Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus. | ||
| Egyptian Journal of Chemistry | ||
| Volume 68, Issue 9, September 2025, Pages 565-571 PDF (262.96 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ejchem.2025.341437.10927 | ||
| Authors | ||
| Mona A. Abbas1; Salma M. Own Allah2; Moustafa B. Ata3; Ibrahim Tantawy* 4; Hamed M. Abdelbarry5 | ||
| 1Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Menoufia University, Menoufia, Egypt | ||
| 2Chemistry Department, Faculty of Science, Menoufia University, Shebin El Koom 3251 , Egypt. | ||
| 3Internal Medicine Department, Faculty of Medicine, Shebin El Koom 3251, Egypt | ||
| 4Department of Chemistry, Faculty of Science, Menoufia University, Shebin El-Kom, Egypt. | ||
| 5Chemistry Department, Faculty of Science, Menoufia University, Shebin El Koom 3251 , Egypt | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| MIAT; KCNQ1OT1; Long non-coding RNA; Type 2 Diabetes; Biomarkers; Gene Expression; Insulin Resistance | ||
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