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Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

ABSTRACT: BACKGROUND:ECG QRS duration, a measure of cardiac intraventricular conduction, varies ?2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias. METHODS AND RESULTS:We performed a genome-wide association study to identify genomic markers of QRS duration in 5272 individuals without cardiac disease selected from electronic medical record algorithms at 5 sites in the Electronic Medical Records and Genomics (eMERGE) network. The most significant loci were evaluated within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium QRS genome-wide association study meta-analysis. Twenty-three single-nucleotide polymorphisms in 5 loci, previously described by CHARGE, were replicated in the eMERGE samples; 18 single-nucleotide polymorphisms were in the chromosome 3 SCN5A and SCN10A loci, where the most significant single-nucleotide polymorphisms were rs1805126 in SCN5A with P=1.2×10(-8) (eMERGE) and P=2.5×10(-20) (CHARGE) and rs6795970 in SCN10A with P=6×10(-6) (eMERGE) and P=5×10(-27) (CHARGE). The other loci were in NFIA, near CDKN1A, and near C6orf204. We then performed phenome-wide association studies on variants in these 5 loci in 13859 European Americans to search for diagnoses associated with these markers. Phenome-wide association study identified atrial fibrillation and cardiac arrhythmias as the most common associated diagnoses with SCN10A and SCN5A variants. SCN10A variants were also associated with subsequent development of atrial fibrillation and arrhythmia in the original 5272 "heart-healthy" study population. CONCLUSIONS:We conclude that DNA biobanks coupled to electronic medical records not only provide a platform for genome-wide association study but also may allow broad interrogation of the longitudinal incidence of disease associated with genetic variants. The phenome-wide association study approach implicated sodium channel variants modulating QRS duration in subjects without cardiac disease as predictors of subsequent arrhythmias.

SUBMITTER: Ritchie MD

PROVIDER: S-EPMC3713791 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

Ritchie Marylyn D MD Denny Joshua C JC Zuvich Rebecca L RL Crawford Dana C DC Schildcrout Jonathan S JS Bastarache Lisa L Ramirez Andrea H AH Mosley Jonathan D JD Pulley Jill M JM Basford Melissa A MA Bradford Yuki Y Rasmussen Luke V LV Pathak Jyotishman J Chute Christopher G CG Kullo Iftikhar J IJ McCarty Catherine A CA Chisholm Rex L RL Kho Abel N AN Carlson Christopher S CS Larson Eric B EB Jarvik Gail P GP Sotoodehnia Nona N Manolio Teri A TA Li Rongling R Masys Daniel R DR Haines Jonathan L JL Roden Dan M DM

Circulation 20130305 13

<h4>Background</h4>ECG QRS duration, a measure of cardiac intraventricular conduction, varies ≈2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias.<h4>Methods and results</h4>We performed a genome-wide association study to identify genomic markers of QRS duration in 5272 individuals without cardiac disease selected from electronic medical record algorithms at 5 sites in the Electronic Medical Records and Genomics (eMERGE) network. The most significan ...[more]

PMID: 23463857

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Project description:BackgroundThe microvasculature, the smallest blood vessels in the body, has key roles in maintenance of organ health and tumorigenesis. The retinal fundus is a window for human in vivo noninvasive assessment of the microvasculature. Large-scale complementary machine learning-based assessment of the retinal vasculature with phenome-wide and genome-wide analyses may yield new insights into human health and disease.MethodsWe used 97 895 retinal fundus images from 54 813 UK Biobank participants. Using convolutional neural networks to segment the retinal microvasculature, we calculated vascular density and fractal dimension as a measure of vascular branching complexity. We associated these indices with 1866 incident International Classification of Diseases-based conditions (median 10-year follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity.ResultsLow retinal vascular fractal dimension and density were significantly associated with higher risks for incident mortality, hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions, as well as corresponding quantitative traits. Genome-wide association of vascular fractal dimension and density identified 7 and 13 novel loci, respectively, that were enriched for pathways linked to angiogenesis (eg, vascular endothelial growth factor, platelet-derived growth factor receptor, angiopoietin, and WNT signaling pathways) and inflammation (eg, interleukin, cytokine signaling).ConclusionsOur results indicate that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease and provide insights into genes and biological pathways influencing microvascular indices. Moreover, such a framework highlights how deep learning of images can quantify an interpretable phenotype for integration with electronic health record, biomarker, and genetic data to inform risk prediction and risk modification.

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Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

Publications

Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

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