Irisin as an Associative Marker of Metabolic Dysregulation in Obesity: Comparative Profiling of IL-6, IL-15, IL-1β, and CCL2

Background/Objectives: Obesity is a complex metabolic disorder associated with chronic low-grade inflammation, insulin resistance, and increased risk of metabolic complications. Traditional measures, such as body mass index (BMI), may not detect early metabolic disturbances. Myokines and cytokines, including irisin, C-C Motif Chemokine (CCL2), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-15 (IL-15), have been proposed as potential biomarkers. This study aimed to investigate the relationships between these biomarkers and metabolic parameters in adults with varying BMI. Methods: Fifty-one adults (mean age 38 ± 11 years) were stratified by BMI into normal weight, overweight, and obese groups. Serum irisin, CCL2, IL-1β, IL-6, and IL-15 concentrations were measured along with metabolic parameters, including insulin, HOMA-IR, C-peptide, and visceral fat. Statistical analyses included Pearson’s correlation, Kruskal–Wallis ANOVA with Bonferroni correction, and subgroup analyses for insulin resistance (HOMA-IR ≥ 2.5). Results: Irisin concentrations were significantly higher in overweight and obese participants compared with normal-weight individuals (p < 0.001) and positively correlated with insulin (r = 0.77), HOMA-IR (r = 0.63), C-peptide (r = 0.71), and BMI (r = 0.54). In contrast, IL-6 and IL-15 levels did not differ significantly across BMI groups, although IL-15 showed a borderline increase in insulin-resistant individuals (p = 0.048). Both IL-1β and CCL2 were significantly elevated across increasing body-weight categories and showed strong positive correlations with measures of adiposity, visceral fat, and insulin resistance; however, neither marker differed significantly when participants were stratified by insulin-resistance status. Additionally, multivariable linear regression identified irisin as the only independent predictor of insulin resistance, while CCL2 was the strongest predictor of BMI. Principal component analysis (PCA) revealed two dominant components separating metabolic (irisin, HOMA-IR, insulin, BMI) and inflammatory (IL-1β, CCL2) profiles, supporting the distinction between metabolic and inflammatory pathways in obesity. Conclusions: Irisin appears to be a sensitive associative marker of metabolic dysregulation associated with increased body mass and insulin resistance. In contrast, IL-1β and CCL2 reflect obesity-related inflammatory burden rather than early metabolic changes, while IL-6 and IL-15 did not reflect early metabolic alterations in this study. Together, these findings suggest that irisin may serve as an associative biomarker for identifying individuals at risk of obesity-related metabolic disturbances, whereas CCL2 and IL-1β may be more indicative of chronic adipose tissue inflammation.