Prospective observational study to validate a next-generation sequencing blood RNA signature to predict early kidney transplant rejection

Urinary biomarkers of kidney transplant rejection

PURPOSE OF REVIEW

Despite the introduction of many new immunosuppressive medications, allograft rejection remains a significant complication in transplantation. The use of "liquid biopsy" to evaluate allograft function and detect early rejection has recently become a prominent focus of investigation as it holds promise in providing noninvasive and immediate insights into the cellular and molecular makeup of the graft.

RECENT FINDINGS

In recent years, the introduction of molecular medicine along with the use of new technologies, including high-throughput techniques, has not only accelerated biomarker discovery but has also contributed to improving our understanding of the mechanisms underlying immune rejection. Genomics, transcriptomics, and metabolomics approaches, along with the increasing use of machine learning techniques, have paved the way for the discovery and development of novel biomarkers.

SUMMARY

Each year, there are hundreds of new biomarker discoveries in the publications. However, only a small fraction can be practically used as clinical tests or surrogate endpoints, receive FDA approval, and reach clinical application. Well designed and reproducible discovery and validation studies are rare and crucial. A contributing factor could be poor study design or quality of biospecimen repositories. In this review, we discuss urinary biomarkers of kidney allograft rejection that have shown promising findings but have yet to be successfully transitioned from bench to bedside.

Chronic Allograft Nephropathy-A Narrative Review of Its Pathogenesis, Diagnosis, and Evolving Management Strategies

Chronic allograft nephropathy is the leading cause of kidney allograft failure. Clinically, it is characterized by a progressive decline in kidney function, often in combination with proteinuria and hypertension. Histologically, interstitial fibrosis and tubular atrophy, along with features of glomerulosclerosis with occasional double contour appearance, arteriolar hyalinosis, and arteriosclerosis, are characteristic findings. The pathophysiology, though complex and incompletely understood, is thought to involve a sequence of immunologic and non-immunologic injuries eventually leading to tissue remodeling and scarring within the graft. The optimal strategy to prevent chronic allograft nephropathy is to minimize both immune- and non-immune-mediated graft injury.

Biomarkers of Rejection in Kidney Transplantation

Alloimmune injury is a major cause of long-term kidney allograft failure whether due to functionally stable (subclinical) or overt clinical rejection. These episodes may be mediated by immune cells (cellular rejection) or alloantibody (antibody-mediated rejection). Early recognition of immune injury is needed for timely appropriate intervention to maintain graft functional viability. However, the conventional measure of kidney function (ie, serum creatinine) is insufficient for immune monitoring due to limited sensitivity and specificity for rejection. As a result, there is need for biomarkers that more sensitively detect the immune response to the kidney allograft. Recently, several biomarkers have been clinically implemented into the care of kidney transplant recipients. These biomarkers attempt to achieve multiple goals including (1) more sensitive detection of clinical and subclinical rejection, (2) predicting impending rejection, (3) monitoring for the adequacy of treatment response, and (4) facilitating personalized immunosuppression. In this review, we summarize the findings to date in commercially available biomarkers, along with biomarkers approaching clinical implementation. While we discuss the analytical and clinical validity of these biomarkers, we identify the challenges and limitations to widespread biomarker use, including the need for biomarker-guided prospective studies to establish evidence of clinical utility of these new assays.

Trends in Precision Medicine and Pharmacogenetics as an Adjuvant in Establishing a Correct Immunosuppressive Therapy for Kidney Transplant: An Up-to-Date Historical Overview

Kidney transplantation is currently the treatment of choice for patients with end-stage kidney diseases. Although significant advancements in kidney transplantation have been achieved over the past decades, the host's immune response remains the primary challenge, often leading to potential graft rejection. Effective management of the immune response is essential to ensure the long-term success of kidney transplantation. To address this issue, immunosuppressives have been developed and are now fully integrated into the clinical management of transplant recipients. However, the considerable inter- and intra-patient variability in pharmacokinetics (PK) and pharmacodynamics (PD) of these drugs represents the primary cause of graft rejection. This variability is primarily attributed to the polymorphic nature (genetic heterogeneity) of genes encoding xenobiotic-metabolizing enzymes, transport proteins, and, in some cases, drug targets. These genetic differences can influence drug metabolism and distribution, leading to either toxicity or reduced efficacy. The main objective of the present review is to report an historical overview of the pharmacogenetics of immunosuppressants, shedding light on the most recent findings and also suggesting how relevant is the research and investment in developing validated NGS-based commercial panels for pharmacogenetic profiling in kidney transplant recipients. These advancements will enable the implementation of precision medicine, optimizing immunosuppressive therapies to improve graft survival and kidney transplanted patient outcomes.

