Preliminary Investigation of the Biomarkers of Acute Renal Transplant Rejection Using Integrated Proteomics Studies, Gene Expression Omnibus Datasets, and RNA Sequencing

Frontiers in Medicine

article

Shuai Han¹  Wenjun Zhao¹  Cuili Wang¹  Yucheng Wang¹  Rong Song⁵  Hermann Haller⁵  Hong Jiang¹  Jianghua Chen¹ 

[1] Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University;Key Laboratory of Nephropathy;Institute of Nephropathy, Zhejiang University;Zhejiang Clinical Research Center of Kidney and Urinary System Disease;Department of Nephrology, Hannover Medical School

关键词: biomarkers;    renal allograft rejection;    proteomics studies;    gene expression omnibus datasets;    RNA sequencing;   

DOI  :  10.3389/fmed.2022.905464

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

A kidney transplant is often the best treatment for end-stage renal disease. Although immunosuppressive therapy sharply reduces the occurrence of acute allograft rejection (AR), it remains the main cause of allograft dysfunction. We aimed to identify effective biomarkers for AR instead of invasive kidney transplant biopsy. We integrated the results of several proteomics studies related to AR and utilized public data sources. Gene ontology (GO) and pathway analyses were used to identify important biological processes and pathways. The performance of the identified proteins was validated using several public gene expression omnibus (GEO) datasets. Samples that performed well were selected for further validation through RNA sequencing of peripheral blood mononuclear cells of patients with AR ( n = 16) and non-rejection ( n = 19) from our medical center. A total of 25 differentially expressed proteins (DEPs) overlapped in proteomic studies of urine and blood samples. GO analysis showed that the DEPs were mainly involved in the immune system and blood coagulation. Pathway analysis showed that the complement and coagulation cascade pathways were well enriched. We found that immunoglobulin heavy constant alpha 1 (IGHA1) and immunoglobulin κ constant (IGKC) showed good performance in distinguishing AR from non-rejection groups validated with several GEO datasets. Through RNA sequencing, the combination of IGHA1, IGKC, glomerular filtration rate, and donor age showed good performance in the diagnosis of AR with ROC AUC 91.4% (95% CI: 82–100%). Our findings may contribute to the discovery of potential biomarkers for AR monitoring.

【 授权许可】

CC BY