Abstract 114: Apolipoprotein(a) Secretion is Modulated by Sortilin, Proprotein Convertase Subtilisin/Kexin Type 9, and Microsomal Triglyceride Transfer Protein
Bibliographic record
Abstract
Elevated plasma lipoprotein(a) (Lp(a)) levels are the most prevalent inherited risk factor for CVD, but development of specific Lp(a) lowering therapeutics has been hindered by a lack of fundamental understanding of Lp(a) biology. In this study, we used an in vitro model to assess if the secretion of apo(a) is regulated by proteins known to modulate the cellular trafficking and metabolism of other lipoprotein classes. Genetic studies have identified an association between sortilin, a multi-ligand sorting receptor, with plasma Lp(a)-cholesterol concentrations. Monoclonal antibody inhibitors of PCSK9, used to treat elevated plasma LDL-cholesterol, also reduce Lp(a). Lomitapide is used to treat elevated plasma LDL-cholesterol and also appears to reduce Lp(a) levels. In each of these cases, the mechanisms involved are unclear or unknown. In this study, HepG2 (human hepatoma) cells expressing a 17-Kringle (17K) apo(a) isoform were (1) transiently transfected with empty vector control, wild-type (WT) sortilin, or different human sortilin polymorphic variants; (2) exposed to 20 μg/mL of PCSK9; or (3) treated with Lomitapide, an MTP inhibitor. Apo(a) and apoB100 secretion was measured by pulse-chase analysis. . Overexpression of WT sortilin significantly increased the secretion of both apo(a) (89%) and apoB100 (152%) relative to control (both p<0.05). Importantly, sortilin overexpression decreased apoB100 secretion in cells lacking apo(a) co-expression, as previously shown. Expression of the sortilin variants F404Y, K302E and V650M significantly increased secretion of apo(a) compared to WT (by a further 118%, 112% and 125% respectively; p<0.05). Treating 17K-expressing HepG2 cells with 20 μg/mL PCSK9 significantly increased (90%; p<0.05) apo(a) secretion versus control. Interestingly, this effect was dependent on the presence of the lysine binding sites in apo(a) required for non-covalent binding to apoB-100. Finally, treating 17K-expressing HepG2 cells with 20 nM lomitapide significantly reduced (by 64%; p<0.05) the secretion of apo(a). Our findings suggest roles for sortilin, PCSK9, and MTP in modulating Lp(a) levels through effects on apo(a) secretion, possibly through impacts on the secretion or bioavailability of apoB100.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".