RNA interference versus antibody-based PCSK9 inhibition for the prevention of cardiovascular disease: a drug-target Mendelian randomization study
Bibliographic record
Abstract
AIMS: RNA interference therapies targeting liver expression of the gene proprotein convertase subtilisin/kexin type 9 (PCSK9) lower LDL-cholesterol (LDL-C) and apolipoprotein B (apoB) levels. As opposed to monoclonal antibodies, which neutralise PCSK9 circulating protein, their effect on atherosclerotic cardiovascular disease (ASCVD) outcomes is unknown. We used genetic variants in the PCSK9 locus influencing PCSK9 function or gene expression in the liver to determine whether antibodies against PCSK9 and RNA interference therapies could have comparable effects on ASCVD. METHODS AND RESULTS: We performed genome-wide genotyping and RNA sequencing of 504 human liver sample and identified a genetic variant (rs472495) explaining 5.6% of liver PCSK9 gene expression to mimic lifelong RNA interference of PCSK9. We used the PCSK9 R46L variant, known to alter PCSK9 function, to model antibody-based PCSK9 inhibition. For each standard deviation decrease in apoB levels, both variants were similarly associated with coronary artery disease risk: (odds ratio [OR] = 0.40, 95% confidence interval [CI]: 0.31-0.51, P = 3.7e-13 for rs472495 which affects liver PCSK9 expression) and (OR = 0.48, 95% CI: 0.43-0.55, P = 1.3e-28 for R46L which affects protein levels). Comparable effects of these two genetic inhibition approaches were observed for aortic stenosis, heart failure, ischemic stroke, Type 2 diabetes and glycemic traits as well as non-alcoholic fatty liver disease and liver enzymes. CONCLUSION: For a given reduction in apoB levels, genetically predicted reductions in PCSK9 function (mimicking PCSK9 neutralizing antibodies) and liver PCSK9 gene expression levels (mimicking PCSK9 RNA interference) were comparably associated with a lower risk of coronary artery disease. These genetic data suggest that LDL-C/apoB reductions may provide cardiovascular benefits, regardless of how PCSK9 function is inhibited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".