Functional genomic analysis of peripheral blood during early acute renal allograft rejection

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.

Identification of Candidate Biomarkers for Transplant Rejection from Transcriptome Data: A Systematic Review

BACKGROUND

Traditional methods for rejection control in transplanted patients are considered invasive, risky, and prone to sampling errors. Using molecular biomarkers as an alternative protocol to biopsies, for monitoring rejection may help to mitigate some of these problems, increasing the survival rates and well-being of patients. Recent advances in omics technologies provide an opportunity for screening new molecular biomarkers to identify those with clinical utility.

OBJECTIVE

This systematic literature review (SLR) aimed to summarize existing evidence derived from large-scale expression profiling regarding differentially expressed mRNA and miRNA in graft rejection, highlighting potential molecular biomarkers in transplantation.

METHODS

The study was conducted following PRISMA methodology and the BiSLR guide for performing SLR in bioinformatics. PubMed, ScienceDirect, and EMBASE were searched for publications from January 2001 to January 2018, and studies (i) aiming at the identification of transplant rejection biomarkers, (ii) including human subjects, and (iii) applying methodologies for differential expression analysis from large-scale expression profiling were considered eligible. Differential expression patterns reported for genes and miRNAs in rejection were summarized from both cross-organ and organ-specific perspectives, and pathways enrichment analysis was performed for candidate biomarkers to interrogate their functional role in transplant rejection.

RESULTS

A total of 821 references were collected, resulting in 604 studies after removal of duplicates. After application of inclusion and exclusion criteria, 33 studies were included in our analysis. Among the 1517 genes and 174 miRNAs identifed, CXCL9, CXCL10, STAT1, hsa-miR-142-3p, and hsa-miR-155 appeared to be particularly promising as biomarkers in transplantation, with an increased expression associated with transplant rejection in multiple organs. In addition, hsa-miR-28-5p was consistently decreased in samples taken from rejected organs.

CONCLUSION

Despite the need for further research to fill existing knowledge gaps, transcriptomic technologies have a relevant role in the discovery of accurate biomarkers for transplant rejection diagnostics. Studies have reported consistent evidence of differential expression associated with transplant rejection, although issues such as experimental heterogeneity hinder a more systematic characterization of observed molecular changes. Special attention has been giving to large-scale mRNA expression profiling in rejection, whereas there is still room for improvements in the characterization of miRnome in this condition.

PROSPERO REGISTRATION NUMBER

CRD42018083321.

Establishing Biomarkers in Transplant Medicine: A Critical Review of Current Approaches

Although the management of kidney transplant recipients has greatly improved over recent decades, the assessment of individual risks remains highly imperfect. Individualized strategies are necessary to recognize and prevent immune complications early and to fine-tune immunosuppression, with the overall goal to improve patient and graft outcomes. This review discusses current biomarkers and their limitations, and recent advancements in the field of noninvasive biomarker discovery. A wealth of noninvasive monitoring tools has been suggested that use easily accessible biological fluids such as urine and blood, allowing frequent and sequential assessments of recipient's immune status. This includes functional cell-based assays and the evaluation of molecular expression on a wide spectrum of platforms. Nevertheless, the translation and validation of exploratory findings and their implementation into standard clinical practice remain challenging. This requires dedicated prospective interventional trials demonstrating that the use of these biomarkers avoids invasive procedures and improves patient or transplant outcomes.

Novel multivariate methods for integration of genomics and proteomics data: applications in a kidney transplant rejection study

Multi-omics research is a key ingredient of data-intensive life sciences research, permitting measurement of biological molecules at different functional levels in the same individual. For a complete picture at the biological systems level, appropriate statistical techniques must however be developed to integrate different 'omics' data sets (e.g., genomics and proteomics). We report here multivariate projection-based analyses approaches to genomics and proteomics data sets, using the case study of and applications to observations in kidney transplant patients who experienced an acute rejection event (n=20) versus non-rejecting controls (n=20). In this data sets, we show how these novel methodologies might serve as promising tools for dimension reduction and selection of relevant features for different analytical frameworks. Unsupervised analyses highlighted the importance of post transplant time-of-rejection, while supervised analyses identified gene and protein signatures that together predicted rejection status with little time effect. The selected genes are part of biological pathways that are representative of immune responses. Gene enrichment profiles revealed increases in innate immune responses and neutrophil activities and a depletion of T lymphocyte related processes in rejection samples as compared to controls. In all, this article offers candidate biomarkers for future detection and monitoring of acute kidney transplant rejection, as well as ways forward for methodological advances to better harness multi-omics data sets.

