Pulmonary function measures are heritable traits that predict morbidity and mortality and define chronic obstructive pulmonary disease (COPD). We tested genome-wide association with forced expiratory ...volume in 1 s (FEV(1)) and the ratio of FEV(1) to forced vital capacity (FVC) in the SpiroMeta consortium (n = 20,288 individuals of European ancestry). We conducted a meta-analysis of top signals with data from direct genotyping (n < or = 32,184 additional individuals) and in silico summary association data from the CHARGE Consortium (n = 21,209) and the Health 2000 survey (n < or = 883). We confirmed the reported locus at 4q31 and identified associations with FEV(1) or FEV(1)/FVC and common variants at five additional loci: 2q35 in TNS1 (P = 1.11 x 10(-12)), 4q24 in GSTCD (2.18 x 10(-23)), 5q33 in HTR4 (P = 4.29 x 10(-9)), 6p21 in AGER (P = 3.07 x 10(-15)) and 15q23 in THSD4 (P = 7.24 x 10(-15)). mRNA analyses showed expression of TNS1, GSTCD, AGER, HTR4 and THSD4 in human lung tissue. These associations offer mechanistic insight into pulmonary function regulation and indicate potential targets for interventions to alleviate respiratory disease.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that ...is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (n = 10,623 Europeans from pregnancy/birth cohorts) and followed up two lead ...signals in 13 replication studies (n = 27,591). rs900400 near LEKR1 and CCNL1 (P = 2 × 10−35) and rs9883204 in ADCY5 (P = 7 × 10−15) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and susceptibility to type 2 diabetes, providing evidence that the well-described association between lower birth weight and subsequent type 2 diabetes has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, we found that the 9% of Europeans carrying four birth weight-lowering alleles were, on average, 113 g (95% CI 89-137 g) lighter at birth than the 24% with zero or one alleles (Ptrend = 7 × 10−30). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Our genome-wide association study of celiac disease previously identified risk variants in the IL2-IL21 region. To identify additional risk variants, we genotyped 1,020 of the most strongly ...associated non-HLA markers in an additional 1,643 cases and 3,406 controls. Through joint analysis including the genome-wide association study data (767 cases, 1,422 controls), we identified seven previously unknown risk regions (P < 5 x 10(-7)). Six regions harbor genes controlling immune responses, including CCR3, IL12A, IL18RAP, RGS1, SH2B3 (nsSNP rs3184504) and TAGAP. Whole-blood IL18RAP mRNA expression correlated with IL18RAP genotype. Type 1 diabetes and celiac disease share HLA-DQ, IL2-IL21, CCR3 and SH2B3 risk regions. Thus, this extensive genome-wide association follow-up study has identified additional celiac disease risk variants in relevant biological pathways.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Genome-wide association studies have previously identified 23 genetic loci associated with circulating fibrinogen concentration. These studies used HapMap imputation and did not examine the ...X-chromosome. 1000 Genomes imputation provides better coverage of uncommon variants, and includes indels. We conducted a genome-wide association analysis of 34 studies imputed to the 1000 Genomes Project reference panel and including ∼120 000 participants of European ancestry (95 806 participants with data on the X-chromosome). Approximately 10.7 million single-nucleotide polymorphisms and 1.2 million indels were examined. We identified 41 genome-wide significant fibrinogen loci; of which, 18 were newly identified. There were no genome-wide significant signals on the X-chromosome. The lead variants of five significant loci were indels. We further identified six additional independent signals, including three rare variants, at two previously characterized loci: FGB and IRF1. Together the 41 loci explain 3% of the variance in plasma fibrinogen concentration.
Association of Novel Genetic Loci With Circulating Fibrinogen Levels A Genome-Wide Association Study in 6 Population-Based Cohorts
Abbas Dehghan, MD, DSc * ;
Qiong Yang, PhD * ;
Annette Peters, PhD * ...;
Saonli Basu, PhD ;
Joshua C. Bis, PhD ;
Alicja R. Rudnicka, PhD ;
Maryam Kavousi, MD, MSc ;
Ming-Huei Chen, PhD ;
Jens Baumert, PhD ;
Gordon D.O. Lowe, DSc ;
Barbara McKnight, PhD ;
Weihong Tang, MD, PhD ;
Moniek de Maat, PhD ;
Martin G. Larson ;
Susana Eyhermendy, PhD ;
Wendy L. McArdle, PhD ;
Thomas Lumley, PhD ;
James S. Pankow, PhD ;
Albert Hofman, MD, PhD ;
Joseph M. Massaro ;
Fernando Rivadeneira, MD, PhD ;
Melanie Kolz, MPH ;
Kent D. Taylor, PhD ;
Cornelia M. van Duijn, PhD ;
Sekar Kathiresan ;
Thomas Illig, PhD ;
Yurii S. Aulchenko, PhD ;
Kelly A. Volcik, PhD ;
Andrew D. Johnson, PhD ;
Andre G. Uitterlinden, PhD ;
Geoffrey H. Tofler ;
Christian Gieger, PhD ;
Wellcome Trust Case Control Consortium ;
Bruce M. Psaty, MD, PhD ;
David J. Couper, PhD ;
Eric Boerwinkle, PhD ;
Wolfgang Koenig, MD ;
Christopher J. O'Donnell, MD, MPH ;
Jacqueline C. Witteman, PhD ;
David P. Strachan, MD, PhD ;
Nicholas L. Smith, PhD and
Aaron R. Folsom, MD
From the Department of Epidemiology (A.D., M.K., A.H., C.M.v.D., Y.S.A., J.C.W.), Erasmus Medical Center, Rotterdam, The Netherlands; National Heart, Lung, and Blood Institute Framingham Heart Study (Q.Y., M.G.L., J.M.M., S.K., A.D.J., C.J.O.), Framingham, Mass; Department of Biostatistics (A.D., Q.Y., M.-H.C.), School of Public Health, Boston University; Department of Neurology and Framingham Heart Study (M.-H.C.), Boston University, Boston, Mass; Division of Biostatistics University of Minnesota (S.B.), Minneapolis, Minn; Departments of Hematology (M.d.M.) and Internal Medicine (F.R., A.G.U.), Erasmus Medical Center, Rotterdam, The Netherlands; Department of Mathematics (M.G.L., J.M.M.), Boston University, Boston, Mass; Division of Epidemiology and Community Health (W.T., J.S.P., A.R.F.), University of Minnesota, Minneapolis, Minn; Human Genetics Center and Institute of Molecular Medicine (K.A.V., E.B.), University of Texas Health Science Center, Houston, Tex; Department of Biostatistics, University of North Carolina, Chapel Hill, NC (D.J.C.); Division of Community Health Sciences (A.R.R., D.P.S.), St Georges, University of London, London, United Kingdom; ALSPAC Laboratory (W.L.M.), University of Bristol, Bristol, United Kingdom; Division of Cardiovascular and Medical Sciences (G.D.O.L.), University of Glasgow, Royal Infirmary, Glasgow, United Kingdom; The Wellcome Trust (W.T.C.C.C.), Hinxton, Cambridge, United Kingdom; Helmholtz Zentrum München, German Research Center for Environmental Health (A.P., J.B., M.K., T.I., C.G.), Institute of Epidemiology, Neuherberg, Germany; Cardiology Division (C.J.O.), Cardiovascular Research Center (S.K.), and Center for Human Genetic Research (S.K.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Royal North Shore Hospital (G.H.T.), Sydney, Australia; Department of Internal Medicine II-Cardiology (W.K.), University of Ulm, Ulm, Germany; Department of Statistics (S.E.), Pontificia Universidad Catolica de Chile, Chile; Seattle Epidemiologic Research and Information Center (N.L.S.), the Veterans Affairs Office of Research and Development; Center for Health Studies (B.M.P.), Group Health; Departments of Biostatistics (B.M., T.L.), Epidemiology (B.M.P., N.L.S.), Health Services (B.M.P.) and Medicine (J.C.B., B.M.P.), University of Washington, Seattle, Wash; Medical Genetics Institute (K.D.T.), Cedars-Sinai Medical Center, Los Angeles, Calif; and Division of Intramural Research (A.D.J., C.J.O.), National Heart, Lung and Blood Institute, Bethesda, Md.
Correspondence to Jacqueline C. Witteman, PhD, Department of Epidemiology, Erasmus Medical Center, P.O. Box 2040, 3000CA Rotterdam, The Netherlands (e-mail j.witteman{at}erasmusmc.nl ) or Christopher J. O'Donnell, MD, MPH, NHLBIs Framingham Heart Study, 73 Mount Wayte Ave, Suite #2, Framingham, MA 01702 (e-mail odonnellc@nhlbi.nih.gov).
Received October 1, 2008; accepted January 5, 2009.
Background— Fibrinogen is both central to blood coagulation and an acute-phase reactant. We aimed to identify common variants influencing circulation fibrinogen levels.
Methods and Results— We conducted a genome-wide association analysis on 6 population-based studies, the Rotterdam Study, the Framingham Heart Study, the Cardiovascular Health Study, the Atherosclerosis Risk in Communities Study, the Monitoring of Trends and Determinants in Cardiovascular Disease/KORA Augsburg Study, and the British 1958 Birth Cohort Study, including 22 096 participants of European ancestry. Four loci were marked by 1 or more single-nucleotide polymorphisms that demonstrated genome-wide significance ( P <5.0 x 10 –8 ). These included a single-nucleotide polymorphism located in the fibrinogen β chain ( FGB ) gene and 3 single-nucleotide polymorphisms representing newly identified loci. The high-signal single-nucleotide polymorphisms were rs1800789 in exon 7 of FGB ( P =1.8 x 10 –30 ), rs2522056 downstream from the interferon regulatory factor 1 ( IRF1 ) gene ( P =1.3 x 10 –15 ), rs511154 within intron 1 of the propionyl coenzyme A carboxylase ( PCCB ) gene ( P =5.9 x 10 –10 ), and rs1539019 on the NLR family pyrin domain containing 3 isoforms ( NLRP3 ) gene ( P =1.04 x 10 –8 ).
Conclusions— Our findings highlight biological pathways that may be important in regulation of inflammation underlying cardiovascular disease.
Key Words: genome-wide association study fibrinogen genes meta-analysis
CLINICAL PERSPECTIVE
*Drs Dehghan, Yang, and Peters contributed equally to this work.
Drs Strachan, Smith, and Folsom contributed equally to this work.
Guest Editor for this article was Donna K. Arnett, PhD.
The online-only Data Supplement is available at http://circgenetics.ahajournals.org/cgi/content/full/2/2/125/DC1.
Related Article
Association of Novel Genetic Loci With Circulating Fibrinogen Levels: A Genome-Wide Association Study in 6 Population-Based Cohorts
Abbas Dehghan, Qiong Yang, Annette Peters, Saonli Basu, Joshua C. Bis, Alicja R. Rudnicka, Maryam Kavousi, Ming-Huei Chen, Jens Baumert, Gordon D.O. Lowe, Barbara McKnight, Weihong Tang, Moniek de Maat, Martin G. Larson, Susana Eyhermendy, Wendy L. McArdle, Thomas Lumley, James S. Pankow, Albert Hofman, Joseph M. Massaro, Fernando Rivadeneira, Melanie Kolz, Kent D. Taylor, Cornelia M. van Duijn, Sekar Kathiresan, Thomas Illig, Yurii S. Aulchenko, Kelly A. Volcik, Andrew D. Johnson, Andre G. Uitterlinden, Geoffrey H. Tofler, Christian Gieger, Wellcome Trust Case Control Consortium, Bruce M. Psaty, David J. Couper, Eric Boerwinkle, Wolfgang Koenig, Christopher J. O'Donnell, Jacqueline C. Witteman, David P. Strachan, Nicholas L. Smith, and Aaron R. Folsom
Circ Cardiovasc Genet 2009 2: 125-133.
Abstract
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Background: High birth weight is associated with adult body mass index (BMI). We hypothesized that birth weight and BMI may partly share a common genetic background.
Objective: The objective was to ...examine the associations of 12 established BMI variants in or near the NEGR1, SEC16B, TMEM18, ETV5, GNPDA2, BDNF, MTCH2, BCDIN3D, SH2B1, FTO, MC4R, and KCTD15 genes and their additive score with birth weight.
Design:A meta-analysis was conducted with the use of 1) the European Prospective Investigation into Cancer and Nutrition (EPIC)–Norfolk, Hertfordshire, Fenland, and European Youth Heart Study cohorts (nmax = 14,060); 2) data extracted from the Early Growth Genetics Consortium meta-analysis of 6 genome-wide association studies for birth weight (nmax = 10,623); and 3) all published data (nmax = 14,837).
Results: Only the MTCH2 and FTO loci showed a nominally significant association with birth weight. The BMI-increasing allele of the MTCH2 variant (rs10838738) was associated with a lower birth weight (β ± SE: −13 ± 5 g/allele; P = 0.012; n = 23,680), and the BMI-increasing allele of the FTO variant (rs1121980) was associated with a higher birth weight (β ± SE: 11 ± 4 g/allele; P = 0.013; n = 28,219). These results were not significant after correction for multiple testing.
Conclusions: Obesity-susceptibility loci have a small or no effect on weight at birth. Some evidence of an association was found for the MTCH2 and FTO loci, ie, lower and higher birth weight, respectively. These findings may provide new insights into the underlying mechanisms by which these loci confer an increased risk of obesity.
Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common ...complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified 10 novel risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with novel secondary signals at 4 of these). Notably, the new loci include candidate genes with roles in regulation of innate host defenses and T-cell function, underscoring the important contribution of (auto-)immune mechanisms to atopic dermatitis pathogenesis.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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