The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury

Key genes and immune pathways in T-cell mediated rejection post-liver transplantation identified via integrated RNA-seq and machine learning

Liver transplantation is the definitive treatment for end-stage liver disease, yet T-cell mediated rejection (TCMR) remains a major challenge. This study aims to identify key genes associated with TCMR and their potential biological processes and mechanisms. The GSE145780 dataset was subjected to differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to pinpoint key genes associated with TCMR. Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and regulatory networks were constructed to ascertain the biological relevance of these genes. Expression validation was performed using single-cell RNA-seq (scRNA-seq) data and liver biopsy tissues from patients. We identified 5 key genes (ITGB2, FCER1G, IL-18, GBP1, and CD53) that are associated with immunological functions, such as chemotactic activity, antigen processing, and T cell differentiation. GSEA highlighted enrichment in chemokine signaling and antigen presentation pathways. A lncRNA-miRNA-mRNA network was delineated, and drug target prediction yielded 26 potential drugs. Evaluation of expression levels in non-rejection (NR) and TCMR groups exhibited significant disparities in T cells and myeloid cells. Tissue analyses from patients corroborated the upregulation of GBP1, IL-18, CD53, and FCER1G in TCMR cases. Through comprehensive analysis, this research has identified 4 genes intimately connected with TCMR following liver transplantation, shedding light on the underlying immune activation pathways and suggesting putative targets for therapeutic intervention.

Contemporary and Emerging MRI Strategies for Assessing Kidney Allograft Complications: Arterial Stenosis and Parenchymal Injury, From the AJR Special Series on Imaging of Fibrosis

MRI plays an important role in the evaluation of kidney allografts for vascular complications as well as parenchymal insults. Transplant renal artery stenosis, the most common vascular complication of kidney transplant, can be evaluated by MRA using gadolinium and nongadolinium contrast agents as well as by unenhanced MRA techniques. Parenchymal injury occurs through a variety of pathways, including graft rejection, acute tubular injury, BK polyomavirus infection, drug-induced interstitial nephritis, and pyelonephritis. Investigational MRI techniques have sought to differentiate among these causes of dysfunction as well as to assess the degree of interstitial fibrosis or tubular atrophy (IFTA)-the common end pathway for all of these processes-which is currently evaluated by invasively obtained core biopsies. Some of these MRI sequences have shown promise in not only assessing the cause of parenchymal injury but also assessing IFTA noninvasively. This review describes current clinically used MRI techniques and previews promising investigational MRI techniques for assessing complications of kidney grafts.

Proteomic analysis investigating kidney transplantation outcomes- a scoping review

BACKGROUND

Kidney transplantation is the optimal treatment option for most patients with end-stage kidney disease given the significantly lower morbidity and mortality rates compared to remaining on dialysis. Rejection and graft failure remain common in transplant recipients with limited improvement in long-term transplant outcomes despite therapeutic advances. There is an unmet need in the development of non-invasive biomarkers that specifically monitor graft function and predict transplant pathologies that affect outcomes. Despite the potential of proteomic investigatory approaches, up to now, no candidate biomarkers of sufficient sensitivity or specificity have translated into clinical use. The aim of this review was to collate and summarise protein findings and protein pathways implicated in the literature to date, and potentially flag putative biomarkers worth validating in independent patient cohorts.

METHODS

This review followed the Joanna Briggs' Institute Methodology for a scoping review. MedlineALL, Embase, Web of Science Core Collection, Scopus and Google Scholar databases were searched from inception until December 2022. Abstract and full text review were undertaken independently by two reviewers. Data was collated using a pre-designed data extraction tool.

RESULTS

One hundred one articles met the inclusion criteria. The majority were single-centre retrospective studies of small sample size. Mass spectrometry was the most used technique to evaluate differentially expressed proteins between diagnostic groups and studies identified various candidate biomarkers such as immune or structural proteins.

DISCUSSION

Putative immune or structural protein candidate biomarkers have been identified using proteomic techniques in multiple sample types including urine, serum and fluid used to perfuse donor kidneys. The most consistent findings implicated proteins associated with tubular dysfunction and immunological regulatory pathways such as leukocyte trafficking. However, clinical translation and adoption of candidate biomarkers is limited, and these will require comprehensive evaluation in larger prospective, multicentre trials.

Allograft tissue under the microscope: only the beginning

PURPOSE OF REVIEW

To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema.

RECENT FINDINGS

Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation.

SUMMARY

Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.

SLAMF8 Participates in Acute Renal Transplant Rejection via TLR4 Pathway on Pro-Inflammatory Macrophages

Background

Acute rejection (AR) in kidney transplantation is an established risk factor that reduces the survival rate of allografts. Despite standard immunosuppression, molecules with regulatory control in the immune pathway of AR can be used as important targets for therapeutic operations to prevent rejection.

Methods

We downloaded the microarray data of 15 AR patients and 37 non-acute rejection (NAR) patients from Gene Expression Omnibus (GEO). Gene network was constructed, and genes were classified into different modules using weighted gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cytoscape were applied for the hub genes in the most related module to AR. Different cell types were explored by xCell online database and single-cell RNA sequencing. We also validated the SLAMF8 and TLR4 levels in Raw264.7 and human kidney tissues of TCMR.

Results

A total of 1,561 differentially expressed genes were filtered. WGCNA was constructed, and genes were classified into 12 modules. Among them, the green module was most closely associated with AR. These genes were significantly enriched in 20 pathway terms, such as cytokine–cytokine receptor interaction, chemokine signaling pathway, and other important regulatory processes. Intersection with GS > 0.4, MM > 0.9, the top 10 MCC values and DEGs in the green module, and six hub genes (DOCK2, NCKAP1L, IL2RG, SLAMF8, CD180, and PTPRE) were identified. Their expression levels were all confirmed to be significantly elevated in AR patients in GEO, Nephroseq, and quantitative real-time PCR (qRT-PCR). Single-cell RNA sequencing showed that AR patient had a higher percentage of native T, CD1C+_B DC, NKT, NK, and monocytes in peripheral blood mononuclear cells (PBMCs). Xcell enrichment scores of 20 cell types were significantly different (p<0.01), mostly immune cells, such as B cells, CD4+ Tem, CD8+ T cells, CD8+ Tcm, macrophages, M1, and monocytes. GSEA suggests that highly expressed six hub genes are correlated with allograft rejection, interferon γ response, interferon α response, and inflammatory response. In addition, SLAMF8 is highly expressed in human kidney tissues of TCMR and in M1 phenotype macrophages of Raw264.7 cell line WGCNA accompanied by high expression of TLR4.

Conclusion

This study demonstrates six hub genes and functionally enriched pathways related to AR. SLAMF8 is involved in the M1 macrophages via TLR4, which contributed to AR process.

Surfing the Big Data Wave: Omics Data Challenges in Transplantation

In both research and care, patients, caregivers, and researchers are facing a leap forward in the quantity of data that are available for analysis and interpretation, marking the daunting "big data era." In the biomedical field, this quantitative shift refers mostly to the -omics that permit measuring and analyzing biological features of the same type as a whole. Omics studies have greatly impacted transplantation research and highlighted their potential to better understand transplant outcomes. Some studies have emphasized the contribution of omics in developing personalized therapies to avoid graft loss. However, integrating omics data remains challenging in terms of analytical processes. These data come from multiple sources. Consequently, they may contain biases and systematic errors that can be mistaken for relevant biological information. Normalization methods and batch effects have been developed to tackle issues related to data quality and homogeneity. In addition, imputation methods handle data missingness. Importantly, the transplantation field represents a unique analytical context as the biological statistical unit is the donor-recipient pair, which brings additional complexity to the omics analyses. Strategies such as combined risk scores between 2 genomes taking into account genetic ancestry are emerging to better understand graft mechanisms and refine biological interpretations. The future omics will be based on integrative biology, considering the analysis of the system as a whole and no longer the study of a single characteristic. In this review, we summarize omics studies advances in transplantation and address the most challenging analytical issues regarding these approaches.

Advances in single-cell sequencing: insights from organ transplantation

Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.

Molecular Analysis of Renal Allograft Biopsies: Where Do We Stand and Where Are We Going?

A renal core biopsy for histological evaluation is the gold standard for diagnosing renal transplant pathology. However, renal biopsy interpretation is subjective and can render insufficient precision, making it difficult to apply a targeted therapeutic regimen for the individual patient. This warrants a need for additional methods assessing disease state in the renal transplant. Significant research activity has been focused on the role of molecular analysis in the diagnosis of renal allograft rejection. The identification of specific molecular expression patterns in allograft biopsies related to different types of allograft injury could provide valuable information about the processes underlying renal transplant dysfunction and can be used for the development of molecular classifier scores, which could improve our diagnostic and prognostic ability and could guide treatment. Molecular profiling has the potential to be more precise and objective than histological evaluation and may identify injury even before it becomes visible on histology, making it possible to start treatment at the earliest time possible. Combining conventional diagnostics (histology, serology, and clinical data) and molecular evaluation will most likely offer the best diagnostic approach. We believe that the use of state-of-the-art molecular analysis will have a significant impact in diagnostics after renal transplantation. In this review, we elaborate on the molecular phenotype of both acute and chronic T cell-mediated rejection and antibody-mediated rejection and discuss the additive value of molecular profiling in the setting of diagnosing renal allograft rejection and how this will improve transplant patient care.

