miRNA Targeting of Oxysterol-Binding Protein-Like 6 Regulates Cholesterol Trafficking and Efflux
Bibliographic record
Abstract
OBJECTIVE: Cholesterol homeostasis is fundamental to human health and is, thus, tightly regulated. MicroRNAs exert potent effects on biological pathways, including cholesterol metabolism, by repressing genes with related functions. We reasoned that this mode of pathway regulation could be exploited to identify novel genes involved in cholesterol homeostasis. APPROACH AND RESULTS: Here, we identify oxysterol-binding protein-like 6 (OSBPL6) as a novel target of 2 miRNA hubs regulating cholesterol homeostasis: miR-33 and miR-27b. Characterization of OSBPL6 revealed that it is transcriptionally regulated in macrophages and hepatocytes by liver X receptor and in response to cholesterol loading and in mice and nonhuman primates by Western diet feeding. OSBPL6 encodes the OSBPL-related protein 6 (ORP6), which contains dual membrane- and endoplasmic reticulum-targeting motifs. Subcellular localization studies showed that ORP6 is associated with the endolysosomal network and endoplasmic reticulum, suggesting a role for ORP6 in cholesterol trafficking between these compartments. Accordingly, knockdown of OSBPL6 results in aberrant clustering of endosomes and promotes the accumulation of free cholesterol in these structures, resulting in reduced cholesterol esterification at the endoplasmic reticulum. Conversely, ORP6 overexpression enhances cholesterol trafficking and efflux in macrophages and hepatocytes. Moreover, we show that hepatic expression of OSBPL6 is positively correlated with plasma levels of high-density lipoprotein cholesterol in a cohort of 200 healthy individuals, whereas its expression is reduced in human atherosclerotic plaques. CONCLUSIONS: These studies identify ORP6 as a novel regulator of cholesterol trafficking that is part of the miR-33 and miR-27b target gene networks that contribute to the maintenance of cholesterol homeostasis.
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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) | 0.001 | 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".