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ABSTRACT: Background
Dermatomyositis is an autoimmune disease characterized by damage to the skin and muscles. CD4+ T cells are of crucial importance in the occurrence and development of dermatomyositis (DM). However, there are few bioinformatics studies on potential pathogenic genes and immune cell infiltration of DM. Therefore, this study intended to explore CD4+ T-cell infiltration-associated key genes in DM and construct a new model to predict the level of CD4+ T-cell infiltration in DM.Methods
GSE46239, GSE142807, GSE1551, and GSE193276 datasets were downloaded. The WGCNA and CIBERSORT algorithms were performed to identify the most correlated gene module with CD4+ T cells. Matascape was used for GO enrichment and KEGG pathway analysis
SUBMITTER: Huang P
PROVIDER: S-EPMC9196312 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature