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

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

doi:10.3389/fmed.2021.799051

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

Front Med (Lausanne). 2022 Jan 7:8:799051. doi: 10.3389/fmed.2021.799051. eCollection 2021.

Authors

Wenyu Xiang^{1

2

3

4}, Shuai Han^{1

2

3

4}, Cuili Wang^{1

2

3

4}, Hongjun Chen^{1

2

3

4}, Lingling Shen^{1

2

3

4}, Tingting Zhu^{1

2

3

4}, Kai Wang⁵, Wenjie Wei⁶, Jing Qin⁵, Nelli Shushakova⁷, Song Rong⁷, Hermann Haller⁷, Hong Jiang^{1

2

3

4}, Jianghua Chen^{1

2

3

4}

Affiliations

¹ Kidney Disease Center, College of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China.
² Key Laboratory of Nephropathy, Hangzhou, China.
³ Institute of Nephropathy, Zhejiang University, Hangzhou, China.
⁴ Zhejiang Clinical Research Center of Kidney and Urinary System Disease, Hangzhou, China.
⁵ School of Pharmaceutical Science, Sun Yat-sen University, Shenzhen, China.
⁶ Department of Nephropathy, School of Medicine, Shanghai Ruijin Hospital, Shanghai Jiaotong University, Shanghai, China.
⁷ Department of Nephrology, Hannover Medical School, Hannover, Germany.

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. Pretransplant 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 analysed RNA-Seq data for identifying differentially expressed genes (DEGs), and then gene ontology (GO) analysis, Reactome, and ingenuity pathway analysis (IPA), protein-protein interaction (PPI) network, and cell-type enrichment analysis were utilised for bioinformatics analysis. We identified 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, interleukin-10 (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 proinflammatory pathways were upregulated, whereas antiinflammatory 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 82.8-100). 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.

Keywords: PBMCs; RNA-Seq; actue renal allograft rejection; bioinformatics; biomarker.