Does fetal leptin and adiponectin influence children’s lung function and risk of wheeze?
Bibliographic record
Abstract
Adipocytokines, which are secreted during fetal development by both mothers and fetuses, may influence fetal lung development, but little human data are available. We used data from the HOME Study to investigate the associations of cord blood adipocytokine concentrations with children's lung forced expiratory volume (FEV1; N = 160) and their risk of wheeze (N = 281). We measured umbilical cord serum adipocytokine concentrations using enzyme-linked immunosorbent assays and FEV1 using a portable spirometer at ages 4 and 5 to calculate the percent predicted FEV1 (%FEV1). Parents completed standardized questionnaires of their child's wheeze symptoms every 6 months from birth to age 5, then again at ages 6 and 8. We used multivariable linear mixed models and modified Poisson regression with generalized estimating equations to estimate associations of adipocytokine concentrations (log2-transformed) with children's %FEV1 and the risk of wheeze, respectively, adjusting for sociodemographic, perinatal, and child factors. Cord serum leptin was not associated with children's %FEV1. Higher cord serum adiponectin concentrations were associated with higher %FEV1 in girls (β = 3.1, 95% confidence interval [CI]: 0.6, 5.6), but not in boys (β = -1.3, 95% CI: -5.9, 3.3) (sex × adiponectin p-value = 0.05). Higher leptin was associated with lower risk of wheeze in girls (RR = 0.74, 95% CI: 0.66, 0.84), but not boys (RR = 0.87, 95% CI: 0.69, 1.11) (sex × leptin p-value = 0.01). In contrast, higher adiponectin concentrations were associated with lower risk of wheeze (RR = 0.84, 95% CI: 0.73, 0.96) in both boys and girls. These data suggest that fetal adipocytokines may impact lung development and function in early childhood. Future studies are needed to confirm these findings and explore the mechanisms underlying these associations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".