Abstract 4357141: Polygenic score analyses in a large multinational HCM clinical cohort identifies effects on disease penetrance and severity
Bibliographic record
Abstract
Background: Disease expressivity in hypertrophic cardiomyopathy (HCM) varies widely, ranging from unaffected genetically predisposed individuals to life-threatening complications. Polygenic scores (PGS) were shown to predict disease penetrance of HCM-causing rare genetic variants (HCMrv) and HCM-related outcomes in large biobanks. However, the utility of PGS in clinical cohorts remains unclear. Research Questions: Can PGS predict disease penetrance in carriers of HCMrv in the clinical setting? Is PGS associated with disease severity and complications in individuals with HCM? Methods: We studied a well-characterized clinical HCM cohort from Canada, Italy, the Netherlands and Spain, comprising 6,111 individuals affected by HCM and/or carrying a HCMrv. We used SBayesRC to derive a novel PGS for HCM from the largest published genome-wide association study. Standardized ancestry-adjusted PGS were calculated for all individuals and tested for association with HCM penetrance, maximal left ventricular wall thickness (MLVWT) and major adverse clinical events (MACE) using logistic, linear and Cox regression models, respectively, with adjustment for sex, rare variant status, site, and other covariates as relevant. MACE were defined as major ventricular arrhythmic or heart failure event, stroke, septal reduction therapy or all-cause mortality. Results: PGS was tested for association with HCM in the subset of 1,667 relatives carrying a HCMrv (age at last follow-up 47 ± 19, 49% female), of which 57% meet diagnostic criteria for HCM. PGS was associated with a diagnosis of HCM (Odds ratio 1.6 per standard deviation [SD] increase in PGS; 95% CI: 1.4-1.8). Male sex and hypertension also independently increased penetrance by 3-fold and 2-fold, respectively. HCM-penetrance increased with increasing PGS, in the entire set as well as in carriers of MYH7 pathogenic variants, MYBPC3 truncating variants, or intermediate effect variants (Figure). In 4,949 affected individuals (age at diagnosis 48 ± 17, 33% female, 49% carrying HCMrv), PGS was associated with disease severity. Each SD increase in PGS was associated with a 0.5 mm increase in MLVWT (95% CI: 0.3-0.6), and a 12% increase in lifetime risk of MACE (Hazard ratio 1.12, 95% CI: 1.06-1.18). Conclusions: PGS assessment may enhance risk stratification and personalize monitoring strategies—guiding the timing, frequency, and scope of clinical evaluations in both genetically predisposed individuals and patients with manifest HCM.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".