Peritransplant Soluble CD30 as a Risk Factor for Slow Kidney Allograft Function, Early Acute Rejection, Worse Long-Term Allograft Function, and Patients' Survival

Biomarkers as diagnostic tests for delayed graft function in kidney transplantation

Delayed graft function (DGF) after kidney transplantation is associated with inferior outcomes and higher healthcare costs. DGF is currently defined as the requirement for dialysis within seven days post-transplant; however, this definition is subjective and nonspecific. Novel biomarkers have potential to improve objectivity and enable earlier diagnosis of DGF. We reviewed the literature to describe the range of novel biomarkers previously studied to predict DGF. We identified marked heterogeneity and low reporting quality of published studies. Among the novel biomarkers, serum NGAL had the greatest potential as a biomarker to predict DGF, but requires further assessment and validation through larger scale studies of diagnostic test performance. Given inadequacies in the dialysis-based definition, coupled with the high incidence and impact of DGF, such studies should be pursued.

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.

Predictive tools to determine risk of infection in kidney transplant recipients

Introduction: Infection represents a major complication after kidney transplantation (KT). Therapeutic drug monitoring is essentially the only approach for the adjustment of immunosuppression in current practice, with suboptimal results. The implementation of immune monitoring strategies may contribute to minimizing the risk of adverse events attributable to over-immunosuppression without compromising graft outcomes.Areas covered: The present review (based on PubMed/MEDLINE searches from database inception to November 2019) is focused on immune biomarkers with no antigen specificity (non-pathogen-specific), including serum levels of immunoglobulins and complement factors, peripheral blood lymphocyte subpopulations, soluble CD30, intracellular ATP production by stimulated CD4⁺ T-cells, and other cell-based immune assays. We also summarized recent advances in the use of replication kinetics of latent viruses to assess the functionality of T-cell immunity, with focus on the nonpathogenic anelloviruses. Finally, the composite risk scores reported in the literature are critically discussed.Expert opinion: Notable efforts have been made to develop an enlarging repertoire of immune biomarkers and prediction models, although most of them still lack technical standardization and external validation. Preventive interventions based on these tools (prolongation of prophylaxis, tapering of immunosuppression, or immunoglobulin replacement therapy in hypogammaglobulinemic patients) remain to be defined, ideally in the context of controlled trials.

Soluble CD30, the Immune Response, and Acute Rejection in Human Kidney Transplantation: A Systematic Review and Meta-Analysis

Soluble CD30 (sCD30) is considered to be a marker for the activated immune system in which T cells can damage the allograft. Some studies reported that post-transplant sCD30 can predict early acute rejection and can thereby be used as a biomarker to detect acute rejection. However, several other studies found no relation between post-transplant sCD30 and acute rejection. This meta-analysis study aims to answer this main question of whether sCD30 can help clinicians to monitor transplant recipients. The electronic databases, including PubMed, Web of Science, ProQuest, Embase, Scopus, Google Scholar, the gray literature, and the key journals, were searched for observational studies from 1 January 1990 up to 30 April 2018. Eighteen studies, with a total of 1,453 patients, were included in this paper. With regard to the different measurement times, post-transplant sCD30 was separately analyzed and divided into five groups (i.e., 1, 2, 3, 4 week, and 1 month post-transplant sCD30). All groups indicated a strong association between sCD30 and the acute rejection. The standardized mean difference (SMD) is 1.22 in 1 week, 0.77 in 2 week, 1.11 in 3 week, 1.27 in 4 week, and 0.71 in 1 month groups. The association between sCD30 and acute rejection was consistent across all the subgroup analyses. We found that post-transplant sCD30 had a strong association with acute kidney rejection. We also found that the deceased donors had more association with the high amount of sCD30 than living donors in patients with acute rejection. Finally, we realized that donor type was an important factor leading to the heterogeneous results in the primary studies.