Effects of Plasma Phospholipid Fatty Acid Composition and PPAR‐alpha L162V Polymorphism on C‐reactive Protein Levels in Response to an n‐3 Fatty Acid Supplementation
Bibliographic record
Abstract
Background Fish-oil derived fatty acids (FAs) of the n-3 family including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) reduce inflammation through several underlying mechanisms including altered phospholipids FA composition. The L162V polymorphism of the PPAR-α gene is associated with a deteriorated metabolic profile and with obesity indices in numerous studies. Objective: To study whether the PPAR-α L162V polymorphism and changes in plasma phospholipid FA composition influence plasma C-reactive protein (CRP) levels in healthy adults following the n-3 FA supplementation. Method: 189 subjects were supplemented daily with 3g of n-3 FAs (1.9-2.2g EPA and 1.1g DHA) during six weeks. Changes in CRP levels are defined by Δ CRP and changes in plasma phospholipids n-3 (EPA+DHA) by Δ n-3. Results: In univariate analyses, Δ n-3 was negatively correlated with Δ CRP (r=-0.17 p=0.02). After stratification for sex, correlations were stronger in men (r=-0.24 p=0.02) and no longer significant in women (r=-0.11 p=0.31). In multiple linear regression analyses including age, sex, BMI, and hormonal contraceptives as independent variables, Δ n-3 (3.65% p= 0.01) and PPAR-α L162V (2.10% p= 0.04) were the strongest correlates of Δ CRP. Conclusions These results suggest that the incorporation of n-3 FAs in plasma phospholipids and PPAR-α L162V polymorphism may contribute to changes in plasma CRP levels in response to an n-3 FA supplementation. Funding provided by 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 | 0.001 |
| 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 | 0.000 |
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".