Blood Gene Signature as a Biomarker for Subclinical Kidney Allograft Rejection: Where Are We?

The observation decades ago that inflammatory injuries because of an alloimmune response might be present even in the absence of concomitant clinical impairment in allograft function conduced to the later definition of subclinical rejection. Many studies have investigated the different subclinical rejections defined according to the Banff classification (subclinical T cell-mediated rejection and antibody-mediated rejection), overall concluding that these episodes worsened long-term allograft function and survival. These observations led several transplant teams to perform systematic protocolar biopsies to anticipate treatment of rejection episodes and possibly prevent allograft loss. Paradoxically, the invasive characteristics and associated logistics of such procedures paved the way to investigate noninvasive biomarkers (urine and blood) of subclinical rejection. Among them, several research teams proposed a blood gene signature developed from cohort studies, most of which achieved excellent predictive values for the occurrence of subclinical rejection, mainly antibody-mediated rejection. Interestingly, although all identified genes relate to immune subsets and pathways involved in rejection pathophysiology, very few transcripts are shared among these sets of genes, highlighting the heterogenicity of such episodes and the difficult but mandatory need for external validation of such tools. Beyond this, their application and value in clinical practice remain to be definitively demonstrated in both biopsy avoidance and prevention of clinical rejection episodes. Their combination with other biomarkers, either epidemiological or biological, could contribute to a more accurate picture of a patient's risk of rejection and guide clinicians in the follow-up of kidney transplant recipients.

The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications

Kidney allograft rejection is one of the main limitations to long-term kidney transplant survival. The diagnostic gold standard for detecting rejection is a kidney biopsy, an invasive procedure that can often give imprecise results due to complex diagnostic criteria and high interobserver variability. In recent years, several additional diagnostic approaches to rejection have been investigated, some of them with the aid of machine learning (ML). In this review, we addressed studies that investigated the detection of kidney allograft rejection over the last decade using various ML algorithms. Various ML techniques were used in three main categories: (a) histopathologic assessment of kidney tissue with the aim to improve the diagnostic accuracy of a kidney biopsy, (b) assessment of gene expression in rejected kidney tissue or peripheral blood and the development of diagnostic classifiers based on these data, (c) radiologic assessment of kidney tissue using diffusion-weighted magnetic resonance imaging and the construction of a computer-aided diagnostic system. In histopathology, ML algorithms could serve as a support to the pathologist to avoid misclassifications and overcome interobserver variability. Diagnostic platforms based on biopsy-based transcripts serve as a supplement to a kidney biopsy, especially in cases where histopathologic diagnosis is inconclusive. ML models based on radiologic evaluation or gene signature in peripheral blood may be useful in cases where kidney biopsy is contraindicated in addition to other non-invasive biomarkers. The implementation of ML-based diagnostic methods is usually slow and undertaken with caution considering ethical and legal issues. In summary, the approach to the diagnosis of rejection should be individualized and based on all available diagnostic tools (including ML-based), leaving the responsibility for over- and under-treatment in the hands of the clinician.

Detection of Subclinical Rejection in Pediatric Kidney Transplantation: Current and Future Practices

INTRODUCTION

The successes in the field of pediatric kidney transplantation over the past 60 years have been extraordinary. Year over year, there have been significant improvements in short-term graft survival. However, improvements in longer-term outcomes have been much less apparent. One important contributor has been the phenomenon of low-level rejection in the absence of clinical manifestations-so-called subclinical rejection (SCR).

METHODS

Traditionally, rejection has been diagnosed by changes in clinical parameters, including but not limited to serum creatinine and proteinuria. This review examines the shortcomings of this approach, the effects of SCR on kidney allograft outcome, the benefits and drawbacks of surveillance biopsies to identify SCR, and new urine and blood biomarkers that define the presence or absence of SCR.

RESULTS

Serum creatinine is an unreliable index of SCR. Surveillance biopsies are the method most utilized to detect SCR. However, these have significant drawbacks. New biomarkers show promise. These biomarkers include blood gene expression profiles and donor derived-cell free DNA; urine gene expression profiles; urinary cytokines, chemokines, and metabolomics; and other promising blood and urine tests.

CONCLUSION

Specific emphasis is placed on studies carried out in pediatric kidney transplant recipients.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT03719339.

