Year: 2025
Type: article
Abstract: Background: Liver transplantation is a critical treatment for chronic liver disease; however, rejection and chronic fibrosis of the transplanted liver remain significant challenges. Understanding the mechanisms and high‐level factors contributing to these complications has garnered considerable interest. Methods: Gene expression matrices from homozygous liver samples in the Gene Expression Omnibus database were screened for inclusion. Differentially expressed genes (DEGs) between nonfibrotic and fibrotic liver groups were identified to construct a diagnostic biomarker model using logistic regression and functional enrichment analysis. Additionally, the relationships between immune cell infiltration, fibrosis, and differential gene expression were explored through immune infiltration analysis. Results: The gene expression matrix from frequent liver puncture biopsy samples in the GSE193135 dataset identified 11 DEGs (STMN2, JCHAIN, IGHA1, IGHG3, DCDC2, GSN, KRT7, HLA‐DRB5, CRP, CXCL13, and SPINK1). These genes were utilized to construct a predictive model, achieving robust performance (area under the curve = 0.805, 95% confidence interval: 0.736–0.862). Enrichment and immune infiltration analyses further elucidated the differential gene pathways and immune cell infiltration patterns associated with liver fibrosis. Conclusion: We developed a predictive model for identifying the risk of fibrosis in transplanted livers and investigated the role of immune cell infiltration during fibrosis progression. This model provides valuable insights for understanding and managing fibrosis in liver transplantation.
DOI: 10.1155/ijcp/6433958
Authors: Meicheng Pan, Yawei Qian, Junjie Zhou, Yi Liu, Zhihan Xiao, Lian Gu
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,350
Award: G3841038076
OpenAlex ID: W4410695841