AUTHOR=Xiang Wenyu , Han Shuai , Wang Cuili , Chen Hongjun , Shen Lingling , Zhu Tingting , Wang Kai , Wei Wenjie , Qin Jing , Shushakova Nelli , Rong Song , Haller Hermann , Jiang Hong , Chen Jianghua 

TITLE=Pre-transplant Transcriptional Signature in Peripheral Blood Mononuclear Cells of Acute Renal Allograft Rejection

JOURNAL=Frontiers in Medicine

VOLUME=Volume 8 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2021.799051

DOI=10.3389/fmed.2021.799051

ISSN=2296-858X

ABSTRACT=Acute rejection (AR) is closely associated with renal allograft dysfunction. Here, we utilised RNA sequencing (RNA-Seq) and bioinformatic methods to characterise the peripheral blood mononuclear cells (PBMCs) of patients with acute renal allograft rejection. Pre-transplant blood samples were collected from 32 kidney allograft donors and 42 corresponding recipients with biopsies classified as T cell–mediated rejection (TCMR, n=18), antibody-mediated rejection (ABMR, n=5), and normal/non-specific changes (non-AR, n =19). The patients with TCMR and ABMR were assigned to the AR group and the patients with normal/non-specific changes (n=19) were assigned to the non-AR group. We analyzed RNA-Seq data for identifying differentially expressed genes and then gene ontology (GO) analysis, REACTOME and Ingenuity Pathway Analysis (IPA), protein-protein-interaction network and cell type enrichment analysis were utilized for bioinformatics analysis. We identified genes differentially expressed (DEGs) in the PBMCs of the non-AR group when compared with the AR, ABMR and TCMR groups. Pathway and GO analysis showed significant inflammatory responses, complement activation, IL-10 signalling pathways, classical antibody-mediated complement activation pathways, etc., which were significantly enriched in the DEGs. PPI analysis showed that IL-10, VEGFA, CXCL8, MMP9, and several histone-related genes were the hub genes with the highest degree scores. Moreover, IPA analysis showed that several pro-inflammatory pathways were upregulated, whereas anti-inflammatory pathways were downregulated. The combination of NFSF14+TANK+ANKRD 33 B +HSPA1B was able to discriminate between AR and non-AR with an AUC of 92.3% (95% CI 82.8 to 100). Characterisation of PBMCs by RNA-Seq and bioinformatics analysis demonstrated gene signatures and biological pathways associated with AR. Our study may provide the foundation for the discovery of biomarkers and an in-depth understanding of acute renal allograft rejection.