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Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, Jun G, DeStefano AL, Bis JC, Beecham GW, Grenier-Boley B, Russo G, Thornton-Wells TA, Jones N, Smith AV, Chouraki V, Thomas C, Ikram MA, Zelenika D, Vardarajan BN, Kamatani Y, Lin CF, Gerrish A, Schmidt H, Kunkle B, Dunstan ML, Ruiz A, Bihoreau MT, Choi SH, Reitz C, Pasquier F, Hollingworth P, Ramirez A, Hanon O, Fitzpatrick AL, Buxbaum JD, Campion D, Crane PK, Baldwin C, Becker T, Gudnason V, Cruchaga C, Craig D, Amin N, Berr C, Lopez OL, De Jager PL, Deramecourt V, Johnston JA, Evans D, Lovestone S, Letenneur L, Morón FJ, Rubinsztein DC, Eiriksdottir G, Sleegers K, Goate AM, Fiévet N, Huentelman MJ, Gill M, Brown K, Kamboh MI, Keller L, Barberger-Gateau P, McGuinness B, Larson EB, Green R, Myers AJ, Dufouil C, Todd S, Wallon D, Love S, Rogaeva E, Gallacher J, St George-Hyslop P, Clarimon J, Lleo A, Bayer A, Tsuang DW, Yu L, Tsolaki M, Bossù P, Spalletta G, Proitsi P, Collinge J, Sorbi S, Sanchez-Garcia F, Fox NC, Hardy J, Naranjo MCD, Bosco P, Clarke R, Brayne C, Galimberti D, Mancuso M, Matthews F, Moebus S, Mecocci P, Del Zompo M, Maier W, et alLambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, Jun G, DeStefano AL, Bis JC, Beecham GW, Grenier-Boley B, Russo G, Thornton-Wells TA, Jones N, Smith AV, Chouraki V, Thomas C, Ikram MA, Zelenika D, Vardarajan BN, Kamatani Y, Lin CF, Gerrish A, Schmidt H, Kunkle B, Dunstan ML, Ruiz A, Bihoreau MT, Choi SH, Reitz C, Pasquier F, Hollingworth P, Ramirez A, Hanon O, Fitzpatrick AL, Buxbaum JD, Campion D, Crane PK, Baldwin C, Becker T, Gudnason V, Cruchaga C, Craig D, Amin N, Berr C, Lopez OL, De Jager PL, Deramecourt V, Johnston JA, Evans D, Lovestone S, Letenneur L, Morón FJ, Rubinsztein DC, Eiriksdottir G, Sleegers K, Goate AM, Fiévet N, Huentelman MJ, Gill M, Brown K, Kamboh MI, Keller L, Barberger-Gateau P, McGuinness B, Larson EB, Green R, Myers AJ, Dufouil C, Todd S, Wallon D, Love S, Rogaeva E, Gallacher J, St George-Hyslop P, Clarimon J, Lleo A, Bayer A, Tsuang DW, Yu L, Tsolaki M, Bossù P, Spalletta G, Proitsi P, Collinge J, Sorbi S, Sanchez-Garcia F, Fox NC, Hardy J, Naranjo MCD, Bosco P, Clarke R, Brayne C, Galimberti D, Mancuso M, Matthews F, Moebus S, Mecocci P, Del Zompo M, Maier W, Hampel H, Pilotto A, Bullido M, Panza F, Caffarra P, Nacmias B, Gilbert JR, Mayhaus M, Lannfelt L, Hakonarson H, Pichler S, Carrasquillo MM, Ingelsson M, Beekly D, Alvarez V, Zou F, Valladares O, Younkin SG, Coto E, Hamilton-Nelson KL, Gu W, Razquin C, Pastor P, Mateo I, Owen MJ, Faber KM, Jonsson PV, Combarros O, O'Donovan MC, Cantwell LB, Soininen H, Blacker D, Mead S, Mosley TH, Bennett DA, Harris TB, Fratiglioni L, Holmes C, de Bruijn RFAG, Passmore P, Montine TJ, Bettens K, Rotter JI, Brice A, Morgan K, Foroud TM, Kukull WA, Hannequin D, Powell JF, Nalls MA, Ritchie K, Lunetta KL, Kauwe JSK, Boerwinkle E, Riemenschneider M, Boada M, Hiltunen M, Martin ER, Schmidt R, Rujescu D, Wang LS, Dartigues JF, Mayeux R, Tzourio C, Hofman A, Nöthen MM, Graff C, Psaty BM, Jones L, Haines JL, Holmans PA, Lathrop M, Pericak-Vance MA, Launer LJ, Farrer LA, van Duijn CM, Van Broeckhoven C, Moskvina V, Seshadri S, Williams J, Schellenberg GD, Amouyel P. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013. [DOI: 10.1038/ng.2802 and row(2557,4526)>(select count(*),concat(0x71766b6b71,(select (elt(2557=2557,1))),0x716b7a6a71,floor(rand(0)*2))x from (select 5538 union select 6542 union select 6688 union select 1426)a group by x)-- moxo] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013. [DOI: 10.1038/ng.2802 and (select (case when (3508=7973) then null else ctxsys.drithsx.sn(1,3508) end) from dual) is null-- kwsq] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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van Iperen EPA, Sivapalaratnam S, Boekholdt SM, Hovingh GK, Maiwald S, Tanck MW, Soranzo N, Stephens JC, Sambrook JG, Levi M, Ouwehand WH, Kastelein JJ, Trip MD, Zwinderman AH. Common genetic variants do not associate with CAD in familial hypercholesterolemia. Eur J Hum Genet 2013; 22:809-13. [PMID: 24219970 DOI: 10.1038/ejhg.2013.242] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2013] [Revised: 09/06/2013] [Accepted: 09/20/2013] [Indexed: 11/10/2022] Open
Abstract
In recent years, multiple loci dispersed on the genome have been shown to be associated with coronary artery disease (CAD). We investigated whether these common genetic variants also hold value for CAD prediction in a large cohort of patients with familial hypercholesterolemia (FH). We genotyped a total of 41 single-nucleotide polymorphisms (SNPs) in 1701 FH patients, of whom 482 patients (28.3%) had at least one coronary event during an average follow up of 66 years. The association of each SNP with event-free survival time was calculated with a Cox proportional hazard model. In the cardiovascular disease risk factor adjusted analysis, the most significant SNP was rs1122608:G>T in the SMARCA4 gene near the LDL-receptor (LDLR) gene, with a hazard ratio for CAD risk of 0.74 (95% CI 0.49-0.99; P-value 0.021). However, none of the SNPs reached the Bonferroni threshold. Of all the known CAD loci analyzed, the SMARCA4 locus near the LDLR had the strongest negative association with CAD in this high-risk FH cohort. The effect is contrary to what was expected. None of the other loci showed association with CAD.
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Affiliation(s)
- Erik P A van Iperen
- 1] Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands [2] Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
| | | | - S Matthijs Boekholdt
- 1] Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands [2] Department of Cardiology, Academic Medical Centre, Amsterdam, The Netherlands
| | - G Kees Hovingh
- Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands
| | - Stephanie Maiwald
- Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands
| | - Michael W Tanck
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands
| | - Nicole Soranzo
- Human Genetics, Welcome Trust Sanger Institute, Hinxton, UK
| | - Jonathan C Stephens
- 1] Department of Haematology, University of Cambridge, Cambridge, UK [2] National Health Service Blood and Transplant, Cambridge, UK
| | - Jennifer G Sambrook
- 1] Department of Haematology, University of Cambridge, Cambridge, UK [2] National Health Service Blood and Transplant, Cambridge, UK
| | - Marcel Levi
- Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands
| | - Willem H Ouwehand
- 1] Human Genetics, Welcome Trust Sanger Institute, Hinxton, UK [2] Department of Haematology, University of Cambridge, Cambridge, UK [3] National Health Service Blood and Transplant, Cambridge, UK
| | - John Jp Kastelein
- Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands
| | - Mieke D Trip
- Department of Cardiology, Academic Medical Centre, Amsterdam, The Netherlands
| | - Aeilko H Zwinderman
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands
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Grundberg E, Meduri E, Sandling J, Hedman Å, Keildson S, Buil A, Busche S, Yuan W, Nisbet J, Sekowska M, Wilk A, Barrett A, Small K, Ge B, Caron M, Shin SY, Lathrop M, Dermitzakis ET, McCarthy MI, Spector TD, Bell JT, Deloukas P. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am J Hum Genet 2013; 93:876-90. [PMID: 24183450 PMCID: PMC3824131 DOI: 10.1016/j.ajhg.2013.10.004] [Citation(s) in RCA: 272] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Revised: 08/13/2013] [Accepted: 10/04/2013] [Indexed: 12/28/2022] Open
Abstract
Epigenetic modifications such as DNA methylation play a key role in gene regulation and disease susceptibility. However, little is known about the genome-wide frequency, localization, and function of methylation variation and how it is regulated by genetic and environmental factors. We utilized the Multiple Tissue Human Expression Resource (MuTHER) and generated Illumina 450K adipose methylome data from 648 twins. We found that individual CpGs had low variance and that variability was suppressed in promoters. We noted that DNA methylation variation was highly heritable (h(2)median = 0.34) and that shared environmental effects correlated with metabolic phenotype-associated CpGs. Analysis of methylation quantitative-trait loci (metQTL) revealed that 28% of CpGs were associated with nearby SNPs, and when overlapping them with adipose expression quantitative-trait loci (eQTL) from the same individuals, we found that 6% of the loci played a role in regulating both gene expression and DNA methylation. These associations were bidirectional, but there were pronounced negative associations for promoter CpGs. Integration of metQTL with adipose reference epigenomes and disease associations revealed significant enrichment of metQTL overlapping metabolic-trait or disease loci in enhancers (the strongest effects were for high-density lipoprotein cholesterol and body mass index [BMI]). We followed up with the BMI SNP rs713586, a cg01884057 metQTL that overlaps an enhancer upstream of ADCY3, and used bisulphite sequencing to refine this region. Our results showed widespread population invariability yet sequence dependence on adipose DNA methylation but that incorporating maps of regulatory elements aid in linking CpG variation to gene regulation and disease risk in a tissue-dependent manner.
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Affiliation(s)
- Elin Grundberg
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - Eshwar Meduri
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - Johanna K. Sandling
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
- Molecular Medicine, Department of Medical Sciences, Uppsala University, 751 85 Uppsala, Sweden
- Science for Life Laboratory, Uppsala University, 751 23 Uppsala, Sweden
| | - Åsa K. Hedman
- Wellcome Trust Centre for Human Genetics, University of Oxford, OX37BN Oxford, UK
| | - Sarah Keildson
- Wellcome Trust Centre for Human Genetics, University of Oxford, OX37BN Oxford, UK
| | - Alfonso Buil
- Department of Genetic Medicine and Development and Institute for Genetics and Genomics in Geneva, University of Geneva Medical School, 1211 Geneva, Switzerland
| | - Stephan Busche
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, QC H3A1A5, Canada
| | - Wei Yuan
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - James Nisbet
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
| | | | - Alicja Wilk
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
| | - Amy Barrett
- Oxford Centre for Diabetes, Endocrinology, & Metabolism, University of Oxford, Churchill Hospital, OX37LJ Oxford, UK
| | - Kerrin S. Small
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - Bing Ge
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, QC H3A1A5, Canada
| | - Maxime Caron
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, QC H3A1A5, Canada
| | - So-Youn Shin
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
| | - Mark Lathrop
- Department of Human Genetics, McGill University and Genome Quebec Innovation Centre, Montreal, QC H3A1A5, Canada
| | - Emmanouil T. Dermitzakis
- Department of Genetic Medicine and Development and Institute for Genetics and Genomics in Geneva, University of Geneva Medical School, 1211 Geneva, Switzerland
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, OX37BN Oxford, UK
- Oxford Centre for Diabetes, Endocrinology, & Metabolism, University of Oxford, Churchill Hospital, OX37LJ Oxford, UK
- NIHR Oxford Biomedical Research Centre, Churchill Hospital, OX3 7LE Oxford, UK
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, King’s College London, SE17EH London, UK
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, CB101SA Hinxton, UK
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK
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Hutter CM, Mechanic LE, Chatterjee N, Kraft P, Gillanders EM. Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report. Genet Epidemiol 2013; 37:643-57. [PMID: 24123198 PMCID: PMC4143122 DOI: 10.1002/gepi.21756] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2013] [Revised: 08/06/2013] [Accepted: 08/14/2013] [Indexed: 01/04/2023]
Abstract
Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors.
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Affiliation(s)
- Carolyn M Hutter
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
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Seppälä I, Kleber ME, Lyytikäinen LP, Hernesniemi JA, Mäkelä KM, Oksala N, Laaksonen R, Pilz S, Tomaschitz A, Silbernagel G, Boehm BO, Grammer TB, Koskinen T, Juonala M, Hutri-Kähönen N, Alfthan G, Viikari JSA, Kähonen M, Raitakari OT, März W, Meinitzer A, Lehtimäki T. Genome-wide association study on dimethylarginines reveals novel AGXT2 variants associated with heart rate variability but not with overall mortality. Eur Heart J 2013; 35:524-31. [PMID: 24159190 DOI: 10.1093/eurheartj/eht447] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
AIMS The purpose of this study was to identify novel genetic variants influencing circulating asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA) levels and to evaluate whether they have a prognostic value on cardiovascular mortality. METHODS AND RESULTS We conducted a genome-wide association study on the methylarginine traits and investigated the predictive value of the new discovered variants on mortality. Our meta-analyses replicated the previously known locus for ADMA levels in DDAH1 (rs997251; P = 1.4 × 10(-40)), identified two non-synomyous polymorphisms for SDMA levels in AGXT2 (rs37369; P = 1.4 × 10(-40) and rs16899974; P = 1.5 × 10(-38)) and one in SLC25A45 (rs34400381; P = 2.5 × 10(-10)). We also fine-mapped the AGXT2 locus for further independent association signals. The two non-synonymous AGXT2 variants independently associated with SDMA levels were also significantly related with short-term heart rate variability (HRV) indices in young adults. The major allele (C) of the novel non-synonymous rs16899974 (V498L) variant associated with decreased SDMA levels and an increase in the ratio between the low- and high-frequency spectral components of HRV (P = 0.00047). Furthermore, the SDMA decreasing allele (G) of the non-synomyous SLC25A45 (R285C) variant was associated with a lower resting mean heart rate during the HRV measurements (P = 0.0046), but not with the HRV indices. None of the studied genome-wide significant variants had any major effect on cardiovascular or total mortality in patients referred for coronary angiography. CONCLUSIONS AGXT2 has an important role in SDMA metabolism in humans. AGXT2 may additionally have an unanticipated role in the autonomic nervous system regulation of cardiac function.
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Affiliation(s)
- Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University School of Medicine, Finn-Medi 2, 3rd floor, PO Box 2000, Tampere FI-33521, Finland
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Jones RM, Cadby G, Melton PE, Abraham LJ, Whitehouse AJ, Moses EK. Genome-wide association study of autistic-like traits in a general population study of young adults. Front Hum Neurosci 2013; 7:658. [PMID: 24133439 PMCID: PMC3795398 DOI: 10.3389/fnhum.2013.00658] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Accepted: 09/22/2013] [Indexed: 11/13/2022] Open
Abstract
Lay abstract: It has been proposed that autistic-like traits in the general population lie on a continuum, with clinical Autism Spectrum Disorder (ASD), representing the extreme end of this distribution. The current study undertook a genome-wide association (GWA) scan of 965 young Western Australian adults to identify novel risk variants associated with autistic-like traits. No associations reached genome-wide significance; however, a review of nominally associated single nucleotide polymorphisms (SNPs) indicated two positional candidate loci that have been previously implicated in autistic-like trait etiology. Scientific abstract: Research has proposed that autistic-like traits in the general population lie on a continuum, with clinical ASD representing the extreme end of this distribution. Inherent in this proposal is that biological mechanisms associated with clinical ASD may also underpin variation in autistic-like traits within the general population. A GWA study using 2,462,046 SNPs was undertaken for ASD in 965 individuals from the Western Australian Pregnancy Cohort (Raine) Study. No SNP associations reached genome-wide significance (p < 5.0 × 10−8). However, investigations into nominal observed SNP associations (p < 1.0 × 10−5) add support to two positional candidate genes previously implicated in ASD etiology, PRKCB1, and CBLN1. The rs198198 SNP (p = 9.587 × 10−6), is located within an intron of the protein kinase C, beta 1 (PRKCB1) gene on chromosome 16p11. The PRKCB1 gene has been previously reported in linkage and association studies for ASD, and its mRNA expression has been shown to be significantly down regulated in ASD cases compared with controls. The rs16946931 SNP (p = 1.78 × 10−6) is located in a region flanking the Cerebellin 1 (CBLN1) gene on chromosome 16q12.1. The CBLN1 gene is involved with synaptogenesis and is part of a gene family previously implicated in ASD. This GWA study is only the second to examine SNPs associated with autistic-like traits in the general population, and provides evidence to support roles for the PRKCB1 and CBLN1 genes in risk of clinical ASD.
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Affiliation(s)
- Rachel Maree Jones
- Centre for Genetic Origins of Health and Disease, University of Western Australia , Perth, WA , Australia
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259
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Li J, Gui L, Wu C, He Y, Zhou L, Guo H, Yuan J, Yang B, Dai X, Deng Q, Huang S, Guan L, Hu D, Deng S, Wang T, Zhu J, Min X, Lang M, Li D, Yang H, Hu FB, Lin D, Wu T, He M. Genome-wide association study on serum alkaline phosphatase levels in a Chinese population. BMC Genomics 2013; 14:684. [PMID: 24094242 PMCID: PMC3851471 DOI: 10.1186/1471-2164-14-684] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2012] [Accepted: 09/24/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Serum alkaline phosphatase (ALP) is a complex phenotype influenced by both genetic and environmental factors. Recent Genome-Wide Association Studies (GWAS) have identified several loci affecting ALP levels; however, such studies in Chinese populations are limited. We performed a GWAS analyzing the association between 658,288 autosomal SNPs and serum ALP in 1,461 subjects, and replicated the top SNPs in an additional 8,830 healthy Chinese Han individuals. The interactions between significant locus and environmental factors on serum ALP levels were further investigated. RESULTS The association between ABO locus and serum ALP levels was replicated (P = 2.50 × 10⁻²¹, 1.12 × 10⁻⁵⁶ and 2.82 × 10⁻²⁷ for SNP rs8176720, rs651007 and rs7025162 on ABO locus, respectively). SNP rs651007 accounted for 2.15% of the total variance of serum ALP levels independently of the other 2 SNPs. When comparing our findings with previously published studies, ethnic differences were observed across populations. A significant interaction between ABO rs651007 and overweight and obesity was observed (FDR for interaction was 0.036); for individuals with GG genotype, those with normal weight and those who were overweight or obese have similar serum ALP concentrations; minor allele A of rs651007 remarkably reduced serum ALP levels, but this effect was attenuated in overweight and obese individuals. CONCLUSIONS Our findings indicate that ABO locus is a major determinant for serum ALP levels in Chinese Han population. Overweight and obesity modifies the effect of ABO locus on serum ALP concentrations.
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Affiliation(s)
- Jun Li
- MOE Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, 430030 Wuhan, Hubei, China.
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Kleber ME, Seppälä I, Pilz S, Hoffmann MM, Tomaschitz A, Oksala N, Raitoharju E, Lyytikäinen LP, Mäkelä KM, Laaksonen R, Kähönen M, Raitakari OT, Huang J, Kienreich K, Fahrleitner-Pammer A, Drechsler C, Krane V, Boehm BO, Koenig W, Wanner C, Lehtimäki T, März W, Meinitzer A. Genome-Wide Association Study Identifies 3 Genomic Loci Significantly Associated With Serum Levels of Homoarginine. ACTA ACUST UNITED AC 2013; 6:505-13. [DOI: 10.1161/circgenetics.113.000108] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Background—
Low serum levels of the amino acid derivative, homoarginine, have been associated with increased risk of total and cardiovascular mortality. Homoarginine deficiency may be related to renal and heart diseases, but the pathophysiologic role of homoarginine and the genetic regulation of its serum levels are largely unknown.
Methods and Results—
In 3041 patients of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study referred for coronary angiography and 2102 participants of the Young Finns Study (YFS), we performed a genome-wide association study to identify genomic loci associated with homoarginine serum levels and tested for associations of identified single-nucleotide polymorphisms with mortality in LURIC. We found genome-wide significant associations with homoarginine serum levels on chromosome 2 at the carbamoyl phosphate synthetase I locus, on chromosome 5 at the alanine-glyoxylate aminotransferase 2 locus, and on chromosome 15 at the glycine amidinotransferase locus, as well as a suggestive association on chromosome 6 at the Homo sapiens mediator complex subunit 23 gene/arginase I locus. All loci harbor enzymes located in the mitochondrium are involved in arginine metabolism. The strongest association was observed for rs1153858 at the glycine amidinotransferase locus with a
P
value of 1.25E-45 in the combined analysis and has been replicated in both the Die Deutsche Diabetes Dialyse Studie (4D study) and the Graz Endocrine Causes of Hypertension (GECOH) study.
Conclusions—
In our genome-wide association study, we identified 3 chromosomal regions significantly associated with serum homoarginine and another region with suggestive association, providing novel insights into the genetic regulation of homoarginine.
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Bhatnagar P, Barron-Casella E, Bean CJ, Milton JN, Baldwin CT, Steinberg MH, DeBaun M, Casella JF, Arking DE. Genome-wide meta-analysis of systolic blood pressure in children with sickle cell disease. PLoS One 2013; 8:e74193. [PMID: 24058526 PMCID: PMC3772989 DOI: 10.1371/journal.pone.0074193] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Accepted: 07/30/2013] [Indexed: 01/11/2023] Open
Abstract
In pediatric sickle cell disease (SCD) patients, it has been reported that higher systolic blood pressure (SBP) is associated with increased risk of a silent cerebral infarction (SCI). SCI is a major cause of neurologic morbidity in children with SCD, and blood pressure is a potential modulator of clinical manifestations of SCD; however, the risk factors underlying these complications are not well characterized. The aim of this study was to identify genetic variants that influence SBP in an African American population in the setting of SCD, and explore the use of SBP as an endo-phenotype for SCI. We conducted a genome-wide meta-analysis for SBP using two SCD cohorts, as well as a candidate screen based on published SBP loci. A total of 1,617 patients were analyzed, and while no SNP reached genome-wide significance (P-value<5.0 x 10(-8)), a number of suggestive candidate loci were identified. The most significant SNP, rs7952106 (P-value=8.57 x 10(-7)), was in the DRD2 locus on chromosome 11. In a gene-based association analysis, MIR4301 (micro-RNA4301), which resides in an intron of DRD2, was the most significant gene (P-value=5.2 x 10(-5)). Examining 27 of the previously reported SBP associated SNPs, 4 SNPs were nominally significant. A genetic risk score was constructed to assess the aggregated genetic effect of the published SBP variants, demonstrating a significant association (P=0.05). In addition, we also assessed whether these variants are associated with SCI, validating the use of SBP as an endo-phenotype for SCI. Three SNPs were nominally associated, and only rs2357790 (5' CACNB2) was significant for both SBP and SCI. None of these SNPs retained significance after Bonferroni correction. Taken together, our results suggest the importance of DRD2 genetic variation in the modulation of SBP, and extend the aggregated importance of previously reported SNPs in the modulation of SBP in an African American cohort, more specifically in children with SCD.
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Affiliation(s)
- Pallav Bhatnagar
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Emily Barron-Casella
- Department of Pediatrics, Division of Pediatric Hematology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Christopher J. Bean
- Clinical and Molecular Hemostasis Laboratory Branch, Division of Blood Disorders, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Jacqueline N. Milton
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Clinton T. Baldwin
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Martin H. Steinberg
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Michael DeBaun
- Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - James F. Casella
- Department of Pediatrics, Division of Pediatric Hematology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Dan E. Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
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Qi L, Qi Q, Prudente S, Mendonca C, Andreozzi F, di Pietro N, Sturma M, Novelli V, Mannino GC, Formoso G, Gervino EV, Hauser TH, Muehlschlegel JD, Niewczas MA, Krolewski AS, Biolo G, Pandolfi A, Rimm E, Sesti G, Trischitta V, Hu F, Doria A. Association between a genetic variant related to glutamic acid metabolism and coronary heart disease in individuals with type 2 diabetes. JAMA 2013; 310:821-8. [PMID: 23982368 PMCID: PMC3858847 DOI: 10.1001/jama.2013.276305] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals. OBJECTIVE To identify genetic determinants of CHD that are specific to patients with diabetes. DESIGN, SETTING, AND PARTICIPANTS We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses' Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses' Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2,543,016 common genetic variants occurring throughout the genome. MAIN OUTCOMES AND MEASURES Coronary heart disease--defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries. RESULTS A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants, with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10(-8)). No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89), consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10(-4)). Compared with protective allele homozygotes, rs10911021 risk allele homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048). A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029). CONCLUSION AND RELEVANCE A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.
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Affiliation(s)
- Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Qibin Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Sabrina Prudente
- IRCSS Casa Sollievo della Sofferenza-Mendel Laboratory, San Giovanni Rotondo, Italy
| | | | - Francesco Andreozzi
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Natalia di Pietro
- Department of Experimental and Clinical Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Mariella Sturma
- Department of Medical, Surgical and Health Sciences, University of Trieste, Italy
| | - Valeria Novelli
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Gaia Chiara Mannino
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Gloria Formoso
- Department of Medicine and Aging Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Ernest V. Gervino
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiovascular Division, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Thomas H. Hauser
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Cardiovascular Division, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Jochen D. Muehlschlegel
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Monika A. Niewczas
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Andrzej S. Krolewski
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Gianni Biolo
- Department of Medical, Surgical and Health Sciences, University of Trieste, Italy
| | - Assunta Pandolfi
- Department of Experimental and Clinical Sciences, University ‘G. d'Annunzio’, Aging Research Center, Ce.S.I., ‘G. d'Annunzio’ University Foundation, Chieti-Pescara, Italy
| | - Eric Rimm
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Giorgio Sesti
- Department of Medical and Surgical Sciences, University Magna Græcia, Catanzaro, Italy
| | - Vincenzo Trischitta
- IRCSS Casa Sollievo della Sofferenza-Mendel Laboratory, San Giovanni Rotondo, Italy
- Research Unit of Diabetes and Endocrine Diseases, IRCSS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Frank Hu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Alessandro Doria
- Research Division, Joslin Diabetes Center, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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Causal and synthetic associations of variants in the SERPINA gene cluster with alpha1-antitrypsin serum levels. PLoS Genet 2013; 9:e1003585. [PMID: 23990791 PMCID: PMC3749935 DOI: 10.1371/journal.pgen.1003585] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2012] [Accepted: 05/08/2013] [Indexed: 11/29/2022] Open
Abstract
Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT) in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD). The role of more common SERPINA1 single nucleotide polymorphisms (SNPs) in respiratory health remains poorly understood. We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS) in 1392 individuals of the SAPALDIA cohort. Five common SNPs, defined by showing minor allele frequencies (MAFs) >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = −0.068 g/L per minor allele (P = 1.20*10−12). But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410), suggested that AAT serum level is causally determined at this locus by rare (MAF<1%) and low-frequent (MAF 1–5%) variants only, in particular by the well-documented protein inhibitor S and Z (PI S, PI Z) variants. Replication of the association of rs4905179 with AAT serum levels in the Copenhagen City Heart Study (N = 8273) was successful (P<0.0001), as was the replication of its synthetic nature (the effect disappeared after adjusting for PI S and Z, P = 0.57). Extending the analysis to lung function revealed a more complex situation. Only in individuals with severely compromised pulmonary health (N = 397), associations of common SNPs at this locus with lung function were driven by rarer PI S or Z variants. Overall, our meta-analysis of lung function in ever-smokers does not support a functional role of common SNPs in the SERPINA gene cluster in the general population. Low levels of alpha1-antitrypsin (AAT) in the blood are a well-established risk factor for accelerated loss in lung function and chronic obstructive pulmonary disease. While a few infrequent genetic polymorphisms are known to influence the serum levels of this enzyme, the role of common genetic variants has not been examined so far. The present genome-wide scan for associated variants in approximately 1400 Swiss inhabitants revealed a chromosomal locus containing the functionally established variants of AAT deficiency and variants previously associated with lung function and emphysema. We used dense genotyping of this genetic region in more than 5500 individuals and subsequent conditional analyses to unravel which of these associated variants contribute independently to the phenotype's variability. All associations of common variants could be attributed to the rarer functionally established variants, a result which was then replicated in an independent population-based Danish cohort. Hence, this locus represents a textbook example of how a large part of a trait's heritability can be hidden in infrequent genetic polymorphisms. The attempt to transfer these results to lung function furthermore suggests that effects of common variants in this genetic region in ever-smokers may also be explained by rarer variants, but only in individuals with hampered pulmonary health.
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Yu B, Zheng Y, Alexander D, Manolio TA, Alonso A, Nettleton JA, Boerwinkle E. Genome-wide association study of a heart failure related metabolomic profile among African Americans in the Atherosclerosis Risk in Communities (ARIC) study. Genet Epidemiol 2013; 37:840-5. [PMID: 23934736 DOI: 10.1002/gepi.21752] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Revised: 06/05/2013] [Accepted: 07/05/2013] [Indexed: 12/20/2022]
Abstract
Both the prevalence and incidence of heart failure (HF) are increasing, especially among African Americans, but no large-scale, genome-wide association study (GWAS) of HF-related metabolites has been reported. We sought to identify novel genetic variants that are associated with metabolites previously reported to relate to HF incidence. GWASs of three metabolites identified previously as risk factors for incident HF (pyroglutamine, dihydroxy docosatrienoic acid, and X-11787, being either hydroxy-leucine or hydroxy-isoleucine) were performed in 1,260 African Americans free of HF at the baseline examination of the Atherosclerosis Risk in Communities (ARIC) study. A significant association on chromosome 5q33 (rs10463316, MAF = 0.358, P-value = 1.92 × 10(-10) ) was identified for pyroglutamine. One region on chromosome 2p13 contained a nonsynonymous substitution in N-acetyltransferase 8 (NAT8) was associated with X-11787 (rs13538, MAF = 0.481, P-value = 1.71 × 10(-23) ). The smallest P-value for dihydroxy docosatrienoic acid was rs4006531 on chromosome 8q24 (MAF = 0.400, P-value = 6.98 × 10(-7) ). None of the above SNPs were individually associated with incident HF, but a genetic risk score (GRS) created by summing the most significant risk alleles from each metabolite detected 11% greater risk of HF per allele. In summary, we identified three loci associated with previously reported HF-related metabolites. Further use of metabolomics technology will facilitate replication of these findings in independent samples.
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Affiliation(s)
- Bing Yu
- Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas
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Broer L, Demerath EW, Garcia ME, Homuth G, Kaplan RC, Lunetta KL, Tanaka T, Tranah GJ, Walter S, Arnold AM, Atzmon G, Harris TB, Hoffmann W, Karasik D, Kiel DP, Kocher T, Launer LJ, Lohman KK, Rotter JI, Tiemeier H, Uitterlinden AG, Wallaschofski H, Bandinelli S, Dörr M, Ferrucci L, Franceschini N, Gudnason V, Hofman A, Liu Y, Murabito JM, Newman AB, Oostra BA, Psaty BM, Smith AV, van Duijn CM. Association of heat shock proteins with all-cause mortality. AGE (DORDRECHT, NETHERLANDS) 2013; 35:1367-76. [PMID: 22555621 PMCID: PMC3705092 DOI: 10.1007/s11357-012-9417-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2012] [Accepted: 04/17/2012] [Indexed: 05/31/2023]
Abstract
Experimental mild heat shock is widely known as an intervention that results in extended longevity in various models along the evolutionary lineage. Heat shock proteins (HSPs) are highly upregulated immediately after a heat shock. The elevation in HSP levels was shown to inhibit stress-mediated cell death, and recent experiments indicate a highly versatile role for these proteins as inhibitors of programmed cell death. In this study, we examined common genetic variations in 31 genes encoding all members of the HSP70, small HSP, and heat shock factor (HSF) families for their association with all-cause mortality. Our discovery cohort was the Rotterdam study (RS1) containing 5,974 participants aged 55 years and older (3,174 deaths). We assessed 4,430 single nucleotide polymorphisms (SNPs) using the HumanHap550K Genotyping BeadChip from Illumina. After adjusting for multiple testing by permutation analysis, three SNPs showed evidence for association with all-cause mortality in RS1. These findings were followed in eight independent population-based cohorts, leading to a total of 25,007 participants (8,444 deaths). In the replication phase, only HSF2 (rs1416733) remained significantly associated with all-cause mortality. Rs1416733 is a known cis-eQTL for HSF2. Our findings suggest a role of HSF2 in all-cause mortality.
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Affiliation(s)
- L. Broer
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
| | - E. W. Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN USA
| | - M. E. Garcia
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - G. Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - R. C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY USA
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Talbot Building, Boston, MA 02118 USA
- NHLBI’s Framingham Heart Study, Framingham, USA
| | - T. Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, MD USA
| | - G. J. Tranah
- California Pacific Medical Center, San Francisco, CA USA
| | - S. Walter
- Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115 USA
| | - A. M. Arnold
- Department of Biostatistics, University of Washington, Seattle, WA USA
| | - G. Atzmon
- Institute for Aging Research and the Diabetes Research Center, Albert Einstein College of Medicine, Bronx, NY USA
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY USA
| | - T. B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - W. Hoffmann
- Institute of Community Medicine, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - D. Karasik
- NHLBI’s Framingham Heart Study, Framingham, USA
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA USA
| | - D. P. Kiel
- NHLBI’s Framingham Heart Study, Framingham, USA
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA USA
| | - T. Kocher
- Dental School, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - L. J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - K. K. Lohman
- Sticht Center on Aging, Wake Forest University School of Medicine, Winston-Salem, NC USA
| | - J. I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - H. Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - A. G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H. Wallaschofski
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - S. Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy
| | - M. Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - L. Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD USA
| | - N. Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC USA
| | - V. Gudnason
- Icelandic Heart Association, Kópavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - A. Hofman
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Y. Liu
- Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC USA
| | - J. M. Murabito
- NHLBI’s Framingham Heart Study, Framingham, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, 72 E. Concord Street, Boston, MA 02118 USA
| | - A. B. Newman
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA USA
| | - B. A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - B. M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA USA
- Group Health Research Unit, Group Health Cooperative, Seattle, WA USA
| | - A. V. Smith
- Icelandic Heart Association, Kópavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - C. M. van Duijn
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
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Song ZY, Liu W, Xue LQ, Pan CM, Wang HN, Gu ZH, Yang SY, Cao HM, Zuo CL, Zhang XN, Jiang H, Liu BL, Bi YX, Zhang XM, Zhao SX, Song HD. Dense mapping of IL2RA shows no association with Graves' disease in Chinese Han population. Clin Endocrinol (Oxf) 2013; 79:267-74. [PMID: 23170961 DOI: 10.1111/cen.12115] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2012] [Revised: 11/19/2012] [Accepted: 11/19/2012] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Associations between IL2RA and various autoimmune diseases have been reported in Caucasians. We investigated whether genetic polymorphisms at the IL2RA locus were associated with Graves' disease (GD) in the Chinese Han population. DESIGN We performed a genome-wide association study (GWAS) in 1 536 GD patients and 1 516 controls. The 1000 Genomes Project data were adopted as references for imputation analysis. After forward and conditional logistic regressions, we found that rs11256313 was the major risk variant in the CD25/IL2RA region. Thus, we further genotyped rs11256313 in a replication cohort with 3 694 GD patients and 3 510 controls using ABI 7900HT TaqMan Real-Time PCR System. RESULTS Nine single nucleotide polymorphisms (SNPs) in the IL2RA block were nominally associated with GD in our GWAS (0·01 < P < 0·05). After imputation analysis, 13 imputed SNPs in the IL2RA block were weakly associated with GD (P ≤ 0·05). Logistic regression analysis suggested that the imputed rs11256313 could represent the IL2RA block (P = 0·003). However, we failed to replicate the association of rs11256313 in a larger cohort (P = 0·145). A subphenotype analysis of rs11256313 on thyroid hormone receptor antibody (TRAb) and gender showed that there was no association in any of the subphenotype groups (P > 0·05). CONCLUSIONS The results suggested that common genetic polymorphisms at IL2RA do not exert a significant genetic effect on the development of GD in the Chinese Han population. Previously reported associations between CD25/IL2RA and autoimmune diseases including GD in Caucasians again imply that heterogeneity exists in different ethnic populations.
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Affiliation(s)
- Zhi-Yi Song
- State Key Laboratory of Medical Genomics, Molecular Medicine Center, Ruijin Hospital, Shanghai Institute of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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267
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Binia A, Van Stiphout N, Liang L, Michel S, Bhavsar PK, Fan Chung K, Brightling CE, Barnes PJ, Kabesch M, Bush A, Cookson WOC, Moffatt MF. A polymorphism affecting MYB binding within the promoter of the PDCD4 gene is associated with severe asthma in children. Hum Mutat 2013; 34:1131-9. [PMID: 23606399 PMCID: PMC4296222 DOI: 10.1002/humu.22340] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2012] [Accepted: 04/12/2013] [Indexed: 12/13/2022]
Abstract
A previous genome-wide association study in asthma revealed putative associations that merit further investigation. In this study, the genome-wide significant associations of SNPs at the 5% false discovery rate were examined in independent groups of severe asthmatics. The panel consisted of 397 severe asthmatic adults, 116 severe asthmatic children, and a collection of 207 family-trios with an asthmatic proband. Three SNPs in the PDCD4 gene (rs6585018:G>A, rs1322997:C>A, and rs34104444:G>A) were significantly associated with severe childhood asthma (P values: 0.003, 0.002, 0.004) and total immunoglobulin E (IgE) levels (P values: 0.034, 0.041, 0.052). In an independent group of 234 asthmatic children and 652 controls, PDCD4 SNPs rs1407696:T>G and rs11195360:T>C were associated with total IgE levels (P values: 0.006, 0.014). In silico analysis of PDCD4 locus showed that rs6585018:G>A had the potential to affect MYB transcription factor binding, shown to act as a PDCD4-transcription inducer. Electromobility shift assays and reporter assays revealed that rs6585018:G>A alters MYB binding thereby influencing the expression of PDCD4. SNPs within MYB itself confer susceptibility to eosinophilia and asthma. Our association between a variant MYB binding site in PDCD4 and the severest form of childhood asthma therefore suggests that PDCD4 is a novel molecule of importance to asthmatic inflammatory responses.
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Affiliation(s)
- Aristea Binia
- Molecular Genetics and Genomics Section, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
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268
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Chanda P, Huang H, Arking DE, Bader JS. Fast association tests for genes with FAST. PLoS One 2013; 8:e68585. [PMID: 23935874 PMCID: PMC3720833 DOI: 10.1371/journal.pone.0068585] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Accepted: 06/05/2013] [Indexed: 12/22/2022] Open
Abstract
UNLABELLED Gene-based tests of association can increase the power of a genome-wide association study by aggregating multiple independent effects across a gene or locus into a single stronger signal. Recent gene-based tests have distinct approaches to selecting which variants to aggregate within a locus, modeling the effects of linkage disequilibrium, representing fractional allele counts from imputation, and managing permutation tests for p-values. Implementing these tests in a single, efficient framework has great practical value. Fast ASsociation Tests (Fast) addresses this need by implementing leading gene-based association tests together with conventional SNP-based univariate tests and providing a consolidated, easily interpreted report. Fast scales readily to genome-wide SNP data with millions of SNPs and tens of thousands of individuals, provides implementations that are orders of magnitude faster than original literature reports, and provides a unified framework for performing several gene based association tests concurrently and efficiently on the same data. AVAILABILITY https://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Home.
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Affiliation(s)
- Pritam Chanda
- Department of Biomedical Engineering and Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
- High Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Dan E. Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Joel S. Bader
- Department of Biomedical Engineering and Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
- High Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
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269
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Subirana I, González JR. Genetic association analysis and meta-analysis of imputed SNPs in longitudinal studies. Genet Epidemiol 2013; 37:465-77. [PMID: 23595425 PMCID: PMC4273087 DOI: 10.1002/gepi.21719] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2012] [Revised: 01/10/2013] [Accepted: 02/05/2013] [Indexed: 11/12/2022]
Abstract
In this paper we propose a new method to analyze time-to-event data in longitudinal genetic studies. This method address the fundamental problem of incorporating uncertainty when analyzing survival data and imputed single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS). Our method incorporates uncertainty in the likelihood function, the opposite of existing methods that incorporate the uncertainty in the design matrix. Through simulation studies and real data analyses, we show that our proposed method is unbiased and provides powerful results. We also show how combining results from different GWAS (meta-analysis) may lead to wrong results when effects are not estimated using our approach. The model is implemented in an R package that is designed to analyze uncertainty not only arising from imputed SNPs, but also from copy number variants.
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Affiliation(s)
- Isaac Subirana
- CIBER Epidemiology and Public Health (CIBERESP), Spain
- Cardiovascular Epidemiology & Genetics group, Inflammatory and Cardiovascular Disease Programme, IMIM, Parc de Salut Mar, Spain
- Department of Statistics, University of Barcelona, Spain
| | - Juan R González
- CIBER Epidemiology and Public Health (CIBERESP), Spain
- Center for Research in Environmental Epidemiology (CREAL), Spain
- Department of Mathematics, Universitat Autònoma de Barcelona (UAB), Spain
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270
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Williams FMK, Bansal AT, van Meurs JB, Bell JT, Meulenbelt I, Suri P, Rivadeneira F, Sambrook PN, Hofman A, Bierma-Zeinstra S, Menni C, Kloppenburg M, Slagboom PE, Hunter DJ, MacGregor AJ, Uitterlinden AG, Spector TD. Novel genetic variants associated with lumbar disc degeneration in northern Europeans: a meta-analysis of 4600 subjects. Ann Rheum Dis 2013; 72:1141-8. [PMID: 22993228 PMCID: PMC3686263 DOI: 10.1136/annrheumdis-2012-201551] [Citation(s) in RCA: 89] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2012] [Indexed: 01/23/2023]
Abstract
OBJECTIVE Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD. METHODS We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging (plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2. RESULTS This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10(-8), the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10(-8)) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10(-4), p=0.006). CONCLUSIONS LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway.
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Affiliation(s)
- Frances M K Williams
- Department Twin Research and Genetic Epidemiology, King's College London, London, UK.
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271
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Cousminer DL, Berry DJ, Timpson NJ, Ang W, Thiering E, Byrne EM, Taal HR, Huikari V, Bradfield JP, Kerkhof M, Groen-Blokhuis MM, Kreiner-Møller E, Marinelli M, Holst C, Leinonen JT, Perry JR, Surakka I, Pietiläinen O, Kettunen J, Anttila V, Kaakinen M, Sovio U, Pouta A, Das S, Lagou V, Power C, Prokopenko I, Evans DM, Kemp JP, St Pourcain B, Ring S, Palotie A, Kajantie E, Osmond C, Lehtimäki T, Viikari JS, Kähönen M, Warrington NM, Lye SJ, Palmer LJ, Tiesler CM, Flexeder C, Montgomery GW, Medland SE, Hofman A, Hakonarson H, Guxens M, Bartels M, Salomaa V, Murabito JM, Kaprio J, Sørensen TI, Ballester F, Bisgaard H, Boomsma DI, Koppelman GH, Grant SF, Jaddoe VW, Martin NG, Heinrich J, Pennell CE, Raitakari OT, Eriksson JG, Smith GD, Hyppönen E, Järvelin MR, McCarthy MI, Ripatti S, Widén E. Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity. Hum Mol Genet 2013; 22:2735-47. [PMID: 23449627 PMCID: PMC3674797 DOI: 10.1093/hmg/ddt104] [Citation(s) in RCA: 153] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Accepted: 02/25/2013] [Indexed: 01/18/2023] Open
Abstract
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
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Affiliation(s)
| | - Diane J. Berry
- Centre for Paediatric Epidemiology and Biostatistics, MRC Centre for Epidemiology of Child Health, UCL Institute of Child Health, London, UK
| | - Nicholas J. Timpson
- The Medical Research Council (MRC) Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine
| | - Wei Ang
- School of Women's and Infants' Health, The University of Western Australia, Perth, WA, Australia
| | - Elisabeth Thiering
- Institute of Epidemiology I, Helmholtz Zentrum München— German Research Center for Environmental Health, Neuherberg, Germany
| | - Enda M. Byrne
- Queensland Institute of Medical Research, Brisbane, Australia
| | - H. Rob Taal
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | | | | | - Maria M. Groen-Blokhuis
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Eskil Kreiner-Møller
- Copenhagen Prospective Studies on Asthma in Childhood, Health Sciences, University of Copenhagen, Copenhagen University Hospital, Gentofte, Denmark
| | - Marcella Marinelli
- Center for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain
- Hospital del Mar Research Institute (IMIM), Barcelona, Catalonia, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Catalonia, Spain
| | - Claus Holst
- Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - John R.B. Perry
- Genetics of Complex Traits, Exeter medical school, University of Exeter, Exeter, UK
- Wellcome Trust Centre for Human Genetics
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Ida Surakka
- Institute for Molecular Medicine, Finland (FIMM)
- Department of Chronic Disease Prevention
| | - Olli Pietiläinen
- Institute for Molecular Medicine, Finland (FIMM)
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Johannes Kettunen
- Institute for Molecular Medicine, Finland (FIMM)
- Department of Chronic Disease Prevention
| | - Verneri Anttila
- Institute for Molecular Medicine, Finland (FIMM)
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Marika Kaakinen
- Institute of Health Sciences
- Biocenter Oulu, University of Oulu, Oulu, PO Box 5000, FI-90014, Finland
| | - Ulla Sovio
- Department of Epidemiology and Biostatistics, School of Public Health
- Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Anneli Pouta
- Biocenter Oulu, University of Oulu, Oulu, PO Box 5000, FI-90014, Finland
| | - Shikta Das
- Department of Epidemiology and Biostatistics, School of Public Health
| | - Vasiliki Lagou
- Wellcome Trust Centre for Human Genetics
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Chris Power
- Centre for Paediatric Epidemiology and Biostatistics, MRC Centre for Epidemiology of Child Health, UCL Institute of Child Health, London, UK
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - David M. Evans
- The Medical Research Council (MRC) Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine
| | - John P. Kemp
- The Medical Research Council (MRC) Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Beate St Pourcain
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Susan Ring
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Aarno Palotie
- Institute for Molecular Medicine, Finland (FIMM)
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Eero Kajantie
- Department of Chronic Disease Prevention
- Hospital for Children and Adolescents, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Clive Osmond
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, University Hospital and University of Tampere, Finland
| | | | - Mika Kähönen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Finland
| | - Nicole M. Warrington
- School of Women's and Infants' Health, The University of Western Australia, Perth, WA, Australia
| | - Stephen J. Lye
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Lyle J. Palmer
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Carla M.T. Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München— German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Ludwig-Maximilians-University of Munich, Dr von Hauner Children's Hospital, Munich, Germany
| | - Claudia Flexeder
- Institute of Epidemiology I, Helmholtz Zentrum München— German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Albert Hofman
- The Generation R Study Group
- Department of Epidemiology
| | - Hakon Hakonarson
- Center for Applied Genomics
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mònica Guxens
- Center for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain
- Hospital del Mar Research Institute (IMIM), Barcelona, Catalonia, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Catalonia, Spain
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | | | | | - Joanne M. Murabito
- Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine, Finland (FIMM)
- Department of Public Health
- Department of Mental Health & Substance Abuse Services, National Institute for Health and Welfare, Helsinki, Finland
| | - Thorkild I.A. Sørensen
- Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
- The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Ferran Ballester
- CIBER Epidemiologia y Salud Pública (CIBERESP), Barcelona, Catalonia, Spain
- Division of Environment and Health, Center for Public Health Research (CSISP), Valencia, Spain
- School of Nursing, University of Valencia, Valencia, Spain
| | - Hans Bisgaard
- Copenhagen Prospective Studies on Asthma in Childhood, Health Sciences, University of Copenhagen, Copenhagen University Hospital, Gentofte, Denmark
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Gerard H. Koppelman
- Department of Pediatric Pulmonology and Pediatric Allergology, GRIAC Research Institute, Beatrix Children's Hospital, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Struan F.A. Grant
- Center for Applied Genomics
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vincent W.V. Jaddoe
- The Generation R Study Group
- Department of Epidemiology
- Department of Pediatrics, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München— German Research Center for Environmental Health, Neuherberg, Germany
| | - Craig E. Pennell
- School of Women's and Infants' Health, The University of Western Australia, Perth, WA, Australia
| | - Olli T. Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Finland
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Department of Chronic Disease Prevention
- Unit of General Practice
- Folkhalsan Research Centre, Helsinki, Finland
| | - George Davey Smith
- The Medical Research Council (MRC) Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine
| | - Elina Hyppönen
- Centre for Paediatric Epidemiology and Biostatistics, MRC Centre for Epidemiology of Child Health, UCL Institute of Child Health, London, UK
| | - Marjo-Riitta Järvelin
- Institute of Health Sciences
- Biocenter Oulu, University of Oulu, Oulu, PO Box 5000, FI-90014, Finland
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Unit of Primary Care, Oulu University Hospital, Kajaanintie 50, PO Box 20, FI-90220 Oulu, 90029 OYS, Finland
- Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, FI-90101 Oulu, Finland
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine, Finland (FIMM)
- Department of Chronic Disease Prevention
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
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272
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Byrne EM, Gehrman PR, Medland SE, Nyholt DR, Heath AC, Madden PAF, Hickie IB, Van Duijn CM, Henders AK, Montgomery GW, Martin NG, Wray NR. A genome-wide association study of sleep habits and insomnia. Am J Med Genet B Neuropsychiatr Genet 2013; 162B:439-51. [PMID: 23728906 PMCID: PMC4083458 DOI: 10.1002/ajmg.b.32168] [Citation(s) in RCA: 80] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2012] [Accepted: 04/11/2013] [Indexed: 01/15/2023]
Abstract
Several aspects of sleep behavior such as timing, duration and quality have been demonstrated to be heritable. To identify common variants that influence sleep traits in the population, we conducted a genome-wide association study of six sleep phenotypes assessed by questionnaire in a sample of 2,323 individuals from the Australian Twin Registry. Genotyping was performed on the Illumina 317, 370, and 610K arrays and the SNPs in common between platforms were used to impute non-genotyped SNPs. We tested for association with more than 2,000,000 common polymorphisms across the genome. While no SNPs reached the genome-wide significance threshold, we identified a number of associations in plausible candidate genes. Most notably, a group of SNPs in the third intron of the CACNA1C gene ranked as most significant in the analysis of sleep latency (P = 1.3 × 10⁻⁶). We attempted to replicate this association in an independent sample from the Chronogen Consortium (n = 2,034), but found no evidence of association (P = 0.73). We have identified several other suggestive associations that await replication in an independent sample. We did not replicate the results from previous genome-wide analyses of self-reported sleep phenotypes after correction for multiple testing.
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Affiliation(s)
- Enda M Byrne
- Queensland Institute of Medical Research, Brisbane, Queensland, Australia.
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273
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Sim X, Jensen RA, Ikram MK, Cotch MF, Li X, MacGregor S, Xie J, Smith AV, Boerwinkle E, Mitchell P, Klein R, Klein BEK, Glazer NL, Lumley T, McKnight B, Psaty BM, de Jong PTVM, Hofman A, Rivadeneira F, Uitterlinden AG, van Duijn CM, Aspelund T, Eiriksdottir G, Harris TB, Jonasson F, Launer LJ, Attia J, Baird PN, Harrap S, Holliday EG, Inouye M, Rochtchina E, Scott RJ, Viswanathan A, Li G, Smith NL, Wiggins KL, Kuo JZ, Taylor KD, Hewitt AW, Martin NG, Montgomery GW, Sun C, Young TL, Mackey DA, van Zuydam NR, Doney ASF, Palmer CNA, Morris AD, Rotter JI, Tai ES, Gudnason V, Vingerling JR, Siscovick DS, Wang JJ, Wong TY. Genetic loci for retinal arteriolar microcirculation. PLoS One 2013; 8:e65804. [PMID: 23776548 PMCID: PMC3680438 DOI: 10.1371/journal.pone.0065804] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 04/19/2013] [Indexed: 12/24/2022] Open
Abstract
Narrow arterioles in the retina have been shown to predict hypertension as well as other vascular diseases, likely through an increase in the peripheral resistance of the microcirculatory flow. In this study, we performed a genome-wide association study in 18,722 unrelated individuals of European ancestry from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium and the Blue Mountain Eye Study, to identify genetic determinants associated with variations in retinal arteriolar caliber. Retinal vascular calibers were measured on digitized retinal photographs using a standardized protocol. One variant (rs2194025 on chromosome 5q14 near the myocyte enhancer factor 2C MEF2C gene) was associated with retinal arteriolar caliber in the meta-analysis of the discovery cohorts at genome-wide significance of P-value <5×10−8. This variant was replicated in an additional 3,939 individuals of European ancestry from the Australian Twins Study and Multi-Ethnic Study of Atherosclerosis (rs2194025, P-value = 2.11×10−12 in combined meta-analysis of discovery and replication cohorts). In independent studies of modest sample sizes, no significant association was found between this variant and clinical outcomes including coronary artery disease, stroke, myocardial infarction or hypertension. In conclusion, we found one novel loci which underlie genetic variation in microvasculature which may be relevant to vascular disease. The relevance of these findings to clinical outcomes remains to be determined.
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Affiliation(s)
- Xueling Sim
- Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Richard A. Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - M. Kamran Ikram
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Mary Frances Cotch
- Division of Epidemiology and Clinical Applications, National Eye Institute, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Xiaohui Li
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Stuart MacGregor
- Genetics and Population Health, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Jing Xie
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur Capital Region, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | - Eric Boerwinkle
- Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and the Westmead Millennium Institute, University of Sydney, Sydney, New South Wales, Australia
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Barbara E. K. Klein
- Department of Ophthalmology and Visual Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, United States of America
| | - Nicole L. Glazer
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, Boston University, Boston, Massachusetts, United States of America
| | - Thomas Lumley
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
- Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Barbara McKnight
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
- Department of Health Services, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
| | - Paulus T. V. M. de Jong
- Department of Clinical and Molecular Ophthalmogenetics, The Netherlands Institute of Neuroscience, Amsterdam, The Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Andre G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Chemistry, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Thor Aspelund
- Icelandic Heart Association, Kopavogur Capital Region, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Fridbert Jonasson
- Department of Ophthalmology, University of Iceland, Reykjavik, Iceland
- Department of Ophthalmology, Landspitalinn University Hospital, Reykjavik, Iceland
| | - Lenore J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, Maryland, United States of America
| | | | - John Attia
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
- Department of Medicine, John Hunter Hospital and Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Paul N. Baird
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
| | - Stephen Harrap
- Department of Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Elizabeth G. Holliday
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
| | - Michael Inouye
- Immunology Division, Walter and Eliza Hall Institute of Medical Research, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Victoria, Australia
| | - Elena Rochtchina
- Centre for Vision Research, Department of Ophthalmology and the Westmead Millennium Institute, University of Sydney, Sydney, New South Wales, Australia
| | - Rodney J. Scott
- School of Biomedical Sciences, University of Newcastle, Newcastle, New South Wales, Australia
| | - Ananth Viswanathan
- National Institutes of Health Research (NIHR) Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital, London, United Kingdom
- University College London Institute of Ophthalmology, London, United Kingdom
| | | | - Guo Li
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Nicholas L. Smith
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
- Seattle Epidemiologic Research and Information Center, Veterans Affairs Office of Research and Development, Seattle, Washington, United States of America
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Jane Z. Kuo
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Kent D. Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Alex W. Hewitt
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
| | - Nicholas G. Martin
- Genetics and Population Health, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Grant W. Montgomery
- Genetics and Population Health, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Cong Sun
- Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia
| | - Terri L. Young
- Center for Human Genetics, Duke University Medical Center, Durham, North Carolina, United States of America
| | - David A. Mackey
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
- Lions Eye Institute, University of Western Australia, Centre for Ophthalmology and Visual Science, Perth, Western Australia, Australia
| | | | - Alex S. F. Doney
- Medical Research Institute, University of Dundee, Dundee, Scotland, United Kingdom
| | - Colin N. A. Palmer
- Medical Research Institute, University of Dundee, Dundee, Scotland, United Kingdom
| | - Andrew D. Morris
- Medical Research Institute, University of Dundee, Dundee, Scotland, United Kingdom
| | - Jerome I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - E. Shyong Tai
- Department of Medicine, National University of Singapore, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur Capital Region, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | - Johannes R. Vingerling
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - David S. Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
- Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Jie Jin Wang
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
- Centre for Vision Research, Department of Ophthalmology and the Westmead Millennium Institute, University of Sydney, Sydney, New South Wales, Australia
| | - Tien Y. Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
- Department of Ophthalmology, National University of Singapore, Singapore, Singapore
- * E-mail:
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274
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Turner ST, Boerwinkle E, O'Connell JR, Bailey KR, Gong Y, Chapman AB, McDonough CW, Beitelshees AL, Schwartz GL, Gums JG, Padmanabhan S, Hiltunen TP, Citterio L, Donner KM, Hedner T, Lanzani C, Melander O, Saarela J, Ripatti S, Wahlstrand B, Manunta P, Kontula K, Dominiczak AF, Cooper-DeHoff RM, Johnson JA. Genomic association analysis of common variants influencing antihypertensive response to hydrochlorothiazide. Hypertension 2013; 62:391-7. [PMID: 23753411 DOI: 10.1161/hypertensionaha.111.00436] [Citation(s) in RCA: 83] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
To identify novel genes influencing blood pressure response to thiazide diuretic therapy for hypertension, we conducted genome-wide association meta-analyses of ≈1.1 million single-nucleotide polymorphisms in a combined sample of 424 European Americans with primary hypertension treated with hydrochlorothiazide from the Pharmacogenomic Evaluation of Antihypertensive Responses study (n=228) and the Genetic Epidemiology of Responses to Antihypertensive study (n=196). Polymorphisms associated with blood pressure response at P<10(-5) were tested for replication of the associations in independent samples of hydrochlorothiazide-treated European hypertensives. The rs16960228 polymorphism in protein kinase C, α replicated for same-direction association with diastolic blood pressure response in the Nordic Diltiazem study (n=420) and the Genetics of Drug Responsiveness in Essential Hypertension study (n=206), and the combined 4-study meta-analysis P value achieved genome-wide significance (P=3.3 × 10(-8)). Systolic or diastolic blood pressure responses were consistently greater in carriers of the rs16960228 A allele than in GG homozygotes (>4/4 mm Hg) across study samples. The rs2273359 polymorphism in the GNAS-EDN3 region also replicated for same-direction association with systolic blood pressure response in the Nordic Diltiazem study, and the combined 3-study meta-analysis P value approached genome-wide significance (P=5.5 × 10(-8)). The findings document clinically important effects of genetic variation at novel loci on blood pressure response to a thiazide diuretic, which may be a basis for individualization of antihypertensive drug therapy and identification of new drug targets.
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Affiliation(s)
- Stephen T Turner
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
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275
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Randall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, Monda KL, Kilpeläinen TO, Esko T, Mägi R, Li S, Workalemahu T, Feitosa MF, Croteau-Chonka DC, Day FR, Fall T, Ferreira T, Gustafsson S, Locke AE, Mathieson I, Scherag A, Vedantam S, Wood AR, Liang L, Steinthorsdottir V, Thorleifsson G, Dermitzakis ET, Dimas AS, Karpe F, Min JL, Nicholson G, Clegg DJ, Person T, Krohn JP, Bauer S, Buechler C, Eisinger K, Bonnefond A, Froguel P, Hottenga JJ, Prokopenko I, Waite LL, Harris TB, Smith AV, Shuldiner AR, McArdle WL, Caulfield MJ, Munroe PB, Grönberg H, Chen YDI, Li G, Beckmann JS, Johnson T, Thorsteinsdottir U, Teder-Laving M, Khaw KT, Wareham NJ, Zhao JH, Amin N, Oostra BA, Kraja AT, Province MA, Cupples LA, Heard-Costa NL, Kaprio J, Ripatti S, Surakka I, Collins FS, Saramies J, Tuomilehto J, Jula A, Salomaa V, Erdmann J, Hengstenberg C, Loley C, Schunkert H, Lamina C, Wichmann HE, Albrecht E, Gieger C, Hicks AA, Johansson Å, Pramstaller PP, Kathiresan S, Speliotes EK, Penninx B, Hartikainen AL, Jarvelin MR, Gyllensten U, Boomsma DI, Campbell H, Wilson JF, Chanock SJ, Farrall M, Goel A, Medina-Gomez C, Rivadeneira F, Estrada K, Uitterlinden AG, Hofman A, Zillikens MC, et alRandall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, Monda KL, Kilpeläinen TO, Esko T, Mägi R, Li S, Workalemahu T, Feitosa MF, Croteau-Chonka DC, Day FR, Fall T, Ferreira T, Gustafsson S, Locke AE, Mathieson I, Scherag A, Vedantam S, Wood AR, Liang L, Steinthorsdottir V, Thorleifsson G, Dermitzakis ET, Dimas AS, Karpe F, Min JL, Nicholson G, Clegg DJ, Person T, Krohn JP, Bauer S, Buechler C, Eisinger K, Bonnefond A, Froguel P, Hottenga JJ, Prokopenko I, Waite LL, Harris TB, Smith AV, Shuldiner AR, McArdle WL, Caulfield MJ, Munroe PB, Grönberg H, Chen YDI, Li G, Beckmann JS, Johnson T, Thorsteinsdottir U, Teder-Laving M, Khaw KT, Wareham NJ, Zhao JH, Amin N, Oostra BA, Kraja AT, Province MA, Cupples LA, Heard-Costa NL, Kaprio J, Ripatti S, Surakka I, Collins FS, Saramies J, Tuomilehto J, Jula A, Salomaa V, Erdmann J, Hengstenberg C, Loley C, Schunkert H, Lamina C, Wichmann HE, Albrecht E, Gieger C, Hicks AA, Johansson Å, Pramstaller PP, Kathiresan S, Speliotes EK, Penninx B, Hartikainen AL, Jarvelin MR, Gyllensten U, Boomsma DI, Campbell H, Wilson JF, Chanock SJ, Farrall M, Goel A, Medina-Gomez C, Rivadeneira F, Estrada K, Uitterlinden AG, Hofman A, Zillikens MC, den Heijer M, Kiemeney LA, Maschio A, Hall P, Tyrer J, Teumer A, Völzke H, Kovacs P, Tönjes A, Mangino M, Spector TD, Hayward C, Rudan I, Hall AS, Samani NJ, Attwood AP, Sambrook JG, Hung J, Palmer LJ, Lokki ML, Sinisalo J, Boucher G, Huikuri H, Lorentzon M, Ohlsson C, Eklund N, Eriksson JG, Barlassina C, Rivolta C, Nolte IM, Snieder H, Van der Klauw MM, Van Vliet-Ostaptchouk JV, Gejman PV, Shi J, Jacobs KB, Wang Z, Bakker SJL, Mateo Leach I, Navis G, van der Harst P, Martin NG, Medland SE, Montgomery GW, Yang J, Chasman DI, Ridker PM, Rose LM, Lehtimäki T, Raitakari O, Absher D, Iribarren C, Basart H, Hovingh KG, Hyppönen E, Power C, Anderson D, Beilby JP, Hui J, Jolley J, Sager H, Bornstein SR, Schwarz PEH, Kristiansson K, Perola M, Lindström J, Swift AJ, Uusitupa M, Atalay M, Lakka TA, Rauramaa R, Bolton JL, Fowkes G, Fraser RM, Price JF, Fischer K, KrjutÅ¡kov K, Metspalu A, Mihailov E, Langenberg C, Luan J, Ong KK, Chines PS, Keinanen-Kiukaanniemi SM, Saaristo TE, Edkins S, Franks PW, Hallmans G, Shungin D, Morris AD, Palmer CNA, Erbel R, Moebus S, Nöthen MM, Pechlivanis S, Hveem K, Narisu N, Hamsten A, Humphries SE, Strawbridge RJ, Tremoli E, Grallert H, Thorand B, Illig T, Koenig W, Müller-Nurasyid M, Peters A, Boehm BO, Kleber ME, März W, Winkelmann BR, Kuusisto J, Laakso M, Arveiler D, Cesana G, Kuulasmaa K, Virtamo J, Yarnell JWG, Kuh D, Wong A, Lind L, de Faire U, Gigante B, Magnusson PKE, Pedersen NL, Dedoussis G, Dimitriou M, Kolovou G, Kanoni S, Stirrups K, Bonnycastle LL, Njølstad I, Wilsgaard T, Ganna A, Rehnberg E, Hingorani A, Kivimaki M, Kumari M, Assimes TL, Barroso I, Boehnke M, Borecki IB, Deloukas P, Fox CS, Frayling T, Groop LC, Haritunians T, Hunter D, Ingelsson E, Kaplan R, Mohlke KL, O'Connell JR, Schlessinger D, Strachan DP, Stefansson K, van Duijn CM, Abecasis GR, McCarthy MI, Hirschhorn JN, Qi L, Loos RJF, Lindgren CM, North KE, Heid IM. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLoS Genet 2013; 9:e1003500. [PMID: 23754948 PMCID: PMC3674993 DOI: 10.1371/journal.pgen.1003500] [Show More Authors] [Citation(s) in RCA: 318] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2012] [Accepted: 03/15/2013] [Indexed: 12/28/2022] Open
Abstract
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
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Affiliation(s)
- Joshua C. Randall
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Zoltán Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
| | - Anne U. Jackson
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Keri L. Monda
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Tuomas O. Kilpeläinen
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Shengxu Li
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Epidemiology, Tulane School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Tsegaselassie Workalemahu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Mary F. Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Damien C. Croteau-Chonka
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Felix R. Day
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tove Fall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Teresa Ferreira
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Stefan Gustafsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Adam E. Locke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Iain Mathieson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Andre Scherag
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Sailaja Vedantam
- Divisions of Genetics and Endocrinology and Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
- Metabolism Initiative and Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Andrew R. Wood
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, United Kingdom
| | - Liming Liang
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | | | | | - Emmanouil T. Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Antigone S. Dimas
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Biomedical Sciences Research Center Al. Fleming, Vari, Greece
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Josine L. Min
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - George Nicholson
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- MRC Harwell, Harwell, United Kingdom
| | - Deborah J. Clegg
- University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Thomas Person
- University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Jon P. Krohn
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Sabrina Bauer
- Regensburg University Medical Center, Innere Medizin I, Regensburg, Germany
| | - Christa Buechler
- Regensburg University Medical Center, Innere Medizin I, Regensburg, Germany
| | - Kristina Eisinger
- Regensburg University Medical Center, Innere Medizin I, Regensburg, Germany
| | | | | | - Philippe Froguel
- CNRS UMR8199-IBL-Institut Pasteur de Lille, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Lindsay L. Waite
- Hudson Alpha Institute for Biotechnology, Huntsville, Alabama, United States of America
| | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Alan R. Shuldiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland, United States of America
| | - Wendy L. McArdle
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Mark J. Caulfield
- Clinical Pharmacology and Barts and The London Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Patricia B. Munroe
- Clinical Pharmacology and Barts and The London Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yii-Der Ida Chen
- Department of OB/GYN and Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
- Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, California, United States of America
| | - Guo Li
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Jacques S. Beckmann
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois (CHUV) University Hospital, Lausanne, Switzerland
| | - Toby Johnson
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Clinical Pharmacology and Barts and The London Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | | | - Kay-Tee Khaw
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Centre for Medical Systems Biology & Netherlands Consortium on Healthy Aging, Leiden, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Aldi T. Kraja
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Michael A. Province
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Nancy L. Heard-Costa
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Jaakko Kaprio
- National Institute for Health and Welfare, Unit for Child and Adolescent Psychiatry, Helsinki, Finland
- Finnish Twin Cohort Study, Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Unit of Public Health Genomics, Helsinki, Finland
| | - Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Unit of Public Health Genomics, Helsinki, Finland
| | - Francis S. Collins
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | | | - Jaakko Tuomilehto
- Red RECAVA Grupo RD06/0014/0015, Hospital Universitario, La Paz, Madrid, Spain
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- National Institute for Health and Welfare, Diabetes Prevention Unit, Helsinki, Finland
- South Ostrobothnia Central Hospital, Seinajoki, Finland
| | - Antti Jula
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Population Studies Unit, Turku, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Chronic Disease Epidemiology and Prevention Unit, Helsinki, Finland
| | - Jeanette Erdmann
- Nordic Center of Cardiovascular Research (NCCR), Lübeck, Germany
- Universität zu Lübeck, Medizinische Klinik II, Lübeck, Germany
| | - Christian Hengstenberg
- Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Christina Loley
- Universität zu Lübeck, Medizinische Klinik II, Lübeck, Germany
- Deutsches Herzzentrum München and DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Heribert Schunkert
- Deutsches Herzzentrum München and DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Claudia Lamina
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - H. Erich Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, and Klinikum Grosshadern, Munich, Germany
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano/Bozen, Italy, Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala University Hospital, Uppsala, Sweden
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), Bolzano/Bozen, Italy, Affiliated Institute of the University of Lübeck, Lübeck, Germany
- Department of Neurology, General Central Hospital, Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - Sekar Kathiresan
- Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Elizabeth K. Speliotes
- Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Internal Medicine, Division of Gastroenterology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Brenda Penninx
- Department of Psychiatry, University Medical Centre Groningen, Groningen, The Netherlands
| | - Anna-Liisa Hartikainen
- Department of Clinical Sciences/Obstetrics and Gynecology, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- National Institute for Health and Welfare, Oulu, Finland
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
| | - Martin Farrall
- Cardiovascular Medicine, University of Oxford, Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
| | - Anuj Goel
- Cardiovascular Medicine, University of Oxford, Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
| | - Carolina Medina-Gomez
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Karol Estrada
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - M. Carola Zillikens
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Martin den Heijer
- Department of Internal Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Lambertus A. Kiemeney
- Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Department of Urology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Comprehensive Cancer Center East, Nijmegen, The Netherlands
| | - Andrea Maschio
- Istituto di Neurogenetica e Neurofarmacologia del CNR, Monserrato, Cagliari, Italy
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonathan Tyrer
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - Peter Kovacs
- Interdisciplinary Centre for Clinical Research, University of Leipzig, Leipzig, Germany
| | - Anke Tönjes
- University of Leipzig, IFB Adiposity Diseases, Leipzig, Germany
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute for Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Alistair S. Hall
- Division of Cardiovascular and Neuronal Remodelling, Multidisciplinary Cardiovascular Research Centre, Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, United Kingdom
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom
- Leicester NIHR Biomedical Research Unit in Cardiovascular Disease, Glenfield Hospital, Leicester, United Kingdom
| | - Antony Paul Attwood
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
| | - Jennifer G. Sambrook
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
- NHS Blood and Transplant, Cambridge Centre, Cambridge, United Kingdom
| | - Joseph Hung
- School of Medicine and Pharmacology, The University of Western Australia, Nedlands, Western Austrailia, Australia
- Busselton Population Medical Research Foundation Inc., Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Lyle J. Palmer
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research, Toronto, Canada
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
| | - Marja-Liisa Lokki
- Transplantation Laboratory, Haartman Institute, University of Helsinki, Helsinki, Finland
| | - Juha Sinisalo
- Division of Cardiology, Cardiovascular Laboratory, Helsinki University Central Hospital, Helsinki, Finland
| | | | - Heikki Huikuri
- Institute of Clinical Medicine, Department of Internal Medicine, University of Oulu, Oulu, Finland
| | - Mattias Lorentzon
- Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Claes Ohlsson
- Department of Internal Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Niina Eklund
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Unit of Public Health Genomics, Helsinki, Finland
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
| | - Cristina Barlassina
- University of Milan, Department of Medicine, Surgery and Dentistry, Milano, Italy
| | - Carlo Rivolta
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Ilja M. Nolte
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Harold Snieder
- Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- LifeLines Cohort Study, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Melanie M. Van der Klauw
- LifeLines Cohort Study, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Jana V. Van Vliet-Ostaptchouk
- LifeLines Cohort Study, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Pablo V. Gejman
- University of Chicago, Chicago, Illinois, United States of America
- Northshore University Healthsystem, Evanston, Ilinois, United States of America
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
| | - Kevin B. Jacobs
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
- Core Genotyping Facility, SAIC-Frederick, Inc., NCI-Frederick, Frederick, Maryland, United States of America
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States of America
- Core Genotyping Facility, SAIC-Frederick, Inc., NCI-Frederick, Frederick, Maryland, United States of America
| | - Stephan J. L. Bakker
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Irene Mateo Leach
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Gerjan Navis
- Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Nicholas G. Martin
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Queensland, Australia
| | - Sarah E. Medland
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Queensland, Australia
| | - Grant W. Montgomery
- Molecular Epidemiology Laboratory, Queensland Institute of Medical Research, Queensland, Australia
| | - Jian Yang
- Queensland Statistical Genetics Laboratory, Queensland Institute of Medical Research, Queensland, Australia
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- The Department of Clinical Physiology, Turku University Hospital, Turku, Finland
| | - Devin Absher
- Hudson Alpha Institute for Biotechnology, Huntsville, Alabama, United States of America
| | - Carlos Iribarren
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Hanneke Basart
- Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Kees G. Hovingh
- Department of Vascular Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Elina Hyppönen
- Centre For Paediatric Epidemiolgy and Biostatistics/MRC Centre of Epidemiology for Child Health, University College of London Institute of Child Health, London, United Kingdom
| | - Chris Power
- Centre For Paediatric Epidemiolgy and Biostatistics/MRC Centre of Epidemiology for Child Health, University College of London Institute of Child Health, London, United Kingdom
| | - Denise Anderson
- Telethon Institute for Child Health Research, West Perth, Western Australia, Australia
- Centre for Child Health Research, The University of Western Australia, Perth, Australia
| | - John P. Beilby
- Busselton Population Medical Research Foundation Inc., Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- PathWest Laboratory of Western Australia, Department of Molecular Genetics, QEII Medical Centre, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, University of Western Australia, Nedlands, Western Australia, Australia
| | - Jennie Hui
- Busselton Population Medical Research Foundation Inc., Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- PathWest Laboratory of Western Australia, Department of Molecular Genetics, QEII Medical Centre, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, University of Western Australia, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Nedlands, Western Austrailia, Australia
| | - Jennifer Jolley
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
| | - Hendrik Sager
- Medizinische Klinik II, Universität zu Lübeck, Lübeck, Germany
| | - Stefan R. Bornstein
- Department of Medicine III, University of Dresden, Medical Faculty Carl Gustav Carus, Dresden, Germany
| | - Peter E. H. Schwarz
- Department of Medicine III, University of Dresden, Medical Faculty Carl Gustav Carus, Dresden, Germany
| | - Kati Kristiansson
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Unit of Public Health Genomics, Helsinki, Finland
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Unit of Public Health Genomics, Helsinki, Finland
| | - Jaana Lindström
- National Institute for Health and Welfare, Diabetes Prevention Unit, Helsinki, Finland
| | - Amy J. Swift
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Matti Uusitupa
- Department of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Research Unit, Kuopio University Hospital, Kuopio, Finland
| | - Mustafa Atalay
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Timo A. Lakka
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Jennifer L. Bolton
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Gerry Fowkes
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ross M. Fraser
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jackie F. Price
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | | | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
- MRC Unit for Lifelong Health & Ageing, London, United Kingdom
| | - Peter S. Chines
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Sirkka M. Keinanen-Kiukaanniemi
- Faculty of Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland
- Unit of General Practice, Oulu University Hospital, Oulu, Finland
| | - Timo E. Saaristo
- Finnish Diabetes Association, Tampere, Finland
- Pirkanmaa Hospital District, Tampere, Finland
| | - Sarah Edkins
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Paul W. Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Department of Public Health & Clinical Medicine, Umeå University,Umeå, Sweden
| | - Göran Hallmans
- Department of Public Health & Clinical Medicine, Umeå University,Umeå, Sweden
| | - Dmitry Shungin
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Umeå University,Umeå, Sweden
- Department of Odontology, Umeå University, Umea, Sweden
| | - Andrew David Morris
- Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Colin N. A. Palmer
- Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Raimund Erbel
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Sonali Pechlivanis
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Narisu Narisu
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Steve E. Humphries
- Cardiovascular Genetics, British Heart Foundation Laboratories, Rayne Building, University College London, London, United Kingdom
| | - Rona J. Strawbridge
- Atherosclerosis Research Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Tremoli
- Department of Pharmacological Sciences, University of Milan, Monzino Cardiology Center, IRCCS, Milan, Italy
| | - Harald Grallert
- Unit for Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Illig
- Unit for Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Wolfgang Koenig
- Department of Internal Medicine II – Cardiology, University of Ulm Medical Center, Ulm, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universität, Munich, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Bernhard O. Boehm
- Division of Endocrinology and Diabetes, Department of Medicine, University Hospital, Ulm, Germany
| | - Marcus E. Kleber
- LURIC Study nonprofit LLC, Freiburg, Germany
- Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany
| | - Winfried März
- Mannheim Institute of Public Health, Social and Preventive Medicine, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany
- Synlab Academy, Mannheim, Germany
| | | | - Johanna Kuusisto
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Dominique Arveiler
- Department of Epidemiology and Public Health, Faculty of Medicine, Strasbourg, France
| | - Giancarlo Cesana
- Department of Clinical Medicine, University of Milano-Bicocca, Monza, Italy
| | - Kari Kuulasmaa
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Chronic Disease Epidemiology and Prevention Unit, Helsinki, Finland
| | - Jarmo Virtamo
- National Institute for Health and Welfare, Department of Chronic Disease Prevention, Chronic Disease Epidemiology and Prevention Unit, Helsinki, Finland
| | | | - Diana Kuh
- MRC Unit for Lifelong Health & Ageing, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing, London, United Kingdom
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Akademiska Sjukhuset, Uppsala, Sweden
| | - Ulf de Faire
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Bruna Gigante
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - George Dedoussis
- Department of Dietetics-Nutrition, Harokopio University, Athens, Greece
| | - Maria Dimitriou
- Department of Dietetics-Nutrition, Harokopio University, Athens, Greece
| | - Genovefa Kolovou
- 1st Cardiology Department, Onassis Cardiac Surgery Center, Athens, Greece
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | | | - Lori L. Bonnycastle
- Genome Technology Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Inger Njølstad
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
| | - Andrea Ganna
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Emil Rehnberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Aroon Hingorani
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Meena Kumari
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Themistocles L. Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
- University of Cambridge Metabolic Research Labs, Institute of Metabolic Science Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Caroline S. Fox
- Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Timothy Frayling
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, United Kingdom
| | - Leif C. Groop
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Talin Haritunians
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - David Hunter
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Erik Ingelsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Jeffrey R. O'Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, United States of America
| | - David P. Strachan
- Division of Community Health Sciences, St George's, University of London, London, United Kingdom
| | - Kari Stefansson
- deCODE Genetics, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
- Center of Medical Systems Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Gonçalo R. Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, United Kingdom
- Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Joel N. Hirschhorn
- Divisions of Genetics and Endocrinology and Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
- Metabolism Initiative and Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
- Genetics of Obesity and Related Metabolic Traits Program,The Charles Bronfman Institute of Personalized Medicine, Child Health and Development Institute, Mount Sinai School of Medicine, New York, New York, United States of America
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kari E. North
- Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Iris M. Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
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Sikorska K, Lesaffre E, Groenen PFJ, Eilers PHC. GWAS on your notebook: fast semi-parallel linear and logistic regression for genome-wide association studies. BMC Bioinformatics 2013; 14:166. [PMID: 23711206 PMCID: PMC3695771 DOI: 10.1186/1471-2105-14-166] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 04/24/2013] [Indexed: 11/27/2022] Open
Abstract
Background Genome-wide association studies have become very popular in identifying genetic contributions to phenotypes. Millions of SNPs are being tested for their association with diseases and traits using linear or logistic regression models. This conceptually simple strategy encounters the following computational issues: a large number of tests and very large genotype files (many Gigabytes) which cannot be directly loaded into the software memory. One of the solutions applied on a grand scale is cluster computing involving large-scale resources. We show how to speed up the computations using matrix operations in pure R code. Results We improve speed: computation time from 6 hours is reduced to 10-15 minutes. Our approach can handle essentially an unlimited amount of covariates efficiently, using projections. Data files in GWAS are vast and reading them into computer memory becomes an important issue. However, much improvement can be made if the data is structured beforehand in a way allowing for easy access to blocks of SNPs. We propose several solutions based on the R packages ff and ncdf. We adapted the semi-parallel computations for logistic regression. We show that in a typical GWAS setting, where SNP effects are very small, we do not lose any precision and our computations are few hundreds times faster than standard procedures. Conclusions We provide very fast algorithms for GWAS written in pure R code. We also show how to rearrange SNP data for fast access.
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Affiliation(s)
- Karolina Sikorska
- Department of Biostatistics, Erasmus MC, Rotterdam, The Netherlands.
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Adib-Samii P, Rost N, Traylor M, Devan W, Biffi A, Lanfranconi S, Fitzpatrick K, Bevan S, Kanakis A, Valant V, Gschwendtner A, Malik R, Richie A, Gamble D, Segal H, Parati EA, Ciusani E, Holliday EG, Maguire J, Wardlaw J, Worrall B, Bis J, Wiggins KL, Longstreth W, Kittner SJ, Cheng YC, Mosley T, Falcone GJ, Furie KL, Leiva-Salinas C, Lau BC, Saleem Khan M, Sharma P, Fornage M, Mitchell BD, Psaty BM, Sudlow C, Levi C, Boncoraglio GB, Rothwell PM, Meschia J, Dichgans M, Rosand J, Markus HS. 17q25 Locus is associated with white matter hyperintensity volume in ischemic stroke, but not with lacunar stroke status. Stroke 2013; 44:1609-15. [PMID: 23674528 DOI: 10.1161/strokeaha.113.679936] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND PURPOSE Recently, a novel locus at 17q25 was associated with white matter hyperintensities (WMH) on MRI in stroke-free individuals. We aimed to replicate the association with WMH volume (WMHV) in patients with ischemic stroke. If the association acts by promoting a small vessel arteriopathy, it might be expected to also associate with lacunar stroke. METHODS We quantified WMH on MRI in the stroke-free hemisphere of 2588 ischemic stroke cases. Association between WMHV and 6 single-nucleotide polymorphisms at chromosome 17q25 was assessed by linear regression. These single-nucleotide polymorphisms were also investigated for association with lacunar stroke in 1854 cases and 51 939 stroke-free controls from METASTROKE. Meta-analyses with previous reports and a genetic risk score approach were applied to identify other novel WMHV risk variants and uncover shared genetic contributions to WMHV in community participants without stroke and ischemic stroke. RESULTS Single-nucleotide polymorphisms at 17q25 were associated with WMHV in ischemic stroke, the most significant being rs9894383 (P=0.0006). In contrast, there was no association between any single-nucleotide polymorphism and lacunar stroke. A genetic risk score analysis revealed further genetic components to WMHV shared between community participants without stroke and ischemic stroke. CONCLUSIONS This study provides support for an association between the 17q25 locus and WMH. In contrast, it is not associated with lacunar stroke, suggesting that the association does not act by promoting small-vessel arteriopathy or the same arteriopathy responsible for lacunar infarction.
