Evaluation of The Expression Levels of Three Long Non-Coding RNAs in Multiple Sclerosis.

Autoimmune Disease Gene Expression Profiling Long Non-coding RNA Multiple Sclerosis Neurodegenerative Disease

Journal

Cell journal
ISSN: 2228-5806
Titre abrégé: Cell J
Pays: Iran
ID NLM: 101566618

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 23 11 2018
accepted: 12 03 2019
entrez: 14 11 2019
pubmed: 14 11 2019
medline: 14 11 2019
Statut: ppublish

Résumé

Multiple sclerosis (MS) is a chronic disorder involving both inflammatory and neurodegenerative responses. Long non-coding RNAs (lncRNAs) have been had an emerging role as the biomarkers of different disorders, including autoimmune diseases. Previous studies have shown that NR_003531.3 (MEG3a), AC000061.1_201, and AC007182.6 play a role in the pathogenesis of human autoimmune diseases. However, the potential significance of these lncRNAs, as the diagnostic biomarkers of MS, has not been studied yet. We aimed to quantitatively evaluate the expression levels of NR_003531.3, AC000061.1_201, and AC007182.6 in peripheral blood samples of MS patients in comparison with healthy controls. In this case-control study, the blood samples from 20 MS patients and 10 healthy controls were collected. Total RNA was extracted, and the expression levels of three selected lncRNAs were quantitatively measured using the quantitative real time-polymerase chain reaction (qRT-PCR) method. We detected a significant down-regulation in the expression of NR_003531.3 in MS patients, while no marked changes were observed in the expression of AC000061.1_201 and AC007182.6 in patients compared with controls. Based on the receiver operating characteristic (ROC) curve analysis, NR_003531.3 could discriminate MS patients from healthy subjects effectively. Regarding the prognosis of MS patients, NR_003531.3 is significantly and inversely correlated with the expanded disability status scale (EDSS). The potential role of NR_003531.3 lncRNA as a diagnostic biomarker to distinguish MS patients is proposed. Prognostically, NR_003531.3 correlates with lower disability rates in MS patients.

Identifiants

pubmed: 31721530
doi: 10.22074/cellj.2020.6555
pmc: PMC6874792
doi:

Types de publication

Journal Article

Langues

eng

Pagination

165-170

Informations de copyright

Copyright© by Royan Institute. All rights reserved.

Déclaration de conflit d'intérêts

There is no conflict of interest in this study.

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Auteurs

Afshin Moradi (A)

Department of Medical Laboratory Sciences, Faculty of Allied Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Mahdis Rahimi Naiini (M)

Department of Biochemistry, Medical School and Kerman Physiology Research Center, Kerman University of Medical Science, Kerman, Iran.
Zist-fanavari Novin, Biotechnology Institute, Isfahan, Iran.

Nasrin Yazdanpanahi (N)

Department of Genetics, Falavarjan Branch, Islamic Azad University, Isfahan, Iran.

Hossein Tabatabaeian (H)

Division of Genetics, Department of Biology, Faculty of Sciences, University of Isfahan, Isfahan, Iran.
Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Fariba Nabatchian (F)

Department of Medical Laboratory Sciences, Faculty of Allied Medicine, Tehran University of Medical Sciences, Tehran, Iran. Electronic Address: fnabatchian@yahoo.com.

Masoud Baghi (M)

Department of Biology, School of Sciences, University of Isfahan, Isfahan, Iran.
Department of Cellular Biotechnology, Cell Science Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran.

Mansoureh Azadeh (M)

Zist-fanavari Novin, Biotechnology Institute, Isfahan, Iran.

Kamran Ghaedi (K)

Department of Biology, School of Sciences, University of Isfahan, Isfahan, Iran.
Department of Cellular Biotechnology, Cell Science Research Center, Royan Institute for Biotechnology, ACECR, Isfahan, Iran. Electronic Address: kamranghaedi@royaninstitute.org.

Classifications MeSH