Beyond glycemia: adropin, asprosin, and irisin as potential biomarkers for cardiovascular risk in diabetes and prediabetes

Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder. Adropin, asprosin, and irisin, recognized for their metabolic roles, lack clear establishment in cardiovascular disease (CVD) risk and T2DM guidelines. This study aimed to investigate the relationships between serum levels of these biomarkers and CVD risk in healthy, prediabetic, and T2DM individuals. A total of 30 individuals with T2DM, 30 prediabetic subjects, and 29 healthy controls were included in the study. The Framingham Risk Score (FRS) was calculated for each participant. Anthropometric measurements and key biochemical parameters, including fasting blood glucose, HbA1c (glycated hemoglobin), and lipid profile, were recorded. Serum levels of adropin, asprosin, and irisin were quantified using enzyme-linked immunosorbent assay. No statistically significant differences were found in serum adropin, irisin, and asprosin levels across diabetes status groups (p > 0.05). Adropin levels were significantly higher in individuals with lower waist circumference (WC) and body mass index (BMI) (p = 0.029; p = 0.024). Low asprosin levels correlated with greater WC (p = 0.021). FRS correlated significantly with metabolic parameters (age, BMI, WC, blood pressure, glucose, HbA1c, TG (triglycerides), HDL (High-Density Lipoprotein), HOMA-IR (Homeostatic Model Assessment of Insulin Resistance)). While no direct significant relationship was observed between these biomarkers and FRS, a positive significant correlation was found among adropin, asprosin, and irisin levels across all groups. These findings should be interpreted as exploratory and hypothesis generating. To the best of our knowledge, this study is the first to evaluate the associations of adropin, asprosin, and irisin with CVD risk in healthy, prediabetic, and T2DM individuals using FRS. The findings indicate that, although these proteins may not serve as independent predictors of CVD risk, their positive inter-correlations likely reflect underlying subclinical metabolic processes, providing valuable insights for future risk assessment strategies.