Genome-wide association meta-analysis in 652,134 participants identifies 9 novel susceptibility loci for aortic stenosis
Bibliographic record
Abstract
Abstract Background Aortic stenosis (AS) is the most common form of incident valvular heart disease. While valve replacement is effective, the absence of an approved medical therapy provides no alternatives to patients with contraindications or mild disease. An improved understanding of the genetics of AS could identify targets for pharmacological intervention. Methods An inverse variance-weighted, fixed effects meta-analysis of the association of 11,591,806 variants with AS was undertaken using data from 10 European cohorts totalling 652,134 participants (13,758 cases of AS). We queried publicly available datasets to characterize the functional consequences of genome-wide significant variants, conducted a phenome-wide association study to assess their association with other outcomes, and constructed polygenic risk scores to examine their association with AS. We also performed gene- and gene-set enrichment analyses, estimated genetic correlation with cardiovascular traits, and assessed whether five lipid or immunological biomarkers were causally associated with AS using Mendelian randomization. Results Eighteen independent variants at 16 loci attained genome-wide significance in the meta-analysis, including variants at all seven previously reported loci. Many of the significant variants were intronic or intergenic, and the phenome-wide association study revealed extensive pleiotropy with apolipoprotein B, C-reactive protein, and other cardiovascular and immunological traits. A weighted polygenic risk score composed of the 18 variants was strongly associated with AS (adjusted OR per SD, 1.38; 95% CI, 1.33 to 1.44; p=4.6×10–57), and improved the discriminatory ability for AS when added to a model that contained clinical risk factors (difference in the area under the curve p=2.0×10–11). Gene-based approaches indicated higher IL6R expression in the blood among AS cases compared to controls (p=3.1×10–6), and the association of LDLR with AS (p=2.3×10–10). Gene set analyses revealed that genes bound by the transcription factor TCF7 or micro-RNAs miR-21, miR-219, miR-491, and miR-19 were differentially expressed in the liver depending on AS status (p≤5.7×10–4), suggesting disease development may be mediated by tissue-specific transcriptional and post-transcriptional regulation. Mendelian randomization supported a causal association of five lipid and immunological biomarkers with AS, including low-density lipoprotein cholesterol (OR per mmol/L, 1.61; 95% CI, 1.48 to 1.75; p=1.3×10–30). Conclusions Evidence from large-scale genetic analyses indicate that lipid metabolism, inflammation, and calcification are key contributors to AS. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Canadian Institutes of Health Research, National Institutes of Health
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.031 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".