel
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Andrew Taylor
- 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
| | - S. Mohsen Hosseini
- Institute of Medical Science, University of Toronto, Toronto, Canada
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Canada
| | - DCCT/EDIC Research Group
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, Maryland, United States of America
- Biostatics Division, The George Washington University, Washington, D.C., United States of America
| | - Hans-Henrik Parving
- Department of Medical Endocrinology, University Hospital of Copenhagen, Copenhagen, Denmark
- Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
| | - Peter Rossing
- Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Lise Tarnow
- Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Claes Ladenvall
- Department of Clinical Sciences, Diabetes, and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | - François Alhenc-Gelas
- INSERM U872, Paris-Descartes University, Pierre and Marie Curie University, Paris, France
| | | | | | - Ronan Roussel
- AP-HP, Hôpital Bichat, Diabetology Endocrinology Nutrition, Paris, France
- Université Paris Diderot, Sorbonne Paris Cité, UMR 738, Paris, France
- INSERM, UMR872, Equipe 2, Centre de Recherche des Cordeliers, Paris, France
| | - David-Alexandre Tregouet
- INSERM UMR_S 937, ICAN Institute for Cardiometabolism and Nutrition, Pierre and Marie Curie University, Paris, France
| | - Anna Maestroni
- Complications of Diabetes Unit, Division of Metabolic and Cardiovascular Sciences, San Raffaele Scientific Institute, Milano, Italy
| | - Silvia Maestroni
- Complications of Diabetes Unit, Division of Metabolic and Cardiovascular Sciences, San Raffaele Scientific Institute, Milano, Italy
| | - Henrik Falhammar
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Metabolism, and Diabetes, Karolinska University Hospital, Stockholm, Sweden
| | - Tianwei Gu
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Anna Möllsten
- Department of Clinical Sciences, Paediatrics, Umeå University, Umeå, Sweden
| | | | - Mihai Ioana
- University of Medicine and Pharmacy of Craiova, Craiova, Romania
| | - Maria Mota
- University of Medicine and Pharmacy of Craiova, Craiova, Romania
| | - Eugen Mota
- University of Medicine and Pharmacy of Craiova, Craiova, Romania
| | | | | | - Robert L. Hanson
- Diabetes Epidemiology and Clinical Research Section, NIDDK, Phoenix, Arizona, United States of America
| | - Robert G. Nelson
- Diabetes Epidemiology and Clinical Research Section, NIDDK, Phoenix, Arizona, United States of America
| | - Matthias Kretzler
- Internal Medicine, Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Helen M. Colhoun
- Wellcome Trust Centre for Molecular Medicine, University of Dundee, Dundee, Scotland, United Kingdom
| | | | - Harvest F. Gu
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Kerstin Brismar
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Metabolism, and Diabetes, Karolinska University Hospital, Stockholm, Sweden
| | - Gianpaolo Zerbini
- Complications of Diabetes Unit, Division of Metabolic and Cardiovascular Sciences, San Raffaele Scientific Institute, Milano, Italy
| | - Samy Hadjadj
- CHU Poitiers–Endocrinology, University of Poitiers, Poitiers, France
- INSERM CIC0802, CHU Poitiers, Poitiers, France
| | - Michel Marre
- AP-HP, Hôpital Bichat, Diabetology Endocrinology Nutrition, Paris, France
- Université Paris Diderot, Sorbonne Paris Cité, UMR 738, Paris, France
- INSERM, U695 (Genetic Determinants of Type 2 Diabetes and Its Vascular Complications), Paris, France
| | - Leif Groop
- Department of Clinical Sciences, Diabetes, and Endocrinology, Skåne University Hospital, Lund University, Malmö, Sweden
| | | | - Shelley B. Bull
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Daryl Waggott
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, Hospital for Sick Children, Toronto, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - David A. Savage
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
| | - Stephen C. Bain
- Institute of Life Sciences, Swansea University, Swansea, United Kingdom
| | - Finian Martin
- Diabetes Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
- Mater Misericordiae Hospital, Dublin, Ireland
| | - Joel N. Hirschhorn
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Endocrine Research Unit, Department of Endocrinology, Children's Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Catherine Godson
- Diabetes Research Centre, Conway Institute, School of Medicine and Medical Sciences, University College Dublin, Dublin, Ireland
- Mater Misericordiae Hospital, Dublin, Ireland
| | - Jose C. Florez
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Baker IDI Heart and Diabetes Institute, Melbourne, Australia
| | - Alexander P. Maxwell
- Nephrology Research, Centre for Public Health, Queen's University of Belfast, Belfast, United Kingdom
- Regional Nephrology Unit, Belfast City Hospital, Belfast, United Kingdom
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3629
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Adrianto I, Lin CP, Hale JJ, Levin AM, Datta I, Parker R, Adler A, Kelly JA, Kaufman KM, Lessard CJ, Moser KL, Kimberly RP, Harley JB, Iannuzzi MC, Rybicki BA, Montgomery CG. Genome-wide association study of African and European Americans implicates multiple shared and ethnic specific loci in sarcoidosis susceptibility. PLoS One 2012; 7:e43907. [PMID: 22952805 PMCID: PMC3428296 DOI: 10.1371/journal.pone.0043907] [Citation(s) in RCA: 90] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Accepted: 07/27/2012] [Indexed: 12/21/2022] Open
Abstract
Sarcoidosis is a systemic inflammatory disease characterized by the formation of granulomas in affected organs. Genome-wide association studies (GWASs) of this disease have been conducted only in European population. We present the first sarcoidosis GWAS in African Americans (AAs, 818 cases and 1,088 related controls) followed by replication in independent sets of AAs (455 cases and 557 controls) and European Americans (EAs, 442 cases and 2,284 controls). We evaluated >6 million SNPs either genotyped using the Illumina Omni1-Quad array or imputed from the 1000 Genomes Project data. We identified a novel sarcoidosis-associated locus, NOTCH4, that reached genome-wide significance in the combined AA samples (rs715299, P(AA-meta) = 6.51 × 10(-10)) and demonstrated the independence of this locus from others in the MHC region in the same sample. We replicated previous European GWAS associations within HLA-DRA, HLA-DRB5, HLA-DRB1, BTNL2, and ANXA11 in both our AA and EA datasets. We also confirmed significant associations to the previously reported HLA-C and HLA-B regions in the EA but not AA samples. We further identified suggestive associations with several other genes previously reported in lung or inflammatory diseases.
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Affiliation(s)
- Indra Adrianto
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Chee Paul Lin
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Jessica J. Hale
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Albert M. Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan, United States of America
| | - Indrani Datta
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan, United States of America
| | - Ryan Parker
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Adam Adler
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Jennifer A. Kelly
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
| | - Kenneth M. Kaufman
- Division of Rheumatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
- The United States Department of Veterans Affairs Medical Center, Cincinnati, Ohio, United States of America
| | - Christopher J. Lessard
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Kathy L. Moser
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States of America
| | - Robert P. Kimberly
- Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - John B. Harley
- Division of Rheumatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
- The United States Department of Veterans Affairs Medical Center, Cincinnati, Ohio, United States of America
| | - Michael C. Iannuzzi
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, United States of America
| | - Benjamin A. Rybicki
- Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan, United States of America
| | - Courtney G. Montgomery
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America
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3630
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Cheng I, Chen GK, Nakagawa H, He J, Wan P, Laurie CC, Shen J, Sheng X, Pooler LC, Crenshaw AT, Mirel DB, Takahashi A, Kubo M, Nakamura Y, Al Olama AA, Benlloch S, Donovan JL, Guy M, Hamdy FC, Kote-Jarai Z, Neal DE, Wilkens LR, Monroe KR, Stram DO, Muir K, Eeles RA, Easton DF, Kolonel LN, Henderson BE, Le Marchand L, Haiman CA. Evaluating genetic risk for prostate cancer among Japanese and Latinos. Cancer Epidemiol Biomarkers Prev 2012; 21:2048-58. [PMID: 22923026 DOI: 10.1158/1055-9965.epi-12-0598] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND There have been few genome-wide association studies (GWAS) of prostate cancer among diverse populations. To search for novel prostate cancer risk variants, we conducted GWAS of prostate cancer in Japanese and Latinos. In addition, we tested prostate cancer risk variants and developed genetic risk models of prostate cancer for Japanese and Latinos. METHODS Our first-stage GWAS of prostate cancer included Japanese (cases/controls = 1,033/1,042) and Latino (cases/controls = 1,043/1,057) from the Multiethnic Cohort (MEC). Significant associations from stage I (P < 1.0 × 10(-4)) were examined in silico in GWAS of prostate cancer (stage II) in Japanese (cases/controls = 1,583/3,386) and Europeans (cases/controls = 1,854/1,894). RESULTS No novel stage I single-nucleotide polymorphism (SNP) outside of known risk regions reached genome-wide significance. For Japanese, in stage I, the most notable putative novel association was seen with 10 SNPs (P ≤ 8.0 × 10(-6)) at chromosome 2q33; however, this was not replicated in stage II. For Latinos, the most significant association was observed with rs17023900 at the known 3p12 risk locus (stage I: OR = 1.45; P = 7.01 × 10(-5) and stage II: OR = 1.58; P = 3.05 × 10(-7)). The majority of the established risk variants for prostate cancer, 79% and 88%, were positively associated with prostate cancer in Japanese and Latinos (stage I), respectively. The cumulative effects of these variants significantly influence prostate cancer risk (OR per allele = 1.10; P = 2.71 × 10(-25) and OR = 1.07; P = 1.02 × 10(-16) for Japanese and Latinos, respectively). CONCLUSION AND IMPACT Our GWAS of prostate cancer did not identify novel genome-wide significant variants. However, our findings show that established risk variants for prostate cancer significantly contribute to risk among Japanese and Latinos.
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Affiliation(s)
- Iona Cheng
- Epidemiology Program, University of Hawaii Cancer Center, 1236 Lauhala Street, Suite 407, Honolulu, HI 96813, USA.
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3631
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El-Sayed Moustafa JS, Eleftherohorinou H, de Smith AJ, Andersson-Assarsson JC, Couto Alves A, Hadjigeorgiou E, Walters RG, Asher JE, Bottolo L, Buxton JL, Sladek R, Meyre D, Dina C, Visvikis-Siest S, Jacobson P, Sjöström L, Carlsson LM, Walley A, Falchi M, Froguel P, Blakemore AI, Coin LJ. Novel association approach for variable number tandem repeats (VNTRs) identifies DOCK5 as a susceptibility gene for severe obesity. Hum Mol Genet 2012; 21:3727-38. [PMID: 22595969 PMCID: PMC3406755 DOI: 10.1093/hmg/dds187] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Accepted: 05/11/2012] [Indexed: 12/18/2022] Open
Abstract
Variable number tandem repeats (VNTRs) constitute a relatively under-examined class of genomic variants in the context of complex disease because of their sequence complexity and the challenges in assaying them. Recent large-scale genome-wide copy number variant mapping and association efforts have highlighted the need for improved methodology for association studies using these complex polymorphisms. Here we describe the in-depth investigation of a complex region on chromosome 8p21.2 encompassing the dedicator of cytokinesis 5 (DOCK5) gene. The region includes two VNTRs of complex sequence composition which flank a common 3975 bp deletion, all three of which were genotyped by polymerase chain reaction and fragment analysis in a total of 2744 subjects. We have developed a novel VNTR association method named VNTRtest, suitable for association analysis of multi-allelic loci with binary and quantitative outcomes, and have used this approach to show significant association of the DOCK5 VNTRs with childhood and adult severe obesity (P(empirical)= 8.9 × 10(-8) and P= 3.1 × 10(-3), respectively) which we estimate explains ~0.8% of the phenotypic variance. We also identified an independent association between the 3975 base pair (bp) deletion and obesity, explaining a further 0.46% of the variance (P(combined)= 1.6 × 10(-3)). Evidence for association between DOCK5 transcript levels and the 3975 bp deletion (P= 0.027) and both VNTRs (P(empirical)= 0.015) was also identified in adipose tissue from a Swedish family sample, providing support for a functional effect of the DOCK5 deletion and VNTRs. These findings highlight the potential role of DOCK5 in human obesity and illustrate a novel approach for analysis of the contribution of VNTRs to disease susceptibility through association studies.
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Affiliation(s)
| | | | - Adam J. de Smith
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Johanna C. Andersson-Assarsson
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
- Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, The Sahlgrenska Academy at University of Gothenburg, Gothenburg 413 45, Sweden
| | | | - Eleni Hadjigeorgiou
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Robin G. Walters
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Julian E. Asher
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Leonardo Bottolo
- MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College London, UK
- Department of Mathematics, Imperial College London, London SW7 AZ, UK
| | - Jessica L. Buxton
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Rob Sladek
- Department of Medicine and
- Department of Human Genetics, McGill University, Montreal, CanadaH3A 1A4
| | - David Meyre
- CNRS 8199-University Lille North of France, Institut Pasteur de Lille, Lille 59000, France
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, CanadaL8S 4K1
| | - Christian Dina
- INSERM UMR 915, l'institut du thorax, CNRS ERL3147, University of Nantes, France and
| | - Sophie Visvikis-Siest
- Unité de Recherche ‘Génétique Cardiovasculaire’, EA-4373, Faculté de Pharmacie, Université de Lorraine, 30, rue Lionnois, Nancy 54000, France
| | - Peter Jacobson
- Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, The Sahlgrenska Academy at University of Gothenburg, Gothenburg 413 45, Sweden
| | - Lars Sjöström
- Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, The Sahlgrenska Academy at University of Gothenburg, Gothenburg 413 45, Sweden
| | - Lena M.S. Carlsson
- Department of Molecular and Clinical Medicine and Center for Cardiovascular and Metabolic Research, The Sahlgrenska Academy at University of Gothenburg, Gothenburg 413 45, Sweden
| | - Andrew Walley
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Mario Falchi
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Philippe Froguel
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
- CNRS 8199-University Lille North of France, Institut Pasteur de Lille, Lille 59000, France
| | - Alexandra I.F. Blakemore
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
| | - Lachlan J.M. Coin
- Department of Genomics of Common Disease, School of Public Health Inperial College London, W12 ONN, UK
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3632
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Avery CL, Sethupathy P, Buyske S, He Q, Lin DY, Arking DE, Carty CL, Duggan D, Fesinmeyer MD, Hindorff LA, Jeff JM, Klein L, Patton KK, Peters U, Shohet RV, Sotoodehnia N, Young AM, Kooperberg C, Haiman CA, Mohlke KL, Whitsel EA, North KE. Fine-mapping and initial characterization of QT interval loci in African Americans. PLoS Genet 2012; 8:e1002870. [PMID: 22912591 PMCID: PMC3415454 DOI: 10.1371/journal.pgen.1002870] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2012] [Accepted: 06/06/2012] [Indexed: 01/27/2023] Open
Abstract
The QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women's Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P≤1.20×10(-4)): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P≤1.37×10(-5)): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.
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Affiliation(s)
- Christy L Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
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3633
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Ibrahim-Verbaas CA, Zorkoltseva IV, Amin N, Schuur M, Coppus AMW, Isaacs A, Aulchenko YS, Breteler MMB, Ikram MA, Axenovich TI, Verbeek MM, van Swieten JC, Oostra BA, van Duijn CM. Linkage analysis for plasma amyloid beta levels in persons with hypertension implicates Aβ-40 levels to presenilin 2. Hum Genet 2012; 131:1869-76. [PMID: 22872014 DOI: 10.1007/s00439-012-1210-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2012] [Accepted: 07/21/2012] [Indexed: 12/16/2022]
Abstract
Plasma concentrations of Aβ40 and Aβ42 rise with age and are increased in people with mutations that cause early-onset Alzheimer's disease (AD). Amyloid beta (Aβ) plasma levels were successfully used as an (endo)phenotype for gene discovery using a linkage approach in families with dominant forms of disease. Here, we searched for loci involved in Aβ plasma levels in a series of non-demented patients with hypertension in the Erasmus Rucphen Family study. Aβ40 and Aβ42 levels were determined in 125 subjects with severe hypertension. All patients were genotyped with a 6,000 single nucleotide polymorphisms (SNPs) illumina array designed for linkage analysis. We conducted linkage analysis of plasma Aβ levels. None of the linkage analyses yielded genome-wide significant logarithm of odds (LOD) score over 3.3, but there was suggestive evidence for linkage (LOD > 1.9) for two regions: 1q41 (LOD = 2.07) and 11q14.3 (LOD = 2.97), both for Aβ40. These regions were followed up with association analysis in the study subjects and in 320 subjects from a population-based cohort. For the Aβ40 region on chromosome 1, association of several SNPs was observed at the presenilin 2 gene (PSEN2) (p = 2.58 × 10(-4) for rs6703170). On chromosome 11q14-21, we found some association (p = 3.1 × 10(-3) for rs2514299). This linkage study of plasma concentrations of Aβ40 and Aβ42 yielded two suggestive regions, of which one points toward a known locus for familial AD.
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Affiliation(s)
- Carla A Ibrahim-Verbaas
- Department of Neurology, Erasmus University Medical Center, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
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3634
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Guo X, Cui J, Jones MR, Haritunians T, Xiang AH, Chen YDI, Taylor KD, Buchanan TA, Davis RC, Hsueh WA, Raffel LJ, Rotter JI, Goodarzi MO. Insulin clearance: confirmation as a highly heritable trait, and genome-wide linkage analysis. Diabetologia 2012; 55:2183-92. [PMID: 22584727 PMCID: PMC3391346 DOI: 10.1007/s00125-012-2577-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2012] [Accepted: 04/09/2012] [Indexed: 01/11/2023]
Abstract
AIMS/HYPOTHESIS We have previously documented a high heritability of insulin clearance in a Hispanic cohort. Here, our goal was to confirm the high heritability in a second cohort and search for genetic loci contributing to insulin clearance. METHODS Hyperinsulinaemic-euglycaemic clamps were performed in 513 participants from 140 Hispanic families. Heritability was estimated for clamp-derived insulin clearance and a two-phase genome-wide linkage scan was conducted using a variance components approach. Linkage peaks were further investigated by candidate gene association analysis in two cohorts. RESULTS The covariate-adjusted heritability of insulin clearance was 73%, indicating that the majority of the phenotypic variance is due to genetic factors. In the Phase 1 linkage scan, no signals with a logarithm of odds (LOD) score >2 were detected. In the Phase 2 scan, two linkage peaks with an LOD >2 for insulin clearance were identified on chromosomes 15 (LOD 3.62) and 20 (LOD 2.43). These loci harbour several promising candidate genes for insulin clearance, with 12 single nucleotide polymorphisms (SNPs) on chromosome 15 and six SNPs on chromosome 20 being associated with insulin clearance in both Hispanic cohorts. CONCLUSIONS/INTERPRETATION In a second Hispanic cohort, we confirmed that insulin clearance is a highly heritable trait and identified chromosomal loci that harbour genes regulating insulin clearance. The identification of such genes may improve our understanding of how the body clears insulin, thus leading to improved risk assessment, diagnosis, prevention and therapy of diabetes, as well as of other hyperinsulinaemic disorders, such as the metabolic syndrome and polycystic ovary syndrome.
