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. 2024 Jun 22;10(15):e33359.
doi: 10.1016/j.heliyon.2024.e33359. eCollection 2024 Aug 15.

Computational identification of novel potential genetic pathogenesis and otherwise biomarkers in acute liver allograft rejection

Cheng Zhang  1 , Jun-Ze Chen  1 , Kun Dong  1 , Yong-Yuan Jian  1 , Kai-Yong Huang  1 , Rui-Ling Su  1 , Xue-Lin Tan  1 , Guan-Dou Yuan  2   3   4 , Yu-Yan Lan  5 , Song-Qing He  2   3   4 , Chun-Qiang Dong  1
Affiliations

Computational identification of novel potential genetic pathogenesis and otherwise biomarkers in acute liver allograft rejection

Cheng Zhang et al. Heliyon. .

Abstract

Acute cellular rejection (ACR) is a prevalent postoperative complication following liver transplantation (LT), exhibiting an increasing incidence of morbidity and mortality. However, the molecular mechanisms of ACR following LT remain unclear. To explore the genetic pathogenesis and identify biomarkers of ACR following LT, three relevant Gene Expression Omnibus (GEO) datasets consisting of data on ACR or non-ACR patients after LT were comprehensively investigated by computational analysis. A total of 349 upregulated and 260 downregulated differentially expressed genes (DEGs) and eight hub genes (ISG15, HELZ2, HNRNPK, TIAL1, SKIV2L2, PABPC1, SIRT1, and PPARA) were identified. Notably, HNRNPK, TIAL1, and PABPC1 exhibited the highest predictive potential for ACR with AUCs of 0.706, 0.798, and 0.801, respectively. KEGG analysis of hub genes revealed that ACR following LT was predominately associated with ferroptosis, protein processing in the endoplasmic reticulum, complement and coagulation pathways, and RIG-I/NOD/Toll-like receptor signaling pathway. According to the immune cell infiltration analysis, γδT cells, NK cells, Tregs, and M1/M2-like macrophages had the highest levels of infiltration. Compared to SIRT1, ISG15 was positively correlated with γδT cells and M1-like macrophages but negatively correlated with NK cells, CD4+ memory T cells, and Tregs. In conclusion, this study identified eight hub genes and their potential pathways, as well as the immune cells involved in ACR following LT with the greatest levels of infiltration. These findings provide a new direction for future research on the underlying mechanism of ACR following LT.

Keywords: Acute cellular rejection; Biomarkers; Hub genes; Liver transplantation; Mechanisms.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Chun-Qiang Dong reports financial support was provided by The First Affiliated Hospital of 10.13039/501100011827Guangxi Medical University. Song-Qing He reports financial support was provided by The First Affiliated Hospital of 10.13039/501100011827Guangxi Medical University. Chun-Qiang Dong reports a relationship with The First Affiliated Hospital of 10.13039/501100011827Guangxi Medical University that includes: funding grants. Song-Qing He reports a relationship with The First Affiliated Hospital of 10.13039/501100011827Guangxi Medical University that includes: funding grants. No other conflicts of interest. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Venn diagrams analysis of DEGs in three datasets. (a) A total of 349 upregulated DEGs in the ACR groups of three datasets were identified by intersecting with Venn diagrams analysis. (b) A total of 260 down-regulated DEGs in the ACR groups of three datasets were identified by intersecting with Venn diagrams analysis. |log2FC| > 0 and P-value <0.05 were set as the threshold values.
Fig. 2
Fig. 2
Functional enrichment on the identified DEGs. (a–c) The top 20 terms of biological process (BP) terms, molecular function (MF) terms, and cellular component (CC) terms of DEGs identified by GO analysis. (d) The top 20 terms of KEGG pathways of DEGs identified by KEGG pathway analysis.
Fig. 3
Fig. 3
Identification of key modules via WGCNA in GSE26625. (a) Three modules (ME-blue, ME-turquoise, and ME-grey modules) and the module-trait relationships of the three modules were identified via WGCNA. (b–d) The correlation of gene significance with ACR features and indicated module membership.
Fig. 4
Fig. 4
KEGG pathway analysis of DEGs from three key modules. (a–c) The top 20 terms of KEGG pathways of DEGs from ME-blue, ME-turquoise, and ME-grey, respectively. (d–f) The association of DEGs with top 5 KEGG terms from ME-blue, ME-turquoise, and ME-grey, respectively.
Fig. 5
Fig. 5
Identification of hub genes. (a–c) The top 10 hub genes identified using different algorithms in cytoHubba, including Betweenness (a), Closeness (b), and Stress (c). (d) Eight overlapped genes from three algorithms identified by Venn diagram analysis.
Fig. 6
Fig. 6
Validation and ROC curves of the eight hub genes in the indicated GEO datasets. (a) Heat map showing the log2(FC) values of the eight hub genes. Correlation of the eight hub genes in GSE26625 (b), GSE26622 (c), and GSE52420 (d). The red line represents a positive correlation, and the green line represents a negative correlation, with a deeper color indicating a stronger correlation. (e–g) ROC curves reflecting the efficiency of the eight hub genes for predicting the ACR event in the indicated GEO datasets.
Fig. 7
Fig. 7
Results of immune infiltration analysis in tissues from GSE26625. (a) The proportion of indicated immune cells in GSE26625. (b–i) The correlation of the infiltrated immune cells with the indicated hub genes.
Fig. 8
Fig. 8
Top 20 terms of the KEGG pathways of the indicated hub genes from GSE26625. (a–h) The top 20 terms of KEGG pathways associated with the eight hub genes (HNRNPK, ISG15, PABPC1, PPARA, HELZ2, SIRT1, SKIV2L2, and TIAL1).
Fig. S1
Fig. S1
Normalization of the three datasets.
Fig. S2
Fig. S2
Identification of DEGs from three datasets.
Fig. S3
Fig. S3
Results of WGCNA analysis for identification of key modules.
Fig. S4
Fig. S4
PPI network for DEGs from ME-blue module.
Fig. S5
Fig. S5
The co-expression analysis of hub genes and all genes in GSE26625.
See this image and copyright information in PMC

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