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Updated: Sep 20, 2025

Investigating the Pathogenesis of MYH7 Mutation Gly823Glu in Familial Hypertrophic Cardiomyopathy using a Mouse Model
Published on: August 8, 2022
Common genetic modifiers influence cardiomyopathy susceptibility among the carriers of rare pathogenic variants
Samantha J Klasfeld1, Katherine A Knutson2, Melissa R Miller3
1Internal Medicine Research Unit, Pfizer Research and Development, Cambridge, MA 02139, USA; Rare Disease Research Unit, Pfizer Research and Development, Cambridge, MA 02139, USA.
Insights
Common genetic factors significantly increase cardiomyopathy risk in rare variant carriers. Polygenic risk scores highlight this interplay, refining understanding of hypertrophic and dilated cardiomyopathies.
Area of Science:
- Genetics
- Cardiology
- Bioinformatics
Background:
- Cardiomyopathy imposes a substantial healthcare burden.
- It is often viewed as a rare monogenic disorder, but common genetic factors also play a role.
- Understanding the interaction between rare and common genetic variants is complex.
Purpose of the Study:
- To investigate the genetic architecture of hypertrophic and dilated cardiomyopathies.
- To analyze the influence of common genetic modifiers on disease risk and variability in rare variant carriers.
- To assess the utility of polygenic risk scores in conjunction with predicted pathogenic variants.
Main Methods:
- Utilized large-scale genetic and phenotypic data from the UK Biobank.
- Identified known and predicted pathogenic variants using ClinVar and variant effect prediction tools.
- Calculated polygenic risk scores and assessed their association with disease risk and cardiac phenotypes.
Main Results:
- Polygenic risk scores were significantly associated with increased cardiomyopathy risk in rare pathogenic variant carriers.
- Carriers in the top 20% of polygenic risk showed substantially higher risk for hypertrophic (5.7x) and dilated (2.3x) cardiomyopathies.
- Including predicted pathogenic variants enhanced statistical power and strengthened associations.
Conclusions:
- Common genetic modifiers significantly influence cardiomyopathy risk among rare pathogenic variant carriers.
- Polygenic risk scores are valuable tools for dissecting the genetic complexity of cardiomyopathies.
- Integrating variant effect predictions improves the power to detect polygenic influences in rare disease research.
Abstract:
Cardiomyopathy presents a significant medical burden due to frequent hospitalizations and invasive interventions. While cardiomyopathy is considered a rare monogenic disorder caused by rare pathogenic variants in a few genes, emerging evidence suggests that common genetic modifiers influence disease penetrance and clinical variability. Quantifying the interplay between common genetic modifiers and rare pathogenic variants is challenging due to the rarity of subjects with cardiomyopathy and pathogenic variant carriers. In this study, we utilized large-scale genetic and phenotypic data from the UK Biobank to refine the genetic architecture of hypertrophic and dilated cardiomyopathies. Using ClinVar annotations and variant effect prediction tools, we first identified known and predicted pathogenic variants and evaluated their association with disease risk, age of diagnosis, and quantitative cardiac phenotypes that reflect disease progression. We next examined the impact of polygenic risk scores on disease in the combined sets of known and predicted pathogenic variant carriers. Indeed, the polygenic risk scores were significantly associated with increased disease risk, with rare pathogenic variant carriers in the top 20% of polygenic risk having 5.7 and 2.3 times higher risk than those in the bottom 20% for hypertrophic and dilated cardiomyopathies, respectively. We observed stronger associations in the carrier sets that included predicted pathogenic variant carriers, suggesting improved statistical power. In summary, our study adds to the evidence that common genetic modifiers influence the cardiomyopathy disease risk among rare pathogenic variant carriers and illustrates the benefits and limitations of incorporating variant effect predictions to examine the polygenic influence in rare disease variant carriers.
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