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ABSTRACT: Background
The study aimed to identify core biomarkers related to diagnosis and immune microenvironment regulation and explore the immune molecular mechanism of diabetic nephropathy (DN) through bioinformatics analysis.Methods
GSE30529, GSE99325, and GSE104954 were merged with removing batch effects, and different expression genes (DEGs) were screened at a criterion |log2FC| >0.5 and adjusted P <0.05. KEGG, GO, and GSEA analyses were performed. Hub genes were screened by conducting PPI networks and calculating node genes using five algorithms with CytoHubba, followed by LASSO and ROC analysis to accurately identify diagnostic biomarkers. In addition, two different GEO datasets, GSE175759 and GSE47184, and an experiment cohort with 30 controls and 40 DN patients detected by
SUBMITTER: Zhou H
PROVIDER: S-EPMC10030848 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature