Cardiometabolic risk factors are influenced by Stearoyl‐CoA Desaturase‐1 (SCD1) polymorphisms and n‐3 polyunsaturated fatty acids supplementation
Bibliographic record
Abstract
Polymorphisms (SNPs) in the stearoyl‐CoA desaturase‐1 ( SCD1 ) gene may play a role in the development of the metabolic syndrome. Objective To determine if SCD1 gene SNPs are associated with cardiometabolic risk factors prior and after n ‐3 polyunsaturated fatty acids (PUFA) supplementation. Methods 210 subjects completed a 2‐wk run‐in period followed by 6‐wk supplementation with 5g of fish oil (1.9g EPA and 1.1g DHA). Risk factors were measured pre‐ and post‐ supplementation. FA composition of plasma phospholipids was analyzed by gas chromatography and the desaturase indices were calculated SCD16 (16:1n‐7/16:0) and SCD18 (18:1n‐9/18:0). Genotyping of 8 SNPs of the SCD1 gene was performed. Results N ‐3 PUFA supplementation decreased plasma triglycerides (TG), SCD16 and SCD18 ratios with an increased plasma glucose levels. In repeated measures analysis of variance, where the effects of interest were SNP, supplementation and interaction between the SNP*supplementation on cardiometabolic risk factors, SNPs in SCD1 modified: TG ( rs508384 ), interleukin‐6 (rs3071), C‐reactive protein (rs3829160) and SCD18 ratio (rs2234970). Interaction effects were observed for plasma glucose ( rs508384 ) and insulin levels ( rs508384 and rs3829160). Conclusion Cardiometabolic risk factors are modulated by genetic variations in the SCD1 gene alone or in combination with n ‐3 PUFA supplementation. Funding: CIHR .
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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".