Causal Association of Haptoglobin With Obesity in Mexican Children: A Mendelian Randomization Study
Bibliographic record
Abstract
CONTEXT: Little is known about the association between haptoglobin level and cardiometabolic traits. A previous genome-wide association study identified rs2000999 in the HP gene as the stronger genetic contributor to serum haptoglobin level in European populations. OBJECTIVE AND DESIGN: We investigated the association of HP rs2000999 with serum haptoglobin and childhood and adult obesity in up to 540/697 and 592/691 Mexican cases and controls, respectively. Anthropometric and biochemical data were collected. Serum haptoglobin was measured by an immunoturbidimetry assay. HP rs2000999 was genotyped using the TaqMan technology. Mendelian randomization analysis was performed using the Wald and inverse variance weighting methods. RESULTS: Haptoglobin level was positively associated with childhood and adult obesity. HP rs2000999 G allele was positively associated with haptoglobin level in children and adults. HP rs2000999 G allele was positively associated with childhood but not adult obesity. The association between HP rs2000999 and childhood obesity was removed after adjusting for haptoglobin level. In a Mendelian randomization analysis, haptoglobin level genetically predicted by HP rs2000999 showed a significant causal effect on childhood obesity by the Wald and inverse variance weighting methods. CONCLUSION: Our data provide evidence for the first time for a causal positive association between serum haptoglobin level and childhood obesity in the Mexican population. Our study contributes to the genetic elucidation of childhood obesity and proposes haptoglobin as an important biomarker and treatment target for obesity.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".