Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.

Long non-coding RNAs (lncRNAs) are emerging as potential biomarkers in type 2 diabetes (T2D). This study evaluated the expression patterns of MIAT and KCNQ1OT1 in T2D patients to assess their diagnostic potential. A cross-sectional study was conducted in which serum samples from 100 T2D patients and 100 matched healthy controls were analyzed. LncRNA expression was measured using RT-qPCR. Clinical parameters, biochemical markers, and correlations with metabolic indices were assessed. Both MIAT and KCNQ1OT1 showed significant upregulation in T2D patients compared to controls (MIAT: 2.27 ± 1.26 vs. 0.45 ± 0.27, p<0.001; KCNQ1OT1: 1.36 ± 0.66 vs. 1.05 ± 0.32, p=0.002). MIAT demonstrated superior diagnostic performance (AUC=0.972, sensitivity=93%, specificity=97%) and emerged as an independent predictor of T2D (OR=37.892, 95% CI: 2.858-502.32, p=0.006). Significant correlations were observed between MIAT expression and metabolic parameters, including BMI, fasting glucose, HOMA-IR, and HbA1c. MIAT has shown promise as a new diagnostic biomarker for T2D, with high correlations with key metabolic parameters. These findings have clinical relevance in T2D diagnosis and monitoring.