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Transcriptomics-based identification of biomarkers associated with mast cell activation during ischemia-reperfusion
Xingyu Pan1, Jin Luo2, Rong Zhu3
1Department of Nursing, Affiliated Hospital of Zunyi Medical University, Zunyi 563100, China; Nursing School of Zunyi Medical University, Zunyi 563100, China.
Background:
Ischemia-reperfusion injury (IRI) in kidney transplantation can delay graft function recovery and increase the risk of rejection. Mast cell activation releases various bioactive mediators that exacerbate renal IRI. Assessing mast cell activation may be crucial for managing IRI after kidney transplantation.
Methods:
We analyzed the dataset GSE43974 from the Gene Expression Omnibus (GEO) to evaluate immune cell infiltration during the IRI phase of kidney transplantation using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was performed to identify genes most strongly correlated with mast cell activation. Hub genes were identified using protein-protein interaction (PPI) network analysis and machine learning algorithms. Model accuracy for identifying hub genes was assessed using receiver operating characteristic (ROC) curve calibration. Clinical utility was evaluated through decision curve analysis (DCA). Correlation analysis was conducted to explore associations between the selected hub genes and immune cell infiltration. Additionally, a hub gene-miRNA regulatory network was constructed.
Results:
Mast cell activation exhibited the most significant variation among graft-infiltrating immune cells during IRI. WGCNA identified 115 genes closely associated with mast cell activation, from which three hub genes-JUN, MYC, and ALDH2-were selected using a PPI network and machine learning approach. A diagnostic model based on these three genes demonstrated high accuracy, as validated by the Hosmer-Lemeshow test (P = 0.980) and an area under the ROC curve (AUC) of 1. DCA indicated that these hub genes had strong clinical decision-making relevance, while correlation analysis confirmed their associations with multiple immune cell types. Finally, a hub gene-miRNA network provided a theoretical framework for the regulatory mechanisms of the three genes.
Conclusion:
JUN, MYC, and ALDH2 may serve as biomarkers of mast cell activation during IRI in kidney transplantation. Further studies are warranted to explore their potential in mitigating IRI.
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