Two-stage, in silico deconvolution of the lymphocyte compartment of the peripheral whole blood transcriptome in the context of acute kidney allograft rejection

Acute rejection is a major complication of solid organ transplantation that prevents the long-term assimilation of the allograft. Various populations of lymphocytes are principal mediators of this process, infiltrating graft tissues and driving cell-mediated cytotoxicity. Understanding the lymphocyte-specific biology associated with rejection is therefore critical. Measuring genome-wide changes in transcript abundance in peripheral whole blood cells can deliver a comprehensive view of the status of the immune system. The heterogeneous nature of the tissue significantly affects the sensitivity and interpretability of traditional analyses, however. Experimental separation of cell types is an obvious solution, but is often impractical and, more worrying, may affect expression, leading to spurious results. Statistical deconvolution of the cell type-specific signal is an attractive alternative, but existing approaches still present some challenges, particularly in a clinical research setting. Obtaining time-matched sample composition to biologically interesting, phenotypically homogeneous cell sub-populations is costly and adds significant complexity to study design. We used a two-stage, in silico deconvolution approach that first predicts sample composition to biologically meaningful and homogeneous leukocyte sub-populations, and then performs cell type-specific differential expression analysis in these same sub-populations, from peripheral whole blood expression data. We applied this approach to a peripheral whole blood expression study of kidney allograft rejection. The patterns of differential composition uncovered are consistent with previous studies carried out using flow cytometry and provide a relevant biological context when interpreting cell type-specific differential expression results. We identified cell type-specific differential expression in a variety of leukocyte sub-populations at the time of rejection. The tissue-specificity of these differentially expressed probe-set lists is consistent with the originating tissue and their functional enrichment consistent with allograft rejection. Finally, we demonstrate that the strategy described here can be used to derive useful hypotheses by validating a cell type-specific ratio in an independent cohort using the nanoString nCounter assay.

Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion

Background

The molecular profile of circulating blood can reflect physiological and pathological events occurring in other tissues and organs of the body and delivers a comprehensive view of the status of the immune system. Blood has been useful in studying the pathobiology of many diseases. It is accessible and easily collected making it ideally suited to the development of diagnostic biomarker tests. The blood transcriptome has a high complement of globin RNA that could potentially saturate next-generation sequencing platforms, masking lower abundance transcripts. Methods to deplete globin mRNA are available, but their effect has not been comprehensively studied in peripheral whole blood RNA-Seq data. In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples.

Results

We compared technical and biological replicates having undergone globin depletion or not and found that the experimental globin depletion protocol employed removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Differential expression analysis revealed thousands of genes significantly up-regulated as a result of globin depletion. In addition, globin depletion resulted in the down-regulation of genes involved in both iron and zinc metal ion bonding.

Conclusions

Globin depletion appears to meaningfully improve the quality of peripheral whole blood RNA-Seq data, and may improve our ability to detect true biological variation. Some concerns remain, however. Key amongst them the significant reduction in RNA yields following globin depletion. More generally, our investigation of technical and biological variation with and without globin depletion finds that high-throughput sequencing by RNA-Seq is highly reproducible within a large dynamic range of detection and provides an accurate estimation of RNA concentration in peripheral whole blood. High-throughput sequencing is thus a promising technology for whole blood transcriptomics and biomarker discovery.

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated with Acute Renal Allograft Rejection

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature.

Longitudinal analysis of whole blood transcriptomes to explore molecular signatures associated with acute renal allograft rejection

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature.

Analysis of anti-HLA antibodies in sensitized kidney transplant candidates subjected to desensitization with intravenous immunoglobulin and rituximab

BACKGROUND

Preexisting donor-specific antibodies against human leukocyte antigens are major risk factors for acute antibody-mediated and chronic rejection of kidney transplant grafts. Immunomodulation (desensitization) protocols may reduce antibody concentration and improve the success of transplant. We investigated the effect of desensitization with intravenous immunoglobulin and rituximab on the antibody profile in highly sensitized kidney transplant candidates.

METHODS

In 31 transplant candidates (calculated panel-reactive antibody [cPRA], 34%-99%), desensitization included intravenous immunoglobulin on days 0 and 30 and a single dose of rituximab on day 15. Anti-human leukocyte antigen antibodies were analyzed before and after desensitization.

RESULTS

Reduction of cPRA from 25% to 50% was noted for anti-class I (5 patients, within 20-60 days) and anti-class II (3 patients, within 10-20 days) antibodies. After initial reduction of cPRA, the cPRA increased within 120 days. In 24 patients, decrease in mean fluorescence intensity of antibodies by more than 50% was noted at follow-up, but there was no reduction of cPRA. Rebound occurred in 65% patients for anti-class I antibodies at 350 days and anti-class II antibodies at 101 to 200 days. Probability of rebound effect was higher in patients with mean fluorescence intensity of more than 10,700 before desensitization, anti-class II antibodies, and history of previous transplant.

CONCLUSIONS

The desensitization protocol had limited efficacy in highly sensitized kidney transplant candidate because of the short period with antibody reduction and high frequency of rebound effect.

T lymphocyte abnormalities in juvenile systemic sclerosis patients

Multi-center evaluations of pediatric patients with juvenile systemic sclerosis (jSSc) have suggested that the pathogenesis of jSSc may differ from that of systemic sclerosis (SSc) in adult patients. Therefore, we undertook to identify abnormalities in the T lymphocytes of jSSc patients and to determine if they differed from the abnormalities reported in the T lymphocytes of adult SSc patients. We identified decreases in the frequency of resting regulatory T lymphocytes and an increased frequency of CD45RA expressing effector memory (EMRA) CD4 T lymphocytes, which were characterized by an increased frequency of CCR7 protein expressing cells. Neither the increases in the EMRA subpopulation nor the increased CCR7 protein expression have been reported in adult SSc patients. The decrease in resting regulatory T lymphocytes in jSSc patients may permit the expansion of the disease initiating CD4 T lymphocytes present in the CCR7 expressing EMRA CD4 T lymphocyte subpopulation.

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers

Background

Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble?

Results

The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity.

Conclusion

Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway.

Lack of effect in desensitization with intravenous immunoglobulin and rituximab in highly sensitized patients

BACKGROUND

We conducted a prospective cohort study in highly sensitized kidney transplant candidates with a calculated panel reactive antibody (cPRA) greater than 50% and on the deceased-donor waiting list for more than 5 years to investigate the effects of intravenous immunoglobulin (IVIG) and rituximab treatment.

METHODS

Desensitization protocol included two doses of IVIG (2 g/kg, max 120 g each dose) and a single dose of rituximab (375 mg/m(2)). Patients were followed up monthly by Luminex single antigen beads. Whole blood gene expression profiles were studied by Affymetrix Human 1.0 ST GeneChips before and after treatment.

RESULTS

Forty patients were eligible for desensitization treatment. Thirteen of these patients agreed to participate, and 11 completed the treatment. After a mean follow-up of 334 ± 82 days, two desensitized patients (18%) received a kidney transplant compared with 14 patients (52%) in the nondesensitized group. Comparing with 14 patients who received transplants without any desensitization treatment, desensitized patients showed higher class I (99% vs. 80%) and class II (98% vs. 69%) cPRA levels and more unacceptable antigens (32 vs. 8). Desensitization treatment did not lead to any significant reduction in patients' class I and II cPRA levels and any change in the mean number of unacceptable antigens or their mean fluorescence intensity values. Whole blood gene expression analysis by microarrays demonstrated down-regulation of immunoglobulin and B-cell-associated transcripts after treatment.

CONCLUSION

These results suggested that pretransplant desensitization with IVIG and rituximab was not successful in highly sensitized kidney transplant candidates with cPRA levels higher than 90%.

White blood cell differentials enrich whole blood expression data in the context of acute cardiac allograft rejection

Acute cardiac allograft rejection is a serious complication of heart transplantation. Investigating molecular processes in whole blood via microarrays is a promising avenue of research in transplantation, particularly due to the non-invasive nature of blood sampling. However, whole blood is a complex tissue and the consequent heterogeneity in composition amongst samples is ignored in traditional microarray analysis. This complicates the biological interpretation of microarray data. Here we have applied a statistical deconvolution approach, cell-specific significance analysis of microarrays (csSAM), to whole blood samples from subjects either undergoing acute heart allograft rejection (AR) or not (NR). We identified eight differentially expressed probe-sets significantly correlated to monocytes (mapping to 6 genes, all down-regulated in ARs versus NRs) at a false discovery rate (FDR) ≤ 15%. None of the genes identified are present in a biomarker panel of acute heart rejection previously published by our group and discovered in the same data***.

Gene expression profiling in organ transplantation

Aim of Review. Huge effort is being made among the transplant community investigating novel biomarkers that enable transplant clinicians to identify patients at risk for allograft rejection or those who will develop tolerance so that immunosuppression could be safely minimized or even ideally withdrawn. Despite the important advances achieved in the identification of several potential biomarkers of tolerance, rejection, or both, validation and demonstration of their clinical utility still needs to be tested, which will need international cooperative networks. It is important to note that the reproducibility of differently expressed genes might be affected by many factors such as gene ranking and selection methods, inherent differences between types, and the choice of thresholds. However, because microarray analyses are expensive and time consuming and their statistical evaluation is often very difficult, gene expression analysis using the RTPCR method is nowadays recommended. Conclusions. In the field of organ transplantation, gene-expression-based decision might help in improving patient and graft outcome and there are a multitude of studies showing that gene-expression profiling is feasible.

Therapeutic cancer vaccines and translating vaccinomics science to the global health clinic: emerging applications toward proof of concept

As vaccines evolve to be a more common treatment for some cancers, further research is needed to improve the process of developing vaccines and assessing response to treatment. Vaccinomics involves a wide-ranging integration of multiple high throughput technologies including transcriptional, translational, and posttranslational population-based assessments of the human genome, transcriptome, proteome, and immunome. Vaccinomics combines the fields of immunogenetics, immunogenomics, immunoproteomics, and basic immunology to create vaccines that are tailor made to an individual or groups of individuals. This broad range of omics applications to tumor immunology includes antigen discovery, diagnostic biomarkers, cancer vaccine development, predictors of immune response, and clinical response biomarkers. These technologies have aided in the advancement of cancer vaccine development, as illustrated in examples including NY-ESO-1 originally defined by SEREX, and HER2/neu peptides analyzed via high-throughput epitope prediction methods. As technology improves, it presents an opportunity to improve cancer immunotherapy on a global scale, and attention must also be given to utilize these high-throughput methods for the understanding of cancer and immune signatures across populations.

Alternatively Expressed Genes Identified in the CD4+ T Cells of Allograft Rejection Mice

Allograft rejection is a leading cause for the failure of allotransplantation. CD4+ T cells play critical roles in this process. The identification of genes that alternatively expressed in CD4+ T cells during allograft rejection will provide critical information for studying the mechanism of allograft rejection, finding specific gene markers for monitoring, predicting allograft rejection, and opening new ways to regulate and prevent allograft rejection. Here, we established allograft and isograft transplantation models by adoptively transferring wild-type BALB/c mouse CD4+ T cells into severe combined immunodeficient (SCID) mice with a C57BL/6 or BALB/c mouse skin graft. Using the whole transcriptome sequencing-based serial analysis of gene expression (SAGE) technology, we identified 97 increasingly and 88 decreasingly expressed genes that may play important roles in allograft rejection and tolerance. Functional classification of these genes shows that apoptosis, transcription regulation, cell growth and maintenance, and signal transduction are among the frequently changed functional groups. This study provides a genome-wide view for the candidate genes of CD4+ T cells related to allotransplantation, and this report is a good resource for further microarray studies and for identifying the specific markers that are associated with clinical organ transplantations.

Advances of genomic science and systems biology in renal transplantation: a review

The diagnosis of rejection in kidney transplant patients is based on histologic classification of a graft biopsy. The current “gold standard” is the Banff 97 criteria; however, there are several limitations in classifying rejection based on biopsy samples. First, a biopsy involves an invasive procedure. Second, there is significant variance among blinded pathologists in the interpretation of a biopsy. And third, there is also variance between the histology and the molecular profiles of a biopsy. To increase the positive predictive value of classifiers of rejection, a Banff committee is developing criteria that integrate histologic and molecular data into a unified classifier that could diagnose and prognose rejection. To develop the most appropriate molecular criteria, there have been studies by multiple groups applying omics technologies in attempts to identify biomarkers of rejection. In this review, we discuss studies using genome-wide data sets of the transcriptome and proteome to investigate acute rejection, chronic allograft dysfunction, and tolerance. We also discuss studies which focus on genetic biomarkers in urine and peripheral blood, which will provide clinicians with minimally invasive methods for monitoring transplant patients. We also discuss emerging technologies, including whole-exome sequencing and RNA-Seq and new bioinformatic and systems biology approaches, which should increase the ability to develop both biomarkers and mechanistic understanding of the rejection process.

