Integration of genetics into a systems model of electrocardiographic traits using humanCVD beadchip
Date
2012
Authors
Gaunt, T.
Shah, S.
Nelson, C.
Drenos, F.
Braund, P.
Adeniran, I.
Folkersen, L.
Lawlor, D.
Casas, J.
Amuzu, A.
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Advisors
Journal Title
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Type:
Journal article
Citation
Circulation: Cardiovascular Genetics, 2012; 5(6):630-638
Statement of Responsibility
Tom R. Gaunt, Sonia Shah, Christopher P. Nelson, Fotios Drenos, Peter S. Braund, Ismail Adeniran, Lasse Folkersen, Debbie A. Lawlor, Juan-Pablo Casas, Antoinette Amuzu, Mika Kivimaki, John Whittaker, Per Eriksson, Henggui Zhang, Jules C. Hancox, Maciej Tomaszewski, Paul R. Burton, Martin D. Tobin, Steve E. Humphries, Philippa J. Talmud, Peter W. Macfarlane, Aroon D. Hingorani, Nilesh J. Samani, Meena Kumari, Ian N.M. Day
Conference Name
Abstract
Electrocardiographic traits are important, substantially heritable determinants of risk of arrhythmias and sudden cardiac death.In this study, 3 population-based cohorts (n=10,526) genotyped with the Illumina HumanCVD Beadchip and 4 quantitative electrocardiographic traits (PR interval, QRS axis, QRS duration, and QTc interval) were evaluated for single-nucleotide polymorphism associations. Six gene regions contained single nucleotide polymorphisms associated with these traits at P<10(-6), including SCN5A (PR interval and QRS duration), CAV1-CAV2 locus (PR interval), CDKN1A (QRS duration), NOS1AP, KCNH2, and KCNQ1 (QTc interval). Expression quantitative trait loci analyses of top associated single-nucleotide polymorphisms were undertaken in human heart and aortic tissues. NOS1AP, SCN5A, IGFBP3, CYP2C9, and CAV1 showed evidence of differential allelic expression. We modeled the effects of ion channel activity on electrocardiographic parameters, estimating the change in gene expression that would account for our observed associations, thus relating epidemiological observations and expression quantitative trait loci data to a systems model of the ECG.These association results replicate and refine the mapping of previous genome-wide association study findings for electrocardiographic traits, while the expression analysis and modeling approaches offer supporting evidence for a functional role of some of these loci in cardiac excitation/conduction.
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Dissertation Note
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© 2012 American Heart Association, Inc.