Integrative analysis of PANoptosis-related genes in diabetic retinopathy: machine learning identification and experimental validation.

ABSTRACT:

Background

Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therapeutic targets. This study aims to identify differentially expressed PANoptosis-related genes (DE-PRGs) in DR, offering insights into the disease's pathogenesis and potential diagnostic tools.

Methods

DR datasets were obtained from the Gene Expression Omnibus (GEO) database, while PANoptosis-related genes were sourced from the GeneCards database. Differentially expressed genes (DEGs) were identified using the DESeq2 package, followed by functional enrichment analysis through DAVID and Metascape tools. Three machine learning algorith

SUBMITTER: Chen H 

PROVIDER: S-EPMC11652367 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature