Channelpedia

PubMed 23139254


Referenced in Channelpedia wiki pages of: none

Automatically associated channels: KCNQ1 , Kv11.1 , Kv7.1 , Nav1.5



Title: Integration of Genetics into a Systems Model of Electrocardiographic Traits Using HumanCVD BeadChip.

Authors: 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

Journal, date & volume: Circ Cardiovasc Genet, 2012 Dec 1 , 5, 630-8

PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/23139254


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.