Whole blood biomarkers of acute cardiac allograft rejection: double-crossing the biopsy

BACKGROUND

Acute rejection is still a significant barrier to long-term survival of the allograft. Current acute rejection diagnostic methods are not specific enough or are invasive. There have been a number of studies that have explored the blood or the biopsy to discover genomic biomarkers of acute rejection; however, none of the studies to date have used both.

METHODS

We analyzed endomyocardial biopsy tissue and whole blood-derived messenger RNA from 11 acute rejection and 20 nonrejection patients using Affymetrix Human Genome U133 Plus 2.0 chips. We used a novel approach and gained insight into the biology of rejection based on gene expression in the biopsy, and applied this knowledge to the blood analysis to identify novel blood biomarkers.

RESULTS

We identified probesets that are differentially expressed between acute rejection and nonrejection patients in the biopsy and blood, and developed three biomarker panels: (1) based on biopsy-only (area under the curve=0.85), (2) based on biopsy-targeted whole blood (area under the curve=0.83), and (3) based on whole blood-only (area under the curve=0.60) analyses.

CONCLUSIONS

Most of the probesets replicated between biopsy and blood are regulated in opposite direction between the two sources of information. We also observed that the biopsy-targeted blood biomarker discovery approach can improve performance of the biomarker panel. The biomarker panel developed using this targeted approach is able to diagnose acute cardiac allograft rejection almost as well as the biopsy-only based biomarker panel.

CXCL10 and CXCL13 Expression were highly up-regulated in peripheral blood mononuclear cells in acute rejection and poor response to anti-rejection therapy

BACKGROUND

Acute rejection is still one of the main complications which enhances the cost and the risk to renal graft failure. Chemokines, interacting with respective receptors, can recruit leukocytes into grafts and mediate allograft rejection. In this study, we aimed to analyze gene expression of chemokines including CCL5/RANTES, CXCL10/IP-10, CXCL13/BCA-1, and receptors of CCR5, CXCR3, CXCR5 in peripheral blood mononuclear cells (PBMCs) during acute renal allograft rejection

METHODS

Gene expression of all these chemokines and receptors in PBMCs were analyzed by real-time PCR from 14 stable recipients, 32 biopsy-proven acute rejection (AR), and 5 acute tubular necrosis (ATN).

RESULTS

Gene expression of CCL5, CXCL10, CXCL13, and CCR5 were up-regulated both in AR and ATN group compared to stable recipients (fold change>2, P<0.05). Serum creatinine recovered to baseline level after anti-rejection therapy was defined as AR-sensitive and creatinine maintained above 200 μmol/L as AR-resistant. Expression of CXCL10 and CXCL13 were 5.98-, 2.94-, and 20.5, 10.8-fold change in AR-resistant and AR-sensitive compared to stable recipients, respectively. The expression of CXCL10 and CXCL13 was a twofold change in AR-resistant compared to AR-sensitive recipients (P<0.05). Five out of ten AR-resistant recipients lost graft function in the follow-up.

CONCLUSION

CXCL10 and CXCL13 expression were highly up-regulated in PBMCs in acute renal allograft rejection, especially in poor response to anti-rejection therapy and detrimental prognosis.

Feasibility of diagnosing renal allograft dysfunction by oligonucleotide array: Gene expression profile correlates with histopathology

BACKGROUND

Effective non-invasive monitoring method to tell histopathology is a big challenge in renal transplantation.

METHODS

We used 70-mer long oligonucleotide array with 449 immune related genes to determine gene expression profiles of peripheral blood mononuclear cells (PBMCs) under different immune status including stable renal function (TX), acute tubular necrosis (ATN), biopsy conformed acute rejection (AR), clinical rejection with pathology of borderline changes (BL), clinical rejection without biopsy proven/presumed rejection (PR) and renal dysfunction without rejection (NR).

RESULTS

Distinct molecular expression signatures in each group were found to correlate with histopathology. And we concluded that B cell chemokine CXCL13 and mast cell may play a role in renal allograft rejection through significant difference analysis and functional pathway analysis.

CONCLUSIONS

It provides a potential non-invasive method for monitoring renal allograft function and immune status of renal transplant recipients.

