» Articles » PMID: 37652022

The Penetrance of Rare Variants in Cardiomyopathy-associated Genes: A Cross-sectional Approach to Estimating 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 individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 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 cardiomyopathy (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 (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) 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 reports 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 individuals with highly penetrant variants may benefit from SFs.

Citing Articles

Evaluation of Women with Peripartum or Dilated Cardiomyopathy and Their First-Degree Relatives: The DCM Precision Medicine Study.

Kransdorf E, Jain R, Mead J, Haas G, Hofmeyer M, Ewald G medRxiv. 2025; .

PMID: 40034776 PMC: 11875307. DOI: 10.1101/2025.02.18.25322501.


Whole exome sequence reveals genetic profiles of primary cardiomyopathy and genotype-phenotype association in Chinese population.

Liu R, Yang Y, Gong K, Wang L, Yao Y, Xie L BMC Genomics. 2025; 26(1):150.

PMID: 39962380 PMC: 11834636. DOI: 10.1186/s12864-025-11323-4.


Systematic Review, Meta-Analysis, and Population Study to Determine the Biologic Sex Ratio in Dilated Cardiomyopathy.

Bergan N, Prachee I, Curran L, McGurk K, Lu C, de Marvao A Circulation. 2025; 151(7):442-459.

PMID: 39895490 PMC: 11827689. DOI: 10.1161/CIRCULATIONAHA.124.070872.


Three Novel Pathogenic Variants in Unrelated Vietnamese Patients with Cardiomyopathy.

Tran D, Lien N, Van Tung N, Huu N, Nguyen P, Tien D Diagnostics (Basel). 2024; 14(23).

PMID: 39682617 PMC: 11640685. DOI: 10.3390/diagnostics14232709.


Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection.

Kingsmore S, Wright M, Smith L, Liang Y, Mowrey W, Protopsaltis L Am J Hum Genet. 2024; 111(12):2618-2642.

PMID: 39642867 PMC: 11639087. DOI: 10.1016/j.ajhg.2024.10.021.


References
1.
Lindeboom R, Supek F, Lehner B . The rules and impact of nonsense-mediated mRNA decay in human cancers. Nat Genet. 2016; 48(10):1112-8. PMC: 5045715. DOI: 10.1038/ng.3664. View

2.
Lorenzini M, Norrish G, Field E, Ochoa J, Cicerchia M, Akhtar M . Penetrance of Hypertrophic Cardiomyopathy in Sarcomere Protein Mutation Carriers. J Am Coll Cardiol. 2020; 76(5):550-559. PMC: 7397507. DOI: 10.1016/j.jacc.2020.06.011. View

3.
McLaren W, Gil L, Hunt S, Riat H, Ritchie G, Thormann A . The Ensembl Variant Effect Predictor. Genome Biol. 2016; 17(1):122. PMC: 4893825. DOI: 10.1186/s13059-016-0974-4. View

4.
Ioannidis N, Rothstein J, Pejaver V, Middha S, McDonnell S, Baheti S . REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants. Am J Hum Genet. 2016; 99(4):877-885. PMC: 5065685. DOI: 10.1016/j.ajhg.2016.08.016. View

5.
Whiffin N, Walsh R, Govind R, Edwards M, Ahmad M, Zhang X . CardioClassifier: disease- and gene-specific computational decision support for clinical genome interpretation. Genet Med. 2018; 20(10):1246-1254. PMC: 6558251. DOI: 10.1038/gim.2017.258. View