Identification of Biomarkers for Predicting Allograft Rejection following Kidney Transplantation Based on the Weighted Gene Coexpression Network Analysis

Biomed Res Int. 2021 Jul 29:2021:9933136. doi: 10.1155/2021/9933136. eCollection 2021.

Abstract

Kidney transplantation is the promising treatment of choice for chronic kidney disease and end-stage kidney disease and can effectively improve the quality of life and survival rates of patients. However, the allograft rejection following kidney transplantation has a negative impact on transplant success. Therefore, the present study is aimed at screening novel biomarkers for the diagnosis and treatment of allograft rejection following kidney transplantation for improving long-term transplant outcome. In the study, a total of 8 modules and 3065 genes were identified by WGCNA based on the GSE46474 and GSE15296 dataset from the Gene Expression Omnibus (GEO) database. Moreover, the results of Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that these genes were mainly involved in the immune-related biological processes and pathways. Thus, 317 immune-related genes were selected for further analysis. Finally, 5 genes (including CD200R1, VAV2, FASLG, SH2D1B, and RAP2B) were identified as the candidate biomarkers based on the ROC and difference analysis. Furthermore, we also found that in the 5 biomarkers an interaction might exist among each other in the protein and transcription level. Taken together, our study identified CD200R1, VAV2, FASLG, SH2D1B, and RAP2B as the candidate diagnostic biomarkers, which might contribute to the prevention and treatment of allograft rejection following kidney transplantation.

Publication types

  • Retracted Publication

MeSH terms

  • Allografts / immunology
  • Allografts / pathology*
  • Biomarkers / metabolism*
  • Databases, Genetic
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Gene Ontology
  • Gene Regulatory Networks*
  • Graft Rejection / diagnosis*
  • Graft Rejection / genetics*
  • Graft Rejection / immunology
  • Humans
  • Kidney Transplantation / adverse effects*
  • Molecular Sequence Annotation
  • Protein Interaction Maps / genetics
  • ROC Curve

Substances

  • Biomarkers