AUTHOR=Hodkinson Emily C. , Neijts Melanie , Sadrieh Arash , Imtiaz Mohammad S. , Baumert Mathias , Subbiah Rajesh N. , Hayward Christopher S. , Boomsma Dorret , Willemsen Gonneke , Vandenberg Jamie I. , Hill Adam P. , De Geus Eco TITLE=Heritability of ECG Biomarkers in the Netherlands Twin Registry Measured from Holter ECGs JOURNAL=Frontiers in Physiology VOLUME=7 YEAR=2016 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2016.00154 DOI=10.3389/fphys.2016.00154 ISSN=1664-042X ABSTRACT=

Introduction: The resting ECG is the most commonly used tool to assess cardiac electrophysiology. Previous studies have estimated heritability of ECG parameters based on these snapshots of the cardiac electrical activity. In this study we set out to determine whether analysis of heart rate specific data from Holter ECGs allows more complete assessment of the heritability of ECG parameters.

Methods and Results: Holter ECGs were recorded from 221 twin pairs and analyzed using a multi-parameter beat binning approach. Heart rate dependent estimates of heritability for QRS duration, QT interval, Tpeak–Tend and Theight were calculated using structural equation modeling. QRS duration is largely determined by environmental factors whereas repolarization is primarily genetically determined. Heritability estimates of both QT interval and Theight were significantly higher when measured from Holter compared to resting ECGs and the heritability estimate of each was heart rate dependent. Analysis of the genetic contribution to correlation between repolarization parameters demonstrated that covariance of individual ECG parameters at different heart rates overlap but at each specific heart rate there was relatively little overlap in the genetic determinants of the different repolarization parameters.

Conclusions: Here we present the first study of heritability of repolarization parameters measured from Holter ECGs. Our data demonstrate that higher heritability can be estimated from the Holter than the resting ECG and reveals rate dependence in the genetic—environmental determinants of the ECG that has not previously been tractable. Future applications include deeper dissection of the ECG of participants with inherited cardiac electrical disease.