Parental and child genetic contributions to obesity traits in early life based on 83 loci validated in adults: the FAMILY study
Bibliographic record
Abstract
Summary Background The genetic influence on child obesity has not been fully elucidated. Objective This study investigated the parental and child contributions of 83 adult body mass index (BMI)‐associated single‐nucleotide polymorphisms (SNPs) to obesity‐related traits in children from birth to 5 years old. Methods A total of 1402 individuals were genotyped for 83 SNPs. An unweighted genetic risk score (GRS) was generated by the sum of BMI‐increasing alleles. Repeated weight and length/height were measured at birth, 1, 2, 3 and 5 years of age, and age‐specific and sex‐specific weight and BMI Z‐scores were computed. Results The GRS was significantly associated with birthweight Z‐score (P = 0.03). It was also associated with weight/BMI Z‐score gain between birth and 5 years old (P = 0.02 and 6.77 × 10−3, respectively). In longitudinal analyses, the GRS was associated with weight and BMI Z‐score from birth to 5 years (P = 5.91 × 10−3 and 5.08 × 10−3, respectively). The maternal effects of rs3736485 in DMXL2 on weight and BMI variation from birth to 5 years were significantly greater compared with the paternal effects by Z test (P = 1.53 × 10−6 and 3.75 × 10−5, respectively). Conclusions SNPs contributing to adult BMI exert their effect at birth and in early childhood. Parent‐of‐origin effects may occur in a limited subset of obesity predisposing SNPs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".