Integration of genetics into a systems model of electrocardiographic traits using HumanCVD BeadChip

TR Gaunt, S Shah, CP Nelson, F Drenos… - Circulation …, 2012 - Am Heart Assoc
TR Gaunt, S Shah, CP Nelson, F Drenos, PS Braund, I Adeniran, L Folkersen, DA Lawlor…
Circulation: Cardiovascular Genetics, 2012Am Heart Assoc
Background—Electrocardiographic traits are important, substantially heritable determinants
of risk of arrhythmias and sudden cardiac death. Methods and Results—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 …
Background
Electrocardiographic traits are important, substantially heritable determinants of risk of arrhythmias and sudden cardiac death.
Methods and Results
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.
Conclusions
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.
Am Heart Assoc