The <i>WWOX</i> Gene Modulates High-Density Lipoprotein and Lipid Metabolism
Bibliographic record
Abstract
BACKGROUND: Low levels of high-density lipoprotein (HDL) cholesterol constitutes a major risk factor for atherosclerosis. Recent studies from our group reported a genetic association between the WW domain-containing oxidoreductase (WWOX) gene and HDL cholesterol levels. Here, through next-generation resequencing, in vivo functional studies and gene microarray analyses, we investigated the role of WWOX in HDL and lipid metabolism. METHODS AND RESULTS: Using next-generation resequencing of the WWOX region, we first identified 8 variants significantly associated and perfectly segregating with the low-HDL trait in 2 multigenerational French Canadian dyslipidemic families. To understand in vivo functions of WWOX, we used liver-specific Wwox(hep-/-) and total Wwox(-/-) mice models, where we found decreased ApoA-I and Abca1 levels in hepatic tissues. Analyses of lipoprotein profiles in Wwox(-/-), but not Wwox(hep-/-) littermates, also showed marked reductions in serum HDL cholesterol concentrations, concordant with the low-HDL findings observed in families. We next obtained evidence of a sex-specific effect in female Wwox(hep-/-) mice, where microarray analyses revealed an increase in plasma triglycerides and altered lipid metabolic pathways. We further identified a significant reduction in ApoA-I and Lpl and an upregulation in Fas, Angptl4, and Lipg, suggesting that the effects of Wwox involve multiple pathways, including cholesterol homeostasis, ApoA-I/ABCA1 pathway, and fatty acid biosynthesis/triglyceride metabolism. CONCLUSIONS: Our data indicate that WWOX disruption alters HDL and lipoprotein metabolism through several mechanisms and may account for the low-HDL phenotype observed in families expressing the WWOX variants. These findings thus describe a novel gene involved in cellular lipid homeostasis, which effects may impact atherosclerotic disease development.
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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) | 0.001 | 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 | 0.000 |
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 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".