Literature DB >> 34286457

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

Saeed Talebi1,2, Samaneh Maleknia3, Fahimeh Palizban4, Zahra Salehi5, Abdorreza Naser Moghadasi6, Kaveh Kavousi4, Mohammad Ali Sahraian7, Maryam Izad8,9.   

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.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

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

Mesh:

Substances:

Year:  2021        PMID: 34286457     DOI: 10.1007/s12031-021-01878-8

Source DB:  PubMed          Journal:  J Mol Neurosci        ISSN: 0895-8696            Impact factor:   3.444


  47 in total

Review 1.  RNA-Seq and human complex diseases: recent accomplishments and future perspectives.

Authors:  Valerio Costa; Marianna Aprile; Roberta Esposito; Alfredo Ciccodicola
Journal:  Eur J Hum Genet       Date:  2012-06-27       Impact factor: 4.246

2.  Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data.

Authors:  Nadezhda T Doncheva; John H Morris; Jan Gorodkin; Lars J Jensen
Journal:  J Proteome Res       Date:  2018-12-05       Impact factor: 4.466

3.  Susceptibility genes are enriched in those of the herpes simplex virus 1/host interactome in psychiatric and neurological disorders.

Authors:  Chris J Carter
Journal:  Pathog Dis       Date:  2013-09-02       Impact factor: 3.166

4.  OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders.

Authors:  Joanna S Amberger; Carol A Bocchini; François Schiettecatte; Alan F Scott; Ada Hamosh
Journal:  Nucleic Acids Res       Date:  2014-11-26       Impact factor: 19.160

Review 5.  NEAT1 and paraspeckles in neurodegenerative diseases: A missing lnc found?

Authors:  Haiyan An; Non G Williams; Tatyana A Shelkovnikova
Journal:  Noncoding RNA Res       Date:  2018-11-15

6.  No differential gene expression for CD4+ T cells of MS patients and healthy controls.

Authors:  Ina S Brorson; Anna Eriksson; Ingvild S Leikfoss; Elisabeth G Celius; Pål Berg-Hansen; Lisa F Barcellos; Tone Berge; Hanne F Harbo; Steffan D Bos
Journal:  Mult Scler J Exp Transl Clin       Date:  2019-06-13

7.  The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019.

Authors:  Annalisa Buniello; Jacqueline A L MacArthur; Maria Cerezo; Laura W Harris; James Hayhurst; Cinzia Malangone; Aoife McMahon; Joannella Morales; Edward Mountjoy; Elliot Sollis; Daniel Suveges; Olga Vrousgou; Patricia L Whetzel; Ridwan Amode; Jose A Guillen; Harpreet S Riat; Stephen J Trevanion; Peggy Hall; Heather Junkins; Paul Flicek; Tony Burdett; Lucia A Hindorff; Fiona Cunningham; Helen Parkinson
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

8.  ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks.

Authors:  Gabriela Bindea; Bernhard Mlecnik; Hubert Hackl; Pornpimol Charoentong; Marie Tosolini; Amos Kirilovsky; Wolf-Herman Fridman; Franck Pagès; Zlatko Trajanoski; Jérôme Galon
Journal:  Bioinformatics       Date:  2009-02-23       Impact factor: 6.937

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

10.  JAML mediates monocyte and CD8 T cell migration across the brain endothelium.

Authors:  Marc Chabarati; Jorge Iván Alvarez; Hania Kébir; Lara Cheslow; Catherine Larochelle; Alexandre Prat
Journal:  Ann Clin Transl Neurol       Date:  2015-09-29       Impact factor: 4.511

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