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Identification of biomarkers and mechanisms associated with palmitoylation in acute kidney injury using transcriptome and single cell data.


ABSTRACT: Palmitoylation is implicated in acute kidney injury (AKI) development, but its mechanisms are poorly understood. Our study aimed to identify biomarkers associated with palmitoylation-related genes (PRGs) in AKI and explore their biological mechanisms. We analyzed datasets GSE139061, GSE30718, and GSE174220, identifying intersecting genes through differential expression and WGCNA. Candidate genes were selected via PPI analysis, and biomarkers were identified using machine learning, ROC analysis, and gene expression analysis. A nomogram was constructed, and functional analysis along with Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) and Western blotting were performed. scRNA-seq analysis was utilized to identify key cell types and their developmental trajectories in AKI. LIMD1 and MBD2 were identified as AKI biomarkers with elevated expression in AKI samples, confirmed by RT-qPCR and Western blotting. A nomogram based on these biomarkers effectively predicted AKI risk. Functional analysis showed co-enrichment in the "valine leucine and isoleucine degradation" pathway. scRNA-seq analysis identified tubular cells as key in AKI pathogenesis, with a developmental trajectory detailed through pseudo-time analysis. LIMD1 and MBD2 were confirmed as AKI biomarkers, with tubular cells identified as crucial in AKI. Our findings provide new insights into AKI treatment strategies.

SUBMITTER: Sun W 

PROVIDER: S-EPMC12480845 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature

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Identification of biomarkers and mechanisms associated with palmitoylation in acute kidney injury using transcriptome and single cell data.

Sun Weinan W   Wang Juntao J   Zhang Lina L   Zhang Wenwen W   Xu Qin Q   Shao Fengmin F   Gu Yue Y  

Scientific reports 20250929 1


Palmitoylation is implicated in acute kidney injury (AKI) development, but its mechanisms are poorly understood. Our study aimed to identify biomarkers associated with palmitoylation-related genes (PRGs) in AKI and explore their biological mechanisms. We analyzed datasets GSE139061, GSE30718, and GSE174220, identifying intersecting genes through differential expression and WGCNA. Candidate genes were selected via PPI analysis, and biomarkers were identified using machine learning, ROC analysis,  ...[more]

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