Cord Blood DNA Methylation at <i>CHD13</i> Is Associated with Adiponectin Levels at 10 to 14 Years of Age
Bibliographic record
Abstract
BACKGROUND: Low adiponectin levels are associated with higher insulin resistance, the development of type 2 diabetes, and greater adiposity in adults, but the evidence in youth is limited. This study aimed to assess adiponectin as a biomarker of adverse metabolic health in youth and to examine whether cord blood DNA methylation (cbDNAm) is associated with child adiponectin levels. METHODS: Participants from the Hyperglycemia and Adverse Pregnancy Outcome Study and Follow-up Study were included based on availability of cbDNAm, child anthropometry, child adiponectin levels, and glucose oral glucose tolerance test measures (n = 2265) collected at mean age 11.4 ± 1.2 years. Cross-sectional associations between child log-transformed adiponectin and child adiposity and glycemic measures were evaluated via partial correlation. Linear regression models were used for epigenome-wide analysis of cbDNAm and child adiponectin levels. RESULTS: After adjustment for covariates, lower child adiponectin levels were correlated with higher adiposity/dysglycemia outcomes (sum of skinfolds, r = -0.285 and glucose sum of z-scores, r = -0.070) as well as lower Matsuda (r = 0.135) and disposition (r = 0.062) indices. Linear regression was used to assess associations between cbDNAm and child adiponectin levels with covariate adjustments. cbDNAm at cg02713721, located in the CDH13 locus, was associated with child adiponectin levels (β = .35, Bonferroni-adjusted P = .01). CONCLUSION: This study provides evidence of adiponectin as a biomarker of adverse metabolic health in youth. The association of methylation in CDH13, a gene involved in glucose regulation, with child adiponectin levels suggests a contribution to programming of future metabolic health.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".