Placental lipoprotein lipase DNA methylation alterations are associated with gestational diabetes and body composition at 5 years of age
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) is associated with obesity in childhood. This suggests that consequences of in utero exposure to maternal hyperglycemia extend beyond the fetal development, possibly through epigenetic programming. The aims of this study were to assess whether placental DNA methylation (DNAm) marks were associated with maternal GDM status and to offspring body composition at 5 years old in a prospective birth cohort. DNAm levels were measured in the fetal side of the placenta in 66 samples (24 from GDM mothers) using bisDNA-pyrosequencing. Anthropometric and body composition (bioimpedance) were measured in children at 5 years of age. Mann-Whitney and Spearman tests were used to assess associations between GDM, placental DNAm levels at the lipoprotein lipase (LPL) locus and children's weight, height, body mass index (BMI), body fat, and lean masses at 5 years of age. Weight, height, and BMI z-scores were computed according to the World Health Organization growth chart. Analyses were adjusted for gestational age at birth, child sex, maternal age, and pre-pregnancy BMI. LPL DNAm levels were positively correlated with birth weight z-scores (r = 0.252, P = 0.04), and with mid-childhood weight z-scores (r = 0.314, P = 0.01) and fat mass (r = 0.275, P = 0.04), and negatively correlated with lean mass (r = -0.306, P = 0.02). We found a negative correlation between LPL DNAm and mRNA levels in placenta (r = -0.459; P < 0.001), which highlights the regulation of transcriptional activity by these epivariations. We demonstrated that alterations in fetal placental DNAm levels at the LPL gene locus are associated with the anthropometric profile in children at 5 years of age. These findings support the concept of fetal metabolic programming through epigenetic changes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".