Identification of mitophagy-related genes with diagnostic value in focal segmental glomerulosclerosis using bioinformatics analysis

Focal segmental glomerulosclerosis (FSGS), a major cause of end-stage renal disease, involves podocyte injury and immune dysregulation. We integrated GEO transcriptomic datasets to identify 839 differentially expressed genes and 33 differential mitophagy-related genes via differential expression analysis and weighted gene co-expression network analysis. Machine learning identified six candidate diagnostic biomarkers, SLIRP, BLVRB, ATP6V1F, COX5B, TMEM14A, and TRMT112, with moderate-to-good discriminatory capacity across cohorts. xCell analysis revealed extensive renal immune remodeling in FSGS with expanded pro-inflammatory cells, diminished naive T cells and Tregs, and tight correlations between hub genes and immune profiles. Single-cell RNA-sequencing analysis suggested a trend of downregulation of hub genes in FSGS podocytes, alongside suppressed transcriptomic signatures of mitochondrial energy metabolism and mitophagy-related pathways. qRT-PCR and western blot validated their downregulation at the whole-renal-tissue level in FSGS mouse models. These six genes may serve as diagnostic candidates and provide research clues for exploring mitophagy mechanisms in FSGS.