Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis.

ABSTRACT:

Aims/introduction

The aim of the present study was to identify candidate differentially expressed genes (DEGs) and pathways using bioinformatics analysis, and to improve our understanding of the cause and potential molecular events of diabetic nephropathy.

Materials and methods

Two cohort profile datasets (GSE30528 and GSE33744) were integrated and used for deep analysis. We sorted DEGs and analyzed differential pathway enrichment. DEG-associated ingenuity pathway analysis was carried out. The screened gene expression feature was verified in the db/db mouse kidney cortex. Then, rat mesangial cells cultured with high-concentration glucose were used for verification. The target genes of transcriptional factor E26 transformation-specific-1 (ETS1) were predicted with online tool

SUBMITTER: Geng XD 

PROVIDER: S-EPMC6626994 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature