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Circulation. 2018 Nov 11. doi: 10.1161/CIRCULATIONAHA.118.035774. [Epub ahead of print]

Phenotypic Refinement of Heart Failure in a National Biobank Facilitates Genetic Discovery.

Author information

1
Cardiology Division, Massachusetts General Hospital, United States.
2
Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, United States.
3
Division of Cardiovascular Medicine, Vanderbilt University Medical Center, United States.
4
Department of Medicine, Massachusetts General Hospital, United States.
5
Medical and population genetics, Broad Institute of MIT and Harvard, United States.
6
Department of Medicine, Vanderbilt University Medical Center, United States.
7
Medical and Population Genetics, Broad Institute of Harvard and MIT, United States.
8
Cardiovascular Research Center, Massachusetts General Hospital, United States.
9
Cardiology, Massachusetts General Hospital, United States.
10
Lund University and Skane University Hospital, Sweden.
11
Harvard Medical School & Massachusetts General Hospital, Massachusetts General Hospital, United States.
12
Medicine, Pharmacology, and Biomedcial Informatics, Vanderbilt Univ. School of Medicine, United States.
13
Medicine, University of Iowa, United States.
14
Cardiovascular Medicine, Vanderbilt University, United States.
15
Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, United States.
16
Center for Genomic Medicine, Massachusetts General Hospital, United States.

Abstract

BACKGROUND:

Heart failure (HF) is a morbid and heritable disorder for which the biological mechanisms are incompletely understood. We therefore examined genetic associations with HF in a large national biobank, and assessed whether refined phenotypic classification would facilitate genetic discovery.

METHODS:

We defined all-cause HF among 488010 participants from the UK Biobank and performed a genome-wide association analysis. We refined the HF phenotype by classifying individuals with left ventricular dysfunction and without coronary artery disease as having nonischemic cardiomyopathy (NICM), and repeated a genetic association analysis. We then pursued replication of lead HF and NICM variants in independent cohorts, and performed adjusted association analyses to assess whether identified genetic associations were mediated through clinical HF risk factors. In addition, we tested rare, loss-of-function mutations in 24 known dilated cardiomyopathy genes for association with HF and NICM. Finally, we examined associations between lead variants and left ventricular structure and function among individuals without HF using cardiac magnetic resonance imaging (n=4158) and echocardiographic data (n=30201).

RESULTS:

We identified 7382 participants with all-cause HF in the UK Biobank. Genome-wide association analysis of all-cause HF identified several suggestive loci ( P<1×10-6), the majority linked to upstream HF risk factors, ie, coronary artery disease ( CDKN2B-AS1 and MAP3K7CL) and atrial fibrillation ( PITX2). Refining the HF phenotype yielded a subset of 2038 NICM cases. In contrast to all-cause HF, genetic analysis of NICM revealed suggestive loci that have been implicated in dilated cardiomyopathy ( BAG3, CLCNKA-ZBTB17). Dilated cardiomyopathy signals arising from our NICM analysis replicated in independent cohorts, persisted after HF risk factor adjustment, and were associated with indices of left ventricular dysfunction in individuals without clinical HF. In addition, analyses of loss-of-function variants implicated BAG3 as a disease susceptibility gene for NICM (loss-offunction variant carrier frequency=0.01%; odds ratio,12.03; P=3.62×10-5).

CONCLUSIONS:

We found several distinct genetic mechanisms of all-cause HF in a national biobank that reflect well-known HF risk factors. Phenotypic refinement to a NICM subtype appeared to facilitate the discovery of genetic signals that act independently of clinical HF risk factors and that are associated with subclinical left ventricular dysfunction.

KEYWORDS:

nonischemic cardiomyopathy

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