Immune-Related Genes for Predicting Future Kidney Graft Loss: A Study Based on GEO Database

Frontiers in Immunology

Cuixiang Xu¹  Xiaoming Ding²  Kun Zhu²  Chenguang Ding²  Wujun Xue²  Meng Dou²  Puxun Tian²  Ge Deng²  Bingxuan Zheng²  Jin Zheng² 

[1] Center of Shaanxi Provincial Clinical Laboratory, Shaanxi Provincial People’s Hospital, Xi’an, China;Department of Kidney Transplantation, Hospital of Nephropathy, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China;

关键词: immune-related genes;    graft rejection;    graft loss;    prognostic model;    kidney transplantation;    immune infiltration;   

DOI  :  10.3389/fimmu.2022.859693

来源: DOAJ

【 摘 要 】

ObjectiveWe aimed to identify feature immune-related genes that correlated with graft rejection and to develop a prognostic model based on immune-related genes in kidney transplantation.MethodsGene expression profiles were obtained from the GEO database. The GSE36059 dataset was used as a discovery cohort. Then, differential expression analysis and a machine learning method were performed to select feature immune-related genes. After that, univariate and multivariate Cox regression analyses were used to identify prognosis-related genes. A novel Riskscore model was built based on the results of multivariate regression. The levels of these feature genes were also confirmed in an independent single-cell dataset and other GEO datasets.Results15 immune-related genes were expressed differently between non-rejection and rejection kidney allografts. Those differentially expressed immune-related genes (DE-IRGs) were mainly associated with immune-related biological processes and pathways. Subsequently, a 5-immune-gene signature was constructed and showed favorable predictive results in the GSE21374 dataset. Recipients were divided into the high-risk and low-risk groups according to the median value of RiskScore. The GO and KEGG analysis indicated that the differentially expressed genes (DEGs) between high-risk and low-risk groups were mainly involved in inflammatory pathways, chemokine-related pathways, and rejection-related pathways. Immune infiltration analysis demonstrated that RiskScore was potentially related to immune infiltration. Kaplan-Meier survival analysis suggested that recipients in the high-risk group had poor graft survival. AUC values of 1- and 3-year graft survival were 0.804 and 0.793, respectively.ConclusionOur data suggest that this immune-related prognostic model had good sensitivity and specificity in predicting the 1- and 3-year kidney graft survival and might act as a useful tool for predicting kidney graft loss.

【 授权许可】

Unknown