Egyptian Journal of Medical Human Genetics (Mar 2022)

Expression and diagnostic values of MIAT, H19, and NRON long non-coding RNAs in multiple sclerosis patients

  • Mehrnoosh Amiri,
  • Mohammad Javad Mokhtari,
  • Mahnaz Bayat,
  • Anahid Safari,
  • Mehdi Dianatpuor,
  • Reza Tabrizi,
  • Afshin Borhani-Haghighi

DOI
https://doi.org/10.1186/s43042-022-00260-6
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 9

Abstract

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Abstract Background Multiple sclerosis (MS) is a chronic inflammatory disease. Various long non-coding RNAs (lncRNAs) appear to have an important role in the pathophysiology of MS. This study aimed at evaluating the expression levels of lncRNAs, MIAT, H19, and NRON in peripheral blood of MS cases to a healthy control group. We collected blood samples of 95 MS cases (76 relapsing–remitting (RR) and 19 secondary progressive (SP) MS) and 95 controls. We used quantitative real-time PCR for the evaluation of gene expression. The correlation between expression with clinical parameters was analyzed by a multiple linear regression model. Receiver operating characteristic (ROC) curve analysis was carried out to detect the diagnostic potential of lncRNAs levels according to the area under the curve (AUC). Results MIAT, H19, and NRON were significantly increased in the RRMS and SPMS subgroups compared to the controls. We found that the H19 and MIAT expression significantly were higher in SPMS compared with RRMS. Patients with RRMS had a greater level of the average NRON expression is compared with SPMS patients. The expression level of H19 significantly was higher in females relative to male patients. Based on the area under curve (AUC) values, NRON had the best performance in the differentiation of MS patients from controls (AUC = 0.95, P < 0.0001). A combination of MIAT, H19, and NRON expression levels could be useful in differentiating MS patients with 93.6% sensitivity, 98.9% specificity, and diagnostic power of 0.96 (P < 0.0001). Conclusions The levels of MIAT, H19, and NRON in peripheral blood could be important biomarkers for MS diagnosis.

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