Associations between two single nucleotide polymorphisms of the adiponectin gene, its circulating concentrations and cardiometabolic risk factors in prepubertal children with and without abdominal obesity.
Bibliographic record
Abstract
BACKGROUND: The adiponectin gene has been identified as a susceptibility locus for metabolic syndrome, diabetes and cardiovascular disease. AIM: To examine the influence of two single nucleotide polymorphisms (SNPs) of this gene (+276G>T and +45T>G) on circulating adiponectin concentrations, and to evaluate their relationship with adiposity and cardiometabolic risk factors in prepubertal children with and without abdominal obesity. MATERIAL AND METHODS: 168 children (78M, 6-10 yr) were examined, divided into three groups based on waist circumference (WC). Auxological and biochemical parameters were measured by standard procedures. Adiponectin SNPs were genotyped using TaqMan allelic discrimination assays. RESULTS: Adiponectin concentration correlated inversely with measures of adiposity (rBMIz-score=-0.211, pBMIz-score=0.007; rwc=-0.210, pwc=0.008; rwc/height=-0.215, pwc/height=0.006), and was significantly influenced by blood glucose, insulin and systolic blood pressure (SBP). The +276T-allele carriers had higher SBP and diastolic BP compared to GG-homozygotes (p<0.05), and expressed higher obesity-related measures and lower adiponectin concentrations. As to the +45T>G SNP, the GGsubject had higher total cholesterol and LDL-C concentrations compared to the T-allele carriers (p<0.05), showing worse obesity measures, higher triglyceride, glucose and insulin and lower serum adiponectin values. CONCLUSION: Genetic variants of the adiponectin gene had an impact on adiposity, adiponectin concentrations and some cardiometabolic variables among prepubertal children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".