Orthogonal Comparison of Molecular Signatures of Kidney Transplants With Subclinical and Clinical Acute Rejection: Equivalent Performance Is Agnostic to Both Technology and Platform

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.

Review of prognostic factors for kidney transplant survival

Transplantation is the most effective treatment for end-stage chronic kidney disease, as this procedure prolongs and improves the patient's quality of life. One of the key problems is the risk of graft rejection. The purpose of this research was to identify and analyse prognostic factors that will prevent rejection. In particular, the prognostic factors grouped by methods of synthesis, generalisation and statistical processing with calculation and graphical representation of hazard ratio and correlation coefficient were grouped, namely: age of donor and recipient, time of cold kidney ischaemia, duration of preoperative dialysis, body mass index, presence of concomitant diseases (diabetes mellitus, hypertension), primary causes causing transplantation. Several molecular genetic and biochemical prognostic markers (transcription factors, immunocompetent cell signalling and receptors, cytostatin C, creatinine, citrate, lactate, etc.) are annotated. It has been demonstrated that creatinine reduction rate determines the risk of rejection, displaying the dynamics of cystatin C and creatinine changes in the postoperative period. Young recipients who underwent prolonged preoperative dialysis were identified as having the highest risk of rejection. Diabetes and hypertension bear a non-critical but commensurately equal risk of rejection. The survival rate of the graft is better when transplanted from a living donor than from a deceased donor. A correlation between cold ischaemia time, body mass index and the probability of graft failure has been proven, namely, the greater the donor and recipient body mass index and the longer the cold ischaemia time, the lower the chance of successful long-term organ acclimation. The data obtained can be used as prognostic factors for graft accommodation at different intervals after surgery.

Subclinical rejection-free diagnostic after kidney transplantation using blood gene expression

We previously established a six-gene-based blood score associated with operational tolerance in kidney transplantation which was decreased in patients developing anti-HLA donor-specific antibodies (DSA). Herein, we aimed to confirm that this score is associated with immunological events and risk of rejection. We measured this using quantitative PCR (qPCR) and NanoString methods from an independent multicenter cohort of 588 kidney transplant recipients with paired blood samples and biopsies at one year after transplantation validating its association with pre-existing and de novo DSA. From 441 patients with protocol biopsy, there was a significant decrease of the score of tolerance in 45 patients with biopsy-proven subclinical rejection (SCR), a major threat associated with pejorative allograft outcomes that prompted an SCR score refinement. This refinement used only two genes, AKR1C3 and TCL1A, and four clinical parameters (previous experience of rejection, previous transplantation, sex of recipient and tacrolimus uptake). This refined SCR score was able to identify patients unlikely to develop SCR with a C-statistic of 0.864 and a negative predictive value of 98.3%. The SCR score was validated in an external laboratory, with two methods (qPCR and NanoString), and on 447 patients from an independent and multicenter cohort. Moreover, this score allowed reclassifying patients with discrepancies between the DSA presence and the histological diagnosis of antibody mediated rejection unlike kidney function. Thus, our refined SCR score could improve detection of SCR for closer and noninvasive monitoring, allowing early treatment of SCR lesions notably for patients DSA-positive and during lowering of immunosuppressive treatment.

