Vupanorsen, an N-acetyl galactosamine-conjugated antisense drug to <i>ANGPTL3</i> mRNA, lowers triglycerides and atherogenic lipoproteins in patients with diabetes, hepatic steatosis, and hypertriglyceridaemia
Bibliographic record
Abstract
AIMS: Loss-of-function mutations in ANGPTL3 are associated with beneficial effects on lipid and glucose metabolism and reduced risk of coronary artery disease. Vupanorsen (AKCEA-ANGPTL3-L Rx ) is an N-acetyl galactosamine-conjugated antisense oligonucleotide targeted to the liver that selectively inhibits angiopoietin-like 3 (ANGPTL3) protein synthesis. METHODS AND RESULTS: This was a double-blind, placebo-controlled, dose-ranging, Phase 2 study. Patients (N =105) with fasting triglycerides >150 mg/dL (>1.7 mmol/L), type 2 diabetes, and hepatic steatosis were treated for 6 months with 40 or 80 mg every 4 weeks (Q4W), or 20 mg every week (QW) of vupanorsen, or placebo given subcutaneously. The primary efficacy endpoint was per cent change in fasting triglycerides from baseline at 6 months. Median baseline triglycerides were 2.84 mmol/L (252 mg/dL). Significant reductions in triglycerides of 36%, 53%, 47%, and in ANGPTL3 of 41%, 59%, 56%, were observed in the 40 mg Q4W, 80 mg Q4W, and 20 mg QW groups, respectively, compared with 16% reduction in triglycerides and 8% increase in ANGPTL3 in placebo. Compared with placebo, vupanorsen 80 mg Q4W reduced apolipoprotein C-III (58%), remnant cholesterol (38%), total cholesterol (19%), non-high-density lipoprotein cholesterol (HDL-C; 18%), HDL-C (24%), and apolipoprotein B (9%). There was no improvement in glycaemic parameters, or hepatic fat fraction. Treatment with vupanorsen was not associated with clinically significant changes in platelet counts, and the most common adverse events were those at the injection site, which were generally mild. CONCLUSION: Vupanorsen results in a favourable lipid/lipoprotein profile and provides a potential strategy for residual cardiovascular risk reduction.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".