Pre-transplant CD200 and CD200R1 concentrations are associated with post-transplant events in kidney transplant recipients

Preoperative CD52 Level Predicts Graft Survival following Kidney Transplantation

Several factors have been reported to affect graft survival following kidney transplantation. CD52 molecules may increase T cell proliferation and activation, which may contribute to acute graft rejection and graft survival. In the current study, we studied the possible value of preoperative CD52 levels in predicting graft survival following renal transplantation. Ninety-six patients with end-stage renal disease who had kidney transplantation were included in the study from our prospective cohort. Blood samples were taken one day before surgery, and plasma CD52 levels were measured using ELISA (Cloud-Clone Corp., Houston, TX, USA). Acute rejection, acute tubular necrosis, delayed graft function, graft loss, BK infection, cytomegalovirus infection, and graft survival were evaluated. The mean age of recipients was $50.08\pm 12.82\text{years}$ , and 64.6% were male. The incidence of delayed graft function, acute rejection, graft loss ( $p<0.01$ ), BK virus infection, and serum creatinine levels were significantly higher in recipients with high preoperative CD52 levels six months after transplantation ( $p<0.05$ ). Kaplan–Meier analysis revealed that three-year graft survival was significantly higher in patients with low preoperative CD52 levels ( $p<0.0001$ ). Univariate and multivariate Cox regression analyses showed that serum creatinine levels ( $\text{hazard}\text{ratio}\left[\text{HR}\right]=1.7$ , $p<0.05$ ), acute rejection ( $\text{HR}=2.919$ , $p<0.05$ ), and preoperative CD52 levels ( $\text{HR}=3.114$ , $p<0.05$ ) were independent prognostic factors for graft survival after kidney transplantation. We showed that high preoperative CD52 levels are associated with higher rates of acute rejection, delayed graft function, and BK virus infection and lower rates of graft survival after kidney transplantation.

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

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.

Recent Advances on Biomarkers of Early and Late Kidney Graft Dysfunction

New biomarkers of early and late graft dysfunction are needed in renal transplant to improve management of complications and prolong graft survival. A wide range of potential diagnostic and prognostic biomarkers, measured in different biological fluids (serum, plasma, urine) and in renal tissues, have been proposed for post-transplant delayed graft function (DGF), acute rejection (AR), and chronic allograft dysfunction (CAD). This review investigates old and new potential biomarkers for each of these clinical domains, seeking to underline their limits and strengths. OMICs technology has allowed identifying many candidate biomarkers, providing diagnostic and prognostic information at very early stages of pathological processes, such as AR. Donor-derived cell-free DNA (ddcfDNA) and extracellular vesicles (EVs) are further promising tools. Although most of these biomarkers still need to be validated in multiple independent cohorts and standardized, they are paving the way for substantial advances, such as the possibility of accurately predicting risk of DGF before graft is implanted, of making a “molecular” diagnosis of subclinical rejection even before histological lesions develop, or of dissecting etiology of CAD. Identification of “immunoquiescent” or even tolerant patients to guide minimization of immunosuppressive therapy is another area of active research. The parallel progress in imaging techniques, bioinformatics, and artificial intelligence (AI) is helping to fully exploit the wealth of information provided by biomarkers, leading to improved disease nosology of old entities such as transplant glomerulopathy. Prospective studies are needed to assess whether introduction of these new sets of biomarkers into clinical practice could actually reduce the need for renal biopsy, integrate traditional tools, and ultimately improve graft survival compared to current management.