Biomarkers of alloimmune events in pediatric kidney transplantation

Alloimmune events such as the development of de novo donor-specific antibody (dnDSA), T cell-mediated rejection (TCMR), and antibody-mediated rejection (ABMR) are the primary contributors to kidney transplant failure in children. For decades, a creatinine-based estimated glomerular filtration rate (eGFR) has been the non-invasive gold standard biomarker for detecting clinically significant alloimmune events, but it suffers from low sensitivity and specificity, especially in smaller children and older allografts. Many clinically "stable" children (based on creatinine) will have alloimmune events known as "subclinical acute rejection" (based on biopsy) that merely reflect the inadequacy of creatinine-based estimates for alloimmune injury rather than a distinct phenotype from clinical rejection with allograft dysfunction. The poor biomarker performance of creatinine leads to many unnecessary surveillance and for-cause biopsies that could be avoided by integrating non-invasive biomarkers with superior sensitivity and specificity into current clinical paradigms. In this review article, we will present and appraise the current state-of-the-art in monitoring for alloimmune events in pediatric kidney transplantation. We will first discuss the current clinical standards for assessing the presence of alloimmune injury and predicting long-term outcomes. We will review principles of biomarker medicine and the application of comprehensive metrics to assess the performance of a given biomarker against the current gold standard. We will then highlight novel blood- and urine-based biomarkers (with special emphasis on pediatric biomarker studies) that have shown superior diagnostic and prognostic performance to the current clinical standards including creatinine-based eGFR. Finally, we will review some of the barriers to translating this research and implementing emerging biomarkers into common clinical practice, and present a transformative approach to using multiple biomarker platforms at different times to optimize the detection and management of critical alloimmune events in pediatric kidney transplant recipients.

Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.

The Future Role of Machine Learning in Clinical Transplantation

The use of artificial intelligence and machine learning (ML) has revolutionized our daily lives and will soon be instrumental in healthcare delivery. The rise of ML is due to multiple factors: increasing access to massive datasets, exponential increases in processing power, and key algorithmic developments that allow ML models to tackle increasingly challenging questions. Progressively more transplantation research is exploring the potential utility of ML models throughout the patient journey, although this has not yet widely transitioned into the clinical domain. In this review, we explore common approaches used in ML in solid organ clinical transplantation and consider opportunities for ML to help clinicians and patients. We discuss ways in which ML can aid leverage of large complex datasets, generate cutting-edge prediction models, perform clinical image analysis, discover novel markers in molecular data, and fuse datasets to generate novel insights in modern transplantation practice. We focus on key areas in transplantation in which ML is driving progress, explore the future potential roles of ML, and discuss the challenges and limitations of these powerful tools.

A Rejection Gene Expression Score in Indication and Surveillance Biopsies Is Associated with Graft Outcome

Rejection-associated gene expression has been characterized in renal allograft biopsies for cause. The aim is to evaluate rejection gene expression in subclinical rejection and in biopsies with borderline changes or interstitial fibrosis and tubular atrophy (IFTA). We included 96 biopsies. Most differentially expressed genes between normal surveillance biopsies (n = 17) and clinical rejection (n = 12) were obtained. A rejection-associated gene (RAG) score was defined as its geometric mean. The following groups were considered: (a) subclinical rejection (REJ-S, n = 6); (b) borderline changes in biopsies for cause (BL-C, n = 13); (c) borderline changes in surveillance biopsies (BL-S, n = 12); (d) IFTA in biopsies for cause (IFTA-C, n = 20); and (e) IFTA in surveillance biopsies (IFTA-S, n = 16). The outcome variable was death-censored graft loss or glomerular filtration rate decline ≥ 30 % at 2 years. A RAG score containing 109 genes derived from normal and clinical rejection (area under the curve, AUC = 1) was employed to classify the study groups. A positive RAG score was observed in 83% REJ-S, 38% BL-C, 17% BL-S, 25% IFTA-C, and 5% IFTA-S. A positive RAG score was an independent predictor of graft outcome from histological diagnosis (hazard ratio: 3.5 and 95% confidence interval: 1.1–10.9; p = 0.031). A positive RAG score predicts graft outcome in surveillance and for cause biopsies with a less severe phenotype than clinical rejection.

DSA Are Associated With More Graft Injury, More Fibrosis, and Upregulation of Rejection-associated Transcripts in Subclinical Rejection

BACKGROUND

Subclinical T cell-mediated rejection (subTCMR) is commonly found after liver transplantation and has a good short-term prognosis, even when it is left untreated. Donor-specific antibodies (DSA) are putatively associated with a worse prognosis for recipient and graft after liver transplantation.

