Identification of common biomarkers in diabetic kidney disease and cognitive dysfunction using machine learning algorithms.

ABSTRACT: Cognitive dysfunction caused by diabetes has become a serious global medical issue. Diabetic kidney disease (DKD) exacerbates cognitive dysfunction in patients, although the precise mechanism behind this remains unclear. Here, we conducted an investigation using RNA sequencing data from the Gene Expression Omnibus (GEO) database. We analyzed the differentially expressed genes in DKD and three types of neurons in the temporal cortex (TC) of diabetic patients with cognitive dysfunction. Through our analysis, we identified a total of 133 differentially expressed genes (DEGs) shared between DKD and TC neurons (62 up-regulated and 71 down-regulated). To identify potential common biomarkers, we employed machine learning algorithms (LASSO and SVM-RFE) and Venn diagram analysis. Ultimately, we ide

SUBMITTER: Peng J 

PROVIDER: S-EPMC11436791 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature