Ancestral Effect on HOMA-IR Levels Quantitated in an American Population of Mexican Origin
Bibliographic record
Abstract
OBJECTIVE: An elevated insulin resistance index (homeostasis model assessment of insulin resistance [HOMA-IR]) is more commonly seen in the Mexican American population than in European populations. We report quantitative ancestral effects within a Mexican American population, and we correlate ancestral components with HOMA-IR. RESEARCH DESIGN AND METHODS: We performed ancestral analysis in 1,551 participants of the Cameron County Hispanic Cohort by genotyping 103 ancestry-informative markers (AIMs). These AIMs allow determination of the percentage (0-100%) ancestry from three major continental populations, i.e., European, African, and Amerindian. RESULTS: We observed that predominantly Amerindian ancestral components were associated with increased HOMA-IR (β = 0.124, P = 1.64 × 10(-7)). The correlation was more significant in males (Amerindian β = 0.165, P = 5.08 × 10(-7)) than in females (Amerindian β = 0.079, P = 0.019). CONCLUSIONS: This unique study design demonstrates how genomic markers for quantitative ancestral information can be used in admixed populations to predict phenotypic traits such as insulin resistance.
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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 | 0.002 |
| 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".