Abstract 9763: Discovery of a New Role of Human Resistin in Hepatocyte Low-Density Lipoprotein (LDL) Receptor Suppression Mediated by PCSK9
Bibliographic record
Abstract
Background: Serum levels of the adipose tissue-derived signalling protein, resistin, are increased in human obesity and are positively correlated with atherosclerotic cardiovascular disease (ASCVD). However, the function of resistin in humans has been enigmatic. An elevation in serum low-density lipoprotein (LDL) levels is both necessary and sufficient for ASCVD development in humans. However, few physiological factors have been identified that directly affect LDL levels through its main receptor, the LDL receptor (LDLR). In this study, we wished to determine if human resistin plays a role in regulating the uptake of atherogenic LDL in human hepatocytes. Methods: Human hepatocytes (HepG2 and primary) were treated for 24 hours with: (1.) purified human resistin at various concentrations, with and without PCSK9 siRNA, and with and without lovastatin; and (2.) obese human serum with elevated resistin levels or serum from which resistin was removed via antibody-immunoprecipitation. The effect of the treatments on cellular LDL receptor (LDLR) and PCSK9 mRNA and protein levels were determined via real-time PCR and Western blotting, respectively. Results: Resistin, at physiological levels observed in human obesity (50 ng/mL), downregulated hepatocyte LDLR expression substantially by 40%. A key mechanism by which human resistin inhibited hepatocyte LDLR was via increased expression of the recently identified protease, PCSK9, which enhances intracellular LDLR lysosomal degradation. To support this notion, we showed that the addition of resistin reversed the marked over 100% elevation in LDLR expression induced with PCSK9 siRNA treatment. The quantitatively important role of human resistin in LDLR expression was demonstrated by antibody-immunoprecipitation removal of resistin in obese human serum, which increased serum stimulation of LDLR markedly by 80%. Furthermore, resistin diminished statin-mediated upregulation of LDLR by 70%, implicating resistin in the relative ineffectiveness of statins in selective target populations. Conclusions: These results reveal for the first time that resistin is potentially a highly attractive therapeutic target in ameliorating elevated serum LDL, and, thereby, ASCVD, in obese humans.
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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 | 0.001 |
| 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".