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Affiliation(s)
- X. Guo
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - J. Cui
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - M. R. Jones
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Room B-131, Los Angeles, CA 90048, USA
| | - T. Haritunians
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - A. H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group, Pasadena, CA, USA
| | - Y.-D. I. Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - K. D. Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - T. A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - R. C. Davis
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - W. A. Hsueh
- Diabetes Research Center, Division of Diabetes, Obesity and Lipids, Methodist Hospital Research Institute, Houston, TX, USA
| | - L. J. Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - J. I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - M. O. Goodarzi
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Room B-131, Los Angeles, CA 90048, USA
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3635
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Folseraas T, Melum E, Rausch P, Juran BD, Ellinghaus E, Shiryaev A, Laerdahl JK, Ellinghaus D, Schramm C, Weismüller TJ, Gotthardt DN, Hov JR, Clausen OP, Weersma RK, Janse M, Boberg KM, Björnsson E, Marschall HU, Cleynen I, Rosenstiel P, Holm K, Teufel A, Rust C, Gieger C, Wichmann HE, Bergquist A, Ryu E, Ponsioen CY, Runz H, Sterneck M, Vermeire S, Beuers U, Wijmenga C, Schrumpf E, Manns MP, Lazaridis KN, Schreiber S, Baines JF, Franke A, Karlsen TH. Extended analysis of a genome-wide association study in primary sclerosing cholangitis detects multiple novel risk loci. J Hepatol 2012; 57:366-75. [PMID: 22521342 PMCID: PMC3399030 DOI: 10.1016/j.jhep.2012.03.031] [Citation(s) in RCA: 168] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2011] [Revised: 03/07/2012] [Accepted: 03/26/2012] [Indexed: 02/06/2023]
Abstract
BACKGROUND & AIMS A limited number of genetic risk factors have been reported in primary sclerosing cholangitis (PSC). To discover further genetic susceptibility factors for PSC, we followed up on a second tier of single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS). METHODS We analyzed 45 SNPs in 1221 PSC cases and 3508 controls. The association results from the replication analysis and the original GWAS (715 PSC cases and 2962 controls) were combined in a meta-analysis comprising 1936 PSC cases and 6470 controls. We performed an analysis of bile microbial community composition in 39 PSC patients by 16S rRNA sequencing. RESULTS Seventeen SNPs representing 12 distinct genetic loci achieved nominal significance (p(replication) <0.05) in the replication. The most robust novel association was detected at chromosome 1p36 (rs3748816; p(combined)=2.1 × 10(-8)) where the MMEL1 and TNFRSF14 genes represent potential disease genes. Eight additional novel loci showed suggestive evidence of association (p(repl) <0.05). FUT2 at chromosome 19q13 (rs602662; p(comb)=1.9 × 10(-6), rs281377; p(comb)=2.1 × 10(-6) and rs601338; p(comb)=2.7 × 10(-6)) is notable due to its implication in altered susceptibility to infectious agents. We found that FUT2 secretor status and genotype defined by rs601338 significantly influence biliary microbial community composition in PSC patients. CONCLUSIONS We identify multiple new PSC risk loci by extended analysis of a PSC GWAS. FUT2 genotype needs to be taken into account when assessing the influence of microbiota on biliary pathology in PSC.
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Affiliation(s)
- Trine Folseraas
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Research institute for Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Espen Melum
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Research institute for Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Philipp Rausch
- Institute for Experimental Medicine, Christian-Albrechts-University of Kiel, Kiel, Germany
- Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Brian D. Juran
- Center for Basic Research in Digestive Diseases, Division of Gastroenterology and Hepatology, Mayo Clinic, College of Medicine, Rochester, Minnesota, United States of America
| | - Eva Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Alexey Shiryaev
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Research institute for Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Jon K. Laerdahl
- Centre for Molecular Biology and Neuroscience (CMBN) and Department of Microbiology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Bioinformatics Core Facility, Department of Informatics, University of Oslo, Oslo, Norway
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Christoph Schramm
- 1 Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias J. Weismüller
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
- Integrated Research and Treatment Center-Transplantation (IFB-tx), Hannover Medical School, Hannover, Germany
| | | | - Johannes Roksund Hov
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Research institute for Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Ole Petter Clausen
- Faculty of Medicine, University of Oslo, Oslo, Norway
- Division of Pathology, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Rinse K. Weersma
- Department of Gastroenterology and Hepatology, University Medical Center Groningen and University of Groningen, The Netherlands
| | - Marcel Janse
- Department of Gastroenterology and Hepatology, University Medical Center Groningen and University of Groningen, The Netherlands
| | - Kirsten Muri Boberg
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Einar Björnsson
- Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy and University Hospital, Gothenburg, Sweden
| | - Hanns-Ulrich Marschall
- Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy and University Hospital, Gothenburg, Sweden
| | - Isabelle Cleynen
- Department of Gastroenterology, University Hospital Gasthuisberg, Leuven, Belgium
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Kristian Holm
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Andreas Teufel
- 1 Department of Medicine, University of Mainz, Mainz, Germany
| | - Christian Rust
- Department of Medicine 2, Grosshadern, University of Munich, Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Center Munich, German Research, Center for Environmental Health, Neuherberg, Germany
| | - H-Erich Wichmann
- Institute of Epidemiology I, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Grosshadern, Munich, Germany
| | - Annika Bergquist
- Department of Gastroenterology and Hepatology, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Euijung Ryu
- Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, Minnesota, Unites States of America
| | - Cyriel Y. Ponsioen
- Department of Gastroenterology and Hepatology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Heiko Runz
- Department of Human Genetics, University Hospital of Heidelberg, Heidelberg, Germany
| | - Martina Sterneck
- Department of Hepatobiliary Surgery and Transplantation, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Severine Vermeire
- Department of Gastroenterology, University Hospital Gasthuisberg, Leuven, Belgium
| | - Ulrich Beuers
- Department of Gastroenterology and Hepatology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen and University of Groningen, Groningen, the Netherlands
| | - Erik Schrumpf
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Michael P. Manns
- Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany
- Integrated Research and Treatment Center-Transplantation (IFB-tx), Hannover Medical School, Hannover, Germany
| | - Konstantinos N. Lazaridis
- Center for Basic Research in Digestive Diseases, Division of Gastroenterology and Hepatology, Mayo Clinic, College of Medicine, Rochester, Minnesota, United States of America
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
- Department for General Internal Medicine, Christian-Albrechts-University, Kiel, Germany
| | - John F. Baines
- Institute for Experimental Medicine, Christian-Albrechts-University of Kiel, Kiel, Germany
- Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany
| | - Tom H. Karlsen
- Norwegian PSC research center, Department of transplantation medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Research institute for Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway
- Division of Gastroenterology, Institute of Medicine, University of Bergen, Bergen, Norway
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3636
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Billings LK, Hsu YH, Ackerman RJ, Dupuis J, Voight BF, Rasmussen-Torvik LJ, Hercberg S, Lathrop M, Barnes D, Langenberg C, Hui J, Fu M, Bouatia-Naji N, Lecoeur C, An P, Magnusson PK, Surakka I, Ripatti S, Christiansen L, Dalgård C, Folkersen L, Grundberg E, the MAGIC Investigators, the DIAGRAM + Consortium, the MuTHER Consortium, the ASCOT Investigators, the GEFOS Consortium, Eriksson P, Kaprio J, Ohm Kyvik K, Pedersen NL, Borecki IB, Province MA, Balkau B, Froguel P, Shuldiner AR, Palmer LJ, Wareham N, Meneton P, Johnson T, Pankow JS, Karasik D, Meigs JB, Kiel DP, Florez JC. Impact of common variation in bone-related genes on type 2 diabetes and related traits. Diabetes 2012; 61:2176-86. [PMID: 22698912 PMCID: PMC3402303 DOI: 10.2337/db11-1515] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Exploring genetic pleiotropy can provide clues to a mechanism underlying the observed epidemiological association between type 2 diabetes and heightened fracture risk. We examined genetic variants associated with bone mineral density (BMD) for association with type 2 diabetes and glycemic traits in large well-phenotyped and -genotyped consortia. We undertook follow-up analysis in ∼19,000 individuals and assessed gene expression. We queried single nucleotide polymorphisms (SNPs) associated with BMD at levels of genome-wide significance, variants in linkage disequilibrium (r(2) > 0.5), and BMD candidate genes. SNP rs6867040, at the ITGA1 locus, was associated with a 0.0166 mmol/L (0.004) increase in fasting glucose per C allele in the combined analysis. Genetic variants in the ITGA1 locus were associated with its expression in the liver but not in adipose tissue. ITGA1 variants appeared among the top loci associated with type 2 diabetes, fasting insulin, β-cell function by homeostasis model assessment, and 2-h post-oral glucose tolerance test glucose and insulin levels. ITGA1 has demonstrated genetic pleiotropy in prior studies, and its suggested role in liver fibrosis, insulin secretion, and bone healing lends credence to its contribution to both osteoporosis and type 2 diabetes. These findings further underscore the link between skeletal and glucose metabolism and highlight a locus to direct future investigations.
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Affiliation(s)
- Liana K. Billings
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts
| | - Yi-Hsiang Hsu
- Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, Massachusetts
- Molecular and Integrative Physiological Sciences Program, Harvard School of Public Health, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Rachel J. Ackerman
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
| | - Josée Dupuis
- Framingham Heart Study, Framingham, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Benjamin F. Voight
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Serge Hercberg
- INSERM, National Institute of Agronomic Research, University of Paris, Bobigny, France
| | - Mark Lathrop
- National Genotyping Center, Atomic Energy Commission, Institute of Genomics, Evry, France
| | - Daniel Barnes
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, U.K
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, U.K
| | - Jennie Hui
- Molecular Genetics, PathWest Laboratory Medicine of Western Australia, Nedlands, Western Australia, Australia
- School of Population Health and School of Pathology and Laboratory Medicine, University of Western Australia, Nedlands, Western Australia, Australia
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Mao Fu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Nabila Bouatia-Naji
- National Center for Scientific Research, UMR 8199, Genomics and Metabolic Diseases, Lille Pasteur Institute, Lille Nord de France University, Lille, France
| | - Cecile Lecoeur
- National Center for Scientific Research, UMR 8199, Genomics and Metabolic Diseases, Lille Pasteur Institute, Lille Nord de France University, Lille, France
| | - Ping An
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri
| | - Patrik K. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Ida Surakka
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Lene Christiansen
- Danish Twin Registry, Epidemiology, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Christine Dalgård
- Department of Environmental Medicine, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Lasse Folkersen
- Atherosclerosis Research Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Elin Grundberg
- Wellcome Trust Sanger Institute, Hinxton, U.K
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K
| | | | | | | | | | | | - Per Eriksson
- Atherosclerosis Research Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Unit for Child and Adolescent Mental Health, National Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Kirsten Ohm Kyvik
- Institute of Regional Health Services Research, University of Southern Denmark, Odense, Denmark
- Odense Patient Data Explorative Network, Odense University Hospital, Odense, Denmark
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Ingrid B. Borecki
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri
| | - Michael A. Province
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Beverley Balkau
- INSERM, CESP Center for Research in Epidemiology and Health of Populations, U1018, Epidemiology of Diabetes, Obesity and Chronic Kidney Disease Over the Life Course, INSERM, Villejuif, France and Université Paris-Sud 11, UMRS 1018, Villejuif, France
| | - Philippe Froguel
- National Center for Scientific Research, UMR 8199, Genomics and Metabolic Diseases, Lille Pasteur Institute, Lille Nord de France University, Lille, France
- Genomic Medicine, Hammersmith Hospital, Imperial College London, London, U.K
| | - Alan R. Shuldiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Geriatrics Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, Maryland
| | - Lyle J. Palmer
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Nick Wareham
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, U.K
| | | | - Toby Johnson
- Clinical Pharmacology and the Genome Centre, William Harvey Research Institute, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, U.K
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
| | - David Karasik
- Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - James B. Meigs
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Douglas P. Kiel
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, Massachusetts
- Framingham Heart Study, Framingham, Massachusetts
| | - Jose C. Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
- Corresponding author: Jose C. Florez,
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3637
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Williams WW, Salem RM, McKnight AJ, Sandholm N, Forsblom C, Taylor A, Guiducci C, McAteer JB, McKay GJ, Isakova T, Brennan EP, Sadlier DM, Palmer C, Söderlund J, Fagerholm E, Harjutsalo V, Lithovius R, Gordin D, Hietala K, Kytö J, Parkkonen M, Rosengård-Bärlund M, Thorn L, Syreeni A, Tolonen N, Saraheimo M, Wadén J, Pitkäniemi J, Sarti C, Tuomilehto J, Tryggvason K, Österholm AM, He B, Bain S, Martin F, Godson C, Hirschhorn JN, Maxwell AP, Groop PH, Florez JC, for the GENIE Consortium . Association testing of previously reported variants in a large case-control meta-analysis of diabetic nephropathy. Diabetes 2012; 61:2187-94. [PMID: 22721967 PMCID: PMC3402313 DOI: 10.2337/db11-0751] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
We formed the GEnetics of Nephropathy-an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10(-9)). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated.
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Affiliation(s)
- Winfred W. Williams
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Rany M. Salem
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Amy Jayne McKnight
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Biomedical Engineering and Computational Science, Aalto University, Helsinki, Finland
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Andrew Taylor
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Candace Guiducci
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Jarred B. McAteer
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Gareth J. McKay
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Tamara Isakova
- Division of Nephrology, University of Miami, Miller School of Medicine, Miami, Florida
| | - Eoin P. Brennan
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Denise M. Sadlier
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
- Mater University Hospital, Dublin, Ireland
| | - Cameron Palmer
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Jenny Söderlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Emma Fagerholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, Welfare and Health Promotion Division, National Institute for Health and Welfare, Helsinki, Finland
| | - Raija Lithovius
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Daniel Gordin
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Kustaa Hietala
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Kytö
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Maija Parkkonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Milla Rosengård-Bärlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Lena Thorn
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Nina Tolonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Markku Saraheimo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Johan Wadén
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Pitkäniemi
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Cinzia Sarti
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Chronic Disease Prevention, Welfare and Health Promotion Division, National Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- South Ostrobothnia Central Hospital, Seinäjoki, Finland
| | - Karl Tryggvason
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Anne-May Österholm
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Bing He
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Steve Bain
- Institute of Life Sciences, Swansea University, Swansea, U.K
| | - Finian Martin
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Biomolecular and Biomedical Sciences, University College Dublin, Belfield, Dublin, Ireland
| | - Catherine Godson
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Joel N. Hirschhorn
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Alexander P. Maxwell
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Jose C. Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Corresponding author: Jose C. Florez,
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3638
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Hamilton G, Killick R, Lambert JC, Amouyel P, Carrasquillo MM, Pankratz VS, Graff-Radford NR, Dickson DW, Petersen RC, Younkin SG, Powell JF, Wade-Martins R. Functional and genetic analysis of haplotypic sequence variation at the nicastrin genomic locus. Neurobiol Aging 2012; 33:1848.e1-13. [PMID: 22405046 PMCID: PMC3683320 DOI: 10.1016/j.neurobiolaging.2012.02.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2011] [Revised: 01/19/2012] [Accepted: 02/04/2012] [Indexed: 11/23/2022]
Abstract
Nicastrin (NCSTN) is a component of the γ-secretase complex and therefore potentially a candidate risk gene for Alzheimer's disease. Here, we have developed a novel functional genomics methodology to express common locus haplotypes to assess functional differences. DNA recombination was used to engineer 5 bacterial artificial chromosomes (BACs) to each express a different haplotype of the NCSTN locus. Each NCSTN-BAC was delivered to knockout nicastrin (Ncstn(-/-)) cells and clonal NCSTN-BAC(+)/Ncstn(-/-) cell lines were created for functional analyses. We showed that all NCSTN-BAC haplotypes expressed nicastrin protein and rescued γ-secretase activity and amyloid beta (Aβ) production in NCSTN-BAC(+)/Ncstn(-/-) lines. We then showed that genetic variation at the NCSTN locus affected alternative splicing in human postmortem brain tissue. However, there was no robust functional difference between clonal cell lines rescued by each of the 5 different haplotypes. Finally, there was no statistically significant association of NCSTN with disease risk in the 4 cohorts. We therefore conclude that it is unlikely that common variation at the NCSTN locus is a risk factor for Alzheimer's disease.
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Affiliation(s)
- Gillian Hamilton
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK.
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3639
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Stevens KN, Lindstrom S, Scott CG, Thompson D, Sellers TA, Wang X, Wang A, Atkinson E, Rider DN, Eckel-Passow JE, Varghese JS, Audley T, Brown J, Leyland J, Luben RN, Warren RM, Loos RJ, Wareham NJ, Li J, Hall P, Liu J, Eriksson L, Czene K, Olson JE, Shane Pankratz V, Fredericksen Z, Diasio RB, Lee AM, Heit JA, deAndrade M, Goode EL, Vierkant RA, Cunningham JM, Armasu SM, Weinshilboum R, Fridley BL, Batzler A, Ingle JN, Boyd NF, Paterson AD, Rommens J, Martin LJ, Hopper JL, Southey MC, Stone J, Apicella C, Kraft P, Hankinson SE, Hazra A, Hunter DJ, Easton DF, Couch FJ, Tamimi RM, Vachon CM. Identification of a novel percent mammographic density locus at 12q24. Hum Mol Genet 2012; 21:3299-305. [PMID: 22532574 PMCID: PMC3384385 DOI: 10.1093/hmg/dds158] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2012] [Revised: 03/29/2012] [Accepted: 04/17/2012] [Indexed: 11/13/2022] Open
Abstract
Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10(-8)). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10(-8)). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.
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Affiliation(s)
| | - Sara Lindstrom
- Department of Epidemiology
- Program in Molecular and Genetic Epidemiology and
- Department of Biostatistics, Harvard School Of Public Health, Boston, MA 02138, USA
| | | | - Deborah Thompson
- Department of Public Health and Primary Care
- Department of Oncology and
| | - Thomas A. Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA
| | | | | | | | | | | | | | - Tina Audley
- Department of Public Health and Primary Care
- Department of Oncology and
| | - Judith Brown
- Department of Public Health and Primary Care
- Department of Oncology and
| | - Jean Leyland
- Department of Public Health and Primary Care
- Department of Oncology and
| | - Robert N. Luben
- Department of Public Health and Primary Care
- Department of Oncology and
| | - Ruth M.L. Warren
- Department of Radiology, University of Cambridge, Addenbrooke's NHS Foundation Trust, Cambridge CB2 1TN, UK
| | - Ruth J.F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 1TN, UK
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 1TN, UK
| | - Jingmei Li
- Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm SE-171 77, Sweden
| | - Jianjun Liu
- Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm SE-171 77, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm SE-171 77, Sweden
| | | | | | | | - Robert B. Diasio
- Department of Molecular Pharmacology and Experimental Therapeutics
| | - Adam M. Lee
- Department of Molecular Pharmacology and Experimental Therapeutics
| | - John A. Heit
- Division of Cardiovascular Disease, Department of Medicine
| | | | | | | | | | | | - Richard Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics and
| | | | | | - James N. Ingle
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Norman F. Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, CanadaM5G 2M9
| | - Andrew D. Paterson
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, CanadaM5S 1A1
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, CanadaM5G 1X8
| | - Johanna Rommens
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, CanadaM5G 1X8
| | - Lisa J. Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, CanadaM5G 2M9
| | - John L. Hopper
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology School of Population Health, The University of Melbourne, Melbourne 3010, Australia
| | - Melissa C. Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne 3010, Australia and
| | - Jennifer Stone
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology School of Population Health, The University of Melbourne, Melbourne 3010, Australia
| | - Carmel Apicella
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology School of Population Health, The University of Melbourne, Melbourne 3010, Australia
| | - Peter Kraft
- Department of Epidemiology
- Program in Molecular and Genetic Epidemiology and
- Department of Biostatistics, Harvard School Of Public Health, Boston, MA 02138, USA
| | - Susan E. Hankinson
- Department of Epidemiology
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02138, USA
| | - Aditi Hazra
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02138, USA
| | - David J. Hunter
- Department of Epidemiology
- Program in Molecular and Genetic Epidemiology and
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02138, USA
| | - Douglas F. Easton
- Department of Public Health and Primary Care
- Department of Oncology and
| | | | - Rulla M. Tamimi
- Department of Epidemiology
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02138, USA
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3640
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Tang W, Schwienbacher C, Lopez L, Ben-Shlomo Y, Oudot-Mellakh T, Johnson A, Samani N, Basu S, Gögele M, Davies G, Lowe G, Tregouet DA, Tan A, Pankow J, Tenesa A, Levy D, Volpato C, Rumley A, Gow A, Minelli C, Yarnell J, Porteous D, Starr J, Gallacher J, Boerwinkle E, Visscher P, Pramstaller P, Cushman M, Emilsson V, Plump A, Matijevic N, Morange PE, Deary I, Hicks A, Folsom A. Genetic associations for activated partial thromboplastin time and prothrombin time, their gene expression profiles, and risk of coronary artery disease. Am J Hum Genet 2012; 91:152-62. [PMID: 22703881 DOI: 10.1016/j.ajhg.2012.05.009] [Citation(s) in RCA: 73] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2011] [Revised: 04/10/2012] [Accepted: 05/05/2012] [Indexed: 10/28/2022] Open
Abstract
Activated partial thromboplastin time (aPTT) and prothrombin time (PT) are clinical tests commonly used to screen for coagulation-factor deficiencies. One genome-wide association study (GWAS) has been reported previously for aPTT, but no GWAS has been reported for PT. We conducted a GWAS and meta-analysis to identify genetic loci for aPTT and PT. The GWAS for aPTT was conducted in 9,240 individuals of European ancestry from the Atherosclerosis Risk in Communities (ARIC) study, and the GWAS for PT was conducted in 2,583 participants from the Genetic Study of Three Population Microisolates in South Tyrol (MICROS) and the Lothian Birth Cohorts (LBC) of 1921 and 1936. Replication was assessed in 1,041 to 3,467 individuals. For aPTT, previously reported associations with KNG1, HRG, F11, F12, and ABO were confirmed. A second independent association in ABO was identified and replicated (rs8176704, p = 4.26 × 10(-24)). Pooling the ARIC and replication data yielded two additional loci in F5 (rs6028, p = 3.22 × 10(-9)) and AGBL1 (rs2469184, p = 3.61 × 10(-8)). For PT, significant associations were identified and confirmed in F7 (rs561241, p = 3.71 × 10(-56)) and PROCR/EDEM2 (rs2295888, p = 5.25 × 10(-13)). Assessment of existing gene expression and coronary artery disease (CAD) databases identified associations of five of the GWAS loci with altered gene expression and two with CAD. In summary, eight genetic loci that account for ∼29% of the variance in aPTT and two loci that account for ∼14% of the variance in PT were detected and supported by functional data.
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3641
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Zhang LS, Hu HG, Liu YJ, Li J, Yu P, Zhang F, Yang TL, Tian Q, Zheng YP, Guo Y, Deng HW. A follow-up association study of two genetic variants for bone mineral density variation in Caucasians. Osteoporos Int 2012; 23:1867-1875. [PMID: 22159821 PMCID: PMC3682467 DOI: 10.1007/s00198-011-1863-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2011] [Accepted: 09/12/2011] [Indexed: 10/14/2022]
Abstract
SUMMARY We tested whether two genetic variants were associated with BMD at multiple clinically relevant skeletal sites in Caucasians. We found that variant rs7776725 is consistently associated with hip, spine, wrist and whole-body BMD, which highlights the potential importance of this variant or linked variants for osteoporosis. INTRODUCTION A recent genome-wide association study identified two single nucleotide polymorphisms (SNPs), rs7776725 and rs1721400, that were associated with bone mineral density (BMD) variation at the radius, tibia and calcaneus in a Korean population. In this study, we aimed to test whether the association of these two genetic variants can be replicated in Caucasians and whether their association with BMD can be extended to other clinically relevant skeletal sites. METHODS We performed this study in two large cohorts of unrelated US Caucasians. Area BMD at the hip, spine, wrist (ultra-distal radius) and whole body were measured with Hologic dual-energy X-ray absorptiometer. SNPs were genotyped with Affymetrix human genome-wide genotyping arrays. Association analyses were performed using PLINK. RESULTS We detected highly significant association (combined p = 1.42 × 10(-16)) of rs7776725 with wrist BMD but only borderline association signal (combined p = 0.017) for rs1721400 with wrist BMD. In addition, we found that rs7776725 was associated with BMD at the hip, spine and whole body. At the FAM3C gene locus where rs7776725 was located, we identified several other SNPs (rs4727922, rs1803389, rs718766 and rs7793554) that were also associated with BMD. CONCLUSIONS This is the first follow-up association study of rs7776725 and rs1721400 with BMD. The rs7776725 showed consistent association with BMD at multiple clinically important skeletal sites, which highlighted the potential importance of rs7776725 or linked SNPs for risk of osteoporosis. Further in-depth re-sequencing studies and functional assays are necessary to elucidate the underlying mechanisms.
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Affiliation(s)
- L-S Zhang
- College of Life Sciences and Bioengineering, School of Science, Beijing Jiaotong University, Beijing, 100044, People's Republic of China
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3642
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Lu X, Wang L, Chen S, He L, Yang X, Shi Y, Cheng J, Zhang L, Gu CC, Huang J, Wu T, Ma Y, Li J, Cao J, Chen J, Ge D, Fan Z, Li Y, Zhao L, Li H, Zhou X, Chen L, Liu D, Chen J, Duan X, Hao Y, Wang L, Lu F, Liu Z, Yao C, Shen C, Pu X, Yu L, Fang X, Xu L, Mu J, Wu X, Zheng R, Wu N, Zhao Q, Li Y, Liu X, Wang M, Yu D, Hu D, Ji X, Guo D, Sun D, Wang Q, Yang Y, Liu F, Mao Q, Liang X, Ji J, Chen P, Mo X, Li D, Chai G, Tang Y, Li X, Du Z, Liu X, Dou C, Yang Z, Meng Q, Wang D, Wang R, Yang J, Schunkert H, Samani NJ, Kathiresan S, Reilly MP, Erdmann J, Peng X, Wu X, Liu D, Yang Y, Chen R, Qiang B, Gu D. Genome-wide association study in Han Chinese identifies four new susceptibility loci for coronary artery disease. Nat Genet 2012; 44:890-894. [PMID: 22751097 PMCID: PMC3927410 DOI: 10.1038/ng.2337] [Citation(s) in RCA: 261] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2012] [Accepted: 06/05/2012] [Indexed: 02/07/2023]
Abstract
We performed a meta-analysis of 2 genome-wide association studies of coronary artery disease comprising 1,515 cases and 5,019 controls followed by replication studies in 15,460 cases and 11,472 controls, all of Chinese Han ancestry. We identify four new loci for coronary artery disease that reached the threshold of genome-wide significance (P < 5 × 10(-8)). These loci mapped in or near TTC32-WDR35, GUCY1A3, C6orf10-BTNL2 and ATP2B1. We also replicated four loci previously identified in European populations (in or near PHACTR1, TCF21, CDKN2A-CDKN2B and C12orf51). These findings provide new insights into pathways contributing to the susceptibility for coronary artery disease in the Chinese Han population.
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Affiliation(s)
- Xiangfeng Lu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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3643
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Doumatey AP, Chen G, Tekola Ayele F, Zhou J, Erdos M, Shriner D, Huang H, Adeleye J, Balogun W, Fasanmade O, Johnson T, Oli J, Okafor G, Amoah A, Eghan BA, Agyenim-Boateng K, Acheampong J, Adebamowo C, Gerry NP, Christman MF, Adeyemo A, Rotimi CN. C-reactive protein (CRP) promoter polymorphisms influence circulating CRP levels in a genome-wide association study of African Americans. Hum Mol Genet 2012; 21:3063-72. [PMID: 22492993 PMCID: PMC3373247 DOI: 10.1093/hmg/dds133] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2012] [Revised: 03/16/2012] [Accepted: 04/02/2012] [Indexed: 01/05/2023] Open
Abstract
C-reactive protein (CRP) is an acute phase reactant protein produced primarily by the liver. Circulating CRP levels are influenced by genetic and non-genetic factors, including infection and obesity. Genome-wide association studies (GWAS) provide an unbiased approach towards identifying loci influencing CRP levels. None of the six GWAS for CRP levels has been conducted in an African ancestry population. The present study aims to: (i) identify genetic variants that influence serum CRP in African Americans (AA) using a genome-wide association approach and replicate these findings in West Africans (WA), (ii) assess transferability of major signals for CRP reported in European ancestry populations (EA) to AA and (iii) use the weak linkage disequilibrium (LD) structure characteristic of African ancestry populations to fine-map the previously reported CRP locus. The discovery cohort comprised 837 unrelated AA, with the replication of significant single-nucleotide polymorphisms (SNPs) assessed in 486 WA. The association analysis was conducted with 2 366 856 genotyped and imputed SNPs under an additive genetic model with adjustment for appropriate covariates. Genome-wide and replication significances were set at P < 5 × 10(-8) and P < 0.05, respectively. Ten SNPs in (CRP pseudogene-1) CRPP1 and CRP genes were associated with serum CRP (P = 2.4 × 10(-09) to 4.3 × 10(-11)). All but one of the top-scoring SNPs associated with CRP in AA were successfully replicated in WA. CRP signals previously identified in EA samples were transferable to AAs, and we were able to fine-map this signal, reducing the region of interest from the 25 kb of LD around the locus in the HapMap CEU sample to only 8 kb in our AA sample.
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Affiliation(s)
- Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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3644
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Wang S, Adrianto I, Wiley GB, Lessard CJ, Kelly JA, Adler AJ, Glenn SB, Williams AH, Ziegler JT, Comeau ME, Marion MC, Wakeland BE, Liang C, Kaufman KM, Guthridge JM, Alarcón-Riquelme ME, on behalf of the BIOLUPUS and GENLES Networks, Alarcón GS, Anaya JM, Bae SC, Kim JH, Joo YB, Boackle SA, Brown EE, Petri MA, Ramsey-Goldman R, Reveille JD, Vilá LM, Criswell LA, Edberg JC, Freedman BI, Gilkeson GS, Jacob CO, James JA, Kamen DL, Kimberly RP, Martin J, Merrill JT, Niewold TB, Pons-Estel BA, Scofield RH, Stevens AM, Tsao BP, Vyse TJ, Langefeld CD, Harley JB, Wakeland EK, Moser KL, Montgomery CG, Gaffney PM. A functional haplotype of UBE2L3 confers risk for systemic lupus erythematosus. Genes Immun 2012; 13:380-7. [PMID: 22476155 PMCID: PMC3411915 DOI: 10.1038/gene.2012.6] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2011] [Revised: 02/29/2012] [Accepted: 03/06/2012] [Indexed: 02/07/2023]
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse clinical manifestations characterized by the development of pathogenic autoantibodies manifesting in inflammation of target organs such as the kidneys, skin and joints. Genome-wide association studies have identified genetic variants in the UBE2L3 region that are associated with SLE in subjects of European and Asian ancestry. UBE2L3 encodes an ubiquitin-conjugating enzyme, UBCH7, involved in cell proliferation and immune function. In this study, we sought to further characterize the genetic association in the region of UBE2L3 and use molecular methods to determine the functional effect of the risk haplotype. We identified significant associations between variants in the region of UBE2L3 and SLE in individuals of European and Asian ancestry that exceeded a Bonferroni-corrected threshold (P<1 × 10(-4)). A single risk haplotype was observed in all associated populations. Individuals harboring the risk haplotype display a significant increase in both UBE2L3 mRNA expression (P=0.0004) and UBCH7 protein expression (P=0.0068). The results suggest that variants carried on the SLE-associated UBE2L3 risk haplotype influence autoimmunity by modulating UBCH7 expression.
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Affiliation(s)
- Shaofeng Wang
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Indra Adrianto
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Graham B. Wiley
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Christopher J. Lessard
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
- College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Jennifer A. Kelly
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Adam J. Adler
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Stuart B. Glenn
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Adrienne H. Williams
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Julie T. Ziegler
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Mary E. Comeau
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Miranda C. Marion
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Benjamin E. Wakeland
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Chaoying Liang
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Kenneth M. Kaufman
- Division of Rheumatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- US Department of Veterans Affairs Medical Center, Cincinnati, OH
| | - Joel M. Guthridge
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Marta E. Alarcón-Riquelme
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
- Centro de Genómica e Investigaciones Oncológicas (GENyO), Pfizer-Universidad de Granada-Junta de Andalucía Granada, Spain
| | | | | | - Juan-Manuel Anaya
- Center for Autoimmune Diseases Research (CREA), Universidad del Rosario, Bogotá, Colombia
| | - Sang-Cheol Bae
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
| | - Jae-Hoon Kim
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
| | - Young Bin Joo
- Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
| | - Susan A. Boackle
- Division of Rheumatology, University of Colorado Denver, Aurora, CO
| | - Elizabeth E. Brown
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - Michelle A. Petri
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - John D. Reveille
- Rheumatology and Clinical Immunogenetics, University of Texas Health Science Center at Houston, Houston, TX
| | - Luis M. Vilá
- Department of Medicine, Division of Rheumatology, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico
| | - Lindsey A. Criswell
- Rosalind Russell Medical Research Center for Arthritis, University of California San Francisco, San Francisco, CA
| | - Jeffrey C. Edberg
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Barry I. Freedman
- Department of Internal Medicine/Nephrology, Wake Forest School of Medicine, Winston-Salem, NC
| | - Gary S. Gilkeson
- Division of Rheumatology, Medical University of South Carolina, Charleston, SC
| | - Chaim O. Jacob
- Department of Medicine, University of Southern California, Los Angeles, CA
| | - Judith A. James
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
- College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Diane L. Kamen
- Division of Rheumatology, Medical University of South Carolina, Charleston, SC
| | - Robert P. Kimberly
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Javier Martin
- Instituto de Parasitología y Biomedicina “López-Neyra”, Consejo Superior de Investigaciones Científicas (CSIC), Granada, Spain
| | - Joan T. Merrill
- Clinical Pharmacology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Timothy B. Niewold
- Section of Rheumatology and Gwen Knapp Center for Lupus and Immunology Research, University of Chicago, Chicago, IL
| | | | - R. Hal Scofield
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
- College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Anne M. Stevens
- Division of Rheumatology, Department of Pediatrics, University of Washington, Seattle, WA
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA
| | - Betty P. Tsao
- Division of Rheumatology, Department of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Timothy J. Vyse
- Divisions of Genetics and Molecular Medicine and Immunology, Infection and Inflammatory Diseases, King’s College London, London, UK
| | - Carl D. Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - John B. Harley
- Division of Rheumatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
- US Department of Veterans Affairs Medical Center, Cincinnati, OH
| | - Edward K. Wakeland
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX
| | - Kathy L. Moser
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
- College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Courtney G. Montgomery
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
| | - Patrick M. Gaffney
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK
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3645
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Melville SA, Buros J, Parrado AR, Vardarajan B, Logue MW, Shen L, Risacher SL, Kim S, Jun G, DeCarli C, Lunetta KL, Baldwin CT, Saykin AJ, Farrer LA. Multiple loci influencing hippocampal degeneration identified by genome scan. Ann Neurol 2012; 72:65-75. [PMID: 22745009 DOI: 10.1002/ana.23644] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2012] [Revised: 04/17/2012] [Accepted: 05/09/2012] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Large genome-wide association studies (GWASs) have identified many novel genes influencing Alzheimer disease (AD) risk, but most of the genetic variance remains unexplained. We conducted a 2-stage GWAS for AD-related quantitative measures of hippocampal volume (HV), total cerebral volume (TCV), and white matter hyperintensities (WMH). METHODS Brain magnetic resonance imaging measures of HV, TCV, and WMH were obtained from 981 Caucasian and 419 African American AD cases and their cognitively normal siblings in the MIRAGE (Multi Institutional Research in Alzheimer's Genetic Epidemiology) Study, and from 168 AD cases, 336 individuals with mild cognitive impairment, and 188 controls in the Alzheimer's Disease Neuroimaging Initiative Study. A GWAS for each trait was conducted in the 2 Caucasian data sets in stage 1. Results from the 2 data sets were combined by meta-analysis. In stage 2, 1 single nucleotide polymorphism (SNP) from each region that was nominally significant in each data set (p < 0.05) and strongly associated in both data sets (p < 1.0 × 10(-5)) was evaluated in the African American data set. RESULTS Twenty-two markers (14 for HV, 3 for TCV, and 5 for WMH) from distinct regions met criteria for evaluation in stage 2. Novel genome-wide significant associations (p < 5.0 × 10(-8)) were attained for HV with SNPs in the APOE, F5/SELP, LHFP, and GCFC2 gene regions. All of these associations were supported by evidence in each data set. Associations with different SNPs in the same gene (p < 1 × 10(-5) in Caucasians and p < 2.2 × 10(-4) in African Americans) were also observed for PICALM with HV, SYNPR with TCV, and TTC27 with WMH. INTERPRETATION Our study demonstrates the efficacy of endophenotypes for broadening our understanding of the genetic basis of AD.
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Affiliation(s)
- Scott A Melville
- Department of Medicine, Boston University School of Medicine, MA, USA
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3646
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Allen M, Zou F, Chai HS, Younkin CS, Crook J, Pankratz VS, Carrasquillo MM, Rowley CN, Nair AA, Middha S, Maharjan S, Nguyen T, Ma L, Malphrus KG, Palusak R, Lincoln S, Bisceglio G, Georgescu C, Schultz D, Rakhshan F, Kolbert CP, Jen J, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Schellenberg GD, Petersen RC, Graff-Radford NR, Dickson DW, Younkin SG, Ertekin-Taner N, Apostolova LG, Arnold SE, Baldwin CT, Barber R, Barmada MM, Beach T, Beecham GW, Beekly D, Bennett DA, Bigio EH, Bird TD, Blacker D, Boeve BF, Bowen JD, Boxer A, Burke JR, Buros J, Buxbaum JD, Cairns NJ, Cantwell LB, Cao C, Carlson CS, Carney RM, Carroll SL, Chui HC, Clark DG, Corneveaux J, Cotman CW, Crane PK, Cruchaga C, Cummings JL, De Jager PL, DeCarli C, DeKosky ST, Demirci FY, Diaz-Arrastia R, Dick M, Dombroski BA, Duara R, Ellis WD, Evans D, Faber KM, Fallon KB, Farlow MR, Ferris S, Foroud TM, Frosch M, Galasko DR, Gallins PJ, Ganguli M, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Gilman S, Giordani B, Glass JD, Goate AM, Green RC, Growdon JH, Hakonarson H, Hamilton RL, Hardy J, Harrell LE, Head E, Honig LS, Huentelman MJ, et alAllen M, Zou F, Chai HS, Younkin CS, Crook J, Pankratz VS, Carrasquillo MM, Rowley CN, Nair AA, Middha S, Maharjan S, Nguyen T, Ma L, Malphrus KG, Palusak R, Lincoln S, Bisceglio G, Georgescu C, Schultz D, Rakhshan F, Kolbert CP, Jen J, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Schellenberg GD, Petersen RC, Graff-Radford NR, Dickson DW, Younkin SG, Ertekin-Taner N, Apostolova LG, Arnold SE, Baldwin CT, Barber R, Barmada MM, Beach T, Beecham GW, Beekly D, Bennett DA, Bigio EH, Bird TD, Blacker D, Boeve BF, Bowen JD, Boxer A, Burke JR, Buros J, Buxbaum JD, Cairns NJ, Cantwell LB, Cao C, Carlson CS, Carney RM, Carroll SL, Chui HC, Clark DG, Corneveaux J, Cotman CW, Crane PK, Cruchaga C, Cummings JL, De Jager PL, DeCarli C, DeKosky ST, Demirci FY, Diaz-Arrastia R, Dick M, Dombroski BA, Duara R, Ellis WD, Evans D, Faber KM, Fallon KB, Farlow MR, Ferris S, Foroud TM, Frosch M, Galasko DR, Gallins PJ, Ganguli M, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Gilman S, Giordani B, Glass JD, Goate AM, Green RC, Growdon JH, Hakonarson H, Hamilton RL, Hardy J, Harrell LE, Head E, Honig LS, Huentelman MJ, Hulette CM, Hyman BT, Jarvik GP, Jicha GA, Jin LW, Jun G, Kamboh MI, Karlawish J, Karydas A, Kauwe JSK, Kaye JA, Kennedy N, Kim R, Koo EH, Kowall NW, Kramer P, Kukull WA, Lah JJ, Larson EB, Levey AI, Lieberman AP, Lopez OL, Lunetta KL, Mack WJ, Marson DC, Martin ER, Martiniuk F, Mash DC, Masliah E, McCormick WC, McCurry SM, McDavid AN, McKee AC, Mesulam M, Miller BL, Miller CA, Miller JW, Montine TJ, Morris JC, Myers AJ, Naj AC, Nowotny P, Parisi JE, Perl DP, Peskind E, Poon WW, Potter H, Quinn JF, Raj A, Rajbhandary RA, Raskind M, Reiman EM, Reisberg B, Reitz C, Ringman JM, Roberson ED, Rogaeva E, Rosenberg RN, Sano M, Saykin AJ, Schneider JA, Schneider LS, Seeley W, Shelanski ML, Slifer MA, Smith CD, Sonnen JA, Spina S, St George-Hyslop P, Stern RA, Tanzi RE, Trojanowski JQ, Troncoso JC, Tsuang DW, Van Deerlin VM, Vardarajan BN, Vinters HV, Vonsattel JP, Wang LS, Weintraub S, Welsh-Bohmer KA, Williamson J, Woltjer RL. Novel late-onset Alzheimer disease loci variants associate with brain gene expression. Neurology 2012; 79:221-8. [PMID: 22722634 DOI: 10.1212/wnl.0b013e3182605801] [Show More Authors] [Citation(s) in RCA: 126] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE Recent genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) identified 9 novel risk loci. Discovery of functional variants within genes at these loci is required to confirm their role in Alzheimer disease (AD). Single nucleotide polymorphisms that influence gene expression (eSNPs) constitute an important class of functional variants. We therefore investigated the influence of the novel LOAD risk loci on human brain gene expression. METHODS We measured gene expression levels in the cerebellum and temporal cortex of autopsied AD subjects and those with other brain pathologies (∼400 total subjects). To determine whether any of the novel LOAD risk variants are eSNPs, we tested their cis-association with expression of 6 nearby LOAD candidate genes detectable in human brain (ABCA7, BIN1, CLU, MS4A4A, MS4A6A, PICALM) and an additional 13 genes ±100 kb of these SNPs. To identify additional eSNPs that influence brain gene expression levels of the novel candidate LOAD genes, we identified SNPs ±100 kb of their location and tested for cis-associations. RESULTS CLU rs11136000 (p = 7.81 × 10(-4)) and MS4A4A rs2304933/rs2304935 (p = 1.48 × 10(-4)-1.86 × 10(-4)) significantly influence temporal cortex expression levels of these genes. The LOAD-protective CLU and risky MS4A4A locus alleles associate with higher brain levels of these genes. There are other cis-variants that significantly influence brain expression of CLU and ABCA7 (p = 4.01 × 10(-5)-9.09 × 10(-9)), some of which also associate with AD risk (p = 2.64 × 10(-2)-6.25 × 10(-5)). CONCLUSIONS CLU and MS4A4A eSNPs may at least partly explain the LOAD risk association at these loci. CLU and ABCA7 may harbor additional strong eSNPs. These results have implications in the search for functional variants at the novel LOAD risk loci.
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Affiliation(s)
- Mariet Allen
- Department of Neuroscience, Biostatistics Unit, Mayo Clinic Florida, Jacksonville, FL, USA
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3647
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Sung H, Zhang B, Choi JY, Long J, Park SK, Yoo KY, Noh DY, Ahn SH, Zheng W, Kang D. Common genetic variants in the microRNA biogenesis pathway are not associated with breast cancer risk in Asian women. Cancer Epidemiol Biomarkers Prev 2012; 21:1385-7. [PMID: 22714736 DOI: 10.1158/1055-9965.epi-12-0600] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Although the role of miRNA in cancer development and progression has been well established, the association between genetic variants in miRNA biogenesis pathway genes and breast cancer risk has been yet unclear. METHODS We analyzed data from two genome-wide association studies conducted in East Asian women including 5,066 cases and 4,337 controls. Among the single-nucleotide polymorphisms (SNP), which were directly genotyped or imputed, we selected 237 SNPs in 32 genes involved in miRNA biogenesis pathway and its regulation. RESULTS Although eight SNPs were nominally associated with breast cancer risk in combined samples (P < 0.05), none of them were significant after adjustment for multiple comparisons. CONCLUSIONS The common genetic variants in miRNA biogenesis pathway genes may not be associated with breast cancer risk. IMPACT This study suggests no association between the polymorphisms in miRNA biogenesis pathway genes and breast cancer risk. Studies with large sample size and more genetic variants should be warranted to adequately evaluate the potential association.
