Polymorphisms in Genes Involved in the Triglyceride Synthesis Pathway and Marine Omega-3 Polyunsaturated Fatty Acid Supplementation Modulate Plasma Triglyceride Levels
Bibliographic record
Abstract
BACKGROUND: Marine omega-3 (n-3) polyunsaturated fatty acids (PUFA) reduce plasma triglyceride (TG) levels. Genetic factors such as single nucleotide polymorphisms (SNPs) could be responsible for the variability of the plasma TG response to n-3 PUFA supplementation. Previous studies have demonstrated that n-3 PUFA supplementation using fish oil modified the expression levels of three genes involved in the TG synthesis pathway (GPAM, AGPAT3 and AGPAT4) in peripheral blood mononuclear cells. METHODS: A total of 210 subjects consumed 5 g/day of a fish oil supplement for 6 weeks. Plasma lipids were measured before and after the supplementation period. Three SNPs in GPAM, 13 SNPs in AGPAT3 and 35 SNPs in AGPAT4 were genotyped. RESULTS: In an ANOVA for repeated measures adjusted for age, sex and BMI, genotype effects on plasma TG levels were observed for rs1838452 in AGPAT3 as well as for rs746731 and rs2293286 in AGPAT4. Genotype × supplementation interaction effects on plasma TG levels were observed for rs2792751 and rs17129561 in GPAM as well as for rs3798943 and rs9458172 in AGPAT4 (p < 0.05). CONCLUSION: These results suggest that SNPs in genes involved in the TG synthesis pathway may influence plasma TG levels after n-3 PUFA supplementation.
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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) | 0.002 | 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".