Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease
Bibliographic record
Abstract
OBJECTIVE: Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks. APPROACHES AND RESULTS: Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11 089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15 502 cases/55 730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-β/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways. CONCLUSIONS: These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".