Polygenic scores of obesity in childhood based on summary statistics from adults versus children
Bibliographic record
Abstract
The lack of polygenic scores (PGSs) developed for body mass index (BMI) in children may be problematic because the genetic architecture characterizing BMI changes throughout life. This study aims to describe the genetic susceptibility to obesity in children and to compare two PGSs based on data from adults and children and their association with BMI and discrimination of obesity. The study sample comprises 717 participants aged 4–13 years. Adult- and child-based PGSs were evaluated by examining (1) mean BMI across polygenic score risk categories, (2) the capacity to identify obesity with logistic regression, and (3) the linear association with BMI z-scores using linear regression. Increases in one standardized unit of adult-based PGS were related to a stronger increase in BMI z-score (β = 0.24–0.39) than PGS derived in children (β = 0.21–0.30). The association between obesity and the child score was higher (OR = 1.75–2.33) than that for the adult score (OR = 1.74–2.06) for the age group 4–7 years. The inverse was observed for the age group 8–13 years (OR child 1.56–1.79 vs. OR adult 1.78–2.54). Both adult- and child-based PGSs show strong associations with BMI and risk of obesity, with the adult-based score standing out from 8 years old.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".