Omega‐3 fatty acids regulate gene expression levels differently in macrophages of men carrying the PPARα‐L162V polymorphism
Bibliographic record
Abstract
Omega‐3 fatty acids (FAs) are natural ligands of the peroxisome proliferator‐activated receptor‐α (PPARα), a nuclear receptor that modulates expression levels of genes involved in lipid metabolism. The L162V polymorphism located in the ligand binding domain of the PPARα gene is associated with a deteriorated plasma lipid profile. Therefore, we postulate that subjects carrying the V162 allele exhibit differences in the activation of PPARα and its target genes after incubation with omega‐3 FAs compared with L162 homozygotes. Peripheral blood monocytes from 6 men carrying the V162 allele paired for age and for body mass index with 6 L162 homozygotes were differentiated into macrophages and incubated with eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), or mixtures of EPA: DHA. Results demonstrate that gene expression levels of PPARα and apolipoprotein AI were significantly lower for carriers of the V162 allele compared to L162 homozygotes after the addition of DHA and a mixture of EPA: DHA. Additionally, lipoprotein lipase expression displayed a tendency to be lower in carriers of the V162 allele after the addition of a mixture of EPA: DHA. Consequently, subjects bearing the PPARα V162 allele may demonstrate inferior improvements in the plasma lipid profile due to lower PPARα and its target genes expression rates in response to omega‐3 FA supplementation. Funding provided by a CIHR Operating Grant.
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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 | 0.001 | 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".