METHODS

To assess the immune regulation in subTCMR grafts, gene expression of 93 transcripts for graft injury, tolerance, and immune regulation was analyzed in 77 biopsies with "no histologic rejection" (NHR; n = 25), "clinical TCMR" (cTMCR; n = 16), and subTCMR (n = 36). In addition, all available subTCMR biopsies (n = 71) were tested for DSA with bead assays.

RESULTS

SubTCMR showed heterogeneous and intermediate expression profiles of transcripts that were upregulated in cTCMR. Graft gene expression suggested a lower activation of effector lymphocytes and a higher activation of regulatory T cells in grafts with subTCMR compared to cTCMR. DSA positivity in subTCMR was associated with histological evidence of more severe graft inflammation and fibrosis. This more severe DSA+ associated graft injury in subTCMR was converged with an upregulation of cTCMR-associated transcripts. In nonsupervised analysis, DSA positive subTCMR mostly clustered together with cTCMR, while DSA negative subTCMR clustered together with NHR.

CONCLUSIONS

T cell-mediated rejection seems to form a continuum of alloimmune activation. Although subTCMR exhibited less expression of TCMR-associated transcript, DSA positivity in subTCMR was associated with an upregulation of rejection-associated transcripts. The identification of DSA positive subclinical rejection might help to define patients with more inflammation in the graft and development of fibrosis.

Key driver genes as potential therapeutic targets in renal allograft rejection

Acute rejection (AR) in renal transplantation is an established risk factor for reduced allograft survival. Molecules with regulatory control among immune pathways of AR that are inadequately suppressed, despite standard-of-care immunosuppression, could serve as important targets for therapeutic manipulation to prevent rejection. Here, an integrative, network-based computational strategy incorporating gene expression and genotype data of human renal allograft biopsy tissue was applied, to identify the master regulators - the key driver genes (KDGs) - within dysregulated AR pathways. A 982-meta-gene signature with differential expression in AR versus non-AR was identified from a meta-analysis of microarray data from 735 human kidney allograft biopsy samples across 7 data sets. Fourteen KDGs were derived from this signature. Interrogation of 2 publicly available databases identified compounds with predicted efficacy against individual KDGs or a key driver-based gene set, respectively, which could be repurposed for AR prevention. Minocycline, a tetracycline antibiotic, was chosen for experimental validation in a murine cardiac allograft model of AR. Minocycline attenuated the inflammatory profile of AR compared with controls and when coadministered with immunosuppression prolonged graft survival. This study demonstrates that a network-based strategy, using expression and genotype data to predict KDGs, assists target prioritization for therapeutics in renal allograft rejection.

Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection

Introduction

Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes.

Methods

We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell-mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts.

Results

We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples.

Conclusions

This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process.

Activity-based protein profiling guided identification of urine proteinase 3 activity in subclinical rejection after renal transplantation

Background

The pathophysiology of subclinical versus clinical rejection remains incompletely understood given their equivalent histological severity but discordant graft function. The goal was to evaluate serine hydrolase enzyme activities to explore if there were any underlying differences in activities during subclinical versus clinical rejection.

Methods

Serine hydrolase activity-based protein profiling (ABPP) was performed on the urines of a case control cohort of patients with biopsy confirmed subclinical or clinical transplant rejection. In-gel analysis and affinity purification with mass spectrometry were used to demonstrate and identify active serine hydrolase activity. An assay for proteinase 3 (PR3/PRTN3) was adapted for the quantitation of activity in urine.

Results

In-gel ABPP profiles suggested increased intensity and diversity of serine hydrolase activities in urine from patients undergoing subclinical versus clinical rejection. Serine hydrolases (n = 30) were identified by mass spectrometry in subclinical and clinical rejection patients with 4 non-overlapping candidates between the two groups (i.e. ABHD14B, LTF, PR3/PRTN3 and PRSS12). Western blot and the use of a specific inhibitor confirmed the presence of active PR3/PRTN3 in samples from patients undergoing subclinical rejection. Analysis of samples from normal donors or from several serial post-transplant urines indicated that although PR3/PRTN3 activity may be highly associated with low-grade subclinical inflammation, the enzyme activity was not restricted to this patient group.

