Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy
Bibliographic record
Abstract
Abstract Background Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Prior genome-wide association studies (GWAS) identified few genomic loci and disease genes due to limited sample size. Purpose To discover novel genetic loci, genes and mechanisms implicated in HCM using a large scale GWAS and multi-trait analysis of GWAS (MTAG). Methods and results We performed the largest HCM GWAS meta-analysis and MTAG to date including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We estimated the heritability of HCM attributable to common genetic variation (h2SNP) to be 0.25±0.02 using genome-based restricted maximum likelihood (GREML), with higher h2SNP in non-sarcomeric (0.29±0.02) compared to sarcomeric HCM (0.16±0.04). We identified a total of 70 loci (50 novel) associated with HCM (Figure 1), and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin. We performed rare variant burden analysis including 1,845 clinically-diagnosed unrelated HCM cases and 37,481 controls and demonstrated a 10.5-fold (95% CI: 4.1-26.8; P=0.0000002) excess burden of SVIL loss of function (LoF) variants in HCM cases. Two-sample mendelian randomization analyses using LV contractility as exposure and obstructive (oHCM) and non-obstructive HCM (nHCM) as outcomes support a causal role of increased LV contractility in both oHCM and nHCM (Figure 2), suggesting common disease mechanisms and anticipating shared response to therapy. Conclusion We identify 50 novel genomic loci associated with HCM. Our data suggest that LoF variants in SVIL are a cause of HCM, and that increased contractility mediate both nHCM and oHCM. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.Figure 1Figure 2
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".