Integration of Genetic and Immune Infiltration Insights Into Data Mining of Multiple Sclerosis Pathogenesis

Abstract

\n Background: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. Pathogenesis is closely related to environment, genetic and immune system, but the underlying interactions are still not clearly elucidated. Our study aims to uncover the genetic basis and immune landscape of multiple sclerosis pathogenesis with bioinformatics.Methods: In our study, gene matrix were retrieceed from gene expression database NCBI GEO. We then used bioinformatics to standardize the samples and obtain differential gene expressions (DEGs). We constructed a protein-protein interaction network with DEGs on the STRING website, and used Cytohubba plug-in and MCODE plug-in to to mine hub genes. Then we had a functional enrichment hub genes and DEGs. Meanwhile, we use CIBERSORTX algorithm to explore the characteristics of immune cells infiltration in brain tissues of multiple sclerosis, and did a Spearman correlation analysis between genes and immune cells. We also analyzed the correlation between genes and types of brain tissues with WGCNA method.Results: We included a total of 90 samples from 2 datasets in the study, extracted 882 differential genes and 10 hub genes closely related to multiple sclerosis. Functional enrichment analysis suggested roles of immune response in multiple sclerosis. Besides, with CIBERSORTX algorithm we found brain tissues of MS contain a variety of infiltrating immune cells. Correlation analysis suggested that hub genes are highly relevant to chronic active white matter lesions and certain hub genes in our study may play a role in the activation of immune cells such as macrophages and natural killer cells.Conclusions: Our study provides guidance for the study of genetic basis and immune infiltration mechanism of multiple sclerosis.