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.

Single-cell Transcriptomics and Solid Organ Transplantation

Single-cell RNA sequencing (scRNA-seq) allows the measurement of transcriptomes from individual cells providing new insights into complex biological systems. scRNA-seq has enabled the identification of rare cell types, new cell states, and intercellular communication networks that may be masked by traditional bulk transcriptional profiling. Researchers are increasingly using scRNA-seq to comprehensively characterize complex organs in health and disease. The diversity of immune cell types, some present at low frequency, in a transplanted organ undergoing rejection makes scRNA-seq ideally suited to characterize transplant pathologies because it can quantify subtle transcriptional differences between rare cell types. In this review, we discuss single-cell sequencing methods and their application in transplantation to date, current challenges, and future directions. We believe that the remarkably rapid pace of technological development in this field makes it likely that single-cell technologies such as scRNA-seq will have an impact on clinical transplantation within a decade.

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.

Polymorphisms in vasoactive eicosanoid genes of kidney donors affect biopsy scores and clinical outcomes in renal transplantation

Cytochrome P450 (CYP) enzymes metabolize arachidonic acid to vasoactive eicosanoids such as epoxyeicosatrienoic acids (EETs) and 20-Hydroxyeicosatetraenoic acid (20-HETE), whilst soluble epoxide hydrolase, encoded by the EPHX2 gene, is in charge of EETs degradation. We aimed to analyze the influence of common, functional polymorphisms in four genes of the donor on the renal biopsy scores independently assigned by pathologists. Additionally, we examined whether this score or the presence of these SNPs were independent risk factors of clinical outcomes in the first year after grafting. A cohort of 119 recipients and their corresponding 85 deceased donors were included in the study. Donors were genotyped for the CYP4F2 V433M, CYP2C8*3, CYP2J2*7, EPHX2 3’UTR A>G, EPHX2 K55R and EPHX2 R287Q polymorphisms. The association of the donors’ SNPs with the biopsy scores and clinical outcomes was retrospectively evaluated by multivariate regression analysis. The CYP2C8*3 polymorphism in the donor was significantly associated with higher scores assigned to pretransplant biopsies [OR = 3.35 (1.03–10.93), p = 0.045]. In turn, higher scores were related to an increased risk of acute rejection [OR = 5.28 (1.32–21.13), p = 0.019] and worse glomerular filtration rate (eGFR) (45.68±16.05 vs. 53.04±16.93 ml/min in patients whose grafts had lower scores, p = 0.010) one year after transplant. Patients whose donors carried the CYP4F2 433M variant showed lower eGFR values (48.96±16.89 vs. 55.94±18.62 ml/min in non-carriers, p = 0.038) and higher risk of acute rejection [OR = 6.18 (1.03–37.21), p = 0.047]. The CYP2J2*7 SNP in the donor was associated with elevated risk of delayed graft function [OR = 25.68 (1.52–43.53), p = 0.025]. Our results taken together suggest that donor genetic variability may be used as a predictor of tissue damage in the graft as well as to predict clinical outcomes and graft function in the recipient.

Metabolomics study of the therapeutic mechanism of a Chinese herbal formula on collagen-induced arthritis mice

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy. The precise mechanism of WJHL on RA therapy is yet to be elucidated. This study aimed to determine the metabolic biomarkers in the early onset of RA and evaluate the regulation effect of WJHL on metabolite levels. Multivariate statistical analysis identified 93 biomarkers by precise MS/MS. These biomarkers played an important role in the regulation of key metabolic pathways associated with collagen-induced arthritis (CIA). A total of 68 biomarkers were related to the treatment of CIA by WJHL therapy. In addition, pathway analysis results showed six and three significant related pathways according to corresponding differential metabolites before and after WJHL therapy. Finally, disease and function prediction of ingenuity pathway analysis indicated that lipid metabolism, small molecule biochemistry, and carbohydrate metabolism were associated functions of WJHL therapy on CIA. Furthermore, top analysis-ready molecules of up-regulated thiamine and down-regulated arachidonic acid maybe the most related metabolites of WJHL therapy on CIA. The present work indicates that a metabolomics platform provides a new insight into understanding the mechanisms of action of natural medicines, such as WJHL.

