Transcriptional landscape of myasthenia gravis revealed by weighted gene coexpression network analysis

ABSTRACT: Background: As one of the most common autoimmune diseases, myasthenia gravis (MG) severely affects the quality of life of patients. Therefore, exploring the role of dysregulated genes between MG and healthy controls in the diagnosis of MG is beneficial to reveal new and promising diagnostic biomarkers and clinical therapeutic targets. Methods: The GSE85452 dataset was downloaded from the Gene Expression Omnibus (GEO) database and differential gene expression analysis was performed on MG and healthy control samples to identify differentially expressed genes (DEGs). The functions and pathways involved in DEGs were also explored by functional enrichment analysis. Significantly associated modular genes were identified by weighted gene co-expression network analysis (WGCNA), and MG dysregulated

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PROVIDER: S-EPMC10083720 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature