RNA Sequencing of CD4 + T Cells in Relapsing-Remitting Multiple Sclerosis Patients at Relapse: Deciphering the Involvement of Novel genes and Pathways

J Mol Neurosci. 2021 Jul 21. doi: 10.1007/s12031-021-01878-8. Online ahead of print.

Abstract

CD4+ T cells are known as a noteworthy potential modulator of inflammation in multiple sclerosis (MS). In the current study, we investigated the transcriptome profile of CD4+ T cells in patients with relapsing-remitting MS (RRMS) at the relapse phase. We performed RNA sequencing of CD4+ T cells isolated from four relapsing-remitting MS (RRMS) patients at the relapse phase and four age- and sex-matched healthy controls. The edgeR statistical method was employed to determine differentially expressed genes (DEGs). Gene set enrichment analysis was subsequently performed. Applying a physical interaction network, genes with higher degrees were selected as hub genes. A total of 1278 and 1034 genes were defined at significantly higher or lower levels, respectively, in CD4+ T cells of RRMS patients at the relapse phase as compared with healthy controls. The top up- and downregulated genes were JAML and KDM3A. The detected DEGs were remarkable on chromosomes 1 and 2, respectively. The DEGs were mainly enriched in the pathways "regulation of transcription, DNA-templated," "regulation of B cell receptor signaling pathway," "protein phosphorylation," "epidermal growth factor receptor signaling pathway," and "positive regulation of neurogenesis." Moreover, 16 KEGG pathways mostly associated with the immune system and viral infections were enriched. In the constructed physical interaction networks, UBA52 and TP53 were shown to be the most highly ranked hub genes among upregulated and downregulated genes, respectively. By applying global transcriptome profiling of CD4+ T cells, we deciphered the involvement of several novel genes and pathways in MS pathogenesis. The present results must be confirmed by in vivo and in vitro studies.

Keywords: CD4+ T cells; Chromosomal enrichment; Functional modules; RNA sequencing; RRMS; Transcriptome.