Association between Polymorphisms in the Fatty Acid Desaturase Gene Cluster and the Plasma Triacylglycerol Response to an n-3 PUFA Supplementation
Bibliographic record
Abstract
Eicosapentaenoic and docosahexaenoic acids have been reported to have a variety of beneficial effects on cardiovascular disease risk factors. However, a large inter-individual variability in the plasma lipid response to an omega-3 (n-3) polyunsaturated fatty acid (PUFA) supplementation is observed in different studies. Genetic variations may influence plasma lipid responsiveness. The aim of the present study was to examine the effects of a supplementation with n-3 PUFA on the plasma lipid profile in relation to the presence of single-nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) gene cluster. A total of 208 subjects from Quebec City area were supplemented with 3 g/day of n-3 PUFA, during six weeks. In a statistical model including the effect of the genotype, the supplementation and the genotype by supplementation interaction, SNP rs174546 was significantly associated (p = 0.02) with plasma triglyceride (TG) levels, pre- and post-supplementation. The n-3 supplementation had an independent effect on plasma TG levels and no significant genotype by supplementation interaction effects were observed. In summary, our data support the notion that the FADS gene cluster is a major determinant of plasma TG levels. SNP rs174546 may be an important SNP associated with plasma TG levels and FADS1 gene expression independently of a nutritional intervention with n-3 PUFA.
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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) | 0.002 | 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".