A genetic link between prepregnancy body mass index, postpartum weight retention, and offspring weight in early childhood
Bibliographic record
Abstract
OBJECTIVE: The effects of maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) on maternal and offspring obesity traits, as well as the maternal and offspring genetic contribution to GWG and postpartum weight retention, were examined. METHODS: Blood samples from mothers (n = 608) and offspring (n = 541) were genotyped for 83 BMI-associated SNPs and 47 waist-to-hip ratio (WHR)-associated SNPs. Linear regression and mixed-effects regression models were performed to examine clinical epidemiological and genetic associations with unweighted and weighted BMI and WHR genetic risk scores (GRS). RESULTS: Prepregnancy BMI was positively associated with offspring weight and BMI Z-score from birth to 5 years. GWG was positively associated with maternal postpartum weight retention at 1 and 5 years and with offspring weight Z-score from birth to 5 years old. The maternal unweighted BMI GRS was associated with prepregnancy BMI, postpartum weight retention at 5 years, and offspring weight Z-score from birth to 5 years old, but not associated with GWG. Both maternal and offspring unweighted WHR GRSs were negatively associated with GWG. CONCLUSIONS: Maternal BMI-associated SNPs may contribute to the genetic link between prepregnancy BMI variation, long-term postpartum weight retention, and offspring birth weight and longitudinal weight. Maternal and offspring WHR-associated SNPs may contribute to GWG variation.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".