The Walsh CardioGenomics Lab - Evaluation of polygenic scores for

Journal article

Sean L. Zheng, S. Jurgens, K. McGurk, Xiao Xu, C. Grace, P. Theotokis, R. Buchan, C. Francis, A. de Marvao, Lara Curran, Wenjia Bai, C. Pua, H. Tang, P. Jordà, M. V. van Slegtenhorst, J. Verhagen, Andrew R. Harper, Elizabeth Ormondroyd, Calvin W L Chin, Antonio Marjon A. James S. de Marvao van Slegtenhorst Ware, A. de Marvao, James S. Ware, A. Pantazis, J. Baksi, B. Halliday, P. Matthews, Y. Pinto, Roddy Walsh, A. Amin, A. Wilde, Stuart A. Cook, Sanjay K. Prasad, Paul J. R. Barton, D. O’Regan, R. Lumbers, A. Goel, R. Tadros, M. Michels, Hugh Watkins, C. Bezzina, James S. Ware
Nature Genetics, 2025

Semantic Scholar DOI PubMedCentral PubMed

Cite

APA Click to copy
Zheng, S. L., Jurgens, S., McGurk, K., Xu, X., Grace, C., Theotokis, P., … Ware, J. S. (2025). Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings. Nature Genetics.

Chicago/Turabian Click to copy
Zheng, Sean L., S. Jurgens, K. McGurk, Xiao Xu, C. Grace, P. Theotokis, R. Buchan, et al. “Evaluation of Polygenic Scores for Hypertrophic Cardiomyopathy in the General Population and across Clinical Settings.” Nature Genetics (2025).

MLA Click to copy
Zheng, Sean L., et al. “Evaluation of Polygenic Scores for Hypertrophic Cardiomyopathy in the General Population and across Clinical Settings.” Nature Genetics, 2025.

BibTeX Click to copy

@article{sean2025a,
  title = {Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings},
  year = {2025},
  journal = {Nature Genetics},
  author = {Zheng, Sean L. and Jurgens, S. and McGurk, K. and Xu, Xiao and Grace, C. and Theotokis, P. and Buchan, R. and Francis, C. and de Marvao, A. and Curran, Lara and Bai, Wenjia and Pua, C. and Tang, H. and Jordà, P. and van Slegtenhorst, M. V. and Verhagen, J. and Harper, Andrew R. and Ormondroyd, Elizabeth and Chin, Calvin W L and de Marvao van Slegtenhorst Ware, Antonio Marjon A. James S. and de Marvao, A. and Ware, James S. and Pantazis, A. and Baksi, J. and Halliday, B. and Matthews, P. and Pinto, Y. and Walsh, Roddy and Amin, A. and Wilde, A. and Cook, Stuart A. and Prasad, Sanjay K. and Barton, Paul J. R. and O’Regan, D. and Lumbers, R. and Goel, A. and Tadros, R. and Michels, M. and Watkins, Hugh and Bezzina, C. and Ware, James S.}
}

Abstract

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality, with pathogenic variants found in about a third of cases. Large-scale genome-wide association studies (GWAS) demonstrate that common genetic variation contributes to HCM risk. Here we derive polygenic scores (PGS) from HCM GWAS and genetically correlated traits and test their performance in the UK Biobank, 100,000 Genomes Project, and clinical cohorts. We show that higher PGS significantly increases the risk of HCM in the general population, particularly among pathogenic variant carriers, where HCM penetrance differs 10-fold between those in the highest and lowest PGS quintiles. Among relatives of HCM probands, PGS stratifies risks of developing HCM and adverse outcomes. Finally, among HCM cases, PGS strongly predicts the risk of adverse outcomes and death. These findings support the broad utility of PGS across clinical settings, enabling tailored screening and surveillance and stratification of risk of adverse outcomes. Polygenic scores derived from genome-wide association analyses of hypertrophic cardiomyopathy and genetically correlated left ventricular traits effectively stratify risk of disease and adverse outcomes in the general population and across clinical cohorts.