Measuring Lp(a) particles with a novel isoform-insensitive immunoassay illustrates efficacy of muvalaplin
Why this work is in the frame
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Bibliographic record
Abstract
Lipoprotein(a) [Lp(a)] is a cardiovascular risk factor, and there is considerable interest in developing Lp(a)-lowering therapeutics for cardiovascular prevention. Current commercial Lp(a) assays measure total apolipoprotein(a) [apo(a)] and may be insufficient to accurately measure Lp(a) concentrations and determine Lp(a) lowering by a new class of small-molecule Lp(a) formation inhibitors such as muvalaplin. We developed a novel immunoassay that measures only Lp(a) particles. This intact Lp(a) assay demonstrated robust analytical performance, was insensitive to apo(a) isoform size, and correlated with a liquid chromatography-tandem mass spectrometry method. Muvalaplin phase I multiple ascending dose study samples and lepodisiran, a small-interfering RNA that lowers Lp(a), phase I single ascending dose study samples were analyzed using the intact Lp(a) assay and commercial assays. The Lp(a)-lowering efficacy of muvalaplin was underestimated by the commercial assay measuring total apo(a) compared with the intact Lp(a) assay specifically measuring Lp(a) particles. In contrast, the Lp(a)-lowering effect of lepodisiran was clinically comparable between the intact Lp(a) assay and commercial assay. This novel intact Lp(a) assay provides a more accurate approach for the assessment of Lp(a)-lowering agents and the study of Lp(a)-associated risk compared with currently available assays.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it