Significance of pyroptosis-related genes in the diagnosis and classification of diabetic kidney disease.

ABSTRACT:

Objective

This study aimed to identify the potential biomarkers associated with pyroptosis in diabetic kidney disease (DKD).

Methods

Three datasets from the Gene Expression Omnibus (GEO) were downloaded and merged into an integrated dataset. Differentially expressed genes (DEGs) were filtered and intersected with pyroptosis-related genes (PRGs). Pyroptosis-related DEGs (PRDEGs) were obtained and analyzed using functional enrichment analysis. Random forest, Least Absolute Shrinkage and Selection Operator, and logistic regression analyses were used to select the features of PRDEGs. These feature genes were used to build a diagnostic prediction model, identify the subtypes of the disease, and analyze their interactions with transcription factors (TFs)/miRNAs/drugs and small mol

SUBMITTER: Huang Y 

PROVIDER: S-EPMC11463007 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature