The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

Endothelial cell antibodies associated with novel targets and increased rejection.

The initial contact point between a recipient's immune system and a transplanted graft is the vascular endothelium. Clinical studies suggest a pathogenic role for non-HLA antiendothelial cell antibodies (AECAs) in allograft rejection; however, evidence linking AECAs of known specificity to in vivo vascular injury is lacking. Here, we used high-density protein arrays to identify target antigens for AECAs isolated from the sera of recipients of kidney transplants experiencing antibody-mediated rejection in the absence of donor-specific HLA antibodies. Four antigenic targets expressed on endothelial cells were identified: endoglin, Fms-like tyrosine kinase-3 ligand, EGF-like repeats and discoidin I-like domains 3, and intercellular adhesion molecule 4; the first three have been implicated in endothelial cell activation and leukocyte extravasation. To validate these findings, ELISAs were constructed, and sera from an additional 150 renal recipients were tested. All four AECAs were detected in 24% of pretransplant sera, and they were associated with post-transplant donor-specific HLA antibodies, antibody-mediated rejection, and early transplant glomerulopathy. AECA stimulation of endothelial cell cultures increased adhesion molecule expression and production of inflammatory cytokines: regulated on activation, normal T cell expressed and secreted PDGF and RESISTIN. These correlations between in vitro experiments and in vivo histopathology suggest that AECAs activate the vascular endothelium, amplifying the alloimmune response and increasing microvascular damage. Given the growing number of transplant candidates, a better understanding of the antigenic targets, beyond HLA, and mechanisms of immune injury will be essential for improving long-term allograft survival.

A Three-Gene Assay for Monitoring Immune Quiescence in Kidney Transplantation.

Organ transplant recipients face life-long immunosuppression and consequently are at high risk of comorbidities. Occasionally, kidney transplant recipients develop a state of targeted immune quiescence (operational tolerance) against an HLA-mismatched graft, allowing them to withdraw all immunosuppression and retain stable graft function while resuming immune responses to third-party antigens. Methods to better understand and monitor this state of alloimmune quiescence by transcriptional profiling may reveal a gene signature that identifies patients for whom immunosuppression could be titrated to reduce patient and graft morbidities. Therefore, we investigated 571 unique peripheral blood samples from 348 HLA-mismatched renal transplant recipients and 101 nontransplant controls in a four-stage study including microarray, quantitative PCR, and flow cytometry analyses. We report a refined and highly validated (area under the curve, 0.95; 95% confidence interval, 0.92 to 0.97) peripheral blood three-gene assay (KLF6, BNC2, CYP1B1) to detect the state of operational tolerance by quantitative PCR. The frequency of predicted alloimmune quiescence in stable renal transplant patients receiving long-term immunosuppression (n=150) was 7.3% by the three-gene assay. Targeted cell sorting of peripheral blood from operationally tolerant patients showed a significant shift in the ratio of circulating monocyte-derived dendritic cells with significantly different expression of the genes constituting the three-gene assay. Our results suggest that incorporation of patient screening by specific cellular and gene expression assays may support the safety of drug minimization trials and protocols.

Optimization for peptide sample preparation for urine peptidomics.

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput 'peptidomics' methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.

The clinical impact of humoral immunity in pediatric renal transplantation.

The development of anti-donor humoral responses after transplantation associates with higher risks for acute rejection and 1-year graft survival in adults, but the influence of humoral immunity on transplant outcomes in children is not well understood. Here, we studied the evolution of humoral immunity in low-risk pediatric patients during the first 2 years after renal transplantation. Using data from 130 pediatric renal transplant patients randomized to steroid-free (SF) or steroid-based (SB) immunosuppression in the NIH-SNSO1 trial, we correlated the presence of serum anti-HLA antibodies to donor HLA antigens (donor-specific antibodies) and serum MHC class 1-related chain A (MICA) antibody with both clinical outcomes and histology identified on protocol biopsies at 0, 6, 12, and 24 months. We detected de novo antibodies after transplant in 24% (23% of SF group and 25% of SB group), most often after the first year. Overall, 22% developed anti-HLA antibodies, of which 6% were donor-specific antibodies, and 6% developed anti-MICA antibody. Presence of these antibodies de novo associated with significantly higher risks for acute rejection (P=0.02), chronic graft injury (P=0.02), and decline in graft function (P=0.02). In summary, antibodies to HLA and MICA antigens appear in approximately 25% of unsensitized pediatric patients, placing them at greater risk for acute and chronic rejection with accelerated loss of graft function. Avoiding steroids does not seem to modify this incidence. Whether serial assessments of these antibodies after transplant could guide individual tailoring of immunosuppression requires additional study.

