Genotype-Phenotype Discordance in Cardiomyopathies: Pathophysiology, Clinical Expression, and Therapeutic Considerations

Department

Cardiology

Document Type

Article

Publication Title

Health Science Reports

Abstract

BACKGROUND: Cardiomyopathies encompass a spectrum of myocardial disorders often attributed to underlying genetic mutations. However, genotype-phenotype discordance where the genetic profile does not align with the expected clinical presentation poses significant diagnostic, prognostic, and therapeutic challenges.

OBJECTIVE: To review the mechanisms underlying genotype-phenotype discordance in cardiomyopathies, explore its clinical implications, and propose future research directions to bridge the gap between molecular findings and patient outcomes.

METHODS: A narrative review was conducted using PubMed, Scopus, and Embase for articles published between 2000 and 2025. Search terms included "genotype-phenotype discordance", "cardiomyopathy", "penetrance", "expressivity", "modifier genes", and "epigenetics". Included studies focused on genetic and clinical variability in hypertrophic, dilated, arrhythmogenic, and restrictive cardiomyopathies. Priority was given to cohort studies, family-based analyses, and mechanistic investigations addressing epigenetic, polygenic, and environmental contributors to phenotypic heterogeneity.

RESULTS: Multiple factors contribute to genotype-phenotype discordance in cardiomyopathies, including incomplete penetrance, variable expressivity, epigenetic regulation, modifier genes, and environmental influences such as exercise and comorbidities. This discordance complicates risk stratification and personalized therapy. Clinically, individuals with pathogenic variants may remain asymptomatic, while others without identified mutations may exhibit overt disease. Emerging tools such as polygenic risk scores, multi-omics integration, and longitudinal phenotyping are improving phenotype prediction.

CONCLUSION: Genotype-phenotype discordance in cardiomyopathies underscores the complexity of translating genetic insights into clinical practice. A multidimensional approach combining genetic, molecular, and environmental data is essential to refine diagnosis, guide management, and inform genetic counseling. Future research should focus on deep phenotyping, systems biology, and longitudinal cohort studies to unravel the dynamic interplay between genes and environment.

First Page

e72398

DOI

10.1002/hsr2.72398

Volume

9

Publication Date

5-1-2026

PubMed ID

42163949

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