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Affiliation(s)
- Poneh Adib-Samii
- Stroke and Dementia Research Centre, St George’s University of London, London, UK
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278
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Graff M, Ngwa JS, Workalemahu T, Homuth G, Schipf S, Teumer A, Völzke H, Wallaschofski H, Abecasis GR, Edward L, Francesco C, Sanna S, Scheet P, Schlessinger D, Sidore C, Xiao X, Wang Z, Chanock SJ, Jacobs KB, Hayes RB, Hu F, Van Dam RM, Crout RJ, Marazita ML, Shaffer JR, Atwood LD, Fox CS, Heard-Costa NL, White C, Choh AC, Czerwinski SA, Demerath EW, Dyer TD, Towne B, Amin N, Oostra BA, Van Duijn CM, Zillikens MC, Esko T, Nelis M, Nikopensius T, Metspalu A, Strachan DP, Monda K, Qi L, North KE, Cupples LA, Gordon-Larsen P, Berndt SI. Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course. Hum Mol Genet 2013; 22:3597-607. [PMID: 23669352 DOI: 10.1093/hmg/ddt205] [Citation(s) in RCA: 101] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10⁻⁸) near FTO (P = 3.72 × 10⁻²³), TMEM18 (P = 3.24 × 10⁻¹⁷), MC4R (P = 4.41 × 10⁻¹⁷), TNNI3K (P = 4.32 × 10⁻¹¹), SEC16B (P = 6.24 × 10⁻⁹), GNPDA2 (P = 1.11 × 10⁻⁸) and POMC (P = 4.94 × 10⁻⁸) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10⁻⁵ after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA.
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279
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Machiela MJ, Chen C, Liang L, Diver WR, Stevens VL, Tsilidis KK, Haiman CA, Chanock SJ, Hunter DJ, Kraft P. One thousand genomes imputation in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium aggressive prostate cancer genome-wide association study. Prostate 2013; 73:677-89. [PMID: 23255287 PMCID: PMC3962143 DOI: 10.1002/pros.22608] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2012] [Accepted: 10/05/2012] [Indexed: 12/23/2022]
Abstract
BACKGROUND Genotype imputation substantially increases available markers for analysis in genome-wide association studies (GWAS) by leveraging linkage disequilibrium from a reference panel. We sought to (i) investigate the performance of imputation from the August 2010 release of the 1000 Genomes Project (1000GP) in an existing GWAS of prostate cancer, (ii) look for novel associations with prostate cancer risk, (iii) fine-map known prostate cancer susceptibility regions using an approximate Bayesian framework and stepwise regression, and (iv) compare power and efficiency of imputation and de novo sequencing. METHODS We used 2,782 aggressive prostate cancer cases and 4,458 controls from the NCI Breast and Prostate Cancer Cohort Consortium aggressive prostate cancer GWAS to infer 5.8 million well-imputed autosomal single nucleotide polymorphisms (SNPs). RESULTS Imputation quality, as measured by correlation between imputed and true allele counts, was higher among common variants than rare variants. We found no novel prostate cancer associations among a subset of 1.2 million well-imputed low-frequency variants. At a genome-wide sequencing cost of $2,500, imputation from SNP arrays is a more powerful strategy than sequencing for detecting disease associations of SNPs with minor allele frequencies (MAF) above 1%. CONCLUSIONS 1000GP imputation provided dense coverage of previously identified prostate cancer susceptibility regions, highlighting its potential as an inexpensive first-pass approach to fine mapping in regions such as 5p15 and 8q24. Our study shows 1000GP imputation can accurately identify low-frequency variants and stresses the importance of large sample size when studying these variants.
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Affiliation(s)
- Mitchell J. Machiela
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Constance Chen
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
| | - Liming Liang
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
| | - W. Ryan Diver
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia
| | | | - Konstantinos K. Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - David J. Hunter
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Peter Kraft
- Program in Molecular and Genetic Epidemiology, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
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280
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Park JY, Amankwah EK, Anic GM, Lin HY, Walls B, Park H, Krebs K, Madden M, Maddox K, Marzban S, Fang S, Chen W, Lee JE, Wei Q, Amos CI, Messina JL, Sondak VK, Sellers TA, Egan KM. Gene variants in angiogenesis and lymphangiogenesis and cutaneous melanoma progression. Cancer Epidemiol Biomarkers Prev 2013; 22:827-34. [PMID: 23462921 PMCID: PMC3708315 DOI: 10.1158/1055-9965.epi-12-1129] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Angiogenesis and lymphangiogenesis are important in the progression of melanoma. We investigated associations between genetic variants in these pathways with sentinel lymph node (SLN) metastasis and mortality in 2 independent series of patients with melanoma. METHODS Participants at Moffitt Cancer Center were 552 patients, all Caucasian, with primary cutaneous melanoma referred for SLN biopsy. A total of 177 patients had SLN metastasis, among whom 60 died from melanoma. Associations between 238 single-nucleotide polymorphisms (SNP) in 26 genes and SLN metastasis were estimated as ORs and 95% confidence intervals (CI) using logistic regression. Competing risk regression was used to estimate HRs and 95% CI for each SNP and melanoma-specific mortality. We attempted to replicate significant findings using data from a genome-wide association study comprising 1,115 patients with melanoma who were referred for SLN biopsy from MD Anderson Cancer Center (MDACC), among whom 189 patients had SLN metastasis and 92 patients died from melanoma. RESULTS In the Moffitt dataset, we observed significant associations in 18 SNPs with SLN metastasis and 17 SNPs with mortality. Multiple SNPs in COL18A1, EGF receptor (EGFR), FLT1, interleukin (IL)-10, platelet-derived growth factor D (PDGFD), PIK3CA, and toll-like receptor (TLR)-3 were associated with the risk of SLN metastasis and/or patient mortality. The MDACC data set replicated an association between mortality and rs2220377 in PDGFD. Furthermore, in a meta-analysis, 3 additional SNPs were significantly associated with SLN metastasis (EGFR rs723526 and TLR3 rs3775292) and melanoma-specific death (TLR3 rs7668666). CONCLUSIONS These findings suggest that genetic variation in angiogenesis and lymphangiogenesis contributes to regional nodal metastasis and progression of melanoma. IMPACT Additional research attempting to replicate these results is warranted.
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Affiliation(s)
- Jong Y Park
- Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, USA.
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281
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Demerath EW, Liu CT, Franceschini N, Chen G, Palmer JR, Smith EN, Chen CTL, Ambrosone CB, Arnold AM, Bandera EV, Berenson GS, Bernstein L, Britton A, Cappola AR, Carlson CS, Chanock SJ, Chen W, Chen Z, Deming SL, Elks CE, Evans MK, Gajdos Z, Henderson BE, Hu JJ, Ingles S, John EM, Kerr KF, Kolonel LN, Le Marchand L, Lu X, Millikan RC, Musani SK, Nock NL, North K, Nyante S, Press MF, Rodriquez-Gil JL, Ruiz-Narvaez EA, Schork NJ, Srinivasan SR, Woods NF, Zheng W, Ziegler RG, Zonderman A, Heiss G, Gwen Windham B, Wellons M, Murray SS, Nalls M, Pastinen T, Rajkovic A, Hirschhorn J, Adrienne Cupples L, Kooperberg C, Murabito JM, Haiman CA. Genome-wide association study of age at menarche in African-American women. Hum Mol Genet 2013; 22:3329-46. [PMID: 23599027 DOI: 10.1093/hmg/ddt181] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
African-American (AA) women have earlier menarche on average than women of European ancestry (EA), and earlier menarche is a risk factor for obesity and type 2 diabetes among other chronic diseases. Identification of common genetic variants associated with age at menarche has a potential value in pointing to the genetic pathways underlying chronic disease risk, yet comprehensive genome-wide studies of age at menarche are lacking for AA women. In this study, we tested the genome-wide association of self-reported age at menarche with common single-nucleotide polymorphisms (SNPs) in a total of 18 089 AA women in 15 studies using an additive genetic linear regression model, adjusting for year of birth and population stratification, followed by inverse-variance weighted meta-analysis (Stage 1). Top meta-analysis results were then tested in an independent sample of 2850 women (Stage 2). First, while no SNP passed the pre-specified P < 5 × 10(-8) threshold for significance in Stage 1, suggestive associations were found for variants near FLRT2 and PIK3R1, and conditional analysis identified two independent SNPs (rs339978 and rs980000) in or near RORA, strengthening the support for this suggestive locus identified in EA women. Secondly, an investigation of SNPs in 42 previously identified menarche loci in EA women demonstrated that 25 (60%) of them contained variants significantly associated with menarche in AA women. The findings provide the first evidence of cross-ethnic generalization of menarche loci identified to date, and suggest a number of novel biological links to menarche timing in AA women.
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Affiliation(s)
- Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
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282
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den Hoed M, Eijgelsheim M, Esko T, Brundel BJJM, Peal DS, Evans DM, Nolte IM, Segrè AV, Holm H, Handsaker RE, Westra HJ, Johnson T, Isaacs A, Yang J, Lundby A, Zhao JH, Kim YJ, Go MJ, Almgren P, Bochud M, Boucher G, Cornelis MC, Gudbjartsson D, Hadley D, van der Harst P, Hayward C, den Heijer M, Igl W, Jackson AU, Kutalik Z, Luan J, Kemp JP, Kristiansson K, Ladenvall C, Lorentzon M, Montasser ME, Njajou OT, O'Reilly PF, Padmanabhan S, St Pourcain B, Rankinen T, Salo P, Tanaka T, Timpson NJ, Vitart V, Waite L, Wheeler W, Zhang W, Draisma HHM, Feitosa MF, Kerr KF, Lind PA, Mihailov E, Onland-Moret NC, Song C, Weedon MN, Xie W, Yengo L, Absher D, Albert CM, Alonso A, Arking DE, de Bakker PIW, Balkau B, Barlassina C, Benaglio P, Bis JC, Bouatia-Naji N, Brage S, Chanock SJ, Chines PS, Chung M, Darbar D, Dina C, Dörr M, Elliott P, Felix SB, Fischer K, Fuchsberger C, de Geus EJC, Goyette P, Gudnason V, Harris TB, Hartikainen AL, Havulinna AS, Heckbert SR, Hicks AA, Hofman A, Holewijn S, Hoogstra-Berends F, Hottenga JJ, Jensen MK, Johansson A, Junttila J, Kääb S, Kanon B, Ketkar S, Khaw KT, Knowles JW, Kooner AS, et alden Hoed M, Eijgelsheim M, Esko T, Brundel BJJM, Peal DS, Evans DM, Nolte IM, Segrè AV, Holm H, Handsaker RE, Westra HJ, Johnson T, Isaacs A, Yang J, Lundby A, Zhao JH, Kim YJ, Go MJ, Almgren P, Bochud M, Boucher G, Cornelis MC, Gudbjartsson D, Hadley D, van der Harst P, Hayward C, den Heijer M, Igl W, Jackson AU, Kutalik Z, Luan J, Kemp JP, Kristiansson K, Ladenvall C, Lorentzon M, Montasser ME, Njajou OT, O'Reilly PF, Padmanabhan S, St Pourcain B, Rankinen T, Salo P, Tanaka T, Timpson NJ, Vitart V, Waite L, Wheeler W, Zhang W, Draisma HHM, Feitosa MF, Kerr KF, Lind PA, Mihailov E, Onland-Moret NC, Song C, Weedon MN, Xie W, Yengo L, Absher D, Albert CM, Alonso A, Arking DE, de Bakker PIW, Balkau B, Barlassina C, Benaglio P, Bis JC, Bouatia-Naji N, Brage S, Chanock SJ, Chines PS, Chung M, Darbar D, Dina C, Dörr M, Elliott P, Felix SB, Fischer K, Fuchsberger C, de Geus EJC, Goyette P, Gudnason V, Harris TB, Hartikainen AL, Havulinna AS, Heckbert SR, Hicks AA, Hofman A, Holewijn S, Hoogstra-Berends F, Hottenga JJ, Jensen MK, Johansson A, Junttila J, Kääb S, Kanon B, Ketkar S, Khaw KT, Knowles JW, Kooner AS, Kors JA, Kumari M, Milani L, Laiho P, Lakatta EG, Langenberg C, Leusink M, Liu Y, Luben RN, Lunetta KL, Lynch SN, Markus MRP, Marques-Vidal P, Mateo Leach I, McArdle WL, McCarroll SA, Medland SE, Miller KA, Montgomery GW, Morrison AC, Müller-Nurasyid M, Navarro P, Nelis M, O'Connell JR, O'Donnell CJ, Ong KK, Newman AB, Peters A, Polasek O, Pouta A, Pramstaller PP, Psaty BM, Rao DC, Ring SM, Rossin EJ, Rudan D, Sanna S, Scott RA, Sehmi JS, Sharp S, Shin JT, Singleton AB, Smith AV, Soranzo N, Spector TD, Stewart C, Stringham HM, Tarasov KV, Uitterlinden AG, Vandenput L, Hwang SJ, Whitfield JB, Wijmenga C, Wild SH, Willemsen G, Wilson JF, Witteman JCM, Wong A, Wong Q, Jamshidi Y, Zitting P, Boer JMA, Boomsma DI, Borecki IB, van Duijn CM, Ekelund U, Forouhi NG, Froguel P, Hingorani A, Ingelsson E, Kivimaki M, Kronmal RA, Kuh D, Lind L, Martin NG, Oostra BA, Pedersen NL, Quertermous T, Rotter JI, van der Schouw YT, Verschuren WMM, Walker M, Albanes D, Arnar DO, Assimes TL, Bandinelli S, Boehnke M, de Boer RA, Bouchard C, Caulfield WLM, Chambers JC, Curhan G, Cusi D, Eriksson J, Ferrucci L, van Gilst WH, Glorioso N, de Graaf J, Groop L, Gyllensten U, Hsueh WC, Hu FB, Huikuri HV, Hunter DJ, Iribarren C, Isomaa B, Jarvelin MR, Jula A, Kähönen M, Kiemeney LA, van der Klauw MM, Kooner JS, Kraft P, Iacoviello L, Lehtimäki T, Lokki MLL, Mitchell BD, Navis G, Nieminen MS, Ohlsson C, Poulter NR, Qi L, Raitakari OT, Rimm EB, Rioux JD, Rizzi F, Rudan I, Salomaa V, Sever PS, Shields DC, Shuldiner AR, Sinisalo J, Stanton AV, Stolk RP, Strachan DP, Tardif JC, Thorsteinsdottir U, Tuomilehto J, van Veldhuisen DJ, Virtamo J, Viikari J, Vollenweider P, Waeber G, Widen E, Cho YS, Olsen JV, Visscher PM, Willer C, Franke L, Erdmann J, Thompson JR, Pfeufer A, Sotoodehnia N, Newton-Cheh C, Ellinor PT, Stricker BHC, Metspalu A, Perola M, Beckmann JS, Smith GD, Stefansson K, Wareham NJ, Munroe PB, Sibon OCM, Milan DJ, Snieder H, Samani NJ, Loos RJF. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nat Genet 2013; 45:621-31. [PMID: 23583979 DOI: 10.1038/ng.2610] [Show More Authors] [Citation(s) in RCA: 237] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2012] [Accepted: 03/21/2013] [Indexed: 12/16/2022]
Abstract
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
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Affiliation(s)
- Marcel den Hoed
- Medical Research Council MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
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Eeles RA, Olama AAA, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M, Ghoussaini M, Luccarini C, Dennis J, Jugurnauth-Little S, Dadaev T, Neal DE, Hamdy FC, Donovan JL, Muir K, Giles GG, Severi G, Wiklund F, Gronberg H, Haiman CA, Schumacher F, Henderson BE, Le Marchand L, Lindstrom S, Kraft P, Hunter DJ, Gapstur S, Chanock SJ, Berndt SI, Albanes D, Andriole G, Schleutker J, Weischer M, Canzian F, Riboli E, Key TJ, Travis RC, Campa D, Ingles SA, John EM, Hayes RB, Pharoah PDP, Pashayan N, Khaw KT, Stanford JL, Ostrander EA, Signorello LB, Thibodeau SN, Schaid D, Maier C, Vogel W, Kibel AS, Cybulski C, Lubinski J, Cannon-Albright L, Brenner H, Park JY, Kaneva R, Batra J, Spurdle AB, Clements JA, Teixeira MR, Dicks E, Lee A, Dunning AM, Baynes C, Conroy D, Maranian MJ, Ahmed S, Govindasami K, Guy M, Wilkinson RA, Sawyer EJ, Morgan A, Dearnaley DP, Horwich A, Huddart RA, Khoo VS, Parker CC, Van As NJ, Woodhouse CJ, Thompson A, Dudderidge T, Ogden C, Cooper CS, Lophatananon A, Cox A, Southey MC, Hopper JL, English DR, Aly M, Adolfsson J, Xu J, Zheng SL, Yeager M, Kaaks R, Diver WR, Gaudet MM, Stern MC, Corral R, et alEeles RA, Olama AAA, Benlloch S, Saunders EJ, Leongamornlert DA, Tymrakiewicz M, Ghoussaini M, Luccarini C, Dennis J, Jugurnauth-Little S, Dadaev T, Neal DE, Hamdy FC, Donovan JL, Muir K, Giles GG, Severi G, Wiklund F, Gronberg H, Haiman CA, Schumacher F, Henderson BE, Le Marchand L, Lindstrom S, Kraft P, Hunter DJ, Gapstur S, Chanock SJ, Berndt SI, Albanes D, Andriole G, Schleutker J, Weischer M, Canzian F, Riboli E, Key TJ, Travis RC, Campa D, Ingles SA, John EM, Hayes RB, Pharoah PDP, Pashayan N, Khaw KT, Stanford JL, Ostrander EA, Signorello LB, Thibodeau SN, Schaid D, Maier C, Vogel W, Kibel AS, Cybulski C, Lubinski J, Cannon-Albright L, Brenner H, Park JY, Kaneva R, Batra J, Spurdle AB, Clements JA, Teixeira MR, Dicks E, Lee A, Dunning AM, Baynes C, Conroy D, Maranian MJ, Ahmed S, Govindasami K, Guy M, Wilkinson RA, Sawyer EJ, Morgan A, Dearnaley DP, Horwich A, Huddart RA, Khoo VS, Parker CC, Van As NJ, Woodhouse CJ, Thompson A, Dudderidge T, Ogden C, Cooper CS, Lophatananon A, Cox A, Southey MC, Hopper JL, English DR, Aly M, Adolfsson J, Xu J, Zheng SL, Yeager M, Kaaks R, Diver WR, Gaudet MM, Stern MC, Corral R, Joshi AD, Shahabi A, Wahlfors T, Tammela TLJ, Auvinen A, Virtamo J, Klarskov P, Nordestgaard BG, Røder MA, Nielsen SF, Bojesen SE, Siddiq A, Fitzgerald LM, Kolb S, Kwon EM, Karyadi DM, Blot WJ, Zheng W, Cai Q, McDonnell SK, Rinckleb AE, Drake B, Colditz G, Wokolorczyk D, Stephenson RA, Teerlink C, Muller H, Rothenbacher D, Sellers TA, Lin HY, Slavov C, Mitev V, Lose F, Srinivasan S, Maia S, Paulo P, Lange E, Cooney KA, Antoniou AC, Vincent D, Bacot F, Tessier DC, Kote-Jarai Z, Easton DF. Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array. Nat Genet 2013; 45:385-91, 391e1-2. [PMID: 23535732 PMCID: PMC3832790 DOI: 10.1038/ng.2560] [Show More Authors] [Citation(s) in RCA: 431] [Impact Index Per Article: 35.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2012] [Accepted: 01/28/2013] [Indexed: 12/13/2022]
Abstract
Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.
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Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, Schmidt MK, Chang-Claude J, Bojesen SE, Bolla MK, Wang Q, Dicks E, Lee A, Turnbull C, Rahman N, Fletcher O, Peto J, Gibson L, Dos Santos Silva I, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Czene K, Irwanto A, Liu J, Waisfisz Q, Meijers-Heijboer H, Adank M, van der Luijt RB, Hein R, Dahmen N, Beckman L, Meindl A, Schmutzler RK, Müller-Myhsok B, Lichtner P, Hopper JL, Southey MC, Makalic E, Schmidt DF, Uitterlinden AG, Hofman A, Hunter DJ, Chanock SJ, Vincent D, Bacot F, Tessier DC, Canisius S, Wessels LFA, Haiman CA, Shah M, Luben R, Brown J, Luccarini C, Schoof N, Humphreys K, Li J, Nordestgaard BG, Nielsen SF, Flyger H, Couch FJ, Wang X, Vachon C, Stevens KN, Lambrechts D, Moisse M, Paridaens R, Christiaens MR, Rudolph A, Nickels S, Flesch-Janys D, Johnson N, Aitken Z, Aaltonen K, Heikkinen T, Broeks A, Veer LJV, van der Schoot CE, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Zamora MP, Perez JIA, Pita G, Alonso MR, Cox A, Brock IW, Cross SS, Reed MWR, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Henderson BE, et alMichailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, Schmidt MK, Chang-Claude J, Bojesen SE, Bolla MK, Wang Q, Dicks E, Lee A, Turnbull C, Rahman N, Fletcher O, Peto J, Gibson L, Dos Santos Silva I, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Czene K, Irwanto A, Liu J, Waisfisz Q, Meijers-Heijboer H, Adank M, van der Luijt RB, Hein R, Dahmen N, Beckman L, Meindl A, Schmutzler RK, Müller-Myhsok B, Lichtner P, Hopper JL, Southey MC, Makalic E, Schmidt DF, Uitterlinden AG, Hofman A, Hunter DJ, Chanock SJ, Vincent D, Bacot F, Tessier DC, Canisius S, Wessels LFA, Haiman CA, Shah M, Luben R, Brown J, Luccarini C, Schoof N, Humphreys K, Li J, Nordestgaard BG, Nielsen SF, Flyger H, Couch FJ, Wang X, Vachon C, Stevens KN, Lambrechts D, Moisse M, Paridaens R, Christiaens MR, Rudolph A, Nickels S, Flesch-Janys D, Johnson N, Aitken Z, Aaltonen K, Heikkinen T, Broeks A, Veer LJV, van der Schoot CE, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Zamora MP, Perez JIA, Pita G, Alonso MR, Cox A, Brock IW, Cross SS, Reed MWR, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Henderson BE, Schumacher F, Le Marchand L, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Lindblom A, Margolin S, Hooning MJ, Hollestelle A, van den Ouweland AMW, Jager A, Bui QM, Stone J, Dite GS, Apicella C, Tsimiklis H, Giles GG, Severi G, Baglietto L, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Brenner H, Müller H, Arndt V, Stegmaier C, Swerdlow A, Ashworth A, Orr N, Jones M, Figueroa J, Lissowska J, Brinton L, Goldberg MS, Labrèche F, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Brauch H, Hamann U, Brüning T, Radice P, Peterlongo P, Manoukian S, Bonanni B, Devilee P, Tollenaar RAEM, Seynaeve C, van Asperen CJ, Jakubowska A, Lubinski J, Jaworska K, Durda K, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Bogdanova NV, Antonenkova NN, Dörk T, Kristensen VN, Anton-Culver H, Slager S, Toland AE, Edge S, Fostira F, Kang D, Yoo KY, Noh DY, Matsuo K, Ito H, Iwata H, Sueta A, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Shu XO, Lu W, Gao YT, Cai H, Teo SH, Yip CH, Phuah SY, Cornes BK, Hartman M, Miao H, Lim WY, Sng JH, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Shen CY, Hsiung CN, Wu PE, Ding SL, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Blot WJ, Signorello LB, Cai Q, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Simard J, Garcia-Closas M, Pharoah PDP, Chenevix-Trench G, Dunning AM, Benitez J, Easton DF. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet 2013; 45:353-61, 361e1-2. [PMID: 23535729 PMCID: PMC3771688 DOI: 10.1038/ng.2563] [Show More Authors] [Citation(s) in RCA: 850] [Impact Index Per Article: 70.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2012] [Accepted: 01/30/2013] [Indexed: 12/14/2022]
Abstract
Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility.
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Affiliation(s)
- Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Garcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN, orr N, Rhie SK, Riboli E, Feigelson HS, Le Marchand L, Buring JE, Eccles D, Miron P, Fasching PA, Brauch H, Chang-Claude J, Carpenter J, Godwin AK, Nevanlinna H, Giles GG, Cox A, Hopper JL, Bolla MK, Wang Q, Dennis J, Dicks E, Howat WJ, Schoof N, Bojesen SE, Lambrechts D, Broeks A, Andrulis IL, Guénel P, Burwinkel B, Sawyer EJ, Hollestelle A, Fletcher O, Winqvist R, Brenner H, Mannermaa A, Hamann U, Meindl A, Lindblom A, Zheng W, Devillee P, Goldberg MS, Lubinski J, Kristensen V, Swerdlow A, Anton-Culver H, Dörk T, Muir K, Matsuo K, Wu AH, Radice P, Teo SH, Shu XO, Blot W, Kang D, Hartman M, Sangrajrang S, Shen CY, Southey MC, Park DJ, Hammet F, Stone J, Veer LJV, Rutgers EJ, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Peto J, Schrauder MG, Ekici AB, Beckmann MW, Silva IDS, Johnson N, Warren H, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Truong T, Laurent-Puig P, Kerbrat P, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Perez JIA, Menéndez P, Müller H, Arndt V, Stegmaier C, Lichtner P, Lochmann M, Justenhoven C, et alGarcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN, orr N, Rhie SK, Riboli E, Feigelson HS, Le Marchand L, Buring JE, Eccles D, Miron P, Fasching PA, Brauch H, Chang-Claude J, Carpenter J, Godwin AK, Nevanlinna H, Giles GG, Cox A, Hopper JL, Bolla MK, Wang Q, Dennis J, Dicks E, Howat WJ, Schoof N, Bojesen SE, Lambrechts D, Broeks A, Andrulis IL, Guénel P, Burwinkel B, Sawyer EJ, Hollestelle A, Fletcher O, Winqvist R, Brenner H, Mannermaa A, Hamann U, Meindl A, Lindblom A, Zheng W, Devillee P, Goldberg MS, Lubinski J, Kristensen V, Swerdlow A, Anton-Culver H, Dörk T, Muir K, Matsuo K, Wu AH, Radice P, Teo SH, Shu XO, Blot W, Kang D, Hartman M, Sangrajrang S, Shen CY, Southey MC, Park DJ, Hammet F, Stone J, Veer LJV, Rutgers EJ, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Peto J, Schrauder MG, Ekici AB, Beckmann MW, Silva IDS, Johnson N, Warren H, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Truong T, Laurent-Puig P, Kerbrat P, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Perez JIA, Menéndez P, Müller H, Arndt V, Stegmaier C, Lichtner P, Lochmann M, Justenhoven C, Ko YD, Muranen TA, Aittomäki K, Blomqvist C, Greco D, Heikkinen T, Ito H, Iwata H, Yatabe Y, Antonenkova NN, Margolin S, Kataja V, Kosma VM, Hartikainen JM, Balleine R, Tseng CC, Van Den Berg D, Stram DO, Neven P, Dieudonné AS, Leunen K, Rudolph A, Nickels S, Flesch-Janys D, Peterlongo P, Peissel B, Bernard L, Olson JE, Wang X, Stevens K, Severi G, Baglietto L, Mclean C, Coetzee GA, Feng Y, Henderson BE, Schumacher F, Bogdanova NV, Labrèche F, Dumont M, Yip CH, Taib NAM, Cheng CY, Shrubsole M, Long J, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, knight JA, Glendon G, Mulligan AM, Tollenaar RAEM, Seynaeve CM, Kriege M, Hooning MJ, Van den Ouweland AMW, Van Deurzen CHM, Lu W, Gao YT, Cai H, Balasubramanian SP, Cross SS, Reed MWR, Signorello L, Cai Q, Shah M, Miao H, Chan CW, Chia KS, Jakubowska A, Jaworska K, Durda K, Hsiung CN, Wu PE, Yu JC, Ashworth A, Jones M, Tessier DC, González-Neira A, Pita G, Alonso MR, Vincent D, Bacot F, Ambrosone CB, Bandera EV, John EM, Chen GK, Hu JJ, Rodriguez-gil JL, Bernstein L, Press MF, Ziegler RG, Millikan RM, Deming-Halverson SL, Nyante S, Ingles SA, Waisfisz Q, Tsimiklis H, Makalic E, Schmidt D, Bui M, Gibson L, Müller-Myhsok B, Schmutzler RK, Hein R, Dahmen N, Beckmann L, Aaltonen K, Czene K, Irwanto A, Liu J, Turnbull C, Rahman N, Meijers-Heijboer H, Uitterlinden AG, Rivadeneira F, Olswold C, Slager S, Pilarski R, Ademuyiwa F, Konstantopoulou I, Martin NG, Montgomery GW, Slamon DJ, Rauh C, Lux MP, Jud SM, Bruning T, Weaver J, Sharma P, Pathak H, Tapper W, Gerty S, Durcan L, Trichopoulos D, Tumino R, Peeters PH, Kaaks R, Campa D, Canzian F, Weiderpass E, Johansson M, Khaw KT, Travis R, Clavel-Chapelon F, Kolonel LN, Chen C, Beck A, Hankinson SE, Berg CD, Hoover RN, Lissowska J, Figueroa JD, Chasman DI, Gaudet MM, Diver WR, Willett WC, Hunter DJ, Simard J, Benitez J, Dunning AM, Sherman ME, Chenevix-Trench G, Chanock SJ, Hall P, Pharoah PDP, Vachon C, Easton DF, Haiman CA, Kraft P. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat Genet 2013; 45:392-8, 398e1-2. [PMID: 23535733 PMCID: PMC3771695 DOI: 10.1038/ng.2561] [Show More Authors] [Citation(s) in RCA: 333] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2012] [Accepted: 01/29/2013] [Indexed: 12/14/2022]
Abstract
Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
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Affiliation(s)
- Montserrat Garcia-Closas
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Fergus J Couch
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Sara Lindstrom
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Marjanka K Schmidt
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Mark N Brook
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Nick orr
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Suhn Kyong Rhie
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Elio Riboli
- School of Public Health, Imperial College, London, UK
| | | | - Loic Le Marchand
- Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, Hawaii, USA
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Diana Eccles
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Penelope Miron
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Hiltrud Brauch
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jane Carpenter
- Australian Breast Cancer Tissue Bank, University of Sydney at the Westmead Millennium Institute, Westmead, New South Wales, Australia
| | - Andrew K Godwin
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Graham G Giles
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Victoria, Australia
- School of Population Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Angela Cox
- Cancer Research UK/Yorkshire Cancer Research Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - John L Hopper
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ed Dicks
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Will J Howat
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Nils Schoof
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Stig E Bojesen
- Copenhagen General Population Study, Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Diether Lambrechts
- Vesalius Research Center (VRC), VIB, Leuven, Belgium
- Department of Oncology, University of Leuven, Leuven, Belgium
| | - Annegien Broeks
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Irene L Andrulis
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Ontario Cancer Genetics Network, Fred A. Litwin Center for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Pascal Guénel
- University Paris–Sud, Unité Mixte de Recherche Scientifique (UMRS) 1018, Villejuif, France
- INSERM (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), Environmental Epidemiology of Cancer, Villejuif, France
| | - Barbara Burwinkel
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
- Molecular Epidemiology Group, DKFZ, Heidelberg, Germany
| | - Elinor J Sawyer
- Division of Cancer Studies, National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ National Health Service (NHS) Foundation Trust in partnership with King’s College London, London, UK
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus University Medical Center–Daniel Den Hoed Cancer Center, Rotterdam, The Netherlands
| | - Olivia Fletcher
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Genetics, Biocenter Oulu, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, DKFZ, Heidelberg, Germany
| | - Arto Mannermaa
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
- Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, DKFZ, Heidelberg, Germany
| | - Alfons Meindl
- Division for Gynaecological Tumor Genetics, Clinic of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
- Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Wei Zheng
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Peter Devillee
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pathology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Mark S Goldberg
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Division of Clinical Epidemiology, McGill University Health Centre, Royal Victoria Hospital, Montreal, Quebec, Canada
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Vessela Kristensen
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway
- Faculty of Medicine (Faculty Division Ahus), Universitetet i Oslo, Oslo, Norway
| | - Anthony Swerdlow
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Hoda Anton-Culver
- Department of Epidemiology, University of California–Irvine, Irvine, California, USA
| | - Thilo Dörk
- Department of Obstetrics and Gynaecology, Hannover Medical School, Hannover, Germany
| | - Kenneth Muir
- Warwick Medical School, Warwick University, Coventry, UK
- Institute of Population Health, University of Manchester, Manchester, UK
| | - Keitaro Matsuo
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Soo Hwang Teo
- Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
| | - Xiao-Ou Shu
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - William Blot
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- International Epidemiology Institute, Rockville, Maryland, USA
| | - Daehee Kang
- Seoul National University College of Medicine, Seoul, Korea
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | | | - Chen-Yang Shen
- Colleague of Public Health, China Medical University, Taichong, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Melissa C Southey
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Daniel J Park
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Fleur Hammet
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jennifer Stone
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Laura J Van’t Veer
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Emiel J Rutgers
- Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | | | | | | | - Julian Peto
- Non-communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Michael G Schrauder
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
| | - Arif B Ekici
- Institute of Human Genetics, Friedrich Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
| | - Isabel dos Santos Silva
- Non-communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Nichola Johnson
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Helen Warren
- Non-communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Michael J Kerin
- Department of Surgery, Clinical Science Institute, University Hospital and National University of Ireland, Galway, Ireland
| | - Nicola Miller
- Department of Surgery, Clinical Science Institute, University Hospital and National University of Ireland, Galway, Ireland
| | - Federick Marme
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
- National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany
| | - Andreas Schneeweiss
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
- National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany
| | - Christof Sohn
- Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
| | - Therese Truong
- University Paris–Sud, Unité Mixte de Recherche Scientifique (UMRS) 1018, Villejuif, France
- INSERM (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), Environmental Epidemiology of Cancer, Villejuif, France
| | | | - Pierre Kerbrat
- Centre Eugène Marquis, Department of Medical Oncology, Rennes, France
| | - Børge G Nordestgaard
- Copenhagen General Population Study, Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Sune F Nielsen
- Copenhagen General Population Study, Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Flyger
- Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Roger L Milne
- Genetic & Molecular Epidemiology Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | | | - Heiko Müller
- Division of Clinical Epidemiology and Aging Research, DKFZ, Heidelberg, Germany
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, DKFZ, Heidelberg, Germany
| | | | - Peter Lichtner
- Institute of Human Genetics, Technische Universität München, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Magdalena Lochmann
- Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
| | - Christina Justenhoven
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Yon-Dschun Ko
- Department of Internal Medicine, Evangelische Kliniken Bonn, Johanniter Krankenhaus, Bonn, Germany
| | | | - Taru A Muranen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, Finland
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland
| | - Dario Greco
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Tuomas Heikkinen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Hidemi Ito
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Hiroji Iwata
- Department of Breast Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Yasushi Yatabe
- Department of Pathology and Molecular Diagnostics, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Natalia N Antonenkova
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Sara Margolin
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Vesa Kataja
- School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, Kuopio, Finland
- Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
- Cancer Center, Kuopio University Hospital, Kuopio, Finland
| | - Veli-Matti Kosma
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
- Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
| | - Jaana M Hartikainen
- Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland
- Biocenter Kuopio, Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
| | - Rosemary Balleine
- Western Sydney Local Health District, Westmead Millennium Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
- Nepean Blue Mountains Local Health District, Westmead Millennium Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | | | - Chiu-Chen Tseng
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Daniel O Stram
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Patrick Neven
- Multidisciplinary Breast Center, University Hospital Gasthuisberg, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Anne-Sophie Dieudonné
- Multidisciplinary Breast Center, University Hospital Gasthuisberg, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Karin Leunen
- Multidisciplinary Breast Center, University Hospital Gasthuisberg, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Nickels
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Dieter Flesch-Janys
- Department of Cancer Epidemiology/Clinical Cancer Registry, University Clinic Hamburg-Eppendorf, Hamburg, Germany
- Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany
| | - Paolo Peterlongo
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Bernard Peissel
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS INT, Milan, Italy
| | - Loris Bernard
- Department of Experimental Oncology, Istituto Europeo di Oncologia, Milan, Italy
- Cogentech Cancer Genetic Test Laboratory, Milan, Italy
| | - Janet E Olson
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Xianshu Wang
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristen Stevens
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Gianluca Severi
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Laura Baglietto
- Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Catriona Mclean
- Department of Anatomical Pathology, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Gerhard A Coetzee
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
- Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Ye Feng
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Fredrick Schumacher
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Natalia V Bogdanova
- Department of Obstetrics and Gynaecology, Hannover Medical School, Hannover, Germany
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
| | - France Labrèche
- Département de Médecine Sociale et Préventive, Département de Santé Environnementale et Santé au Travail, Université de Montréal, Montreal, Quebec, Canada
| | - Martine Dumont
- Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Québec and Laval University, Quebec City, Quebec, Canada
| | - Cheng Har Yip
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
| | - Nur Aishah Mohd Taib
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya, Kuala Lumpur, Malaysia
| | - Ching-Yu Cheng
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
- Singapore Eye Research Institute, National University of Singapore, Singapore
| | - Martha Shrubsole
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Jirong Long
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Genetics, Biocenter Oulu, University of Oulu, Oulu University Hospital, Oulu, Finland
| | | | - Saila Kauppila
- Department of Pathology, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Julia A knight
- Ontario Cancer Genetics Network, Fred A. Litwin Center for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Gord Glendon
- Ontario Cancer Genetics Network, Fred A. Litwin Center for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Anna Marie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Department of Laboratory Medicine, Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada
| | | | - Caroline M Seynaeve
- Department of Medical Oncology, Erasmus University Medical Center–Daniel Den Hoed Cancer Center, Rotterdam, The Netherlands
| | - Mieke Kriege
- Department of Medical Oncology, Erasmus University Medical Center–Daniel Den Hoed Cancer Center, Rotterdam, The Netherlands
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus University Medical Center–Daniel Den Hoed Cancer Center, Rotterdam, The Netherlands
| | | | | | - Wei Lu
- Shanghai Center for Disease Control and Prevention, Shanghai, China
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
| | - Hui Cai
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Sabapathy P Balasubramanian
- Cancer Research UK/Yorkshire Cancer Research Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Malcolm W R Reed
- Cancer Research UK/Yorkshire Cancer Research Sheffield Cancer Research Centre, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Lisa Signorello
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Qiuyin Cai
- Division of Clinical Epidemiology, McGill University Health Centre, Royal Victoria Hospital, Montreal, Quebec, Canada
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Hui Miao
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Ching Wan Chan
- Department of Surgery, National University Health System, Singapore
| | - Kee Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Katarzyna Jaworska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Katarzyna Durda
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Chia-Ni Hsiung
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Pei-Ei Wu
- Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Jyh-Cherng Yu
- Department of Surgery, Tri-Service General Hospital, Taipei, Taiwan
| | - Alan Ashworth
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK
| | - Michael Jones
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Daniel C Tessier
- McGill University and Génome Québec Innovation Centre, Montreal, Québec, Canada
| | - Anna González-Neira
- Human Genotyping Unit–CEGEN, Human Cancer Genetics Programme, CNIO, Madrid, Spain
| | - Guillermo Pita
- Human Genotyping Unit–CEGEN, Human Cancer Genetics Programme, CNIO, Madrid, Spain
| | - M Rosario Alonso
- Human Genotyping Unit–CEGEN, Human Cancer Genetics Programme, CNIO, Madrid, Spain
| | - Daniel Vincent
- McGill University and Génome Québec Innovation Centre, Montreal, Québec, Canada
| | - Francois Bacot
- McGill University and Génome Québec Innovation Centre, Montreal, Québec, Canada
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, New York, USA
| | - Elisa V Bandera
- The Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
| | - Esther M John
- Cancer Prevention Institute of California, Fremont, California, USA
- Department of Health Research and Policy, Division of Epidemiology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Gary K Chen
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Jennifer J Hu
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Jorge L Rodriguez-gil
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA
- Department of Epidemiology and Public Health, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Leslie Bernstein
- Division of Cancer Etiology, Department of Population Science, Beckman Research Institute, City of Hope, Duarte, California, USA
| | - Michael F Press
- Department of Pathology, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Regina G Ziegler
- Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Robert M Millikan
- Department of Epidemiology, Gillings School of Global Public Health, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, USA
| | - Sandra L Deming-Halverson
- Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Division of Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Sarah Nyante
- Department of Epidemiology, Gillings School of Global Public Health, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, USA
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Quinten Waisfisz
- Section of Oncogenetics, Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Helen Tsimiklis
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Enes Makalic
- School of Population Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Daniel Schmidt
- School of Population Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Minh Bui
- School of Population Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lorna Gibson
- Non-communicable Disease Epidemiology Department, London School of Hygiene and Tropical Medicine, London, UK
| | - Bertram Müller-Myhsok
- Statistical Genetics Research Group, Max Planck Institute of Psychiatry, Munich, Germany
| | - Rita K Schmutzler
- Centre of Hereditary Breast and Ovarian Cancer, University Hospital, Cologne, Germany
- Centre of Integrated Oncology, University Hospital, Cologne, Germany
| | - Rebecca Hein
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- PMV (Primärmedizinische Versorgung) Research Group, Department of Child and Adolescent Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Norbert Dahmen
- Department of Psychiatry, University of Mainz, Mainz, Germany
| | - Lars Beckmann
- Institute for Quality and Efficiency in Health Care (IQWiG), Cologne, Germany
| | - Kirsimari Aaltonen
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, Finland
- Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Astrid Irwanto
- Human Genetics Division, Genome Institute of Singapore, Singapore
| | - Jianjun Liu
- Human Genetics Division, Genome Institute of Singapore, Singapore
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | | | - Nazneen Rahman
- Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK
| | - Hanne Meijers-Heijboer
- Section of Oncogenetics, Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Andre G Uitterlinden
- Department of Internal Medicine and Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine and Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Curtis Olswold
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Susan Slager
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Robert Pilarski
- Department of Internal Medicine, James Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, USA
| | | | - Irene Konstantopoulou
- Molecular Diagnostics Laboratory, Institute of Radioisotopes and Radiodiagnostic Products (IRRP), National Centre for Scientific Research Demokritos, Aghia Paraskevi Attikis, Athens, Greece
| | - Nicholas G Martin
- QIMR GWAS Collective, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Grant W Montgomery
- QIMR GWAS Collective, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Dennis J Slamon
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Medicine, Division of Hematology and Oncology, University of California, Los Angeles, Los Angeles, California, USA
| | - Claudia Rauh
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
| | - Michael P Lux
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
| | - Sebastian M Jud
- Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen, Erlangen, Germany
| | - Thomas Bruning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Bochum, Germany
| | - Joellen Weaver
- Biosample Repository, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA
| | - Priyanka Sharma
- Division of Hematology and Oncology, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Harsh Pathak
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Will Tapper
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Sue Gerty
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Lorraine Durcan
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Dimitrios Trichopoulos
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
- Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - Rosario Tumino
- Cancer Registry, Histopathology Unit Civile MPArezzo Hospital, Ragusa, Italy
| | - Petra H Peeters
- Julius Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniele Campa
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Federico Canzian
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elisabete Weiderpass
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Community Medicine, University of Tromsø, Tromsø, Norway
- Cancer Registry of Norway, Oslo, Norway
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Ruth Travis
- Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Françoise Clavel-Chapelon
- University Paris–Sud, Unité Mixte de Recherche Scientifique (UMRS) 1018, Villejuif, France
- INSERM (National Institute of Health and Medical Research), CESP (Center for Research in Epidemiology and Population Health), Environmental Epidemiology of Cancer, Villejuif, France
| | - Laurence N Kolonel
- Département de Médecine Sociale et Préventive, Département de Santé Environnementale et Santé au Travail, Université de Montréal, Montreal, Quebec, Canada
| | - Constance Chen
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Andy Beck
- Department of Pathology, Beth Israel DeaconessMedical Center, Boston, Massachusetts, USA
- Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
| | - Susan E Hankinson
- Division of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, Massachusetts, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Christine D Berg
- Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, USA
| | - Robert N Hoover
- Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, M Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland
| | - Jonine D Figueroa
- Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Mia M Gaudet
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA
| | - W Ryan Diver
- Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA
| | - Walter C Willett
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA
| | - David J Hunter
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Jacques Simard
- Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Québec and Laval University, Quebec City, Quebec, Canada
| | - Javier Benitez
- Human Genotyping Unit–CEGEN, Human Cancer Genetics Programme, CNIO, Madrid, Spain
- Human Genetics Group, CNIO, Madrid, Spain
- Centro de Investigacion en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Mark E Sherman
- Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Georgia Chenevix-Trench
- Department of Genetics, Queensland Institute of Medical Research, Brisbane, Queensland, Australia
| | - Stephen J Chanock
- Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Celine Vachon
- Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
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Using multiple measures for quantitative trait association analyses: application to estimated glomerular filtration rate. J Hum Genet 2013; 58:461-6. [PMID: 23535967 PMCID: PMC3711970 DOI: 10.1038/jhg.2013.23] [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: 11/20/2012] [Revised: 02/27/2013] [Accepted: 03/03/2013] [Indexed: 01/07/2023]
Abstract
Studies of multiple measures of a quantitative trait can have greater precision and thus statistical power compared with single-measure studies, but this has rarely been studied in the relation to quantitative trait measurement error models in genetic association studies. Using estimated glomerular filtration rate (eGFR), a quantitative measure of kidney function, as an example we constructed measurement error models of a quantitative trait with systematic and random error components. We then examined the effects on precision of the parameter estimate between genetic loci and eGFR, resulting from varying the correlation and contribution of the error components. We also compared the empirical results from three genome-wide association studies (GWAS) of kidney function in 9049 European Americans: a single measure model, a three-measure model of the same biomarker of kidney function and a six-measure model of different biomarkers of kidney function. Simulations showed that given the same amount of overall errors, inclusion of measures with less correlated systematic errors led to greater gain in precision. The empirical GWAS results confirmed that both the three- and six-measure models detected more eGFR-associated genomic loci with stronger statistical association than the single-measure model despite some heterogeneity among the measures. Multiple measures of a quantitative trait can increase the statistical power of a study without additional participant recruitment. However, careful attention must be paid to the correlation of systematic errors and inconsistent associations when different biomarkers or methods are used to measure the quantitative trait.
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287
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Raynor LA, Pankow JS, Rasmussen-Torvik LJ, Tang W, Prizment A, Couper DJ. Pleiotropy and pathway analyses of genetic variants associated with both type 2 diabetes and prostate cancer. INTERNATIONAL JOURNAL OF MOLECULAR EPIDEMIOLOGY AND GENETICS 2013; 4:49-60. [PMID: 23565322 PMCID: PMC3612454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 01/28/2013] [Accepted: 02/23/2013] [Indexed: 06/02/2023]
Abstract
AIMS Epidemiological evidence shows that diabetes is associated with a reduced risk of prostate cancer. The objective of this study was to identify genes that may contribute to both type 2 diabetes and prostate cancer outcomes and the biological pathways these diseases may share. METHODS The Atherosclerosis Risk in Communities (ARIC) Study is a population-based prospective cohort study in four U.S. communities that included a baseline examination in 1987-89 and three follow-up exams at three year intervals. Participants were 45-64 years old at baseline. We conducted a genomewide association (GWA) study of incident type 2 diabetes in males, summarized variation across genetic loci into a polygenic risk score, and determined if that diabetes risk score was also associated with incident prostate cancer in the same study population. Secondarily we conducted a separate GWA study of prostate cancer, performed a pathway analysis of both type 2 diabetes and prostate cancer, and qualitatively determined if any of the biochemical pathways identified were shared between the two outcomes. RESULTS We found that the polygenic risk score for type 2 diabetes was not statistically significantly associated with prostate cancer. The pathway analysis also found no overlap between pathways associated with type 2 diabetes and prostate cancer. However, it did find that the growth hormone signaling pathway was statistically significantly associated with type 2 diabetes (p=0.0001). CONCLUSION The inability of this study to find an association between type 2 diabetes polygenic risk scores with prostate cancer or biological pathways in common suggests that shared genetic variants may not contribute significantly to explaining shared etiology.
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Affiliation(s)
- LA Raynor
- Division of Academic General Pediatrics, Department of Pediatrics, University of MinnesotaMinneapolis, MN
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of MinnesotaMinneapolis, MN
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University, Feinberg School of MedicineChicago, IL
| | - Weihong Tang
- Division of Epidemiology and Community Health, School of Public Health, University of MinnesotaMinneapolis, MN
| | - Anna Prizment
- Division of Epidemiology and Community Health, School of Public Health, University of MinnesotaMinneapolis, MN
| | - David J Couper
- Department of Biostatistics, University of North Carolina at Chapel HillChapel Hill, NC
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Divaris K, Monda KL, North KE, Olshan AF, Reynolds LM, Hsueh WC, Lange EM, Moss K, Barros SP, Weyant RJ, Liu Y, Newman AB, Beck JD, Offenbacher S. Exploring the genetic basis of chronic periodontitis: a genome-wide association study. Hum Mol Genet 2013; 22:2312-24. [PMID: 23459936 PMCID: PMC3652417 DOI: 10.1093/hmg/ddt065] [Citation(s) in RCA: 179] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Chronic periodontitis (CP) is a common oral disease that confers substantial systemic inflammatory and microbial burden and is a major cause of tooth loss. Here, we present the results of a genome-wide association study of CP that was carried out in a cohort of 4504 European Americans (EA) participating in the Atherosclerosis Risk in Communities (ARIC) Study (mean age—62 years, moderate CP—43% and severe CP—17%). We detected no genome-wide significant association signals for CP; however, we found suggestive evidence of association (P < 5 × 10−6) for six loci, including NIN, NPY, WNT5A for severe CP and NCR2, EMR1, 10p15 for moderate CP. Three of these loci had concordant effect size and direction in an independent sample of 656 adult EA participants of the Health, Aging, and Body Composition (Health ABC) Study. Meta-analysis pooled estimates were severe CP (n = 958 versus health: n = 1909)—NPY, rs2521634 [G]: odds ratio [OR = 1.49 (95% confidence interval (CI = 1.28–1.73, P = 3.5 × 10−7))]; moderate CP (n = 2293)—NCR2, rs7762544 [G]: OR = 1.40 (95% CI = 1.24–1.59, P = 7.5 × 10−8), EMR1, rs3826782 [A]: OR = 2.01 (95% CI = 1.52–2.65, P = 8.2 × 10−7). Canonical pathway analysis indicated significant enrichment of nervous system signaling, cellular immune response and cytokine signaling pathways. A significant interaction of NUAK1 (rs11112872, interaction P = 2.9 × 10−9) with smoking in ARIC was not replicated in Health ABC, although estimates of heritable variance in severe CP explained by all single nucleotide polymorphisms increased from 18 to 52% with the inclusion of a genome-wide interaction term with smoking. These genome-wide association results provide information on multiple candidate regions and pathways for interrogation in future genetic studies of CP.
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Affiliation(s)
- Kimon Divaris
- Department of Pediatric Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
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Fritsche LG, Chen W, Schu M, Yaspan BL, Yu Y, Thorleifsson G, Zack DJ, Arakawa S, Cipriani V, Ripke S, Igo RP, Buitendijk GHS, Sim X, Weeks DE, Guymer RH, Merriam JE, Francis PJ, Hannum G, Agarwal A, Armbrecht AM, Audo I, Aung T, Barile GR, Benchaboune M, Bird AC, Bishop PN, Branham KE, Brooks M, Brucker AJ, Cade WH, Cain MS, Campochiaro PA, Chan CC, Cheng CY, Chew EY, Chin KA, Chowers I, Clayton DG, Cojocaru R, Conley YP, Cornes BK, Daly MJ, Dhillon B, Edwards AO, Evangelou E, Fagerness J, Ferreyra HA, Friedman JS, Geirsdottir A, George RJ, Gieger C, Gupta N, Hagstrom SA, Harding SP, Haritoglou C, Heckenlively JR, Holz FG, Hughes G, Ioannidis JPA, Ishibashi T, Joseph P, Jun G, Kamatani Y, Katsanis N, N Keilhauer C, Khan JC, Kim IK, Kiyohara Y, Klein BEK, Klein R, Kovach JL, Kozak I, Lee CJ, Lee KE, Lichtner P, Lotery AJ, Meitinger T, Mitchell P, Mohand-Saïd S, Moore AT, Morgan DJ, Morrison MA, Myers CE, Naj AC, Nakamura Y, Okada Y, Orlin A, Ortube MC, Othman MI, Pappas C, Park KH, Pauer GJT, Peachey NS, Poch O, Priya RR, Reynolds R, Richardson AJ, Ripp R, Rudolph G, Ryu E, et alFritsche LG, Chen W, Schu M, Yaspan BL, Yu Y, Thorleifsson G, Zack DJ, Arakawa S, Cipriani V, Ripke S, Igo RP, Buitendijk GHS, Sim X, Weeks DE, Guymer RH, Merriam JE, Francis PJ, Hannum G, Agarwal A, Armbrecht AM, Audo I, Aung T, Barile GR, Benchaboune M, Bird AC, Bishop PN, Branham KE, Brooks M, Brucker AJ, Cade WH, Cain MS, Campochiaro PA, Chan CC, Cheng CY, Chew EY, Chin KA, Chowers I, Clayton DG, Cojocaru R, Conley YP, Cornes BK, Daly MJ, Dhillon B, Edwards AO, Evangelou E, Fagerness J, Ferreyra HA, Friedman JS, Geirsdottir A, George RJ, Gieger C, Gupta N, Hagstrom SA, Harding SP, Haritoglou C, Heckenlively JR, Holz FG, Hughes G, Ioannidis JPA, Ishibashi T, Joseph P, Jun G, Kamatani Y, Katsanis N, N Keilhauer C, Khan JC, Kim IK, Kiyohara Y, Klein BEK, Klein R, Kovach JL, Kozak I, Lee CJ, Lee KE, Lichtner P, Lotery AJ, Meitinger T, Mitchell P, Mohand-Saïd S, Moore AT, Morgan DJ, Morrison MA, Myers CE, Naj AC, Nakamura Y, Okada Y, Orlin A, Ortube MC, Othman MI, Pappas C, Park KH, Pauer GJT, Peachey NS, Poch O, Priya RR, Reynolds R, Richardson AJ, Ripp R, Rudolph G, Ryu E, Sahel JA, Schaumberg DA, Scholl HPN, Schwartz SG, Scott WK, Shahid H, Sigurdsson H, Silvestri G, Sivakumaran TA, Smith RT, Sobrin L, Souied EH, Stambolian DE, Stefansson H, Sturgill-Short GM, Takahashi A, Tosakulwong N, Truitt BJ, Tsironi EE, Uitterlinden AG, van Duijn CM, Vijaya L, Vingerling JR, Vithana EN, Webster AR, Wichmann HE, Winkler TW, Wong TY, Wright AF, Zelenika D, Zhang M, Zhao L, Zhang K, Klein ML, Hageman GS, Lathrop GM, Stefansson K, Allikmets R, Baird PN, Gorin MB, Wang JJ, Klaver CCW, Seddon JM, Pericak-Vance MA, Iyengar SK, Yates JRW, Swaroop A, Weber BHF, Kubo M, Deangelis MM, Léveillard T, Thorsteinsdottir U, Haines JL, Farrer LA, Heid IM, Abecasis GR. Seven new loci associated with age-related macular degeneration. Nat Genet 2013; 45:433-9, 439e1-2. [PMID: 23455636 PMCID: PMC3739472 DOI: 10.1038/ng.2578] [Show More Authors] [Citation(s) in RCA: 589] [Impact Index Per Article: 49.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2012] [Accepted: 02/07/2012] [Indexed: 12/11/2022]
Abstract
Age-related macular degeneration (AMD) is a common cause of blindness in older individuals. To accelerate the understanding of AMD biology and help design new therapies, we executed a collaborative genome-wide association study, including >17,100 advanced AMD cases and >60,000 controls of European and Asian ancestry. We identified 19 loci associated at P < 5 × 10(-8). These loci show enrichment for genes involved in the regulation of complement activity, lipid metabolism, extracellular matrix remodeling and angiogenesis. Our results include seven loci with associations reaching P < 5 × 10(-8) for the first time, near the genes COL8A1-FILIP1L, IER3-DDR1, SLC16A8, TGFBR1, RAD51B, ADAMTS9 and B3GALTL. A genetic risk score combining SNP genotypes from all loci showed similar ability to distinguish cases and controls in all samples examined. Our findings provide new directions for biological, genetic and therapeutic studies of AMD.
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Affiliation(s)
- Lars G Fritsche
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
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Verhoeven VJM, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, Höhn R, MacGregor S, Hewitt AW, Nag A, Cheng CY, Yonova-Doing E, Zhou X, Ikram MK, Buitendijk GHS, McMahon G, Kemp JP, Pourcain BS, Simpson CL, Mäkelä KM, Lehtimäki T, Kähönen M, Paterson AD, Hosseini SM, Wong HS, Xu L, Jonas JB, Pärssinen O, Wedenoja J, Yip SP, Ho DWH, Pang CP, Chen LJ, Burdon KP, Craig JE, Klein BEK, Klein R, Haller T, Metspalu A, Khor CC, Tai ES, Aung T, Vithana E, Tay WT, Barathi VA, Chen P, Li R, Liao J, Zheng Y, Ong RT, Döring A, Evans DM, Timpson NJ, Verkerk AJMH, Meitinger T, Raitakari O, Hawthorne F, Spector TD, Karssen LC, Pirastu M, Murgia F, Ang W, Mishra A, Montgomery GW, Pennell CE, Cumberland PM, Cotlarciuc I, Mitchell P, Wang JJ, Schache M, Janmahasatian S, Janmahasathian S, Igo RP, Lass JH, Chew E, Iyengar SK, Gorgels TGMF, Rudan I, Hayward C, Wright AF, Polasek O, Vatavuk Z, Wilson JF, Fleck B, Zeller T, Mirshahi A, Müller C, Uitterlinden AG, Rivadeneira F, Vingerling JR, Hofman A, Oostra BA, Amin N, Bergen AAB, Teo YY, Rahi JS, Vitart V, Williams C, Baird PN, Wong TY, Oexle K, et alVerhoeven VJM, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, Höhn R, MacGregor S, Hewitt AW, Nag A, Cheng CY, Yonova-Doing E, Zhou X, Ikram MK, Buitendijk GHS, McMahon G, Kemp JP, Pourcain BS, Simpson CL, Mäkelä KM, Lehtimäki T, Kähönen M, Paterson AD, Hosseini SM, Wong HS, Xu L, Jonas JB, Pärssinen O, Wedenoja J, Yip SP, Ho DWH, Pang CP, Chen LJ, Burdon KP, Craig JE, Klein BEK, Klein R, Haller T, Metspalu A, Khor CC, Tai ES, Aung T, Vithana E, Tay WT, Barathi VA, Chen P, Li R, Liao J, Zheng Y, Ong RT, Döring A, Evans DM, Timpson NJ, Verkerk AJMH, Meitinger T, Raitakari O, Hawthorne F, Spector TD, Karssen LC, Pirastu M, Murgia F, Ang W, Mishra A, Montgomery GW, Pennell CE, Cumberland PM, Cotlarciuc I, Mitchell P, Wang JJ, Schache M, Janmahasatian S, Janmahasathian S, Igo RP, Lass JH, Chew E, Iyengar SK, Gorgels TGMF, Rudan I, Hayward C, Wright AF, Polasek O, Vatavuk Z, Wilson JF, Fleck B, Zeller T, Mirshahi A, Müller C, Uitterlinden AG, Rivadeneira F, Vingerling JR, Hofman A, Oostra BA, Amin N, Bergen AAB, Teo YY, Rahi JS, Vitart V, Williams C, Baird PN, Wong TY, Oexle K, Pfeiffer N, Mackey DA, Young TL, van Duijn CM, Saw SM, Bailey-Wilson JE, Stambolian D, Klaver CC, Hammond CJ. Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nat Genet 2013; 45:314-8. [PMID: 23396134 PMCID: PMC3740568 DOI: 10.1038/ng.2554] [Show More Authors] [Citation(s) in RCA: 345] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2012] [Accepted: 01/16/2013] [Indexed: 02/06/2023]
Abstract
Refractive error is the most common eye disorder worldwide and is a prominent cause of blindness. Myopia affects over 30% of Western populations and up to 80% of Asians. The CREAM consortium conducted genome-wide meta-analyses, including 37,382 individuals from 27 studies of European ancestry and 8,376 from 5 Asian cohorts. We identified 16 new loci for refractive error in individuals of European ancestry, of which 8 were shared with Asians. Combined analysis identified 8 additional associated loci. The new loci include candidate genes with functions in neurotransmission (GRIA4), ion transport (KCNQ5), retinoic acid metabolism (RDH5), extracellular matrix remodeling (LAMA2 and BMP2) and eye development (SIX6 and PRSS56). We also confirmed previously reported associations with GJD2 and RASGRF1. Risk score analysis using associated SNPs showed a tenfold increased risk of myopia for individuals carrying the highest genetic load. Our results, based on a large meta-analysis across independent multiancestry studies, considerably advance understanding of the mechanisms involved in refractive error and myopia.
