The association of circulating irisin with metabolic risk factors in Chinese adults: a cross-sectional community-based study
Bibliographic record
Abstract
Abstract Background Irisin is a myokine that leads to increased energy expenditure by stimulating the browning of white adipose tissue. We aimed to investigate the association of serum irisin levels with metabolic parameters in middle aged Chinese population. Methods The study was based on a cross-sectional analysis of data from 524 nondiabetic subjects aged 40~65. All participants were recruited from a screening survey for Metabolic Syndrome in a community in Southwest China, including 294 subjects categorized as overweight (defined as BMI≧25 kg/m 2 ) and 230 subjects as normal control (defined as 18.5≦BMI < 25 kg/m 2 ). Serum irisin concentration was quantified by enzyme linked immunosorbent assay (ELISA). The relationship of irisin with metabolic factors was determined by Pearson correlation. Multivariate linear regression was used to analyze the association of irisin with insulin resistance. Logistic regression was performed to assess the association of irisin with odds of overweight. Results Serum irisin levels were significantly lower in nondiabetic overweight subjects compared with control (11.46 ± 4.11vs14.78 ± 7.03 μg/mL, p = 0.02). Circulating irisin was positively correlated with quantitative insulin sensitivity check index (QUICKI, r = 0.178, p = 0.045) and triglycerides (r = 0.149, p = 0.022); while irisin was negatively correlated with waist circumference (WC, r = − 0.185, p = 0.037), waist-to-hip ratio (WHR, r = − 0.176, p = 0.047), fasting insulin ( r = − 0.2, p = 0.024), serum creatinine ( r = − 0.243, p = 0.006), homeostasis model assessment for insulin resistance (HOMA-IR, r = − 0.189, p = 0.033). Multiple linear regression showed that irisin was inversely associated with HOMA-IR (β = − 0.342 ± 0.154, p = 0.029). Higher irisin was associated with decreased odds of being overweight (OR = 0.281, β = − 1.271, p = 0.024). Conclusions We found that serum irisin levels were lower in overweight subjects. Moreover, serum irisin levels were inversely correlated with adverse metabolic parameters including WC, WHR, creatinine, HOMA-IR and fasting insulin, suggesting that irisin may play a role in obesity related insulin resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".