The penetrance of rare variants in cardiomyopathy-associated genes: a cross-sectional approach to estimate penetrance for secondary findings

Abstract

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of patients referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 cases, 1,340 variants) and dilated cardiomyopathy (DCM; 2,564 cases, 665 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant CM. Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare, and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (51% HCM and 17% DCM cases). 49 variants were observed at least ten times (14% of cases) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry, and simulate the impact of including future cohorts. This dataset is the first to report penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some carriers of highly penetrant variants may benefit from SFs.

Competing Interest Statement

J.S.W. has consulted for MyoKardia, Inc., Foresite Labs, and Pfizer. A.H. now works for AstraZeneca, UK. D.P.O. has consulted for Bayer. L.B. has consulted for Roche. D.G.M. is a paid advisor to GlaxoSmithKline, Insitro, Variant Bio and Overtone Therapeutics, and has received research support from AbbVie, Astellas, Biogen, BioMarin, Eisai, Merck, Pfizer, and Sanofi-Genzyme; none of these activities are directly related to the work presented here.

Funding Statement

This work was supported by the Wellcome Trust [107469/Z/15/Z; 200990/A/16/Z], Medical Research Council (UK) [MC_UP_1605/13], British Heart Foundation [RG/19/6/34387, RE/18/4/34215, FS/IPBSRF/22/27059], and the NIHR Imperial College Biomedical Research Centre. The views expressed in this work are those of the authors and not necessarily those of the funders.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All research participants provided written informed consent, and the studies were reviewed and approved by the relevant research ethics committee (Aswan Heart Centre: FWA00019142, Research Ethics Committee code 20130405MYFAHC_CMR_20130330; NIHR Royal Brompton Biobank: South Central, Hampshire B Research Ethics Committee, 09/H0504/104+5, 19/SC/0257; National Heart Centre Singapore: Singhealth Centralised Institutional Review Board 2020/2353 and Singhealth Biobank Research Scientific Advisory Executive Committee SBRSA 2019/001v1; UK Biobank: National Research Ethics Service 11/NW/0382, 21/NW/0157, under terms of access approval number 47602). In addition, diagnostic laboratories (Oxford Molecular Genetics Laboratory, Belfast Regional Genetics Laboratory, the Partners Laboratory of Molecular Medicine, and GeneDx) provided aggregated (and therefore fully anonymous) cohort level summaries of variant data collected for clinical purposes during routine healthcare. Secondary use of this data did not require research consent from individuals, and approval for public release of the data followed local governance procedures. Data are publicly available, through DECIPHER (https://www.deciphergenomics.org/). Analyses of these data do not require Research Ethics Committee approval.

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