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Record W4407675121 · doi:10.1038/s41588-025-02094-5

Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings

2025· article· en· W4407675121 on OpenAlexaff
Sean L. Zheng, Sean J. Jurgens, Kathryn A. McGurk, Xiao Yun Xu, Chris Grace, Pantazis Theotokis, Rachel Buchan, Catherine Francis, Antonio de Marvao, Lara Curran, Wenjia Bai, Chee Jian Pua, Hak Chiaw Tang, Paloma Jordà, Marjon A. van Slegtenhorst, Judith M.A. Verhagen, Andrew R. Harper, Elizabeth Ormondroyd, Calvin Chin, James S. Ware, Antonios Pantazis, John Baksi, Brian P. Halliday, Paul M. Matthews, Yigal M. Pinto, Roddy Walsh, Ahmad S. Amin, Arthur A.M. Wilde, Stuart A. Cook, Sanjay Prasad, Paul J.R. Barton, Declan P. O’Regan, R Thomas Lumbers, Anuj Goel, Rafik Tadros, Michelle Michels, Hugh Watkins, Connie R. Bezzina

Bibliographic record

VenueNature Genetics · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersMedical Research CouncilAmsterdam Cardiovascular Sciences, Amsterdam University Medical CentersInstitute of Psychiatry, Psychology and Neuroscience, King’s College LondonFondation LeducqEuropean CommissionRosetrees TrustDepartment of Health and Social CareFetal Medicine FoundationNational Institute for Health and Care ResearchCancer Research UKGujarat Council on Science and TechnologyHartstichtingMaudsley CharityBritish Heart FoundationWellcome Trust
KeywordsHypertrophic cardiomyopathyGenome-wide association studyPenetranceProbandBiologyBiobankPopulationPopulation stratificationPolygenic risk scoreGenetic testingGeneticsInternal medicineMedicineGenotypeEnvironmental healthSingle-nucleotide polymorphismMutationPhenotypeGene

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.405
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2025
Admission routes1
Has abstractyes

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