Identification of mitophagy-related genes with diagnostic value in focal segmental glomerulosclerosis using bioinformatics analysis
Abstract
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.
Related
- Finerenone Use in Coenzyme Q8B–Related Focal Segmental Glomerulosclerosis
- Intracardiac thrombus and multiple venous thromboses revealing focal segmental glomerulosclerosis
- Digital pathology approach for the classification of focal and segmental glomerulosclerosis
- Glomerular TRPC5 and Palladin immunohistochemical profiling in focal segmental glomerulosclerosis: tissue heterogeneity and exploratory clinical associations (PRIME-PATH I)
- Identification of pyroptosis-related hub genes and construction of a diagnostic model for acute liver failure based on integrated bioinformatics and machine learning.
BibTeX
@article{ma2026identification,
title = {{Identification of mitophagy-related genes with diagnostic value in focal segmental glomerulosclerosis using bioinformatics analysis}},
author = {Jianan Ma and Tianshuai Ma and Yongrui Zhang and Haijian Wei},
journal = {iScience},
year = {2026},
month = oct,
doi = {10.1016/j.isci.2026.118015},
url = {https://www.cell.com/iscience/fulltext/S2589-0042(26)03398-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Identification of mitophagy-related genes with diagnostic value in focal segmental glomerulosclerosis using bioinformatics analysis
AU - Jianan Ma
AU - Tianshuai Ma
AU - Yongrui Zhang
AU - Haijian Wei
PY - 2026
DA - 2026/10/23
JO - iScience
DO - 10.1016/j.isci.2026.118015
UR - https://www.cell.com/iscience/fulltext/S2589-0042(26)03398-5
AB - 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.
SN - 2589-0042
ER -