Waist-hip ratio related genetic loci are associated with risk of impaired fasting glucose in Chinese children: a case control study
Bibliographic record
Abstract
BACKGROUND: The meta-analyses of genome-wide association studies identified several waist-hip ratio (WHR) related loci in individuals of European ancestry. Since the pattern of fat distribution and the relationship between fat distribution and glucose metabolism disturbance in Chinese are different from those in Europeans, the present study aimed to explore the individual and cumulative effects of WHR-related loci on glycemic phenotypes in Chinese children. METHODS: A total of 2030 children were recruited from two independent studies. Eleven single nucleotide polymorphisms (SNPs) were selected and genotyped using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). Logistic regression and linear regression model were used to examine the association of 11 SNPs and genetic risk score (GRS) with impaired fasting glucose (IFG) and fasting plasma glucose (FPG), respectively. RESULTS: > 0.05). CONCLUSIONS: ) on glycemic phenotypes in Chinese children for the first time. The study suggests that genetic predisposition to central obesity is associated with impaired fasting glucose, providing more evidence for the pathogenesis of diabetes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".