Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings
Why the study?
Although pathogenic variants cause about a third of hypertrophic cardiomyopathy cases and common genetic variation contributes to risk, the performance of polygenic scores across populations and clinical settings needed evaluation.
Does a polygenic score for hypertrophic cardiomyopathy predict disease risk and adverse outcomes across different clinical settings?
Population
Individuals in the UK Biobank, 100,000 Genomes Project, and clinical cohorts
Comparison
Higher vs lower polygenic scores derived from GWAS and genetically correlated traits
Design
Cohort study
Authors
Discussion
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Member takes
Implication
May support PGS stratification of HCM penetrance in carriers; leaves open prospective validation before clinical adoption.
Structured PICO
Does a polygenic score for hypertrophic cardiomyopathy predict disease risk and adverse outcomes across different clinical settings?
P
Population
General population (UK Biobank, 100,000 Genomes Project) and clinical cohorts, including pathogenic variant carriers, relatives of HCM probands, and established HCM cases
I
Intervention
Polygenic scores (PGS) derived from HCM GWAS and genetically correlated traits
C
Comparator
Lower polygenic scores (e.g., lowest vs highest quintiles)
O
Outcome
Risk of developing hypertrophic cardiomyopathy (HCM), adverse outcomes, and deathhard clinical
Polygenic scores for hypertrophic cardiomyopathy can effectively stratify the risk of developing the disease and experiencing adverse outcomes across the general population, variant carriers, and established cases.
Cite This Study
Zheng et al. (2025) studied this question.