LncRNA-miRNA network analysis across the Th17 cell line reveals biomarker potency of lncRNA NEAT1 and KCNQ1OT1 in multiple sclerosis.
Elham KarimiHanieh AzariSirous TahmasebiAmin Reza NikpoorAhmad Agha NegahiNima SanadgolMohammad ShekariMousavi PegahPublished in: Journal of cellular and molecular medicine (2022)
Differentiation of CD 4+ T cells into Th17 cells is an important factor in the onset and progression of multiple sclerosis (MS) and Th17/Treg imbalance. Little is known about the role of lncRNAs in the differentiation of CD 4+ cells from Th17 cells. This study aimed to analyse the lncRNA-miRNAs network involved in MS disease and its role in the differentiation of Th17 cells. The lncRNAs in Th17 differentiation were obtained from GSE66261 using the GEO datasets. Differential expression of lncRNAs in Th17 primary cells compared to Th17 effector cells was investigated by RNA-seq analysis. Next, the most highlighted lncRNAs in autoimmune diseases were downloaded from the lncRNAs disease database, and the most critical miRNA was extracted by literature search. Then, the lncRNA-miRNA interaction was achieved by the Starbase database, and the ceRNA network was designed by Cytoscape. Finally, using the CytoHubba application, two hub lncRNAs with the most interactions with miRNAs were identified by the MCODE plug-in. The expression level of genes was measured by qPCR, and the plasma level of cytokines was analysed by ELISA kits. The results showed an increase in the expression of NEAT1, KCNQ1OT1 and RORC and a decrease in the expression of FOXP3. In plasma, an upregulation of IL17 and a downregulation of TGFB inflammatory cytokines were detected. The dysregulated expression of these genes could be attributed to relapsing-remitting MS (RR-MS) patients and help us understand MS pathogenesis better.
Keyphrases
- multiple sclerosis
- network analysis
- induced apoptosis
- poor prognosis
- cell cycle arrest
- mass spectrometry
- rna seq
- long non coding rna
- ms ms
- signaling pathway
- genome wide identification
- cell death
- regulatory t cells
- emergency department
- oxidative stress
- endoplasmic reticulum stress
- gene expression
- genome wide analysis
- transcription factor
- rheumatoid arthritis
- cell proliferation
- chronic kidney disease
- pi k akt
- high resolution
- electronic health record
- ejection fraction
- data analysis
- disease activity