Identification and experimental validation of autophagy-related genes in focal segmental glomerulosclerosis by integrating bioinformatics and machine learning.

ABSTRACT: Focal segmental glomerulosclerosis (FSGS) is a common chronic glomerular disease characterized by podocyte injury. The aim of the present study was to investigate autophagy-related characteristics in FSGS. GSE200828, GSE99340, GSE47183, GSE108109, and GSE104948 were used as training sets, and GSE129973 was used as the validation set. 222 autophagy-related genes (ARGs) were incorporated. Autophagy-related differentially expressed genes (ARDEGs) were obtained and then analyzed using violin plots, PPI network analysis, functional enrichment analysis, gene set enrichment analysis, immune cell infiltration and cMAP. Two machine learning methods were applied to select candidate ARGs. Nomogram and receiving operating curve were conducted to assess diagnostic value and screen out core genes. An in

SUBMITTER: Yao T 

PROVIDER: S-EPMC12749187 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature