Bioinformatic analysis identifies LPL as a critical gene in diabetic kidney disease via lipoprotein metabolism.

ABSTRACT:

Background

Diabetic kidney disease (DKD) is a common and serious complication of diabetes, affecting approximately 40% of patients with the condition. The pathogenesis of DKD is complex, involving multiple processes such as metabolism, inflammation, and fibrosis. Given its increasing incidence and associated mortality, there is an urgent need to identify novel pathogenic genes and therapeutic targets.

Methods

This study systematically identified hub DKD-associated genes and their potential molecular mechanisms through bioinformatic analysis. Gene expression datasets from DKD patients and healthy controls were obtained from the GEO database. Hub genes were screened using differential expression analysis, weighted gene co-expression network analysis (WGCNA), LASSO regression,

SUBMITTER: Dong Q 

PROVIDER: S-EPMC12310451 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature