Genetic Risk Score Does Not Correlate with Body Mass Index of Latina Women in a Clinical Trial
Bibliographic record
Abstract
Obesity disproportionately affects Latina women. Common genetic variants are convincingly associated with body mass index (BMI) and may be used to create genetic risk scores (GRS) for obesity that could define genetically influenced forms of obesity and alter response to clinical trial interventions. The objective of this study was (1) to identify the frequency and effect size of common obesity genetic variants in Latina women; (2) to determine the clinical utility of a GRS for obesity with Latina women participating in a community-based clinical trial. DNA from 85 Latina women was genotyped for eight genetic variants previously associated with BMI in Caucasians, but not yet assessed in Latina populations. The main outcome measure was the correlation of GRS (sum of eight risk alleles) with BMI, waist circumference, and percent body fat. A majority (83%) of participants had a BMI ≥25. Frequency of loci near FTO, MC4R, and GNPDA2 were lower in Latinas than Caucasians. Association of each locus with BMI was lower in Latinas compared to Caucasians with no significant correlations with BMI. We conclude that an eight locus GRS has no clinical utility for explaining obesity or predicting response to intervention in Latina women participating in a clinical trial.
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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 | 0.003 | 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 | 0.001 |
| 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".