Genetic variation in 9p21 is associated with fasting insulin in women but not men
Bibliographic record
Abstract
BACKGROUND: Single nucleotide polymorphisms (SNPs) in the 9p21 region have been associated with cardiovascular disease (CVD), but previous studies have focussed on older populations. The objective of this study was to determine the association between 9p21 genotypes and biomarkers of CVD risk in young adults from different ethnocultural groups. METHODS: Subjects were 1,626 participants aged 20-29 years from the Toronto Nutrigenomics and Health Study. Fasting blood was collected to measure glucose, insulin, c-reactive protein and serum lipids, as well as to isolate DNA for genotyping subjects for five SNPs in 9p21. Analyses were conducted for the entire population and separately for women (n = 1,109), men (n = 517), Caucasians (n = 771), East Asians (n = 561) South Asians (n = 175) and Others (n = 119). ANOVA and ANCOVA were used to examine if 9p21 genotypes were associated with biomarkers of CVD risk. RESULTS: In the entire group, the risk alleles of rs10757278 and rs2383206 were associated with higher mean insulin (p = 0.01). Risk alleles for rs4977574, rs10757278, rs2383206, rs1333049 and rs10757274 were associated with higher serum insulin in women (p = 0.008, p = 0.008, p = 0.0003, p = 0.002, and p = 0.001, respectively), but not in men (p = 0.41, p = 0.13, p = 0.31, p = 0.34, and 0.35, respectively). The association between 9p21 and insulin remained significant among women not taking hormonal contraceptives (HC), but was not significant among women taking HCs. CONCLUSION: Our findings suggest that 9p21 genotypes may play a role in the development of insulin resistance in early adulthood among women, but not men, and the effects appear to be attenuated by HC use.
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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 | 0.000 |
| 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".