Association of <scp><i>AMY1A</i></scp>/<scp><i>AMY2A</i></scp> copy numbers and <scp>AMY1</scp>/<scp>AMY2</scp> serum enzymatic activity with obesity in Mexican children
Bibliographic record
Abstract
SUMMARY Background Mexican children are characterized by a high‐starch intake diet and high prevalence of obesity. Objectives To investigate the association of AMY1A/AMY2A copy numbers (CNs) and AMY1/AMY2 serum enzymatic activity with childhood obesity in up to 427 and 337 Mexican cases and controls. Methods Anthropometric and dietary starch intake data were collected. CN of AMY1A/AMY2A and AMY1/AMY2 serum enzymatic activity were determined using droplet digital PCR (ddPCR) and enzymatic colorimetry, respectively. An individual participant level data meta‐analysis of association between AMY1A CNVs and obesity was also performed. Results A positive association between AMY1A/AMY2A CNs and their corresponding AMY1/AMY2 serum enzyme activity was observed in children with normal weight and obesity. The serum enzyme activity of AMY1 and AMY2 was negatively associated with childhood obesity risk, and the association was restricted to kids eating medium/high amount of starch (Pinteraction = .004). While no association between AMY1A and AMY2A CNs and childhood obesity was observed in our sample, we confirmed a significant association between AMY1A CN and obesity in a meta‐analysis of 3100 Mexican children. Conclusions Our data suggest that genetically determined salivary and pancreatic amylase activity can increase/decrease the risk of obesity in Mexican children, this effect being blunted by a low‐starch diet.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".