<i>APOA5</i> and <i>APOA1</i> polymorphisms are associated with triglyceride levels in Mexican children
Bibliographic record
Abstract
Summary Background Dyslipidemia is an important risk factor for the development of several diseases. The genetic component of hypertriglyceridemia has been studied in adults, but little is known in children. Objective The objective is to evaluate the association of two variants in APOA5 (rs662799) and APOA1 (rs5072) with triglyceride (TG) levels in Mexican children. Methods Anthropometric parameters were measured in 1559 Mexican children 5–14 years of age. DNA was isolated from blood samples. Lipid profiles and glucose concentrations were determined from serum and genotyping of rs662799, and rs5072 was performed using TaqMan® technology. Additive and dominant models adjusted for age, gender and body mass index were used to evaluate the association of these single nucleotide polymorphisms with TG levels. Results Children with high TG levels were found to have a higher body mass index and waist circumference as well as a worse lipids profile and glucose levels (p < 0.001). Additive and dominant models demonstrated a significant association between the rs662799 and rs5072 with TG. The dominant model showed the strongest significant association (OR = 1.81; 95% CI 1.46–2.24; p = 5.40 × 10−08 for rs662799 and OR = 1.54; 95% CI 1.05–2.25; p = 2.60 × 10−02 for rs5072). Conclusion The minor alleles of rs662799 (APOA5) and rs5072 (APOA1) modulate TG levels in Mexican children.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".