Conclusions

There appear to be limited qualitative and quantitative differences in serine hydrolase activity in patients with subclinical versus clinical renal transplant rejection. The majority of enzymes identified were present in samples from both groups implying that in-gel quantitative differences may largely relate to the activity status of shared enzymes. However qualitative compositional differences were also observed indicating differential activities. The PR3/PRTN3 analyses indicate that the activity status of urine in transplant patients is dynamic possibly reflecting changes in the underlying processes in the transplant. These data suggest that differential serine hydrolase pathways may be active in subclinical versus clinical rejection which requires further exploration in larger patient cohorts. Although this study focused on PR3/PRTN3, this does not preclude the possibility that other enzymes may play critical roles in the rejection process.

An age-independent gene signature for monitoring acute rejection in kidney transplantation

Acute rejection (AR) remains a significant problem that negatively impacts long-term renal allograft survival. Numerous therapies are used to prevent AR that differ by center and recipient age. This variability confounds diagnostic methods. Methods: To develop an age-independent gene signature for AR effective across a broad array of immunosuppressive regimens, we compiled kidney transplant biopsy (n=1091) and peripheral blood (n=392) gene expression profiles from 12 independent public datasets. After removing genes differentially expressed in pediatric and adult patients, we compared gene expression profiles from biopsy and peripheral blood samples of patients with AR to those who were stable (STA), using Mann-Whitney U Tests with validation in independent testing datasets. We confirmed this signature in pediatric and adult patients (42 AR and 47 STA) from our institutional biorepository. Results: We identified a novel age-independent gene network that identified AR from both kidney and blood samples. We developed a 90-probe set signature targeting 76 genes that differentiated AR from STA and found an 8 gene subset (DIP2C, ENOSF1, FBXO21, KCTD6, PDXDC1, REXO2, HLA-E, and RAB31) that was associated with AR. Conclusion: We used publicly available datasets to create a gene signature of AR that identified AR irrespective of immunosuppression regimen or recipient age. This study highlights a novel model to screen and validate biomarkers across multiple treatment regimens.

Molecular Pathways Underlying Adaptive Repair of the Injured Kidney: Novel Donation After Cardiac Death and Acute Kidney Injury Platforms

OBJECTIVE

To test the hypothesis that gene expression profiling in peripheral blood from patients who have undergone kidney transplantation (KT) will provide mechanistic insights regarding graft repair and regeneration.

BACKGROUND

Renal grafts obtained from living donors (LD) typically function immediately, whereas organs from donation after cardiac death (DCD) or acute kidney injury (AKI) donors may experience delayed function with eventual recovery. Thus, recipients of LD, DCD, and AKI kidneys were studied to provide a more complete understanding of the molecular basis for renal recovery.

METHODS

Peripheral blood was collected from LD and DCD/AKI recipients before transplant and throughout the first 30 days thereafter. Total RNA was isolated and assayed on whole genome microarrays.

RESULTS

Comparison of longitudinal gene expression between LD and AKI/DCD revealed 2 clusters, representing 141 differentially expressed transcripts. A subset of 11 transcripts was found to be differentially expressed in AKI/DCD versus LD. In all recipients, the most robust gene expression changes were observed in the first day after transplantation. After day 1, gene expression profiles differed depending upon the source of the graft. In patients receiving LD grafts, the expression of most genes did not remain markedly elevated beyond the first day post-KT. In the AKI/DCD groups, elevations in gene expression were maintained for at least 5 days post-KT. In all recipients, the pattern of coordinate gene overexpression subsided by 28 to 30 days.

CONCLUSIONS

Gene expression in peripheral blood of AKI/DCD recipients offers a novel platform to understand the potential mechanisms and timing of kidney repair and regeneration after transplantation.

Discrepancy analysis comparing molecular and histology diagnoses in kidney transplant biopsies

Discrepancy analysis comparing two diagnostic platforms offers potential insights into both without assuming either is always correct. Having optimized the Molecular Microscope Diagnostic System (MMDx) in renal transplant biopsies, we studied discrepancies within MMDx (reports and sign-out comments) and between MMDx and histology. Interpathologist discrepancies have been documented previously and were not assessed. Discrepancy cases were classified as "clear" (eg, antibody-mediated rejection [ABMR] vs T cell-mediated rejection [TCMR]), "boundary" (eg, ABMR vs possible ABMR), or "mixed" (eg, Mixed vs ABMR). MMDx report scores showed 99% correlations; sign-out interpretations showed 7% variation between observers, all located around boundaries. Histology disagreed with MMDx in 37% of biopsies, including 315 clear discrepancies, all with implications for therapy. Discrepancies were distributed widely in all histology diagnoses but increased in some scenarios; for example, histology TCMR contained 14% MMDx ABMR and 20% MMDx no rejection. MMDx usually gave unambiguous diagnoses in cases with ambiguous histology, for example, borderline and transplant glomerulopathy. Histology lesions or features associated with more frequent discrepancies (eg, tubulitis, arteritis, and polyomavirus nephropathy) were not associated with increased MMDx uncertainty, indicating that MMDx can clarify biopsies with histologic ambiguity. The patterns of histology-MMDx discrepancies highlight specific histology diagnoses in which MMDx assessment should be considered for guiding therapy.

Molecular Assessment of Kidney Allografts: Are We Closer to a Daily Routine?

Kidney allograft pathology assessment has been traditionally based on clinical and histological criteria. Despite improvements in Banff histological classification, the diagnostics in particular cases is problematic reflecting a complex pathogenesis of graft injuries. With the advent of molecular techniques, polymerase-chain reaction, oligo- and microarray technologies allowed to study molecular phenotypes of graft injuries, especially acute and chronic rejections. Moreover, development of the molecular microscope diagnostic system (MMDx) to assess kidney graft biopsies, represents the first clinical application of a microarray-based method in transplantation. Whether MMDx may replace conventional pathology is the subject of ongoing research, however this platform is particularly useful in complex histological findings and may help clinicians to guide the therapy.

Quantitative Proteomics for Monitoring Renal Transplant Injury

PURPOSE

This study is aimed at developing a molecular diagnostics platform to enhance the interpretation of renal allograft biopsies using quantitative proteomic profiling of formalin-fixed and paraffin-embedded (FFPE) specimens.

EXPERIMENTAL DESIGN

A quantitative proteomics platform composed of 1) an optimized FFPE protein sample preparation method, 2) a tandem mass tag TMT10-plex-based proteomic workflow, and 3) a systematic statistical analysis pipeline to reveal differentially expressed proteins has been developed. This platform is then tested on a small sample set (five samples per phenotype) to reveal proteomic signatures that can differentiate T-cell mediated rejection (TCMR) and polyomavirus BK nephropathy (BKPyVN) from healthy functionally stable kidney tissue (STA).

RESULTS

Among 2798 quantified proteins, the expression levels of 740 BKPyVN and 638 TCMR associated proteins are significantly changed compared to STA specimens. Principal component analysis demonstrated good segregation of all three phenotypes investigated. Protein detection and quantitation are highly reproducible: replicate comparative analyses demonstrated 71-84% overlap of detected proteins, and the coefficient of variation for protein measurements is <15% in triplicate liquid chromatography-tandem mass spectrometry runs.

CONCLUSIONS AND CLINICAL RELEVANCE

Quantitative proteomics can be applied to archived FFPE specimens to differentiate different causes of renal allograft injury.

