SREBF1 gene variations modulate insulin sensitivity in response to a fish oil supplementation
Bibliographic record
Abstract
BACKGROUND: An important inter-individual variability in the response of insulin sensitivity following a fish oil supplementation has been observed. The objective was to examine the associations between single nucleotide polymorphisms (SNPs) within sterol regulatory element binding transcription factor 1 (SREBF1) gene and the response of insulin sensitivity to a fish oil supplementation. METHODS: Participants (n = 210) were recruited in the greater Quebec City area and followed a 6-week fish oil supplementation protocol (5 g/day: 1.9-2.2 g EPA; 1.1 g DHA). Insulin sensitivity was assessed by the quantitative insulin sensitivity check index (QUICKI). Three tag SNPs (tSNPs) within SREBF1 gene were genotyped according to TAQMAN methodology. RESULTS: Three tSNPs (rs12953299, rs4925118 and rs4925115) covered 100% of the known genetic variability within SREBF1 gene. None of the three tSNPs was associated with either baseline fasting insulin concentrations (rs12953299, rs4925118 and rs4925115) (p = 0.29, p = 0.20 and p = 0.70, respectively) or QUICKI (p = 0.20, p = 0.18 and p = 0.76, respectively). The three tSNPs (rs12953299, rs4925118 and rs4925115) were associated with differences in the response of plasma insulin levels (p = 0.01, p = 0.005 and p = 0.004, respectively) and rs12953299 as well as rs4925115 were associated with the insulin sensitivity response (p = 0.009 and p = 0.01, respectively) to the fish oil supplementation, independently of the effects of age, sex and BMI. CONCLUSIONS: The genetic variability within SREBF1 gene has an impact on the insulin sensitivity in response to a fish oil supplementation. TRIAL REGISTRATION: clinicaltrials.gov: NCT01343342.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".