Non-HLA antibodies to immunogenic epitopes predict the evolution of chronic renal allograft injury.

Chronic allograft injury (CAI) results from a humoral response to mismatches in immunogenic epitopes between the donor and recipient. Although alloantibodies against HLA antigens contribute to the pathogenesis of CAI, alloantibodies against non-HLA antigens likely contribute as well. Here, we used high-density protein arrays to identify non-HLA antibodies in CAI and subsequently validated a subset in a cohort of 172 serum samples collected serially post-transplantation. There were 38 de novo non-HLA antibodies that significantly associated with the development of CAI (P<0.01) on protocol post-transplant biopsies, with enrichment of their corresponding antigens in the renal cortex. Baseline levels of preformed antibodies to MIG (also called CXCL9), ITAC (also called CXCL11), IFN-γ, and glial-derived neurotrophic factor positively correlated with histologic injury at 24 months. Measuring levels of these four antibodies could help clinicians predict the development of CAI with >80% sensitivity and 100% specificity. In conclusion, pretransplant serum levels of a defined panel of alloantibodies targeting non-HLA immunogenic antigens associate with histologic CAI in the post-transplant period. Validation in a larger, prospective transplant cohort may lead to a noninvasive method to predict and monitor for CAI.

Differentially expressed RNA from public microarray data identifies serum protein biomarkers for cross-organ transplant rejection and other conditions.

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers.

Insights into novel cellular injury mechanisms by gene expression profiling in nephropathic cystinosis.

Nephropathic cystinosis is a rare, inherited metabolic disease caused by functional defects of cystinosin associated with mutations in the CTNS gene. The mechanisms underlying the phenotypic alterations associated with this disease are not well known. In this study, gene expression profiles in peripheral blood of nephropathic cystinosis patients (N = 7) were compared with controls (N = 7) using microarray technology. In unsupervised hierarchical clustering analysis, cystinosis samples co-clustered, and 1,604 genes were significantly differentially expressed between both groups. Gene ontology analysis revealed that differentially expressed genes in cystinosis were enriched in cell organelles such as mitochondria, lysosomes, and endoplasmic reticulum (p ≤ 0.030). The majority of the differentially regulated genes were involved in oxidative phosphorylation, apoptosis, mitochondrial dysfunction, endoplasmic reticulum stress, antigen processing and presentation, B-cell-receptor signaling, and oxidative stress (p ≤ 0.003). Validation of selected genes involved in apoptosis and oxidative phosphorylation was performed by quantitative real-time polymerase chain reaction (PCR). Electron microscopy and confocal imaging of cystinotic renal proximal tubular epithelial cells further confirmed anomalies in the cellular organelles and pathways identified by microarray analysis. Further analysis of these genes and pathways may offer critical insights into the clinical spectrum of cystinosis patients and ultimately lead to novel links for targeted therapy.

Expression of complement components differs between kidney allografts from living and deceased donors.

A disparity remains between graft survival of renal allografts from deceased donors and from living donors. A better understanding of the molecular mechanisms that underlie this disparity may allow the development of targeted therapies to enhance graft survival. Here, we used microarrays to examine whole genome expression profiles using tissue from 53 human renal allograft protocol biopsies obtained both at implantation and after transplantation. The gene expression profiles of living-donor kidneys and pristine deceased-donor kidneys (normal histology, young age) were significantly different before reperfusion at implantation. Deceased-donor kidneys exhibited a significant increase in renal expression of complement genes; posttransplantation biopsies from well-functioning, nonrejecting kidneys, regardless of donor source, also demonstrated a significant increase in complement expression. Peritransplantation phenomena, such as donor death and possibly cold ischemia time, contributed to differences in complement pathway gene expression. In addition, complement gene expression at the time of implantation was associated with both early and late graft function. These data suggest that complement-modulating therapy may improve graft outcomes in renal transplantation.

A urinary Common Rejection Module (uCRM) score for non-invasive kidney transplant monitoring.

A Common Rejection Module (CRM) consisting of 11 genes expressed in allograft biopsies was previously reported to serve as a biomarker for acute rejection (AR), correlate with the extent of graft injury, and predict future allograft damage. We investigated the use of this gene panel on the urine cell pellet of kidney transplant patients. Urinary cell sediments collected from patients with biopsy-confirmed acute rejection, borderline AR (bAR), BK virus nephropathy (BKVN), and stable kidney grafts with normal protocol biopsies (STA) were analyzed for expression of these 11 genes using quantitative polymerase chain reaction (qPCR). We assessed these 11 CRM genes for their abundance, autocorrelation, and individual expression levels. Expression of 10/11 genes were elevated in AR when compared to STA. Psmb9 and Cxcl10could classify AR versus STA as accurately as the 11-gene model (sensitivity = 93.6%, specificity = 97.6%). A uCRM score, based on the geometric mean of the expression levels, could distinguish AR from STA with high accuracy (AUC = 0.9886) and correlated specifically with histologic measures of tubulitis and interstitial inflammation rather than tubular atrophy, glomerulosclerosis, intimal proliferation, tubular vacuolization or acute glomerulitis. This urine gene expression-based score may enable the non-invasive and quantitative monitoring of AR.

Characterization of intra-graft B cells during renal allograft rejection.

Intra-graft CD20(+) B-cell clusters are found during acute rejection of renal allografts and correlate with graft recovery following rejection injury. Here using archived kidney tissue we conducted immunohistochemical studies to measure specific subsets of pathogenic B cells during graft rejection. Cluster-forming CD20(+) B cells in the rejected graft are likely derived from the recipient and are composed of mature B cells. These cells are activated (CD79a(+)), and present MHC Class II antigen (HLADR(+)) to CD4(+) T cells. Some of these clusters contained memory B cells (CD27(+)) and they did not correlate with intra-graft C4d deposition or with detection of donor-specific antibody. Further, several non-cluster forming CD20(-) B-lineage CD38(+) plasmablasts and plasma cells were found to infiltrate the rejected grafts and these cells strongly correlated with circulating donor-specific antibody, and to a lesser extent with intra-graft C4d. Both CD20(+) B cells and CD38(+) cells correlated with poor response of the rejection to steroids. Reduced graft survival was associated with the presence of CD20 cells in the graft. In conclusion, a specific subset of early lineage B cells appears to be an antigen-presenting cell and which when present in the rejected graft may support a steroid-resistant T-cell-mediated cellular rejection. Late lineage interstitial plasmablasts and plasma cells may also support humoral rejection. These studies suggest that detailed analysis of interstitial cellular infiltrates may allow better use of B-cell lineage specific treatments to improve graft outcomes.

Targeted Transcriptional Profiling of Kidney Transplant Biopsies.

INTRODUCTION: Studies are needed to assess the quality of transcriptome analysis in paired human tissue samples preserved by different methods and different gene amplification platforms to enable data comparisons across experimenters. METHODS: RNA was extracted from kidney biopsies, either submerged in RNA-stabilizing solution (RSS) or stored in formalin-fixed, paraffin-embedded (FFPE) blocks. RNA quality and integrity were compared. Gene expression of the common rejection module and other immune cell genes were quantified for both tissue preservation methods in the same sample using conventional quantitative polymerase chain reaction (QPCR) by 2 different commercial platforms, (fluidigm [FD]) or barcoded-oligos (nanostring [NS]). RESULTS: RNA quality was inferior in FFPE tissues. Despite this, gene expression for 19 measured genes on the same sample, stored in FFPE or RSS, were strongly correlated on the FD (r = 0.81) or NS platforms (r = 0.82). For the same samples, interplatform gene expression correlations were excellent (r = 0.80) for RSS and moderate (r = 0.66) for FFPE. Significant differences in gene expression were confirmed on both platforms (FD: P = 1.1E-03; NS: P = 2.5E-04) for biopsy-confirmed acute rejection. CONCLUSION: Our study provided supportive evidence that despite a low RNA quality of archival FFPE kidney transplantation tissue, small quantities of this tissue can be obtained from existing paraffin blocks to provide a viable and rich biospecimen source for focused gene expression assays. In addition, reliable and reproducible gene expression evaluation can be performed on these FFPE tissues using either a QPCR-based or a barcoded-oligo approach, which provides opportunities for collaborative analytics.

Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling.

BACKGROUND: The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. METHODS: We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. RESULTS: We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). CONCLUSIONS: Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection.

Molecular and Functional Noninvasive Immune Monitoring in the ESCAPE Study for Prediction of Subclinical Renal Allograft Rejection.

BACKGROUND: Subclinical acute rejection (sc-AR) is a main cause for functional decline and kidney graft loss and may only be assessed through surveillance biopsies. METHODS: The predictive capacity of 2 novel noninvasive blood biomarkers, the transcriptional kidney Solid Organ Response Test (kSORT), and the IFN-γ enzyme-linked immunosorbent spot assay (ELISPOT) assay were assessed in the Evaluation of Sub-Clinical Acute rejection PrEdiction (ESCAPE) Study in 75 consecutive kidney transplants who received 6-month protocol biopsies. Both assays were run individually and in combination to optimize the use of these techniques to predict sc-AR risk. RESULTS: Subclinical acute rejection was observed in 22 (29.3%) patients (17 T cell-mediated subclinical rejection [sc-TCMR], 5 antibody-mediated subclinical rejection [sc-ABMR]), whereas 53 (70.7%) showed a noninjured, preserved (stable [STA]) parenchyma. High-risk (HR), low-risk, and indeterminate-risk kSORT scores were observed in 15 (20%), 50 (66.7%), and 10 (13.3%) patients, respectively. The ELISPOT assay was positive in 31 (41%) and negative in 44 (58.7%) patients. The kSORT assay showed high accuracy predicting sc-AR (specificity, 98%; positive predictive value 93%) (all sc-ABMR and 58% sc-TCMR showed HR-kSORT), whereas the ELISPOT showed high precision ruling out sc-TCMR (specificity = 70%, negative predictive value = 92.5%), but could not predict sc-ABMR, unlike kSORT. The predictive probabilities for sc-AR, sc-TCMR, and sc-ABMR were significantly higher when combining both biomarkers (area under the curve > 0.85, P < 0.001) and independently predicted the risk of 6-month sc-AR in a multivariate regression analysis. CONCLUSIONS: Combining a molecular and immune cell functional assay may help to identify HR patients for sc-AR, distinguishing between different driving alloimmune effector mechanisms.

Expression of Mitochondrial-Encoded Genes in Blood Differentiate Acute Renal Allograft Rejection.

Despite potent immunosuppression, clinical and biopsy confirmed acute renal allograft rejection (AR) still occurs in 10-15% of recipients, ~30% of patients demonstrate subclinical rejection on biopsy, and ~50% of them can show molecular inflammation, all which increase the risk of chronic dysfunction and worsened allograft outcomes. Mitochondria represent intracellular endogenous triggers of inflammation, which can regulate immune cell differentiation, and expansion and cause antigen-independent graft injury, potentially enhancing the development of acute rejection. In the present study, we investigated the role of mitochondrial DNA encoded gene expression in biopsy matched peripheral blood (PB) samples from kidney transplant recipients. Quantitative PCR was performed in 155 PB samples from 115 unique pediatric (<21 years) and adult (>21 years) renal allograft recipients at the point of AR (n = 61) and absence of rejection (n = 94) for the expression of 11 mitochondrial DNA encoded genes. We observed increased expression of all genes in adult recipients compared to pediatric recipients; separate analyses in both cohorts demonstrated increased expression during rejection, which also differentiated borderline rejection and showed an increasing pattern in serially collected samples (0-3 months prior to and post rejection). Our results provide new insights on the role of mitochondria during rejection and potentially indicate mitochondria as targets for novel immunosuppression.

Intragraft Antiviral-Specific Gene Expression as a Distinctive Transcriptional Signature for Studies in Polyomavirus-Associated Nephropathy.

BACKGROUND: Polyomavirus nephropathy (PVAN) is a common cause of kidney allograft dysfunction and loss. To identify PVAN-specific gene expression and underlying molecular mechanisms, we analyzed kidney biopsies with and without PVAN. METHODS: The study included 168 posttransplant renal allograft biopsies (T cell-mediated rejection [TCMR] = 26, PVAN = 10, normal functioning graft = 73, and interstitial fibrosis/tubular atrophy = 59) from 168 unique kidney allograft recipients. We performed gene expression assays and bioinformatics analysis to identify a set of PVAN-specific genes. Validity and relevance of a subset of these genes are validated by quantitative polymerase chain reaction and immunohistochemistry. RESULTS: Unsupervised hierarchical clustering analysis of all the biopsies revealed high similarity between PVAN and TCMR gene expression. Increased statistical stringency identified 158 and 252 unique PVAN and TCMR injury-specific gene transcripts respectively. Although TCMR-specific genes were overwhelmingly involved in immune response costimulation and TCR signaling, PVAN-specific genes were mainly related to DNA replication process, RNA polymerase assembly, and pathogen recognition receptors. A principal component analysis (PCA) using these genes further confirmed the most optimal separation between the 3 different clinical phenotypes. Validation of 4 PVAN-specific genes (RPS15, complement factor D, lactotransferrin, and nitric oxide synthase interacting protein) by quantitative polymerase chain reaction and confirmation by immunohistochemistry of 2 PVAN-specific proteins with antiviral function (lactotransferrin and IFN-inducible transmembrane 1) was done. CONCLUSIONS: In conclusion, even though PVAN and TCMR kidney allografts share great similarities on gene perturbation, PVAN-specific genes were identified with well-known antiviral properties that provide tools for discerning PVAN and AR as well as attractive targets for rational drug design.

A Computational Gene Expression Score for Predicting Immune Injury in Renal Allografts.

BACKGROUND: Whole genome microarray meta-analyses of 1030 kidney, heart, lung and liver allograft biopsies identified a common immune response module (CRM) of 11 genes that define acute rejection (AR) across different engrafted tissues. We evaluated if the CRM genes can provide a molecular microscope to quantify graft injury in acute rejection (AR) and predict risk of progressive interstitial fibrosis and tubular atrophy (IFTA) in histologically normal kidney biopsies. METHODS: Computational modeling was done on tissue qPCR based gene expression measurements for the 11 CRM genes in 146 independent renal allografts from 122 unique patients with AR (n = 54) and no-AR (n = 92). 24 demographically matched patients with no-AR had 6 and 24 month paired protocol biopsies; all had histologically normal 6 month biopsies, and 12 had evidence of progressive IFTA (pIFTA) on their 24 month biopsies. Results were correlated with demographic, clinical and pathology variables. RESULTS: The 11 gene qPCR based tissue CRM score (tCRM) was significantly increased in AR (5.68 ± 0.91) when compared to STA (1.29 ± 0.28; p < 0.001) and pIFTA (7.94 ± 2.278 versus 2.28 ± 0.66; p = 0.04), with greatest significance for CXCL9 and CXCL10 in AR (p <0.001) and CD6 (p<0.01), CXCL9 (p<0.05), and LCK (p<0.01) in pIFTA. tCRM was a significant independent correlate of biopsy confirmed AR (p < 0.001; AUC of 0.900; 95% CI = 0.705-903). Gene expression modeling of 6 month biopsies across 7/11 genes (CD6, INPP5D, ISG20, NKG7, PSMB9, RUNX3, and TAP1) significantly (p = 0.037) predicted the development of pIFTA at 24 months. CONCLUSIONS: Genome-wide tissue gene expression data mining has supported the development of a tCRM-qPCR based assay for evaluating graft immune inflammation. The tCRM score quantifies injury in AR and stratifies patients at increased risk of future pIFTA prior to any perturbation of graft function or histology.

Transcriptional Perturbations in Graft Rejection.

BACKGROUND: Understanding the regulatory interplay of relevant microRNAs (miRNAs) and messenger RNAs (mRNAs) in the rejecting allograft will result in a better understanding of the molecular pathophysiology of alloimmune injury. METHODS: One hundred sixty-seven allograft biopsies, with (n = 47) and without (n = 120) central histology for Banff scored acute rejection (AR), were transcriptionally profiled for mRNA and miRNA by whole genome microarrays and multiplexed microfluidic quantitative polymerase chain reaction, respectively. A customized database was curated (GO-Elite) and used to identify AR-specific dysregulated mRNAs and the role of perturbations of their relevant miRNAs targets during AR. RESULTS: The AR-specific changes in 1035 specific mRNAs were mirrored by AR-specific perturbations in 9 relevant miRNAs as predicted by Go-Elite and were regulated specifically by p53 and forkhead box P3. Infiltrating lymphocytes and the renal tubules drove the miRNA tissue pertubations in rejection, involving message degradation and transcriptional/translational activation. The expression of many of these miRNAs significantly associated with the intensity of the Banff-scored interstitial inflammation and tubulitis. CONCLUSIONS: There is a highly regulated interplay between specific mRNA/miRNAs in allograft rejection that drive both immune-mediated injury and tissue repair during AR.

A circulating antibody panel for pretransplant prediction of FSGS recurrence after kidney transplantation.

Recurrence of focal segmental glomerulosclerosis (rFSGS) after kidney transplantation is a cause of accelerated graft loss. To evaluate pathogenic antibodies (Abs) in rFSGS, we processed 141 serum samples from 64 patients with and without primary rFSGS and 34 non-FSGS control patients transplanted at four hospitals. We screened about 9000 antigens in pretransplant sera and selected 10 Abs targeting glomerular antigens for enzyme-linked immunosorbent assay (ELISA) validation. A panel of seven Abs (CD40, PTPRO, CGB5, FAS, P2RY11, SNRPB2, and APOL2) could predict posttransplant FSGS recurrence with 92% accuracy. Pretransplant elevation of anti-CD40 Ab alone had the best correlation (78% accuracy) with rFSGS risk after transplantation. Epitope mapping of CD40 with customized peptide arrays and rFSGS sera demonstrated altered immunogenicity of the extracellular CD40 domain in rFSGS. Immunohistochemistry of CD40 demonstrated a differential expression in FSGS compared to non-FSGS controls. Anti-CD40 Abs purified from rFSGS patients were particularly pathogenic in human podocyte cultures. Injection of anti-CD40/rFSGS Ab enhanced suPAR (soluble urokinase receptor)-mediated proteinuria in wild-type mice, yet no sensitizing effect was noted in mice deficient in CD40 or in wild-type mice that received blocking Ab to CD40. In conclusion, a panel of seven Abs can help identify primary FSGS patients at high risk of recurrence before transplantation. Intrarenal CD40 (and possibly other specific glomerular antigens) is an important contributor to FSGS disease pathogenesis. Human trials of anti-CD40 therapies are warranted to evaluate their efficacy for preventing rFSGS and improving graft survival.

Significance and suppression of redundant IL17 responses in acute allograft rejection by bioinformatics based drug repositioning of fenofibrate.

Despite advanced immunosuppression, redundancy in the molecular diversity of acute rejection (AR) often results in incomplete resolution of the injury response. We present a bioinformatics based approach for identification of these redundant molecular pathways in AR and a drug repositioning approach to suppress these using FDA approved drugs currently available for non-transplant indications. Two independent microarray data-sets from human renal allograft biopsies (n = 101) from patients on majorly Th1/IFN-y immune response targeted immunosuppression, with and without AR, were profiled. Using gene-set analysis across 3305 biological pathways, significant enrichment was found for the IL17 pathway in AR in both data-sets. Recent evidence suggests IL17 pathway as an important escape mechanism when Th1/IFN-y mediated responses are suppressed. As current immunosuppressions do not specifically target the IL17 axis, 7200 molecular compounds were interrogated for FDA approved drugs with specific inhibition of this axis. A combined IL17/IFN-y suppressive role was predicted for the antilipidemic drug Fenofibrate. To assess the immunregulatory action of Fenofibrate, we conducted in-vitro treatment of anti-CD3/CD28 stimulated human peripheral blood cells (PBMC), and, as predicted, Fenofibrate reduced IL17 and IFN-γ gene expression in stimulated PMBC. In-vivo Fenofibrate treatment of an experimental rodent model of cardiac AR reduced infiltration of total leukocytes, reduced expression of IL17/IFN-y and their pathway related genes in allografts and recipients' spleens, and extended graft survival by 21 days (p<0.007). In conclusion, this study provides important proof of concept that meta-analyses of genomic data and drug databases can provide new insights into the redundancy of the rejection response and presents an economic methodology to reposition FDA approved drugs in organ transplantation.