Genetic determinants of the plasma triglyceride response to an n-3 fatty acid supplementation in overweight adults
Bibliographic record
Abstract
Diet is a major environmental aspect that could be addressed in prevention program of cardiometabolic diseases. This is the central argument to adopt population-based nutritional guidelines. However, such policies assume that all individuals respond similarly to dietary modifications and do not consider the dramatic inter-individual differences in response to such interventions. There is strong evidence that such variability is, at least partly, determined by genetic factors through interaction between genes and diet. We explored gene-diet interaction effects on cardiometabolic risk factors. In a 6-week supplementation with EPA-DHA, we observed a large inter-individual variability in the plasma triglyceride (TG) response with 28.8% of the subjects being negative responders (i.e. having no reduction or an increase in plasma TG levels after the supplementation). To identify genetic variations underlying this variability, we performed a GWAS of the plasma TG response to an n-3 fatty acid (FA) supplementation. Thirteen loci had allele frequency differences between positive-responders (those with a decrease in plasma TG levels) and negative-responders. A genetic risk score (GRS) computed by summing the risk alleles explained 21.5% of the variation in the plasma TG response to the (p = 0.0002). We further increased the density of markers in GWAS signals and refined the GRS using 505 markers. The new GRS remarkably explained a very significant proportion of the variance of the plasma TG responsiveness. These results will likely serve to develop personalized nutrition applications.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".