Polymorphisms in Fatty Acid Desaturase (FADS) Gene Cluster: Effects on Glycemic Controls Following an Omega-3 Polyunsaturated Fatty Acids (PUFA) Supplementation
Bibliographic record
Abstract
UNLABELLED: Changes in desaturase activity are associated with insulin sensitivity and may be associated with type 2 diabetes mellitus (T2DM). Polymorphisms (SNPs) in the fatty acid desaturase (FADS) gene cluster have been associated with the homeostasis model assessment of insulin sensitivity (HOMA-IS) and serum fatty acid composition. OBJECTIVE: To investigate whether common genetic variations in the FADS gene cluster influence fasting glucose (FG) and fasting insulin (FI) responses following a 6-week n-3 polyunsaturated fatty acids (PUFA) supplementation. METHODS: 210 subjects completed a 2-week run-in period followed by a 6-week supplementation with 5 g/d of fish oil (providing 1.9 g-2.2 g of EPA + 1.1 g of DHA). Genotyping of 18 SNPs of the FADS gene cluster covering 90% of all common genetic variations (minor allele frequency ≥ 0.03) was performed. RESULTS: Carriers of the minor allele for rs482548 (FADS2) had increased plasma FG levels after the n-3 PUFA supplementation in a model adjusted for FG levels at baseline, age, sex, and BMI. A significant genotype*supplementation interaction effect on FG levels was observed for rs482548 (p = 0.008). For FI levels, a genotype effect was observed with one SNP (rs174456). For HOMA-IS, several genotype*supplementation interaction effects were observed for rs7394871, rs174602, rs174570, rs7482316 and rs482548 (p = 0.03, p = 0.01, p = 0.03, p = 0.05 and p = 0.07; respectively). CONCLUSION: RESULTS suggest that SNPs in the FADS gene cluster may modulate plasma FG, FI and HOMA-IS levels in response to 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 | 0.001 |
| 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".