The Second International Consensus Guidelines on the Management of BK Polyomavirus in Kidney Transplantation

BK polyomavirus (BKPyV) remains a significant challenge after kidney transplantation. International experts reviewed current evidence and updated recommendations according to Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). Risk factors for BKPyV-DNAemia and biopsy-proven BKPyV-nephropathy include recipient older age, male sex, donor BKPyV-viruria, BKPyV-seropositive donor/-seronegative recipient, tacrolimus, acute rejection, and higher steroid exposure. To facilitate early intervention with limited allograft damage, all kidney transplant recipients should be screened monthly for plasma BKPyV-DNAemia loads until month 9, then every 3 mo until 2 y posttransplant (3 y for children). In resource-limited settings, urine cytology screening at similar time points can exclude BKPyV-nephropathy, and testing for plasma BKPyV-DNAemia when decoy cells are detectable. For patients with BKPyV-DNAemia loads persisting >1000 copies/mL, or exceeding 10 000 copies/mL (or equivalent), or with biopsy-proven BKPyV-nephropathy, immunosuppression should be reduced according to predefined steps targeting antiproliferative drugs, calcineurin inhibitors, or both. In adults without graft dysfunction, kidney allograft biopsy is not required unless the immunological risk is high. For children with persisting BKPyV-DNAemia, allograft biopsy may be considered even without graft dysfunction. Allograft biopsies should be interpreted in the context of all clinical and laboratory findings, including plasma BKPyV-DNAemia. Immunohistochemistry is preferred for diagnosing biopsy-proven BKPyV-nephropathy. Routine screening using the proposed strategies is cost-effective, improves clinical outcomes and quality of life. Kidney retransplantation subsequent to BKPyV-nephropathy is feasible in otherwise eligible recipients if BKPyV-DNAemia is undetectable; routine graft nephrectomy is not recommended. Current studies do not support the usage of leflunomide, cidofovir, quinolones, or IVIGs. Patients considered for experimental treatments (antivirals, vaccines, neutralizing antibodies, and adoptive T cells) should be enrolled in clinical trials.

Unveiling systemic responses in kidney transplantation: interplay between the allograft transcriptome and serum proteins

Immunity, as defined by systems biology, encompasses a holistic response throughout the body, characterized by intricate connections with various tissues and compartments. However, this concept has been rarely explored in kidney transplantation. In this proof-of-concept study, we investigated a direct association between the allograft phenotype and serum protein signatures. Time-matched samples of graft biopsies and blood serum were collected in a heterogeneous cohort of kidney-transplanted patients (n = 15) for bulk RNA sequencing and proteomics, respectively. RNA transcripts exhibit distinct and reproducible, coregulated gene networks with specific functional profiles. We measured 159 serum proteins and investigated correlations with gene expression networks. Two opposing axes-one related to metabolism and the other to inflammation-were identified. They may represent a biological continuum between the allograft and the serum and correlate with allograft function, but not with interstitial fibrosis or proteinuria. For signature validation, we used two independent proteomic data sets (n = 21). Our findings establish a biological link between the allograft transcriptome and the blood serum proteome, highlighting systemic immune effects in kidney transplantation and offering a promising framework for developing allograft-linked biomarkers.

Antibody Mediated Rejection and T-cell Mediated Rejection Molecular Signatures Using Next-Generation Sequencing in Kidney Transplant Biopsies

Recently, interest in transcriptomic assessment of kidney biopsies has been growing. This study investigates the use of NGS to identify gene expression changes and analyse the pathways involved in rejection. An Illumina bulk RNA sequencing on the polyadenylated RNA of 770 kidney biopsies was conducted. Differentially-expressed genes (DEGs) were determined for AMR and TCMR using DESeq2. Genes were segregated according to their previous descriptions in known panels (microarray or the Banff Human Organ Transplant (B-HOT) panel) to obtain NGS-specific genes. Pathway enrichment analysis was performed using the Reactome and Kyoto Encyclopaedia of Genes and Genomes (KEGG) public repositories. The differential gene expression using NGS analysis identified 6,141 and 8,478 transcripts associated with AMR and TCMR. While most of the genes identified were included in the microarray and the B-HOT panels, NGS analysis identified 603 (9.8%) and 1,186 (14%) new specific genes. Pathways analysis showed that the B-HOT panel was associated with the main immunological processes involved during AMR and TCMR. The microarrays specifically integrated metabolic functions and cell cycle progression processes. Novel NGS-specific based transcripts associated with AMR and TCMR were discovered, which might represent a novel source of targets for drug designing and repurposing.