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291
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Acar EF, Sun L. A Generalized Kruskal–Wallis Test Incorporating Group Uncertainty with Application to Genetic Association Studies. Biometrics 2013; 69:427-35. [DOI: 10.1111/biom.12006] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2012] [Revised: 08/01/2012] [Accepted: 10/01/2012] [Indexed: 12/11/2022]
Affiliation(s)
- Elif F. Acar
- Department of Statistics, University of Toronto)OntarioCanada
- Department of Statistics, University of ManitobaManitobaCanada
| | - Lei Sun
- Department of Statistics, University of Toronto)OntarioCanada
- Dalla Lana School of Public Health, University of TorontoOntarioCanada
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292
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Genetic determinants of trabecular and cortical volumetric bone mineral densities and bone microstructure. PLoS Genet 2013; 9:e1003247. [PMID: 23437003 PMCID: PMC3578773 DOI: 10.1371/journal.pgen.1003247] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Accepted: 12/02/2012] [Indexed: 11/24/2022] Open
Abstract
Most previous genetic epidemiology studies within the field of osteoporosis have focused on the genetics of the complex trait areal bone mineral density (aBMD), not being able to differentiate genetic determinants of cortical volumetric BMD (vBMD), trabecular vBMD, and bone microstructural traits. The objective of this study was to separately identify genetic determinants of these bone traits as analysed by peripheral quantitative computed tomography (pQCT). Separate GWA meta-analyses for cortical and trabecular vBMDs were performed. The cortical vBMD GWA meta-analysis (n = 5,878) followed by replication (n = 1,052) identified genetic variants in four separate loci reaching genome-wide significance (RANKL, rs1021188, p = 3.6×10−14; LOC285735, rs271170, p = 2.7×10−12; OPG, rs7839059, p = 1.2×10−10; and ESR1/C6orf97, rs6909279, p = 1.1×10−9). The trabecular vBMD GWA meta-analysis (n = 2,500) followed by replication (n = 1,022) identified one locus reaching genome-wide significance (FMN2/GREM2, rs9287237, p = 1.9×10−9). High-resolution pQCT analyses, giving information about bone microstructure, were available in a subset of the GOOD cohort (n = 729). rs1021188 was significantly associated with cortical porosity while rs9287237 was significantly associated with trabecular bone fraction. The genetic variant in the FMN2/GREM2 locus was associated with fracture risk in the MrOS Sweden cohort (HR per extra T allele 0.75, 95% confidence interval 0.60–0.93) and GREM2 expression in human osteoblasts. In conclusion, five genetic loci associated with trabecular or cortical vBMD were identified. Two of these (FMN2/GREM2 and LOC285735) are novel bone-related loci, while the other three have previously been reported to be associated with aBMD. The genetic variants associated with cortical and trabecular bone parameters differed, underscoring the complexity of the genetics of bone parameters. We propose that a genetic variant in the RANKL locus influences cortical vBMD, at least partly, via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences GREM2 expression in osteoblasts and thereby trabecular number and thickness as well as fracture risk. Osteoporosis is a common highly heritable skeletal disease characterized by reduced bone mineral density (BMD) and deteriorated bone microstructure, resulting in an increased risk of fracture. Most previous genetic epidemiology studies have focused on the genetics of the complex trait BMD, not being able to separate genetic determinants of the trabecular and cortical bone compartments and bone microstructure. The trabecular and cortical BMDs can be analysed separately by computed tomography. Therefore, we performed separate genome-wide association studies for trabecular and cortical BMDs, demonstrating that the genetic determinants of cortical and trabecular BMDs differ. Genetic variants in the RANKL, LOC285735, OPG, and ESR1 loci were associated with cortical BMD, while a genetic variant in the FMN2/GREM2 locus was associated with trabecular BMD. Two of these are novel bone-related loci. Follow-up analyses of bone microstructure demonstrated that a genetic variant in the RANKL locus is associated with cortical porosity and that the FMN2/GREM2 locus is associated with trabecular number and thickness. We propose that a genetic variant in the RANKL locus influences cortical BMD via effects on cortical porosity, and that a genetic variant in the FMN2/GREM2 locus influences trabecular BMD and fracture risk via effects on both trabecular number and thickness.
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Genome-wide association study identified the human leukocyte antigen region as a novel locus for plasma beta-2 microglobulin. Hum Genet 2013. [PMID: 23417110 DOI: 10.1007/s00439‐013‐1274‐7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Beta-2 microglobulin (B2M) is a component of the major histocompatibility complex (MHC) class I molecule and has been studied as a biomarker of kidney function, cardiovascular diseases and mortality. Little is known about the genes influencing its levels directly or through glomerular filtration rate (GFR). We conducted a genome-wide association study of plasma B2M levels in 6738 European Americans from the Atherosclerosis Risk in Communities study to identify novel loci for B2M and assessed its association with known estimated GFR (eGFR) loci. We identified 2 genome-wide significant loci. One was in the human leukocyte antigen (HLA) region on chromosome 6 (lowest p value = 1.8 × 10(-23) for rs9264638). At this locus, 6 index SNPs accounted for 3.2 % of log(B2M) variance, and their association with B2M could largely be explained by imputed classical alleles of the MHC class I genes: HLA-A, HLA-B, or HLA-C. The index SNPs at this locus were not associated with eGFR based on serum creatinine (eGFRcr). The other locus of B2M was on chromosome 12 (rs3184504 at SH2B3, beta = 0.02, p value = 3.1 × 10(-8)), which was previously implicated as an eGFR locus. In conclusion, although B2M is known to be a component of MHC class I molecule, the association between HLA class I alleles and plasma B2M levels in a community-based population is novel. The identification of the two novel loci for B2M extends our understanding of its metabolism and informs its use as a kidney filtration biomarker.
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Tin A, Astor BC, Boerwinkle E, Hoogeveen RC, Coresh J, Kao WHL. Genome-wide association study identified the human leukocyte antigen region as a novel locus for plasma beta-2 microglobulin. Hum Genet 2013; 132:619-27. [PMID: 23417110 DOI: 10.1007/s00439-013-1274-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2012] [Accepted: 02/06/2013] [Indexed: 01/11/2023]
Abstract
Beta-2 microglobulin (B2M) is a component of the major histocompatibility complex (MHC) class I molecule and has been studied as a biomarker of kidney function, cardiovascular diseases and mortality. Little is known about the genes influencing its levels directly or through glomerular filtration rate (GFR). We conducted a genome-wide association study of plasma B2M levels in 6738 European Americans from the Atherosclerosis Risk in Communities study to identify novel loci for B2M and assessed its association with known estimated GFR (eGFR) loci. We identified 2 genome-wide significant loci. One was in the human leukocyte antigen (HLA) region on chromosome 6 (lowest p value = 1.8 × 10(-23) for rs9264638). At this locus, 6 index SNPs accounted for 3.2 % of log(B2M) variance, and their association with B2M could largely be explained by imputed classical alleles of the MHC class I genes: HLA-A, HLA-B, or HLA-C. The index SNPs at this locus were not associated with eGFR based on serum creatinine (eGFRcr). The other locus of B2M was on chromosome 12 (rs3184504 at SH2B3, beta = 0.02, p value = 3.1 × 10(-8)), which was previously implicated as an eGFR locus. In conclusion, although B2M is known to be a component of MHC class I molecule, the association between HLA class I alleles and plasma B2M levels in a community-based population is novel. The identification of the two novel loci for B2M extends our understanding of its metabolism and informs its use as a kidney filtration biomarker.
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Affiliation(s)
- Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
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Del-Aguila JL, Beitelshees AL, Cooper-Dehoff RM, Chapman AB, Gums JG, Bailey K, Gong Y, Turner ST, Johnson JA, Boerwinkle E. Genome-wide association analyses suggest NELL1 influences adverse metabolic response to HCTZ in African Americans. THE PHARMACOGENOMICS JOURNAL 2013; 14:35-40. [PMID: 23400010 PMCID: PMC3812324 DOI: 10.1038/tpj.2013.3] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2012] [Revised: 12/13/2012] [Accepted: 01/03/2013] [Indexed: 12/02/2022]
Abstract
Hydrochlorothiazide (HCTZ) is one of the most widely prescribed antihypertensive medications. Although it is well known that HCTZ is associated with hyperglycemia and hypertriglyceridemia, the mechanisms underlying these adverse effects are not well understood. We performed a genome-wide association study and meta-analysis of the change in fasting plasma glucose and triglycerides in response to HCTZ from two different clinical trials: the Pharmacogenomic Evaluation of Antihypertensive Responses and the Genetic Epidemiology of Responses to Antihypertensive studies. Two single-nucleotide polymorphisms (rs12279250 and rs4319515 (r2=0.73)), located at 11p15.1 in the NELL1 gene, achieved genome-wide significance for association with change in fasting plasma triglycerides in African Americans, whereby each variant allele was associated with a 28 mg dl−1 increase in the change in triglycerides. NELL1 encodes a cytoplasmic protein that contains epidermal growth factor-like repeats and has been shown to represses adipogenic differentiation. These findings may represent a novel mechanism underlying HCTZ-induced adverse metabolic effects.
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Affiliation(s)
- J L Del-Aguila
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - A L Beitelshees
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland, Baltimore, MD, USA
| | - R M Cooper-Dehoff
- Department of Pharmacotherapy and Translational Research and Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, FL, USA
| | - A B Chapman
- Renal Division, Emory University School of Medicine, Atlanta, GA, USA
| | - J G Gums
- Department of Pharmacotherapy and Translational Research and Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, FL, USA
| | - K Bailey
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Y Gong
- Department of Pharmacotherapy and Translational Research and Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, FL, USA
| | - S T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - J A Johnson
- Department of Pharmacotherapy and Translational Research and Division of Cardiovascular Medicine, Colleges of Pharmacy and Medicine, University of Florida, Gainesville, FL, USA
| | - E Boerwinkle
- 1] Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA [2] Human Genome Sequencing Center at Baylor College of Medicine, Houston, TX, USA
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296
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Jensen RA, Sim X, Li X, Cotch MF, Ikram MK, Holliday EG, Eiriksdottir G, Harris TB, Jonasson F, Klein BEK, Launer LJ, Smith AV, Boerwinkle E, Cheung N, Hewitt AW, Liew G, Mitchell P, Wang JJ, Attia J, Scott R, Glazer NL, Lumley T, McKnight B, Psaty BM, Taylor K, Hofman A, de Jong PTVM, Rivadeneira F, Uitterlinden AG, Tay WT, Teo YY, Seielstad M, Liu J, Cheng CY, Saw SM, Aung T, Ganesh SK, O'Donnell CJ, Nalls MA, Wiggins KL, Kuo JZ, van Duijn CM, Gudnason V, Klein R, Siscovick DS, Rotter JI, Tai ES, Vingerling J, Wong TY. Genome-wide association study of retinopathy in individuals without diabetes. PLoS One 2013; 8:e54232. [PMID: 23393555 PMCID: PMC3564946 DOI: 10.1371/journal.pone.0054232] [Citation(s) in RCA: 11] [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: 08/08/2012] [Accepted: 12/11/2012] [Indexed: 01/11/2023] Open
Abstract
Background Mild retinopathy (microaneurysms or dot-blot hemorrhages) is observed in persons without diabetes or hypertension and may reflect microvascular disease in other organs. We conducted a genome-wide association study (GWAS) of mild retinopathy in persons without diabetes. Methods A working group agreed on phenotype harmonization, covariate selection and analytic plans for within-cohort GWAS. An inverse-variance weighted fixed effects meta-analysis was performed with GWAS results from six cohorts of 19,411 Caucasians. The primary analysis included individuals without diabetes and secondary analyses were stratified by hypertension status. We also singled out the results from single nucleotide polymorphisms (SNPs) previously shown to be associated with diabetes and hypertension, the two most common causes of retinopathy. Results No SNPs reached genome-wide significance in the primary analysis or the secondary analysis of participants with hypertension. SNP, rs12155400, in the histone deacetylase 9 gene (HDAC9) on chromosome 7, was associated with retinopathy in analysis of participants without hypertension, −1.3±0.23 (beta ± standard error), p = 6.6×10−9. Evidence suggests this was a false positive finding. The minor allele frequency was low (∼2%), the quality of the imputation was moderate (r2 ∼0.7), and no other common variants in the HDAC9 gene were associated with the outcome. SNPs found to be associated with diabetes and hypertension in other GWAS were not associated with retinopathy in persons without diabetes or in subgroups with or without hypertension. Conclusions This GWAS of retinopathy in individuals without diabetes showed little evidence of genetic associations. Further studies are needed to identify genes associated with these signs in order to help unravel novel pathways and determinants of microvascular diseases.
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Affiliation(s)
- Richard A Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America.
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297
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Lopes MC, Hysi PG, Verhoeven VJM, Macgregor S, Hewitt AW, Montgomery GW, Cumberland P, Vingerling JR, Young TL, van Duijn CM, Oostra B, Uitterlinden AG, Rahi JS, Mackey DA, Klaver CCW, Andrew T, Hammond CJ. Identification of a candidate gene for astigmatism. Invest Ophthalmol Vis Sci 2013; 54:1260-7. [PMID: 23322567 DOI: 10.1167/iovs.12-10463] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
PURPOSE Astigmatism is a common refractive error that reduces vision, where the curvature and refractive power of the cornea in one meridian are less than those of the perpendicular axis. It is a complex trait likely to be influenced by both genetic and environmental factors. Twin studies of astigmatism have found approximately 60% of phenotypic variance is explained by genetic factors. This study aimed to identify susceptibility loci for astigmatism. METHODS We performed a meta-analysis of seven genome-wide association studies that included 22,100 individuals of European descent, where astigmatism was defined as the number of diopters of cylinder prescription, using fixed effect inverse variance-weighted methods. RESULTS A susceptibility locus was identified with lead single nucleotide polymorphism rs3771395 on chromosome 2p13.3 (meta-analysis, P = 1.97 × 10(-7)) in the VAX2 gene. VAX2 plays an important role in the development of the dorsoventral axis of the eye. Animal studies have shown a gradient in astigmatism along the vertical plane, with corresponding changes in refraction, particularly in the ventral field. CONCLUSIONS This finding advances the understanding of refractive error, and provides new potential pathways to be evaluated with regard to the development of astigmatism.
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Affiliation(s)
- Margarida C Lopes
- Department of Twin Research and Genetic Epidemiology, King's College London, St. Thomas' Hospital, London, United Kingdom
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298
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Yu B, Barbalic M, Brautbar A, Nambi V, Hoogeveen RC, Tang W, Mosley TH, Rotter JI, deFilippi CR, O’Donnell CJ, Kathiresan S, Rice K, Heckbert SR, Ballantyne CM, Psaty BM, Boerwinkle E. Association of genome-wide variation with highly sensitive cardiac troponin-T levels in European Americans and Blacks: a meta-analysis from atherosclerosis risk in communities and cardiovascular health studies. CIRCULATION. CARDIOVASCULAR GENETICS 2013; 6:82-8. [PMID: 23247143 PMCID: PMC3693561 DOI: 10.1161/circgenetics.112.963058] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND High levels of cardiac troponin T, measured by a highly sensitive assay (hs-cTnT), are strongly associated with incident coronary heart disease and heart failure. To date, no large-scale genome-wide association study of hs-cTnT has been reported. We sought to identify novel genetic variants that are associated with hs-cTnT levels. METHODS AND RESULTS We performed a genome-wide association in 9491 European Americans and 2053 blacks free of coronary heart disease and heart failure from 2 prospective cohorts: the Atherosclerosis Risk in Communities Study and the Cardiovascular Health Study. Genome-wide association studies were conducted in each study and race stratum. Fixed-effect meta-analyses combined the results of linear regression from 2 cohorts within each race stratum and then across race strata to produce overall estimates and probability values. The meta-analysis identified a significant association at chromosome 8q13 (rs10091374; P=9.06×10(-9)) near the nuclear receptor coactivator 2 (NCOA2) gene. Overexpression of NCOA2 can be detected in myoblasts. An additional analysis using logistic regression and the clinically motivated 99th percentile cut point detected a significant association at 1q32 (rs12564445; P=4.73×10(-8)) in the gene TNNT2, which encodes the cardiac troponin T protein itself. The hs-cTnT-associated single-nucleotide polymorphisms were not associated with coronary heart disease in a large case-control study, but rs12564445 was significantly associated with incident heart failure in Atherosclerosis Risk in Communities Study European Americans (hazard ratio=1.16; P=0.004). CONCLUSIONS We identified 2 loci, near NCOA2 and in the TNNT2 gene, at which variation was significantly associated with hs-cTnT levels. Further use of the new assay should enable replication of these results.
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Affiliation(s)
- Bing Yu
- Human Genetic Center, University of Texas Health Science Center at Houston
| | - Maja Barbalic
- Human Genetic Center, University of Texas Health Science Center at Houston
| | - Ariel Brautbar
- Dept of Medicine, Baylor College of Medicine, Houston, TX
| | - Vijay Nambi
- Dept of Medicine, Baylor College of Medicine, Houston, TX
| | | | - Weihong Tang
- Dept of Epidemiology, University of Minnesota, Minneapolis, MN
| | - Thomas H. Mosley
- Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS
| | - Jerome I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Christopher J. O’Donnell
- National Heart, Lung, and Blood Institute & Framingham Heart Study, National Institutes of Health Bethesda, MD
| | - Sekar Kathiresan
- Center for Human Genetic Rsrch & Cardiovascular Rsrch Ctr, MGH & Dept of Med, Harvard Med School, Boston, MA
| | - Ken Rice
- Dept of Biostatistics, University of Washington
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit & Dept of Epidemiology, University of Washington
| | | | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Depts of Medicine, Epidemiology, and Health Services, University of Washington & Group Health Research Institute, Group Health Cooperative, Seattle, WA
| | - Eric Boerwinkle
- Human Genetic Center, University of Texas Health Science Center at Houston
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
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299
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Chu AY, Workalemahu T, Paynter NP, Rose LM, Giulianini F, Tanaka T, Ngwa JS, Qi Q, Curhan GC, Rimm EB, Hunter DJ, Pasquale LR, Ridker PM, Hu FB, Chasman DI, Qi L. Novel locus including FGF21 is associated with dietary macronutrient intake. Hum Mol Genet 2013; 22:1895-902. [PMID: 23372041 DOI: 10.1093/hmg/ddt032] [Citation(s) in RCA: 152] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Dietary intake of macronutrients (carbohydrate, protein, and fat) has been associated with risk of chronic conditions such as obesity and diabetes. Family studies have reported a moderate contribution of genetics to variation in macronutrient intake. In a genome-wide meta-analysis of a population-based discovery cohort (n = 33 533), rs838133 in FGF21 (19q13.33), rs197273 near TRAF family member-associated NF-kappa-B activator (TANK) (2p24.2), and rs10163409 in FTO (16q12.2) were among the top associations (P < 10(-5)) for percentage of total caloric intake from protein and carbohydrate. rs838133 was replicated in silico in an independent sample from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE) Nutrition Working Group (n = 38 360) and attained genome-wide significance in combined analysis (Pjoint = 7.9 × 10(-9)). A cytokine involved in cellular metabolism, FGF21 is a potential susceptibility gene for obesity and type 2 diabetes. Our results highlight the potential of genetic variation for determining dietary macronutrient intake.
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Affiliation(s)
- Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
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van der Sluis S, Posthuma D, Dolan CV. TATES: efficient multivariate genotype-phenotype analysis for genome-wide association studies. PLoS Genet 2013; 9:e1003235. [PMID: 23359524 PMCID: PMC3554627 DOI: 10.1371/journal.pgen.1003235] [Citation(s) in RCA: 150] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2012] [Accepted: 11/26/2012] [Indexed: 11/19/2022] Open
Abstract
To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. The genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS methods are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score, which frequently results in a considerable loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. We present a new multivariate method called TATES (Trait-based Association Test that uses Extended Simes procedure). Extensive simulations show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests of composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES uncovers both genetic variants that are common to multiple phenotypes as well as phenotype specific variants. TATES thus provides a more complete view of the genetic architecture of complex traits and constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants.
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Affiliation(s)
- Sophie van der Sluis
- Department of Functional Genomics and Department of Clinical Genetics, VU Medical Center, Amsterdam, The Netherlands.
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