Association of Genetically Predicted Levels of Circulating Blood Lipids with Coronary Artery Disease Incidence
Bibliographic record
Abstract
Abstract Background Estimating the genetic risk of coronary artery disease (CAD) is now possible by aggregating data from genome-wide association studies (GWAS) into polygenic risk scores (PRS). Combining multiple PRS for specific circulating blood lipids could improve risk prediction. Here, we sought to evaluate the performance of PRS derived from CAD and blood lipids GWAS to predict the incidence of CAD. Methods This study included individuals aged between 40 and 69 recruited in UK Biobank (UKB). We conducted GWAS for blood lipids measured by nuclear magnetic resonance in individuals without lipid-lowering treatments (n=73,915). Summary statistics were used to derive and calculate PRS in the remaining participants (n=318,051). A PRS CAD was also derived using the CARDIoGRAMplusC4D GWAS. Hazard ratios (HR) for CAD (9,017 / 301,576; median follow-up time: 12.6 years) were calculated per standard deviation increase in each PRS. Discrimination capacity and goodness of fit of the models were evaluated. Results Out of 30 PRS, 28 were significantly associated with the incidence of CAD ( P <0.05). The optimal combination of PRS included PRS for CAD, VLDL-C, total cholesterol and triglycerides. Discriminative capacities were significantly increased in the model including PRS CAD and clinical risk factors (CRF) (C-statistic=0.778 [0.773-0.782]) compared to the model with CRF only (C-statistic=0.755 [0.751-0.760]). Although the C-statistic remained similar when independent lipids PRS were added to the model with PRS CAD and CRF (C-statistic=0.778 [0.773-0.783]), the goodness of fit was significantly increased (chi-square test statistic=20.18, P =1.56e-04). Conclusions Although independently associated with CAD incidence, blood lipids PRS provide modest improvement in the predictive performance when added to PRS CAD . Highlights Genome-wide association studies were conducted on 29 selected lipid traits measured by nuclear magnetic resonance spectroscopy in 73,915 participants from UK Biobank who were not taking lipid-lowering treatment. Polygenic risk scores for 27 out of 29 of these traits were associated with the incidence of coronary artery disease (CAD) in 9,017 cases out of 301,576 individuals followed for a median of 12.6 years. When combined to a PRS for coronary artery disease, there was a significant but modest improvement in the discrimination capacity for incident CAD. PRS for certain lipid traits might help to stratify the risk of CAD. Graphical Abstract
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".