Abstract 12681: GWAS Meta-Analysis in SCAD, a Women Predominant Ischemic Heart Disease, Reveals Common Variants and Genes Related to Artery Integrity and Tissue-Mediated Coagulation
Bibliographic record
Abstract
Introduction: Spontaneous coronary artery dissection (SCAD) is an understudied cause of acute myocardial infarction due to hematoma formation in coronary arteries primarily affecting women. It is not known to what extent SCAD is genetically distinct from other cardiovascular diseases, including atherosclerotic coronary artery disease (CAD). Methods and Results: Through a meta-analysis of 8 GWAS (1917 cases, 9292 controls of European ancestry), we identified 17 risk loci, including 12 new. Functional annotations pointed at enrichment in enhancer marks of arteries, specifically smooth muscle cells, and strong candidate genes, such as tissue factor gene ( F3 ) on Chr1 near rs1146473 (OR=1.32, P=5.8 х10 -9 ). F3 is novel for SCAD or any cardiovascular disease. The risk allele correlated with F3 lower expression in arteries, supporting a mechanism consistent with hematoma formation. Bayesian gene regulatory networks constructed from expression and genetics data indicated the extracellular matrix organization in arteries as the biological function where most prioritized genes clustered (e.g. COL4A1/A2, HTRA1, and TIMP3 ). Overall, we report substantial polygenicity for SCAD (LDSC: h 2 SNP = 0.71 ± 0.11) and shared genetics with several neurovascular diseases (e.g intracranial aneurysm). Intriguingly, for 6 loci, colocalization analyses showed that SCAD and CAD are likely to share the same causal variants but involve opposite risk alleles (e.g COL4A1/A2 ). In addition, a negative genetic correlation was found between SCAD and CAD (rg=-0.12; P=3.7х10 -3 ), including after conditioning on BP (mt-COJO: rg CAD/SBP =-0.19, P=4.6х10 -6 ). Mendelian randomization analyses indicated higher BP to associate with increased risk for SCAD (beta IVW-SBP =0.05, P=7.6х10 -6 , beta IVW-DBP =0.10, P=1.9х10 -6 ) and CAD (beta IVW-SBP =0.04, P=8.6х10 -49 ; DBP: beta IVW-DBP =0.06, P=1.6х10 -44 ) but not BMI, lipids, or type 2 diabetes, which we confirmed as genetic risk factors for CAD Conclusions: Our results set the stage for future investigation of novel biological pathways relevant to both SCAD and CAD and potential therapeutic and preventive strategies specifically targeting this ischemic disease predominantly affecting women.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".