Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.
Abbas, M., Own Allah, S., Ata, M., Tantawy, I., Abdelbarry, H. (2025). Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.. EKB Journal Management System, 68(9), 565-571. doi: 10.21608/ejchem.2025.341437.10927
Mona A. Abbas; Salma M. Own Allah; Moustafa B. Ata; Ibrahim Tantawy; Hamed M. Abdelbarry. "Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.". EKB Journal Management System, 68, 9, 2025, 565-571. doi: 10.21608/ejchem.2025.341437.10927
Abbas, M., Own Allah, S., Ata, M., Tantawy, I., Abdelbarry, H. (2025). 'Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.', EKB Journal Management System, 68(9), pp. 565-571. doi: 10.21608/ejchem.2025.341437.10927
Abbas, M., Own Allah, S., Ata, M., Tantawy, I., Abdelbarry, H. Assessing MIAT and KCNQ1OT1 Expression as Potential Biomarkers for Diagnosing Type 2 Diabetes Mellitus.. EKB Journal Management System, 2025; 68(9): 565-571. doi: 10.21608/ejchem.2025.341437.10927

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

Egyptian Journal of Chemistry
Volume 68, Issue 9, September 2025, Page 565-571  XML PDF (262.96 K)
Document Type: Original Article
DOI: 10.21608/ejchem.2025.341437.10927
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Authors
Mona A. Abbas1; Salma M. Own Allah2; Moustafa B. Ata3; Ibrahim Tantawy email orcid 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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