No Association between Visfatin <i>(NAMPT)</i> Gene Variants and Metabolic Traits in the Newfoundland Population
Bibliographic record
Abstract
Objective Visfatin is a novel adipokine initially reported to exhibit insulin-mimetic effects that increase insulin sensitivity. Further studies indicate it may also be associated with obesity, serum lipids, and systemic inflammation. At the current time, the role of genetic variation in the visfatin gene (NAMPT) on these parameters is not clear. In the present study, we examined the association between 10 SNPs in NAMPT and insulin resistance, obesity, serum lipids and hsCRP levels. Research design and methods A total of 1838 subjects (413 men, 1425 women) were recruited from the ongoing CODING Study. All subjects were from the genetically homogenous population of Newfoundland and Labrador, Canada. BMI, waist circumference, waist-to-hip ratio, and body fat percentage (determined using DXA) were measured for all subjects. Serum glucose, insulin, HOMA IR , HOMAβ, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides and hsCRP were also determined after a 12-hour fast. Ten SNPs in NAMPT were genotyped using TaqMan validated or functionally tested SNP genotyping assays including rs7789066 (A > G 5′ flanking region), rs3801266 (A > G intron), rs6963243 (G > C intron), rs2058539 (A > C intron), rs6947766 (C > T intron), rs4730153 (G > A intron), rs10808150 (G > A intron), rs2098291 (C > T intron), rs10953502 (T > C intron), and rs10953501 (A > G 3′ UTR). Results We observed no significant associations between any of the variants sites and any parameter of insulin resistance, body composition, serum lipids or hsCRP under an additive model with age and gender included as covariates. This was also true when both dominant and recessive models were applied. Conclusions Our results do not support a significant role for variations in NAMPT with differences in the measured variables in the Newfoundland population.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".