Abstract 4369873: <i>LPA</i> -Targeted siRNAs Lower Lp(a) by Over 90%: A Meta-Analysis of Olpasiran, Lepodisiran, and Zerlasiran
Bibliographic record
Abstract
Introduction: Elevated lipoprotein(a) [Lp(a)] is a genetically determined, independent risk factor for atherosclerotic cardiovascular disease (ASCVD). Currently, no approved therapies specifically target Lp(a) reduction. Small-interfering RNA (siRNA) therapeutics—such as olpasiran, lepodisiran, and zerlasiran—are promising investigational agents designed to address this therapeutic gap. These agents selectively target LPA mRNA in hepatocytes, suppressing apolipoprotein(a) synthesis and reducing circulating Lp(a) concentrations.. Research Question: What is the pooled efficacy and safety profile of siRNA agents that target LPA mRNA? Methods: A systematic search of MEDLINE and EMBASE was conducted through June 2025 to identify trials evaluating siRNA therapies that directly silence LPA mRNA. Outcomes of interest included percent changes in Lp(a), apolipoprotein B (ApoB), and low-density lipoprotein cholesterol (LDL-C), along with adverse event rates compared to placebo. To ensure cross-trial consistency, efficacy endpoints were extracted from assessments conducted between weeks 34 and 36, using data from the highest siRNA dose per study. Forest plots display mean differences with corresponding 95% confidence intervals (CI). Heterogeneity was quantified using the I 2 statistic, and adverse events were summarized as absolute risk differences due to low event rates in control groups. Results: Three phase 2 trials met the inclusion criteria. siRNA therapy achieved a significant pooled mean reduction in Lp(a) of −94.46% [95% CI −102.92 to −86.01], with substantial heterogeneity (I 2 = 89.7%). siRNA therapies decreased ApoB by −15.95% [95% CI −19.36 to −12.54] and LDL-C by −19.70% [95% CI −26.22 to −13.19], both without significant heterogeneity (I 2 = 0%). Adverse events occurred more frequently in the siRNA group, with a pooled absolute risk difference of 26.0% [95% CI −13.0 to 64.0] compared to placebo; however, this finding demonstrated high heterogeneity (I 2 = 97.1%), and the confidence interval crossed the null. Conclusions: siRNA therapeutics targeting LPA mRNA demonstrate substantial efficacy, lowering Lp(a) levels by over 90% with concurrent reductions in ApoB and LDL-C. Ongoing phase 3 trials will be pivotal in further characterizing their safety profile and determining the extent to which these promising lipid changes translate into 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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".