Yongchao Liu1, Aili Jia1, Zijian Li1, Yueran Cui1, Juan Feng2. 1. Department of Neurology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China. 2. Department of Neurology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China. juanfeng@cmu.edu.cn.
Abstract
BACKGROUND: Multiple Sclerosis (MS) is a potentially devastating autoimmune neurological disorder, which characteristically induces demyelination of white matter in the brain and spinal cord. METHODS: In this study, three characteristics of the central nervous system (CNS) immune microenvironment occurring during MS onset were explored; immune cell proportion alteration, differential gene expression profile, and related pathways. The raw data of two independent datasets were obtained from the ArrayExpress database; E-MTAB-69, which was used as a derivation cohort, and E-MTAB-2374 which was used as a validation cohort. Differentially expressed genes (DEGs) were identified by the false discovery rate (FDR) value of < 0.05 and |log2 (Fold Change)|> 1, for further analysis. Then, functional enrichment analyses were performed to explore the pathways associated with MS onset. The gene expression profiles were analyzed using CIBERSORT to identify the immune type alterations involved in MS disease. RESULTS: After verification, the proportion of five types of immune cells (plasma cells, monocytes, macrophage M2, neutrophils and eosinophils) in cerebrospinal fluid (CSF) were revealed to be significantly altered in MS cases compared to the control group. Thus, the complement and coagulation cascades and the systemic lupus erythematosus (SLE) pathways may play critical roles in MS. We identified NLRP3, LILRB2, C1QB, CD86, C1QA, CSF1R, IL1B and TLR2 as eight core genes correlated with MS. CONCLUSIONS: Our study identified the change in the CNS immune microenvironment of MS cases by analysis of the in silico data using CIBERSORT. Our data may assist in providing directions for further research as to the molecular mechanisms of MS and provide future potential therapeutic targets in treatment.
BACKGROUND:Multiple Sclerosis (MS) is a potentially devastating autoimmune neurological disorder, which characteristically induces demyelination of white matter in the brain and spinal cord. METHODS: In this study, three characteristics of the central nervous system (CNS) immune microenvironment occurring during MS onset were explored; immune cell proportion alteration, differential gene expression profile, and related pathways. The raw data of two independent datasets were obtained from the ArrayExpress database; E-MTAB-69, which was used as a derivation cohort, and E-MTAB-2374 which was used as a validation cohort. Differentially expressed genes (DEGs) were identified by the false discovery rate (FDR) value of < 0.05 and |log2 (Fold Change)|> 1, for further analysis. Then, functional enrichment analyses were performed to explore the pathways associated with MS onset. The gene expression profiles were analyzed using CIBERSORT to identify the immune type alterations involved in MS disease. RESULTS: After verification, the proportion of five types of immune cells (plasma cells, monocytes, macrophage M2, neutrophils and eosinophils) in cerebrospinal fluid (CSF) were revealed to be significantly altered in MS cases compared to the control group. Thus, the complement and coagulation cascades and the systemic lupus erythematosus (SLE) pathways may play critical roles in MS. We identified NLRP3, LILRB2, C1QB, CD86, C1QA, CSF1R, IL1B and TLR2 as eight core genes correlated with MS. CONCLUSIONS: Our study identified the change in the CNS immune microenvironment of MS cases by analysis of the in silico data using CIBERSORT. Our data may assist in providing directions for further research as to the molecular mechanisms of MS and provide future potential therapeutic targets in treatment.
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Authors: Aaron M Newman; Chloé B Steen; Chih Long Liu; Andrew J Gentles; Aadel A Chaudhuri; Florian Scherer; Michael S Khodadoust; Mohammad S Esfahani; Bogdan A Luca; David Steiner; Maximilian Diehn; Ash A Alizadeh Journal: Nat Biotechnol Date: 2019-05-06 Impact factor: 54.908
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