Peripheral blood transcriptome analysis and development of classification model for diagnosing antibody-mediated rejection vs accommodation in ABO-incompatible kidney transplant

The major obstacle to successful ABO blood group-incompatible kidney transplantation (ABOi KT) is antibody-mediated rejection (AMR). This study aimed to investigate transcriptional profiles through RNA sequencing and develop a minimally invasive diagnostic tool for discrimination between accommodation and early acute AMR in ABOi KT. Twenty-eight ABOi KT patients were selected: 18 with accommodation and 10 with acute AMR at the 10th day posttransplant protocol biopsy. Complete transcriptomes of their peripheral blood were analyzed by RNA sequencing. Candidate genes were selected by bioinformatics analysis, validated with quantitative polymerase chain reaction, and used to develop a classification model to diagnose accommodation. A total of 1385 genes were differentially expressed in accommodation compared with in AMR with P-adjusted < .05. Functional annotation and gene set enrichment analysis identified several immune-related and immunometabolic pathways. A 5-gene classification model including COX7A2L, CD69, CD14, CFD, and FOXJ3 was developed by logistic regression analysis. The model was further validated with an independent cohort and discriminated between accommodation and AMR with 92.7% sensitivity, 85.7% specificity, and 91.7% accuracy. Our study suggests that a classification model based on peripheral blood transcriptomics may allow minimally invasive diagnosis of acute AMR vs accommodation and subsequent patient-tailored immunosuppression in ABOi KT.

Discovery and cross-validation of peripheral blood and renal biopsy gene expression signatures from ethnically diverse kidney transplant populations

We determined peripheral blood (PB) and biopsy (Bx) RNA expression signatures in a Brazilian and US cohort of kidney transplant patients. Phenotypes assigned by precise histology were: acute rejection (AR), interstitial fibrosis/tubular atrophy/chronic rejection (CR), excellent functioning transplants (TX), and glomerulonephritis recurrence (GN). Samples were analyzed on microarrays and profiles from each cohort were cross-validated on the other cohort with similar phenotypes. We discovered signatures for each tissue: (1) AR vs TX, (2) CR vs TX, and (3) GN vs TX using the Random Forests algorithm. We validated biopsies signatures of AR vs TX (area under the curve [AUC] 0.97) and CR vs TX (AUC 0.87). We also validated both PB and Bx signatures of AR vs TX and CR vs TX with varying degrees of accuracy. Several biological pathways were shared between AR and CR, suggesting similar rejection mechanisms in these 2 clinical phenotypes. Thus, we identified gene expression signatures for AR and CR in transplant patients and validated them in independent cohorts of significantly different racial/ethnic backgrounds. These results reveal that there are strong unifying immune mechanisms driving transplant diseases and identified in the signatures discovered in each cohort, suggesting that molecular diagnostics across populations are feasible despite ethnic and environmental differences.

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant

Noninvasive biomarkers are needed to monitor stable patients after kidney transplant (KT), because subclinical acute rejection (subAR), currently detectable only with surveillance biopsies, can lead to chronic rejection and graft loss. We conducted a multicenter study to develop a blood-based molecular biomarker for subAR using peripheral blood paired with surveillance biopsies and strict clinical phenotyping algorithms for discovery and validation. At a predefined threshold, 72% to 75% of KT recipients achieved a negative biomarker test correlating with the absence of subAR (negative predictive value: 78%-88%), while a positive test was obtained in 25% to 28% correlating with the presence of subAR (positive predictive value: 47%-61%). The clinical phenotype and biomarker independently and statistically correlated with a composite clinical endpoint (renal function, biopsy-proved acute rejection, ≥grade 2 interstitial fibrosis, and tubular atrophy), as well as with de novo donor-specific antibodies. We also found that <50% showed histologic improvement of subAR on follow-up biopsies despite treatment and that the biomarker could predict this outcome. Our data suggest that a blood-based biomarker that reduces the need for the indiscriminate use of invasive surveillance biopsies and that correlates with transplant outcomes could be used to monitor KT recipients with stable renal function, including after treatment for subAR, potentially improving KT outcomes.

Diagnosis of T-cell-mediated kidney rejection in formalin-fixed, paraffin-embedded tissues using RNA-Seq-based machine learning algorithms

Molecular diagnosis is being increasingly used in transplant pathology to render more objective and quantitative determinations that also provide mechanistic and prognostic insights. This study performed RNA-Seq on biopsies from kidneys with stable function (STA) and biopsies with classical findings of T-cell-mediated rejection (TCMR). Machine learning tools were used to develop prediction models for distinguishing TCMR and STA samples using the top genes identified by DSeq2. The prediction models were tested on 703 biopsies with Affymetrix chip gene expression profiles available in the public domain. Linear discriminant analysis predicted TCMR in 55 of 67 biopsies labeled TCMR, and 65 of 105 biopsies designated as antibody-mediated rejection. The random forest and support vector machine models showed comparable performance. These data illustrate the feasibility of using RNA-Seq for molecular diagnosis of TCMR in formalin-fixed tissue. Application of the derived diagnostic algorithms to publicly available data sets demonstrates frequent coexistence of TCMR in biopsies designated as antibody-mediated rejection. This underrecognition of TCMR in renal allograft biopsies has significant implications with respect to patient care.

Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts

Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

Reperfusion Activates AP-1 and Heat Shock Response in Donor Kidney Parenchyma after Warm Ischemia

Utilization of kidneys from extended criteria donors leads to an increase in average warm ischemia time (WIT), which is associated with larger degrees of ischemia-reperfusion injury (IRI). Kidney resuscitation by extracorporeal perfusion in situ allows up to 60 minutes of asystole after the circulatory death. Molecular studies of kidney grafts from human donors with critically expanded WIT are warranted. Transcriptomes of two human kidneys from two different donors were profiled after 35-45 minutes of WIT and after 120 minutes of normothermic perfusion and compared. Baseline gene expression patterns in ischemic grafts display substantial intrinsic differences. IRI does not lead to substantial change in overall transcription landscape but activates a highly connected protein network with hubs centered on Jun/Fos/ATF transcription factors and HSP1A/HSPA5 heat shock proteins. This response is regulated by positive feedback. IRI networks are enriched in soluble proteins and biofluids assayable substances, thus, indicating feasibility of the longitudinal, minimally invasive assessment in vivo. Mapping of IRI related molecules in ischemic and reperfused kidneys provides a rationale for possible organ conditioning during machine assisted ex vivo normothermic perfusion. A study of natural diversity of the transcriptional landscapes in presumably normal, transplantation-suitable human organs is warranted.

Carpe diem-Time to transition from empiric to precision medicine in kidney transplantation

The current immunosuppressive pipeline in kidney transplantation is limited. In part, this is due to excellent one-year allograft outcomes with the current standard of care (ie, calcineurin inhibitor in combination with anti-proliferative agents). Despite this success, a recent Federal government-sponsored systematic review has identified gaps/limits in the evidence of what constitutes optimal calcineurin inhibitor use in the short- and long-term. Moreover, recent empiric approaches to minimize/withdraw/convert from calcineurin inhibitors have come with the price of increased alloreactivity. As the time horizon to replace calcineurin inhibitors on a global scale may be distant, the transplant community should seize the opportunity to develop ways to personalize calcineurin inhibitor immunosuppression to the individual-transitioning from empiricism to precision. The authors argue in this viewpoint that the path to precision will require measures capable of detecting subclinical alloreactivity to define adequacy of immunosuppression, as well as novel genetic analytics to accurately define alloimmune risk at the individual level-both approaches will require validation in clinical trials.

