Evaluating Pro- and Anti-inflammatory Biomarkers for Predicting Type 2 Diabetes Mellitus in the Geriatric Population and Correlation With Clinical and Biochemical Parameters

Background Type 2 diabetes mellitus (T2DM) and aging are associated with inflammation. Our study investigates the diagnostic accuracy of pro- and anti-inflammatory biomarkers in predicting T2DM in the geriatric population and the relation of these biomarkers with clinical and biochemical parameters. Methods This case-control study included age-gender matched, 100 treatment-naïve T2DM cases, and 100 healthy controls. Clinical, biochemical, and anthropometric parameters were comprehensively profiled. The biomarkers were quantified by enzyme-linked immunosorbent assay (ELISA) methods. Results In the T2DM group, serum analyses revealed markedly elevated levels of C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and cortisol, along with notably reduced concentrations of interleukin-10 (IL-10) and adiponectin compared to controls. Despite lower mean insulin-like growth factor-1 (IGF-1) levels in the T2DM group, the differences did not reach statistical significance. The risk of T2DM increased with elevated levels of CRP (odds ratio (OR): 2.69), TNF-α (OR: 1.20), IL-6 (OR: 1.83), and cortisol (OR: 1.01), while higher concentrations of adiponectin (OR: 0.81) and IL-10 (OR: 0.88) were associated with reduced risk (P < 0.05). CRP, TNF-α, IL-6, cortisol, adiponectin, and IL-10 all showed significant area under the curve (AUC) values (P < 0.05), confirming their diagnostic potential. Conversely, insulin-like growth factor-1 (IGF-1) did not reveal any significant diagnostic utility (P=0.327). The optimal cutoff values to diagnose T2DM in the geriatric population determined using the Youden index were as follows: CRP (>3.80 μg/ml), TNF-α (>22.90 pg/ml), IL-6 (>4.67 pg/ml), cortisol (>103.15 ng/ml), adiponectin (≤7.42 μg/ml), and IL-10 (≤5.19 pg/ml). Conclusion This study reveals that pro- and anti-inflammatory biomarkers can predict T2DM, have diagnostic potential and, serve as guidance for future therapeutic strategies.