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Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function.

ABSTRACT: BACKGROUND:Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS:A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS:The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION:The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING:For detailed information per study, see Acknowledgments.

SUBMITTER: Wild PS

PROVIDER: S-EPMC5409098 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function.

Wild Philipp S PS Felix Janine F JF Schillert Arne A Teumer Alexander A Chen Ming-Huei MH Leening Maarten J G MJG Völker Uwe U Großmann Vera V Brody Jennifer A JA Irvin Marguerite R MR Shah Sanjiv J SJ Pramana Setia S Lieb Wolfgang W Schmidt Reinhold R Stanton Alice V AV Malzahn Dörthe D Smith Albert Vernon AV Sundström Johan J Minelli Cosetta C Ruggiero Daniela D Lyytikäinen Leo-Pekka LP Tiller Daniel D Smith J Gustav JG Monnereau Claire C Di Tullio Marco R MR Musani Solomon K SK Morrison Alanna C AC Pers Tune H TH Morley Michael M Kleber Marcus E ME Aragam Jayashri J Benjamin Emelia J EJ Bis Joshua C JC Bisping Egbert E Broeckel Ulrich U Cheng Susan S Deckers Jaap W JW Del Greco M Fabiola F Edelmann Frank F Fornage Myriam M Franke Lude L Friedrich Nele N Harris Tamara B TB Hofer Edith E Hofman Albert A Huang Jie J Hughes Alun D AD Kähönen Mika M Investigators Knhi K Kruppa Jochen J Lackner Karl J KJ Lannfelt Lars L Laskowski Rafael R Launer Lenore J LJ Leosdottir Margrét M Lin Honghuang H Lindgren Cecilia M CM Loley Christina C MacRae Calum A CA Mascalzoni Deborah D Mayet Jamil J Medenwald Daniel D Morris Andrew P AP Müller Christian C Müller-Nurasyid Martina M Nappo Stefania S Nilsson Peter M PM Nuding Sebastian S Nutile Teresa T Peters Annette A Pfeufer Arne A Pietzner Diana D Pramstaller Peter P PP Raitakari Olli T OT Rice Kenneth M KM Rivadeneira Fernando F Rotter Jerome I JI Ruohonen Saku T ST Sacco Ralph L RL Samdarshi Tandaw E TE Schmidt Helena H Sharp Andrew S P ASP Shields Denis C DC Sorice Rossella R Sotoodehnia Nona N Stricker Bruno H BH Surendran Praveen P Thom Simon S Töglhofer Anna M AM Uitterlinden André G AG Wachter Rolf R Völzke Henry H Ziegler Andreas A Münzel Thomas T März Winfried W Cappola Thomas P TP Hirschhorn Joel N JN Mitchell Gary F GF Smith Nicholas L NL Fox Ervin R ER Dueker Nicole D ND Jaddoe Vincent W V VWV Melander Olle O Russ Martin M Lehtimäki Terho T Ciullo Marina M Hicks Andrew A AA Lind Lars L Gudnason Vilmundur V Pieske Burkert B Barron Anthony J AJ Zweiker Robert R Schunkert Heribert H Ingelsson Erik E Liu Kiang K Arnett Donna K DK Psaty Bruce M BM Blankenberg Stefan S Larson Martin G MG Felix Stephan B SB Franco Oscar H OH Zeller Tanja T Vasan Ramachandran S RS Dörr Marcus M

The Journal of clinical investigation 20170410 5

<h4>Background</h4>Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function.<h4>Methods</h4>A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and s ...[more]

PMID: 28394258

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Project description:CONTEXT:Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. OBJECTIVE:To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. DESIGN, SETTING, AND PARTICIPANTS:Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. MAIN OUTCOME MEASURES:Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. RESULTS:In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). CONCLUSIONS:We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

Project description:BackgroundLung function is a heritable complex phenotype with obesity being one of its important risk factors. However, knowledge of their shared genetic basis is limited. Most genome-wide association studies (GWASs) for lung function have been based on European populations, limiting the generalisability across populations. Large-scale lung function GWASs in other populations are lacking.MethodsWe included 100 285 subjects from the China Kadoorie Biobank (CKB). To identify novel loci for lung function, single-trait GWAS analyses were performed on forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC in the CKB. We then performed genome-wide cross-trait analysis between lung function and obesity traits (body mass index (BMI), BMI-adjusted waist-to-hip ratio and BMI-adjusted waist circumference) to investigate the shared genetic effects in the CKB. Finally, polygenic risk scores (PRSs) of lung function were developed in the CKB and their interaction with BMI's association on lung function were examined. We also conducted cross-trait analysis in parallel with the CKB using up to 457 756 subjects from the UK Biobank (UKB) for replication and investigation of ancestry-specific effects.ResultsWe identified nine genome-wide significant novel loci for FEV1, six for FVC and three for FEV1/FVC in the CKB. FEV1 and FVC showed significant negative genetic correlation with obesity traits in both the CKB and UKB. Genetic loci shared between lung function and obesity traits highlighted important biological pathways, including cell proliferation, embryo, skeletal and tissue development, and regulation of gene expression. Mendelian randomisation analysis suggested significant negative causal effects of BMI on FEV1 and on FVC in both the CKB and UKB. Lung function PRSs significantly modified the effect of change in BMI on change in lung function during an average follow-up of 8 years.ConclusionThis large-scale GWAS of lung function identified novel loci and shared genetic aetiology between lung function and obesity. Change in BMI might affect change in lung function differently according to a subject's polygenic background. These findings may open new avenues for the development of molecular-targeted therapies for obesity and lung function improvement.

Project description:BackgroundOvine footrot caused by Dichelobacter nodosus (D. nodosus) is a contagious disease with serious economic and welfare impacts in sheep production systems worldwide. A better understanding of the host genetic architecture regarding footrot resistance/susceptibility is crucial to develop disease control strategies that efficiently reduce infection and its severity. A genome-wide association study was performed using a customized SNP array (47,779 SNPs in total) to identify genetic variants associated to footrot resistance/susceptibility in two Portuguese native breeds, i.e. Merino Branco and Merino Preto, and a population of crossbred animals. A cohort of 1375 sheep sampled across 17 flocks, located in the Alentejo region (southern Portugal), was included in the analyses.ResultsPhenotypes were scored from 0 (healthy) to 5 (severe footrot) based on visual inspection of feet lesions, following the Modified Egerton System. Using a linear mixed model approach, three SNPs located on chromosome 24 reached genome-wide significance after a Bonferroni correction (p < 0.05). Additionally, six genome-wide suggestive SNPs were identified each on chromosomes 2, 4, 7, 8, 9 and 15. The annotation and KEGG pathway analyses showed that these SNPs are located within regions of candidate genes such as the nonsense mediated mRNA decay associated PI3K related kinase (SMG1) (chromosome 24) and the RALY RNA binding protein like (RALYL) (chromosome 9), both involved in immunity, and the heparan sulfate proteoglycan 2 (HSPG2) (chromosome 2) and the Thrombospodin 1 (THBS1) (chromosome 7) implicated in tissue repair and wound healing processes.ConclusionThis is the first attempt to identify molecular markers associated with footrot in Portuguese Merino sheep. These findings provide relevant information on a likely genetic association underlying footrot resistance/susceptibility and the potential candidate genes affecting this trait. Genetic selection strategies assisted on the information obtained from this study could enhance Merino sheep-breeding programs, in combination with farm management strategies, for a more effective and sustainable long-term solution for footrot control.

Project description:ObjectiveSulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.Research design and methodsAs an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.ResultsAfter establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.ConclusionsWe have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

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Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function.

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Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function.

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