Genetic Risk Score Predictive of the Plasma Triglyceride Response to an Omega-3 Fatty Acid Supplementation in a Mexican Population
Bibliographic record
Abstract
Our group built a genetic risk score (GRS) of the plasma triglyceride (TG) response to an omega-3 (n-3) fatty acid (FA) supplementation in Caucasian Canadians that explained 21.53% of the TG variance. The objective was to refine the GRS by fine mapping and to test its association with the TG response in young Mexican adults. A total of 191 participants underwent a 6-week n-3 FA supplementation providing 2.7g/day of docosahexaenoic and eicosapentaenoic acids. Using quantitative polymerase chain reaction (PCR), 103 single-nucleotide polymorphisms (SNPs) were genotyped. A stepwise regression adjusted for age, sex, and body mass index (BMI) was used to select the strongest SNPs to include in the genetic risk model. A GRS was calculated from the sum of at-risk alleles. The contribution of the GRS to the TG response was assessed by ANCOVA with age, sex, and BMI included in the model. Several differences in allele frequency were observed between Canadians and Mexicans. Five lead SNPs were included in the genetic risk model, in which the GRS accounted for 11.01% of the variance of the TG response (p < 0.0001). These findings highlight the important contribution of genetic factors to the heterogeneity of the TG response to an n-3 FA supplementation among Mexicans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".