Irisin levels in patients with prediabetes mellitus: A case-control study and meta-analysis

BACKGROUND Circulating irisin, a myokine, has been inconsistently associated with prediabetes mellitus (PreDM), and its relationship with glucagon is unexplored. Methodological variability, particularly between different enzyme-linked immunosorbent assay (ELISA) kits, is hypothesized to be a primary source of these discrepancies. Therefore, we hypothesized that the reported irisin-PreDM association is critically confounded by assay methodology and inadequate adjustment for key metabolic factors. AIM To investigate circulating irisin in PreDM via a dual-study approach, evaluating methodological variability and metabolic confounders. METHODS A dual-study design was employed: (1) A systematic review and meta-analysis of observational studies; and (2) A single-center, exploratory case-control study of 35 participants (9 PreDM, 26 controls) from a tertiary hospital. Irisin was measured with two commercial ELISA kits (ELK and Elabscience). Key analyses included random-effects meta-analysis, multiple linear regression, Spearman correlation, and Bland-Altman analysis for inter-assay agreement. RESULTS The meta-analysis (8 studies, n = 788) found significantly lower irisin in PreDM (standardized mean difference = -0.524 , 95% confidence interval: -0.897 to -0.152, P = 0.006) with high heterogeneity (I 2 = 86.7%). In the case-control study, unadjusted analysis showed higher irisin in PreDM with the Elabscience kit (median: 7386.3 pg/mL vs 6332.0 pg/mL, P = 0.045) but not the ELK kit. After adjusting for gender, body mass index, and fatty liver, the association was null for both kits. Bland-Altman analysis revealed poor inter-assay agreement (mean bias: 5837.25 pg/mL). Irisin correlated with fatty liver (ρ = 0.350, P = 0.039) and 0.5-hour glucose (ρ = 0.421, P = 0.012), but not with glucagon. CONCLUSION The irisin-PreDM relationship appears to be influenced by assay methodology and metabolic factors. Standardizing irisin measurement and adjusting for key confounders are important considerations for future research.