Big Data

For Better Hearts

BigData@Heart

New paper

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

 

Published: 9 January 2020, Nature Communications

 

Authors: Sonia Shah, Albert Henry, […], R. Thomas Lumbers

 

Abstract

 

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

 

Read the full paper here: https://doi.org/10.1038/s41467-019-13690-5

 

Published on: 04/29/2020