Genomics of chronic allograft injury

Characterizing hub biomarkers for post-transplant renal fibrosis and unveiling their immunological functions through RNA sequencing and advanced machine learning techniques

BACKGROUND

Kidney transplantation stands out as the most effective renal replacement therapy for patients grappling with end-stage renal disease. However, post-transplant renal fibrosis is a prevalent and irreversible consequence, imposing a substantial clinical burden. Unfortunately, the clinical landscape remains devoid of reliable biological markers for diagnosing post-transplant renal interstitial fibrosis.

METHODS

We obtained transcriptome and single-cell sequencing datasets of patients with renal fibrosis from NCBI Gene Expression Omnibus (GEO). Subsequently, we employed Weighted Gene Co-Expression Network Analysis (WGCNA) to identify potential genes by integrating core modules and differential genes. Functional enrichment analysis was conducted to unveil the involvement of potential pathways. To identify key biomarkers for renal fibrosis, we utilized logistic analysis, a LASSO-based tenfold cross-validation approach, and gene topological analysis within Cytoscape. Furthermore, histological staining, Western blotting (WB), and quantitative PCR (qPCR) experiments were performed in a murine model of renal fibrosis to verify the identified hub genes. Moreover, molecular docking and molecular dynamics simulations were conducted to explore possible effective drugs.

RESULTS

Through WGCNA, the intersection of core modules and differential genes yielded a compendium of 92 potential genes. Logistic analysis, LASSO-based tenfold cross-validation, and gene topological analysis within Cytoscape identified four core genes (CD3G, CORO1A, FCGR2A, and GZMH) associated with renal fibrosis. The expression of these core genes was confirmed through single-cell data analysis and validated using various machine learning methods. Wet experiments also verified the upregulation of these core genes in the murine model of renal fibrosis. A positive correlation was observed between the core genes and immune cells, suggesting their potential role in bolstering immune system activity. Moreover, four potentially effective small molecules (ZINC000003830276-Tessalon, ZINC000003944422-Norvir, ZINC000008214629-Nonoxynol-9, and ZINC000085537014-Cobicistat) were identified through molecular docking and molecular dynamics simulations.

CONCLUSION

Four potential hub biomarkers most associated with post-transplant renal fibrosis, as well as four potentially effective small molecules, were identified, providing valuable insights for studying the molecular mechanisms underlying post-transplant renal fibrosis and exploring new targets.

Identifying Biomarkers from Transcriptomic Signatures in Renal Allograft Biopsies Using Deceased and Living Donors

The survival of transplant kidneys using deceased donors (DD) is inferior to living donors (LD). In this study, we conducted a whole-transcriptome expression analysis of 24 human kidney biopsies paired at 30 minutes and 3 months post-transplantation using DD and LD. The transcriptome profile was found significantly different between two time points regardless of donor types. There were 446 differentially expressed genes (DEGs) between DD and LD at 30 minutes and 146 DEGs at 3 months, with 25 genes common to both time points. These DEGs reflected donor injury and acute immune responses associated with inflammation and cell death as early as at 30 minutes, which could be a precious window of potential intervention. DEGs at 3 months mainly represented the changes of adaptive immunity, immunosuppressive treatment, remodeling or fibrosis via different networks and signaling pathways. The expression levels of 20 highly DEGs involved in kidney diseases and 10 genes dysregulated at 30 minutes were found correlated with renal function and histology at 12 months, suggesting they could be potential biomarkers. These genes were further validated by quantitative polymerase chain reaction (qPCR) in 24 samples analysed by microarray, as well as in a validation cohort of 33 time point unpaired allograft biopsies. This analysis revealed that SERPINA3, SLPI and CBF were up-regulated at 30 minutes in DD compared to LD, while FTCD and TASPN7 were up-regulated at both time points. At 3 months, SERPINA3 was up-regulated in LD, but down-regulated in DD, with increased VCAN and TIMP1, and decreased FOS, in both donors. Taken together, divergent transcriptomic signatures between DD and LD, and changed by the time post-transplantation, might contribute to different allograft survival of two type kidney donors. Some DEGs including FTCD and TASPN7 could be novel biomarkers not only for timely diagnosis, but also for early precise genetic intervention at donor preservation, implantation and post-transplantation, in particular to effectively improve the quality and survival of DD.

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.

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

The development and application of high-throughput molecular profiling have transformed the study of human diseases. The problem of handling large, complex data sets has been facilitated by advances in complex computational analysis. In this review, the recent literature regarding the application of transcriptional genomic information to renal transplantation, with specific reference to acute rejection, acute kidney injury in allografts, chronic allograft injury, and tolerance is discussed, as is the current published data regarding other "omics" strategies-proteomics, metabolomics, and the microRNA transcriptome. These data have shed new light on our understanding of the pathogenesis of specific disease conditions after renal transplantation, but their utility as a biomarker of disease has been hampered by study design and sample size. This review aims to highlight the opportunities and obstacles that exist with genomics and other related technologies to better understand and predict renal allograft outcome.

Urinary biomarkers of chronic allograft nephropathy

PURPOSE

Chronic allograft nephropathy (CAN) is widely accepted as the leading cause of renal allograft loss after the first year post transplantation. This study aimed to identify urinary biomarkers that could predict CAN in transplant patients.

EXPERIMENTAL DESIGN

The study included 34 renal transplant patients with histologically proven CAN and 36 renal transplant patients with normal renal function. OrbiTrap MS was utilized to analysis a urinary fraction in order to identify other members of a previously identified biomarker tree . This novel biomarker pattern offers the potential to distinguish between transplant recipients with CAN and those with normal renal function.

RESULTS

The primary node of the biomarker pattern was reconfirmed as β2 microglobulin. Three other members of this biomarker pattern were identified: neutrophil gelatinase-associated lipocalin, clusterin, and kidney injury biomarker 1. Significantly higher urinary concentrations of these proteins were found in patients with CAN compared to those with normal kidney function.

CONCLUSIONS AND CLINICAL RELEVANCE

While further validation in a larger more-diverse patient population is required to determine if this biomarker pattern provides a potential means of diagnosing CAN by noninvasive methods in a clinical setting, this study clearly demonstrates the biomarkers' ability to stratify patients based on transplant function.

Renal allograft fibrosis: biology and therapeutic targets

Renal tubulointerstitial fibrosis is the final common pathway of progressive renal diseases. In allografts, it is assessed with tubular atrophy as interstitial fibrosis/tubular atrophy (IF/TA). IF/TA occurs in about 40% of kidney allografts at 3-6 months after transplantation, increasing to 65% at 2 years. The origin of renal fibrosis in the allograft is complex and includes donor-related factors, in particular in case of expanded criteria donors, ischemia-reperfusion injury, immune-mediated damage, recurrence of underlying diseases, hypertensive damage, nephrotoxicity of immunosuppressants, recurrent graft infections, postrenal obstruction, etc. Based largely on studies in the non-transplant setting, there is a large body of literature on the role of different cell types, be it intrinsic to the kidney or bone marrow derived, in mediating renal fibrosis, and the number of mediator systems contributing to fibrotic changes is growing steadily. Here we review the most important cellular processes and mediators involved in the progress of renal fibrosis, with a focus on the allograft situation, and discuss some of the challenges in translating experimental insights into clinical trials, in particular fibrosis biomarkers or imaging modalities.

Intronic locus determines SHROOM3 expression and potentiates renal allograft fibrosis

Fibrosis underlies the loss of renal function in patients with chronic kidney disease (CKD) and in kidney transplant recipients with chronic allograft nephropathy (CAN). Here, we studied the effect of an intronic SNP in SHROOM3, which has previously been linked to CKD, on the development of CAN in a prospective cohort of renal allograft recipients. The presence of the rs17319721 allele at the SHROOM3 locus in the donor correlated with increased SHROOM3 expression in the allograft. In vitro, we determined that the sequence containing the risk allele at rs17319721 is a transcription factor 7-like 2-dependent (TCF7L2-dependent) enhancer element that functions to increase SHROOM3 transcription. In renal tubular cells, TGF-β1 administration upregulated SHROOM3 expression in a β-catenin/TCF7L2-mediated manner, while SHROOM3 in turn facilitated canonical TGF-β1 signaling and increased α1 collagen (COL1A1) expression. Inducible and tubular cell-specific knockdown of Shroom3 markedly abrogated interstitial fibrosis in mice with unilateral ureteric obstruction. Moreover, SHROOM3 expression in allografts at 3 months after transplant and the presence of the SHROOM3 risk allele in the donor correlated with increased allograft fibrosis and with reduced estimated glomerular filtration rate at 12 months after transplant. Our findings suggest that rs17319721 functions as a cis-acting expression quantitative trait locus of SHROOM3 that facilitates TGF-β1 signaling and contributes to allograft injury.

High-Throughput Proteomic Approaches to the Elucidation of Potential Biomarkers of Chronic Allograft Injury (CAI)

This review focuses on the role of OMICs technologies, concentrating in particular on proteomics, in biomarker discovery in chronic allograft injury (CAI). CAI is the second most prevalent cause of allograft dysfunction and loss in the first decade post-transplantation, after death with functioning graft (DWFG). The term CAI, sometimes referred to as chronic allograft nephropathy (CAN), describes the deterioration of renal allograft function and structure as a result of immunological processes (chronic antibody-mediated rejection), and other non-immunological factors such as calcineurin inhibitor (CNI) induced nephrotoxicity, hypertension and infection. Current methods for assessing allograft function are costly, insensitive and invasive; traditional kidney function measurements such as serum creatinine and glomerular filtration rate (GFR) display poor predictive abilities, while the current “gold-standard” involving histological diagnosis with a renal biopsy presents its own inherent risks to the overall health of the allograft. As early as two years post-transplantation, protocol biopsies have shown more than 50% of allograft recipients have mild CAN; ten years post-transplantation more than 50% of the allograft recipients have progressed to severe CAN which is associated with diminishing graft function. Thus, there is a growing medical requirement for minimally invasive biomarkers capable of identifying the early stages of the disease which would allow for timely intervention. Proteomics involves the study of the expression, localization, function and interaction of the proteome. Proteomic technologies may be powerful tools used to identify novel biomarkers which would predict CAI in susceptible individuals. In this paper we will review the use of proteomics in the elucidation of novel predictive biomarkers of CAI in clinical, animal and in vitro studies.

Antibody-mediated rejection, T cell-mediated rejection, and the injury-repair response: new insights from the Genome Canada studies of kidney transplant biopsies

Prospective studies of unselected indication biopsies from kidney transplants, combining conventional assessment with molecular analysis, have created a new understanding of transplant disease states and their outcomes. A large-scale Genome Canada grant permitted us to use conventional and molecular phenotypes to create a new disease classification. T cell-mediated rejection (TCMR), characterized histologically or molecularly, has little effect on outcomes. Antibody-mediated rejection (ABMR) manifests as microcirculation lesions and transcript changes reflecting endothelial injury, interferon-γ effects, and natural killer cells. ABMR is frequently C4d negative and has been greatly underestimated by conventional criteria. Indeed, ABMR, triggered in some cases by non-adherence, is the major disease causing failure. Progressive dysfunction is usually attributable to specific diseases, and pure calcineurin inhibitor toxicity rarely explains failure. The importance of ABMR argues against immunosuppressive drug minimization and stands as a barrier to tolerance induction. Microarrays also defined the transcripts induced by acute kidney injury (AKI), which correlate with reduced function, whereas histologic changes of acute tubular injury do not. AKI transcripts are induced in kidneys with late dysfunction, and are better predictors of failure than fibrosis and inflammation. Thus progression reflects ongoing parenchymal injury, usually from identifiable diseases such as ABMR, not destructive fibrosis.

Kidney transplants with progressing chronic diseases express high levels of acute kidney injury transcripts

We previously reported that kidney transplants with early acute injury express transcripts indicating injury repair--the acute kidney injury signal. This study investigated the significance of this signal in transplants with other conditions, including rejection and recurrent disease. The injury signal was elevated in biopsies in many different conditions, including T cell-mediated rejection and potentially progressive diseases such as antibody-mediated rejection and glomerulonephritis. A high injury signal correlated with poor function and with inflammation in areas of fibrosis, but not with fibrosis without inflammation. In multivariate survival analysis, the injury signal in late kidney transplant biopsies strongly predicted future graft loss, similar to a published molecular risk score derived in late kidneys. Indeed, the injury signal shared many individual transcripts with the risk score, e.g. ITGB6, VCAN, NNMT. The injury signal was a better predictor of future graft loss than fibrosis, inflammation or expression of collagen genes. Thus the acute injury signal, first defined in early reversible injury, is present in many diseases as a reflection of parenchymal distress, where its significance is dictated by the inducing insult, i.e. treatable/self-limited versus untreatable and sustained. Progression in troubled transplants is primarily a function of ongoing parenchymal injury by disease, not fibrogenesis.

The coin toss of B cells in rejection and tolerance: danger versus defense

Transplantation is the preferred therapy for the end stage organ disease. Since the introduction of organ transplantation into medical practice in 1953 [1], significant progress has been achieved in patient and graft survival rates due to improvements in surgical techniques and more targeted immunosuppressive medications [2]. Nevertheless, current gaps in the management of the transplant patient stem from an incomplete understanding about the heterogeneity of the injury response in organ transplantation, at different rates and different time points after transplantation, as well as our inability to monitor the immunologic threshold of risk versus safety in each individual patient. Recent advances in immunology/transplantation biology with the advent of high throughput "omic" assays such as gene microarrays, proteomics, metabolomics, antibiomics, chemical genomics and functional imaging with nanoparticles, offers us unique methods to interrogate and decipher the variability and unpredictability of the immune response in organ transplantation (Fig. 1) [3]. Recent studies using these applications [3-8] have uncovered a critical and pivotal role for specific B cell lineages in organ injury [9] and organ acceptance [10,11] (Fig. 2). The availability of specific therapies against some of these defined B cell populations provides for an exciting new field of B cell targeted manipulation that can both abrogate the allospecific injury response, as well as promote allospecific graft accommodation and health.