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Affiliation(s)
- Hyuna Sung
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
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3648
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Zou F, Chai HS, Younkin CS, Allen M, Crook J, Pankratz VS, Carrasquillo MM, Rowley CN, Nair AA, Middha S, Maharjan S, Nguyen T, Ma L, Malphrus KG, Palusak R, Lincoln S, Bisceglio G, Georgescu C, Kouri N, Kolbert CP, Jen J, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Schellenberg GD, Alzheimer's Disease Genetics Consortium, Petersen RC, Graff-Radford NR, Dickson DW, Younkin SG, Ertekin-Taner N. Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants. PLoS Genet 2012; 8:e1002707. [PMID: 22685416 PMCID: PMC3369937 DOI: 10.1371/journal.pgen.1002707] [Citation(s) in RCA: 176] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Accepted: 03/27/2012] [Indexed: 02/06/2023] Open
Abstract
Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n = 197, temporal cortex n = 202) and with other brain pathologies (non–AD, cerebellar n = 177, temporal cortex n = 197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non–ADs (q<0.05, p = 7.70×10−5–1.67×10−82). Of these, 2,089 were also significant in the temporal cortex (p = 1.85×10−5–1.70×10−141). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10−6). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinson's disease (PD) MMRN1/rs6532197, Paget's disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10−6) of significant cisSNPs with suggestive AD–risk association (p<10−3) in the Alzheimer's Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics. Genetic variants that regulate gene expression levels can also influence human disease risk. Discovery of genomic loci that alter brain gene expression levels (brain expression quantitative trait loci = eQTLs) can be instrumental in the identification of genetic risk underlying both central nervous system (CNS) and non–CNS diseases. To systematically assess the role of brain eQTLs in human disease and to evaluate the influence of brain region and pathology in eQTL mapping, we performed an expression genome-wide association study (eGWAS) in 773 brain samples from the cerebellum and temporal cortex of ∼200 autopsied subjects with Alzheimer's disease (AD) and ∼200 with other brain pathologies (non–AD). We identified ∼3,000 significant associations between cisSNPs near ∼700 genes and their cerebellar transcript levels, which replicate in ADs and non–ADs. More than 2,000 of these associations were reproducible in the temporal cortex. The top cisSNPs are enriched for both CNS and non–CNS disease-associated variants. We identified novel and confirmed previous cisSNP/transcript associations for many disease loci, suggesting gene expression regulation as their mechanism of action. These findings demonstrate the reproducibility of the eQTL approach across different brain regions and pathologies, and advocate the combined use of gene expression and disease GWAS for identification and functional characterization of human disease-associated variants.
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Affiliation(s)
- Fanggeng Zou
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - High Seng Chai
- Department of Biostatistics, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Curtis S. Younkin
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Julia Crook
- Department of Biostatistics, Mayo Clinic, Jacksonville, Florida, United States of America
| | - V. Shane Pankratz
- Department of Biostatistics, Mayo Clinic, Rochester, Minnesota, United States of America
| | | | - Christopher N. Rowley
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Asha A. Nair
- Department of Biostatistics, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Sumit Middha
- Department of Biostatistics, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Sooraj Maharjan
- Department of Biostatistics, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Thuy Nguyen
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Li Ma
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Kimberly G. Malphrus
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Ryan Palusak
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Sarah Lincoln
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Gina Bisceglio
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Constantin Georgescu
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | | | - Jin Jen
- Microarray Core, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Jonathan L. Haines
- Department of Molecular Physiology and Biophysics and Vanderbilt Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Richard Mayeux
- Gertrude H. Sergievsky Center, Department of Neurology, and Taub Institute on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, United States of America
| | - Margaret A. Pericak-Vance
- The John P. Hussman Institute for Human Genomics and Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, Florida, United States of America
| | - Lindsay A. Farrer
- Departments of Biostatistics, Medicine (Genetics Program), Ophthalmology, Neurology, and Epidemiology, Boston University, Boston, Massachusetts, United States of America
| | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | | | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
| | | | - Dennis W. Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Steven G. Younkin
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, United States of America
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, United States of America
- * E-mail:
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3649
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Prescott J, Thompson DJ, Kraft P, Chanock SJ, Audley T, Brown J, Leyland J, Folkerd E, Doody D, Hankinson SE, Hunter DJ, Jacobs KB, Dowsett M, Cox DG, Easton DF, De Vivo I. Genome-wide association study of circulating estradiol, testosterone, and sex hormone-binding globulin in postmenopausal women. PLoS One 2012; 7:e37815. [PMID: 22675492 PMCID: PMC3366971 DOI: 10.1371/journal.pone.0037815] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2012] [Accepted: 04/24/2012] [Indexed: 01/20/2023] Open
Abstract
Genome-wide association studies (GWAS) have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG) levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS) data from the Nurses’ Health Study (NHS), and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ∼1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint β = -0.126; joint P = 2.09×10–16), downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10–5), several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ∼900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10–5 was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.
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Affiliation(s)
- Jennifer Prescott
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Deborah J. Thompson
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Peter Kraft
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America
| | - Tina Audley
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Judith Brown
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jean Leyland
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Elizabeth Folkerd
- Academic Department of Biochemistry, Royal Marsden Hospital, London, United Kingdom
| | - Deborah Doody
- Academic Department of Biochemistry, Royal Marsden Hospital, London, United Kingdom
| | - Susan E. Hankinson
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Division of Biostatistics and Epidemiology, University of Massachusetts, Amherst, Massachusetts, United States of America
| | - David J. Hunter
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Kevin B. Jacobs
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, United States of America
| | - Mitch Dowsett
- Academic Department of Biochemistry, Royal Marsden Hospital, London, United Kingdom
| | - David G. Cox
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Cancer Research Center of Lyon, INSERM U1052 – CNRS UMR5286, Centre Léon Bérard, Lyon, France
- * E-mail:
| | - Douglas F. Easton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Immaculata De Vivo
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Epidemiology, Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
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3650
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Germain M, Saut N, Oudot-Mellakh T, Letenneur L, Dupuy AM, Bertrand M, Alessi MC, Lambert JC, Zelenika D, Emmerich J, Tiret L, Cambien F, Lathrop M, Amouyel P, Morange PE, Trégouët DA. Caution in interpreting results from imputation analysis when linkage disequilibrium extends over a large distance: a case study on venous thrombosis. PLoS One 2012; 7:e38538. [PMID: 22675575 PMCID: PMC3366937 DOI: 10.1371/journal.pone.0038538] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2012] [Accepted: 05/07/2012] [Indexed: 12/31/2022] Open
Abstract
By applying an imputation strategy based on the 1000 Genomes project to two genome-wide association studies (GWAS), we detected a susceptibility locus for venous thrombosis on chromosome 11p11.2 that was missed by previous GWAS analyses that had been conducted on the same datasets. A comprehensive linkage disequilibrium and haplotype analysis of the whole locus where twelve SNPs exhibited association p-values lower than 2.23 10(-11) and the use of independent case-control samples demonstrated that the culprit variant was a rare variant located ~1 Mb away from the original hits, not tagged by current genome-wide genotyping arrays and even not well imputed in the original GWAS samples. This variant was in fact the rs1799963, also known as the FII G20210A prothrombin mutation. This work may be of major interest not only for its scientific impact but also for its methodological findings.
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Affiliation(s)
- Marine Germain
- INSERM UMR_S 937, ICAN Institute, Université Pierre et Marie Curie, Paris, France
| | - Noémie Saut
- INSERM UMR_S 1062, Université de la Méditerranée, Marseille France
| | | | - Luc Letenneur
- INSERM UMR_S 897, Université Victor Segalen, Bordeaux, France
| | | | - Marion Bertrand
- INSERM UMR_S 708, Université Pierre et Marie Curie, Paris, France
| | | | - Jean-Charles Lambert
- INSERM UMR_S 744, Institut Pasteur de Lille, Université de Lille Nord de France, Lille, France
| | - Diana Zelenika
- Commissariat à l'Energie Atomique, Institut de Génomique, Centre National de Génotypage, Evry, France
| | - Joseph Emmerich
- INSERM UMR_S 765, Hôpital Européen Georges-Pompidou, Université Paris-Descartes, Paris, France
| | - Laurence Tiret
- INSERM UMR_S 937, ICAN Institute, Université Pierre et Marie Curie, Paris, France
| | - Francois Cambien
- INSERM UMR_S 937, ICAN Institute, Université Pierre et Marie Curie, Paris, France
| | - Mark Lathrop
- Commissariat à l'Energie Atomique, Institut de Génomique, Centre National de Génotypage, Evry, France
| | - Philippe Amouyel
- INSERM UMR_S 744, Institut Pasteur de Lille, Université de Lille Nord de France, Lille, France
- Centre Hospitalier Régional Universitaire de Lille, Lille, France
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