Drug target Mendelian randomization supports apolipoprotein C3-lowering for lipoprotein-lipid levels reductions and cardiovascular diseases prevention
Bibliographic record
Abstract
Abstract Background and aims Inhibitors of apolipoprotein C-III (apoC3) are currently approved for the reduction of triglyceride levels in patients with Familial Chylomicronemia Syndrome. We used drug target Mendelian randomization (MR) to assess the effect of genetically predicted decrease in APOC3 blood protein levels on cardiometabolic traits and diseases. Methods We quantified lifelong reductions in APOC3 blood levels by selecting all genome wide significant and independent ( r 2 <0.1) single nucleotide polymorphisms (SNPs) in the APOC3 gene region ±1Mb, from three genome-wide association studies (GWAS) of apoC3 blood protein levels (deCODE, n = 35,378, Fenland, n = 10,708 and ARIC, n = 7,213). We included the largest GWASes on 18 cardiometabolica traits and 9 cardiometabolic diseases as study outcomes. Results A one standard deviation lowering in apoC3 blood protein levels was associated with lower triglycerides, apolipoprotein B, density lipoprotein cholesterol, alanine aminotransferase, and glomerular filtration rate as well as higher high-density lipoprotein cholesterol levels. APOC3 lowering was also associated with lower risk of acute pancreatitis (odds ratio [OR] = 0.91 95% CI=0.82 to 1.00), aortic stenosis (OR = 0.82 95% CI=0.73 to 0.93), and coronary artery disease (OR = 0.86 95% CI=0.80 to 0.93), and was associated with increased parental lifespan (0.06 95% CI=0.03 to 0.09 years). These results were concordant across robust MR methods, the three protein datasets and upon adjustment for APOA1, APOA4 and APOA5 using a multivariable MR framework. Conclusions These results provide evidence that apoC3 lowering could result in widespread benefits for cardiometabolic health and encourage the launch of trials on apoC3 inhibition for coronary artery disease prevention.
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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 | 0.021 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".