Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning.

ABSTRACT:

Background

As the leading cause of chronic kidney disease, diabetic kidney disease (DKD) is an enormous burden for all healthcare systems around the world. However, its early diagnosis has no effective methods.

Methods

First, gene expression data in GEO database were extracted, and the differential genes of diabetic tubulopathy were obtained. Immune-related genesets were generated by WGCNA and immune cell infiltration analyses. Then, differentially expressed immune-related cuproptosis genes (DEICGs) were derived by the intersection of differential genes and genes related to cuproptosis and immune. To investigate the functions of DEICGs, volcano plots and GO term enrichment analysis was performed. Machine learning and protein-protein interaction (PPI) network analysis helped

SUBMITTER: Chen Y 

PROVIDER: S-EPMC10881670 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature