ArticleAnnals of medicine2025
Diagnostic PANoptosis-related genes in acute kidney injury: bioinformatics, machine learning, and validation.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Leveraging ICT Tools to Improve Kidney Health: A Comprehensive Review of Innovations in Nephrology.Healthcare (Basel, Switzerland) · 2026Review
- Identification of common diagnostic biomarkers and immune landscapes in sepsis and acute kidney injury: a transcriptomic study integrating machine learning and single-cell analysis.Frontiers in genetics · 2026Article
- PANoptosis nexus in ischemia-reperfusion injury: from integrated cell death mechanisms to novel therapeutic opportunities.Frontiers in immunology · 2026Review
- Recent advances in PANoptosis research in kidney disease: mechanistic networks, pathological roles, and potential intervention strategies.Frontiers in immunology · 2026Review
- Emerging role of PANoptosis in pathogen infection and systemic diseases.Cell biology and toxicology · 2025Review
- Liquid-liquid phase separation-related genes in the immune microenvironment and diagnosis of focal segmental glomerulosclerosis and minimal change disease.Renal failure · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundAcute kidney injury (AKI) is a prevalent and life-threatening condition characterized by abrupt renal function decline and subsequent inflammatory cascades. PANoptosis has emerged as a significant contributor to the pathophysiology of AKI. This research aimed to explore the diagnostic and therapeutic implications of PANoptosis-related genes in AKI.
methodsKidney biopsy transcriptomic expression data were obtained from the GEO database. Differentially expressed genes (DEGs) associated with PANoptosis were identified between AKI and controls. WGCNA identified hub PANoptosis-related genes. PANoptosis scores and immune cell infiltration were calculated by ssGSEA. Machine learning algorithms was used to select feature genes. ROC analysis evaluated their diagnostic performance. Drug-gene interactions were explored.
resultsWe identified 3460 DEGs between AKI and controls (61 upregulated and 11 downregulated) related to PANoptosis, mainly enriched in cytokine signaling and apoptosis. Eight hub PANoptosis genes were identified. PANoptosis scores were significantly higher in AKI patients (
conclusionsOur study identifies PANoptosis-related genes as potential diagnostic markers and therapeutic targets in AKI, highlighting their role in immune dysregulation in AKI.
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