Bempedoic acid: effects on lipoprotein metabolism and atherosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: Bempedoic acid has emerged as a potent inhibitor of ATP-citrate lyase (ACLY), a target for the reduction of LDL cholesterol (LDL-C). We review the impact of bempedoic acid treatment on lipoprotein metabolism and atherosclerosis in preclinical models and patients with hypercholesterolemia. RECENT FINDINGS: The liver-specific activation of bempedoic acid inhibits ACLY, a key enzyme linking glucose catabolism to lipogenesis by catalyzing the formation of acetyl-CoA from mitochondrial-derived citrate for de novo synthesis of fatty acids and cholesterol. Adenosine monophosphate-activated protein kinase activation by bempedoic acid is not required for its lipid-regulating effects in vivo. Mendelian randomization of large human study cohorts has validated ACLY inhibition as a target for LDL-C lowering and atheroprotection. In rodents, bempedoic acid decreases plasma cholesterol and triglycerides, and prevents hepatic steatosis. In apolipoprotein E-deficient (Apoe) mice, LDL receptor-deficient (Ldlr) mice and LDLR-deficient miniature pigs, bempedoic acid reduces LDL-C and attenuates atherosclerosis. LDLR expression and activity are increased in primary human hepatocytes and in Apoe mouse liver treated with bempedoic acid suggesting a mechanism for LDL-C lowering, although additional pathways are likely involved. Phase 2 and 3 clinical trials revealed that bempedoic acid effectively lowers LDL-C as monotherapy, combined with ezetimibe, added to statin therapy and in statin-intolerant hypercholesterolemic patients. Treatment does not affect plasma concentrations of triglyceride or other lipoproteins. SUMMARY: The LDL-C-lowering and attenuated atherosclerosis in animal models and reduced LDL-C in hypercholesterolemic patients has validated ACLY inhibition as a therapeutic strategy. Positive results from phase 3 long-term cardiovascular outcome trials in high-risk patients are required for bempedoic acid to be approved for prevention of atherosclerosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".