Large-for-Gestational-Age May Be Associated With Lower Fetal Insulin Sensitivity and β-Cell Function Linked to Leptin
Bibliographic record
Abstract
Context: Fetal overgrowth is associated with increased risk for type 2 diabetes in adulthood. It is unclear whether there are alterations in insulin sensitivity and β-cell function in early life. Objective: To determine whether large-for-gestational-age (LGA) (birth weight > 90th percentile), an indicator of fetal overgrowth, is associated with altered fetal insulin sensitivity and β-cell function. Study Design, Population, and Outcomes: In the Design, Development, and Discover birth cohort in Canada, we studied 106 pairs of LGA and optimal-for-gestational-age (OGA; birth weight, 25th to 75th percentiles) infants matched by maternal ethnicity, smoking status, and gestational age. Cord plasma glucose-to-insulin ratio was used as an indicator of fetal insulin sensitivity, and proinsulin-to-insulin ratio was used as an indicator of β-cell function. Cord plasma leptin and high-molecular-weight (HMW) adiponectin concentrations were measured. Results: Comparisons of infants who were born LGA vs OGA, adjusted for maternal and newborn characteristics, showed that cord blood insulin, proinsulin, and leptin concentrations were significantly higher, whereas HWM adiponectin concentrations were similar. Glucose-to-insulin ratios were significantly lower (15.4 ± 28.1 vs 22.0 ± 24.9; P = 0.004), and proinsulin-to-insulin ratios significantly higher (0.73 ± 0.82 vs 0.60 ± 0.78; P = 0.005) in LGA vs OGA newborns, indicating lower insulin sensitivity and β-cell function in LGA newborns. These significant differences were almost unchanged after further adjustment for cord blood adiponectin levels but disappeared upon additional adjustment for cord blood leptin levels. Conclusions: This study demonstrates that LGA may be associated with decreases in both fetal insulin sensitivity and β-cell function. The alterations appear to be linked to elevated leptin levels.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".