Proteomics in Kidney Allograft Transplantation—Application of Molecular Pathway Analysis for Kidney Allograft Disease Phenotypic Biomarker Selection

Machine learning-supported interpretation of kidney graft elementary lesions in combination with clinical data

Interpretation of kidney graft biopsies using the Banff classification is still heterogeneous. In this study, extreme gradient boosting classifiers learned from two large training datasets (n = 631 and 304 cases) where the "reference diagnoses" were not strictly defined following the Banff rules but from central reading by expert pathologists and further interpreted consensually by experienced transplant nephrologists, in light of the clinical context. In three external validation datasets (n = 3744, 589, and 360), the classifiers yielded a mean ROC curve AUC (95%CI) of: 0.97 (0.92-1.00), 0.97 (0.96-0.97), and 0.95 (0.93-0.97) for antibody-mediated rejection (ABMR); 0.94 (0.91-0.96), 0.94 (0.92-0.95), and 0.91 (0.88-0.95) for T cell-mediated rejection; >0.96 (0.90-1.00) with all three for interstitial fibrosis-tubular atrophy. We also developed a classifier to discriminate active and chronic active ABMR with 95% accuracy. In conclusion, we built highly sensitive and specific artificial intelligence classifiers able to interpret kidney graft scoring together with a few clinical data and automatically diagnose rejection, with excellent concordance with the Banff rules and reference diagnoses made by a group of experts. Some discrepancies may point toward possible improvements that could be made to the Banff classification.

The Impact of Donor and Recipient Genetic Variation on Outcomes After Solid Organ Transplantation: A Scoping Review and Future Perspectives

At the outset of solid organ transplantation, genetic variation between donors and recipients was recognized as a major player in mechanisms such as allograft tolerance and rejection. Genome-wide association studies have been very successful in identifying novel variant-trait associations, but have been difficult to perform in the field of solid organ transplantation due to complex covariates, era effects, and poor statistical power for detecting donor-recipient interactions. To overcome a lack of statistical power, consortia such as the International Genetics and Translational Research in Transplantation Network have been established. Studies have focused on the consequences of genetic dissimilarities between donors and recipients and have reported associations between polymorphisms in candidate genes or their regulatory regions with transplantation outcomes. However, knowledge on the exact influence of genetic variation is limited due to a lack of comprehensive characterization and harmonization of recipients' or donors' phenotypes and validation using an experimental approach. Causal research in genetics has evolved from agnostic discovery in genome-wide association studies to functional annotation and clarification of underlying molecular mechanisms in translational studies. In this overview, we summarize how the recent advances and progresses in the field of genetics and genomics have improved the understanding of outcomes after solid organ transplantation.

Urine recirculation prolongs normothermic kidney perfusion via more optimal metabolic homeostasis-a proteomics study

We describe a proteomics analysis to determine the molecular differences between normothermically perfused (normothermic machine perfusion, NMP) human kidneys with urine recirculation (URC) and urine replacement (UR). Proteins were extracted from 16 kidney biopsies with URC (n = 8 donors after brain death [DBD], n = 8 donors after circulatory death [DCD]) and three with UR (n = 2 DBD, n = 1 DCD), followed by quantitative analysis by mass spectrometry. Damage-associated molecular patterns (DAMPs) were decreased in kidney tissue after 6 hours NMP with URC, suggesting reduced inflammation. Vasoconstriction was also attenuated in kidneys with URC as angiotensinogen levels were reduced. Strikingly, kidneys became metabolically active during NMP, which could be enhanced and prolonged by URC. For instance, mitochondrial succinate dehydrogenase enzyme levels as well as carbonic anhydrase were enhanced with URC, contributing to pH stabilization. Levels of cytosolic and the mitochondrial phosphoenolpyruvate carboxykinase were elevated after 24 hours of NMP, more prevalent in DCD than DBD tissue. Key enzymes involved in glucose metabolism were also increased after 12 and 24 hours of NMP with URC, including mitochondrial malate dehydrogenase and glutamic-oxaloacetic transaminase, predominantly in DCD tissue. We conclude that NMP with URC permits prolonged preservation and revitalizes metabolism to possibly better cope with ischemia reperfusion injury in discarded kidneys.

Peritransplant Cardiometabolic and Mitochondrial Function: The Missing Piece in Donor Heart Dysfunction and Graft Failure

Primary graft dysfunction is an important cause of morbidity and mortality after cardiac transplantation. Donor brain stem death (BSD) is a significant contributor to donor heart dysfunction and primary graft dysfunction. There remain substantial gaps in the mechanistic understanding of peritransplant cardiac dysfunction. One of these gaps is cardiac metabolism and metabolic function. The healthy heart is an "omnivore," capable of utilizing multiple sources of nutrients to fuel its enormous energetic demand. When this fails, metabolic inflexibility leads to myocardial dysfunction. Data have hinted at metabolic disturbance in the BSD donor and subsequent heart transplantation; however, there is limited evidence demonstrating specific metabolic or mitochondrial dysfunction. This review will examine the literature surrounding cardiometabolic and mitochondrial function in the BSD donor, organ preservation, and subsequent cardiac transplantation. A more comprehensive understanding of this subject may then help to identify important cardioprotective strategies to improve the number and quality of donor hearts.

Diagnosis of renal transplant rejection: Banff classification and beyond

Diagnosis of renal transplant rejection is dependent on interpretation of renal allograft biopsies. The Banff Classification of Allograft Pathology, which was developed as a standardized working classification system in 1991, has contributed to the standardization of definitions for histologic injuries resulting from renal allograft rejections and provided a universal grading system for assessing these injuries. It has also helped to provide insight into the underlying pathogenic mechanisms that contribute to transplant rejection. In addition to histological and immunologic parameters, molecular tools are now being used to facilitate the diagnosis of rejection. In this review, I will discuss morphologic features of renal transplant rejections as well as major revisions and pitfalls of the Banff classification system, and provide future perspectives.

Urinary Peptidomic Biomarkers in Kidney Diseases

In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a "liquid biopsy" to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases.

Proteomics for Clinical Assessment of Kidney Disease

Kidney disease is one of the fastest growing causes of death worldwide, disclosing an unmet clinical need for early diagnosis and optimized risk stratification that allows high risk patient selection for clinical trials and for more intensive nephroprotective interventions in the clinic. The current issue of PROTEOMICS-Clinical Applications contains four manuscripts that explore different aspects of clinical proteomics implementation in the context of acute kidney injury, chronic kidney disease and, more specifically, diabetic kidney disease, and kidney transplantation from a diagnostic and risk stratification point of view. Overall, the evidence discussed suggests that chronic kidney disease is an example where clinical proteomics has become a valuable tool ready for clinical implementation, expected to have a major impact in patient management.