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy.

Micro RNA 146a-5p expression in Kidney transplant recipients with delayed graft function

Introduction:

The development of novel non-invasive biomarkers of kidney graft dysfunction, especially in the course of the delayed graft function period would be an important step forward in the clinical practice of kidney transplantation.

Methods:

We evaluated by RT-PCR the expression of miRNA-146 to -5p ribonucleic micro-acids (miRNAs) in the peripheral blood and renal tissue obtained from kidney transplant recipients who underwent a surveillance graft biopsy during the period of delayed graft function.

Results:

In biopsy samples, the expression of miR-146a-5p was significantly increased in the group of patients with delayed graft function (DGF) (n = 33) versus stables patients (STA) (n = 13) and patients with acute rejection (AR) (n = 9) (p = 0.008). In peripheral blood samples, a non-significant increase of miR-146a-5p expression was found in the DGF group versus STA and AR groups (p = 0.083). No significant correlation was found between levels of expression in biopsy and plasma. ROC curve analysis revealed an AUC of 0.75 (95% CI: 0.62-0.88) for the renal tissue expression and 0.67 (95% CI 0.52-0.81) for the peripheral blood expression.

Conclusion:

We conclude that miR-146a-5p expression has a distinct pattern in the renal tissue and perhaps in the peripheral blood in the setting of DGF. Further refinements and strategies for studies should be developed in the field of non-invasive molecular diagnosis of kidney graft dysfunction.

Early isolated V-lesion may not truly represent rejection of the kidney allograft

Intimal arteritis is known to be a negative prognostic factor for kidney allograft survival. Isolated v-lesion (IV) is defined as intimal arteritis with minimal tubulointerstitial inflammation (TI). Although the Banff classification assesses IV as T cell-mediated rejection (TCMR), clinical, and prognostic significance of early IV (early IV, eIV) with negative C4d and donor-specific antibodies (DSA) remains unclear. To help resolve if such eIV truly represents acute rejection, a molecular study was performed. The transcriptome of eIV (n=6), T cell-mediated vascular rejection with rich TI (T cell-mediated vascular rejection, TCMRV, n=4) and non-rejection histologic findings (n=8) was compared using microarrays. A total of 310 genes were identified to be deregulated in TCMRV compared with eIV. Gene enrichment analysis categorized deregulated genes to be associated primarily with T-cells associated biological processes involved in an innate and adaptive immune and inflammatory response. Comparison of deregulated gene lists between the study groups and controls showed only a 1.7% gene overlap. Unsupervised hierarchical cluster analysis revealed clear distinction of eIV from TCMRV and showed similarity with a control group. Up-regulation of immune response genes in TCMRV was validated using RT-qPCR in a different set of eIV (n=12) and TCMRV (n=8) samples. The transcriptome of early IV (< 1 month) with negative C4d and DSA is associated with a weak immune signature compared with TCMRV and shows similarity with normal findings. Such eIV may feature non-rejection origin and reflect an injury distinct from an alloimmune response. The present study supports use of molecular methods when interpreting kidney allograft biopsy findings.

Biomarkers and Pharmacogenomics in Kidney Transplantation

This review is focused on present and future biomarkers, along with pharmacogenomics used in clinical practice for kidney transplantation. It aims to highlight biomarkers that could potentially be used to improve kidney transplant early and long-term graft survival, but also potentially patient co-morbidity. Future directions for improving outcomes are discussed, which include immune tolerance and personalising immunosuppression regimens.

Transcriptomic studies in tolerance: Lessons learned and the path forward

Immunosuppression after solid organ transplantation is a delicate balance of the immune response and is a complex phenomenon with many factors involved. Despite advances in the care of patients receiving organ transplants the adverse effects associated with immunosuppressive agents and the risks of long-term immunosuppression present a series of challenges and the need to weigh the risks and benefits of either over or under-immunosuppression. Ideally, if all transplant recipients could develop donor-specific immunological tolerance, it could drastically improve long-term graft survival without the need for immunosuppressive agents. In the absence of this ideal situation, the next best approach would be to develop tools to determine the adequacy of immunosuppression in each patient, in a manner that would individualize or personalize therapy. Despite current genomics-based studies of tolerance biomarkers in transplantation there are currently, no clinically validated tools to safely increase or decrease the level of IS that is beneficial to the patient. However, the successful identification of biomarkers and/or mechanisms of tolerance that have implications on long-term graft survival and outcomes depend on proper integration of study design, experimental protocols, and data-driven hypotheses. The objective of this article is to first, discuss the progress made on genomic biomarkers of immunological tolerance and the future avenues for the development of such biomarkers specifically in kidney transplantation. Secondly, we provide a set of guiding principles and identify the pitfalls, advantages, and drawbacks of studies that generate genomic data aimed at understanding transplant tolerance that is applicable to all solid transplants.

Proteomics for Biomarker Identification and Clinical Application in Kidney Disease

Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.

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

We performed orthogonal technology comparisons of concurrent peripheral blood and biopsy tissue samples from 69 kidney transplant recipients who underwent comprehensive algorithm-driven clinical phenotyping. The sample cohort included patients with normal protocol biopsies and stable transplant (sTx) function (n = 25), subclinical acute rejection (subAR, n = 23), and clinical acute rejection (cAR, n = 21). Comparisons between microarray and RNA sequencing (RNA-seq) signatures were performed and demonstrated a strong correlation between the blood and tissue compartments for both technology platforms. A number of shared differentially expressed genes and pathways between subAR and cAR in both platforms strongly suggest that these two clinical phenotypes form a continuum of alloimmune activation. SubAR is associated with fewer or less expressed genes than cAR in blood, whereas in biopsy tissues, this clinical phenotype demonstrates a more robust molecular signature for both platforms. The discovery work done in this study confirms a clear ability to detect gene expression profiles for sTx, subAR, and cAR in both blood and biopsy tissue, yielding equivalent predictive performance that is agnostic to both technology and platform. Our data also provide strong biological insights into the molecular mechanisms underlying these signatures, underscoring their logistical potential as molecular diagnostics to improve clinical outcomes following kidney transplantation.

Moving Biomarkers toward Clinical Implementation in Kidney Transplantation

Long-term kidney transplant outcomes remain suboptimal, delineating an unmet medical need. Although current immunosuppressive therapy in kidney transplant recipients is effective, dosing is conventionally adjusted empirically on the basis of time after transplant or altered in response to detection of kidney dysfunction, histologic evidence of allograft damage, or infection. Such strategies tend to detect allograft rejection after significant injury has already occurred, fail to detect chronic subclinical inflammation that can negatively affect graft survival, and ignore specific risks and immune mechanisms that differentially contribute to allograft damage among transplant recipients. Assays and biomarkers that reliably quantify and/or predict the risk of allograft injury have the potential to overcome these deficits and thereby, aid clinicians in optimizing immunosuppressive regimens. Herein, we review the data on candidate biomarkers that we contend have the highest potential to become clinically useful surrogates in kidney transplant recipients, including functional T cell assays, urinary gene and protein assays, peripheral blood cell gene expression profiles, and allograft gene expression profiles. We identify barriers to clinical biomarker adoption in the transplant field and suggest strategies for moving biomarker-based individualization of transplant care from a research hypothesis to clinical implementation.

Novel Therapeutics Identification for Fibrosis in Renal Allograft Using Integrative Informatics Approach

Chronic allograft damage, defined by interstitial fibrosis and tubular atrophy (IF/TA), is a leading cause of allograft failure. Few effective therapeutic options are available to prevent the progression of IF/TA. We applied a meta-analysis approach on IF/TA molecular datasets in Gene Expression Omnibus to identify a robust 85-gene signature, which was used for computational drug repurposing analysis. Among the top ranked compounds predicted to be therapeutic for IF/TA were azathioprine, a drug to prevent acute rejection in renal transplantation, and kaempferol and esculetin, two drugs not previously described to have efficacy for IF/TA. We experimentally validated the anti-fibrosis effects of kaempferol and esculetin using renal tubular cells in vitro and in vivo in a mouse Unilateral Ureteric Obstruction (UUO) model. Kaempferol significantly attenuated TGF-β1-mediated profibrotic pathways in vitro and in vivo, while esculetin significantly inhibited Wnt/β-catenin pathway in vitro and in vivo. Histology confirmed significantly abrogated fibrosis by kaempferol and esculetin in vivo. We developed an integrative computational framework to identify kaempferol and esculetin as putatively novel therapies for IF/TA and provided experimental evidence for their therapeutic activities in vitro and in vivo using preclinical models. The findings suggest that both drugs might serve as therapeutic options for IF/TA.