Late graft failure after kidney transplantation as the consequence of late versus early events

Beyond the first posttransplant year, 3% of kidney transplants fail annually. In a prospective, multicenter cohort study, we tested the relative impact of early versus late events on risk of long-term death-censored graft failure (DCGF). In grafts surviving at least 90 days, early events (acute rejection [AR] and delayed graft function [DGF] before day 90) were recorded; serum creatinine (Cr) at day 90 was defined as baseline. Thereafter, a 25% rise in serum Cr or new-onset proteinuria triggered graft biopsy (index biopsy, IBx), allowing comparison of risk of DCGF associated with early events (AR, DGF, baseline serum Cr >2.0 mg/dL) to that associated with later events (IBx). Among 3678 patients followed for 4.7 ± 1.9 years, 753 (20%) had IBx at a median of 15.3 months posttransplant. Early AR (HR = 1.77, P < .001) and elevated Cr at Day 90 (HR = 2.56, P < .0001) were associated with increased risk of DCGF; however, later-onset dysfunction requiring IBx had far greater impact (HR = 13.8, P < .0001). At 90 days, neither clinical characteristics nor early events distinguished those who subsequently did or did not undergo IBx or suffer DCGF. To improve long-term kidney allograft survival, management paradigms should promote prompt diagnosis and treatment of both early and later events.

Biomarkers for posttransplantation outcomes

During the last decade, the development of biomarkers for the complications seen after allogeneic hematopoietic stem cell transplantation has expanded tremendously, with the most progress having been made for acute graft-versus-host disease (aGVHD), a common and often fatal complication. Although many factors are known to determine transplant outcome (including the age of the recipient, comorbidity, conditioning intensity, donor source, donor-recipient HLA compatibility, conditioning regimen, posttransplant GVHD prophylaxis), they are incomplete guides for predicting outcomes. Thanks to the advances in genomics, transcriptomics, proteomics, and cytomics technologies, blood biomarkers have been identified and validated for us in promising diagnostic tests, prognostic tests stratifying for future occurrence of aGVHD, and predictive tests for responsiveness to GVHD therapy and nonrelapse mortality. These biomarkers may facilitate timely and selective therapeutic intervention. However, such blood tests are not yet available for routine clinical care. This article provides an overview of the candidate biomarkers for clinical evaluation and outlines a path from biomarker discovery to first clinical correlation, to validation in independent cohorts, to a biomarker-based clinical trial, and finally to general clinical application. This article focuses on biomarkers discovered with a large-scale proteomics platform and validated with the same reproducible assay in at least 2 independent cohorts with sufficient sample size according to the 2014 National Institutes of Health consensus on biomarker criteria, as well as on biomarkers as tests for risk stratification of outcomes, but not on their pathophysiologic contributions, which have been reviewed recently.

Review: The transcripts associated with organ allograft rejection

The molecular mechanisms operating in human organ transplant rejection are best inferred from the mRNAs expressed in biopsies because the corresponding proteins often have low expression and short half-lives, while small non-coding RNAs lack specificity. Associations should be characterized in a population that rigorously identifies T cell-mediated (TCMR) and antibody-mediated rejection (ABMR). This is best achieved in kidney transplant biopsies, but the results are generalizable to heart, lung, or liver transplants. Associations can be universal (all rejection), TCMR-selective, or ABMR-selective, with universal being strongest and ABMR-selective weakest. Top universal transcripts are IFNG-inducible (eg, CXCL11 IDO1, WARS) or shared by effector T cells (ETCs) and NK cells (eg, KLRD1, CCL4). TCMR-selective transcripts are expressed in activated ETCs (eg, CTLA4, IFNG), activated (eg, ADAMDEC1), or IFNG-induced macrophages (eg, ANKRD22). ABMR-selective transcripts are expressed in NK cells (eg, FGFBP2, GNLY) and endothelial cells (eg, ROBO4, DARC). Transcript associations are highly reproducible between biopsy sets when the same rejection definitions, case mix, algorithm, and technology are applied, but exact ranks will vary. Previously published rejection-associated transcripts resemble universal and TCMR-selective transcripts due to incomplete representation of ABMR. Rejection-associated transcripts are never completely rejection-specific because they are shared with the stereotyped response-to-injury and innate immunity.