Immune monitoring of pancreatic islet graft: towards a better understanding, detection and treatment of harmful events

IMPORTANCE OF THE FIELD

Long-term clinical outcomes of islet transplantation are hampered by rejection and recurrence of autoimmunity, which lead to a gradual decrease in islet function usually taking place over the first five years after transplantation. An accurate monitoring strategy could allow for the detection and treatment of harmful immune events, potentially resulting in higher rates of insulin-independence.

AREAS COVERED IN THIS REVIEW

This article provides a critical review of the various assays currently available for the assessment of allo- and autoimmunity both prior to and after islet transplantation. The accuracy in predicting clinical outcome is specifically addressed.

WHAT THE READER WILL GAIN

Most current tests based on the assessment of allo- and auto-immune antibody are of minimal help in clinical practice. Cell-based tests (including the assessment of cytotoxic T lymphocyte precursors, proliferation tests, enzyme-linked immunospot) have the potential to allow earlier and more accurate detection of harmful events.

TAKE HOME MESSAGE

A specific and accurate immune monitoring has the potential to significantly improve islet transplant outcomes. The development and use of such tests (favouring cell-based tests) should be promoted.

Deconvoluting post-transplant immunity: cell subset-specific mapping reveals pathways for activation and expansion of memory T, monocytes and B cells

A major challenge for the field of transplantation is the lack of understanding of genomic and molecular drivers of early post-transplant immunity. The early immune response creates a complex milieu that determines the course of ensuing immune events and the ultimate outcome of the transplant. The objective of the current study was to mechanistically deconvolute the early immune response by purifying and profiling the constituent cell subsets of the peripheral blood. We employed genome-wide profiling of whole blood and purified CD4, CD8, B cells and monocytes in tandem with high-throughput laser-scanning cytometry in 10 kidney transplants sampled serially pre-transplant, 1, 2, 4, 8 and 12 weeks. Cytometry confirmed early cell subset depletion by antibody induction and immunosuppression. Multiple markers revealed the activation and proliferative expansion of CD45RO⁺CD62L⁻ effector memory CD4/CD8 T cells as well as progressive activation of monocytes and B cells. Next, we mechanistically deconvoluted early post-transplant immunity by serial monitoring of whole blood using DNA microarrays. Parallel analysis of cell subset-specific gene expression revealed a unique spectrum of time-dependent changes and functional pathways. Gene expression profiling results were validated with 157 different probesets matching all 65 antigens detected by cytometry. Thus, serial blood cell monitoring reflects the profound changes in blood cell composition and immune activation early post-transplant. Each cell subset reveals distinct pathways and functional programs. These changes illuminate a complex, early phase of immunity and inflammation that includes activation and proliferative expansion of the memory effector and regulatory cells that may determine the phenotype and outcome of the kidney transplant.

Molecular diagnostics in transplantation

The past few decades are characterized by an explosive evolution of genetics and molecular cell biology. Advances in chemistry and engineering have enabled increased data throughput, permitting the study of complete sets of molecules with increasing speed and accuracy using techniques such as genomics, transcriptomics, proteomics, and metabolomics. Prediction of long-term outcomes in transplantation is hampered by the absence of sufficiently robust biomarkers and a lack of adequate insight into the mechanisms of acute and chronic alloimmune injury and the adaptive mechanisms of immunological quiescence that may support transplantation tolerance. Here, we discuss some of the great opportunities that molecular diagnostic tools have to offer both basic scientists and translational researchers for bench-to-bedside clinical application in transplantation medicine, with special focus on genomics and genome-wide association studies, epigenetics (DNA methylation and histone modifications), gene expression studies and transcriptomics (including microRNA and small interfering RNA studies), proteomics and peptidomics, antibodyomics, metabolomics, chemical genomics and functional imaging with nanoparticles. We address the challenges and opportunities associated with the newer high-throughput sequencing technologies, especially in the field of bioinformatics and biostatistics, and demonstrate the importance of integrative approaches. Although this Review focuses on transplantation research and clinical transplantation, the concepts addressed are valid for all translational research.

Proteomic signatures in plasma during early acute renal allograft rejection

Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long term graft survival. Plasma biomarkers may offer an important option for post-transplant monitoring and permit timely and effective therapeutic intervention to minimize graft damage. This case-control discovery study (n = 32) used isobaric tagging for relative and absolute protein quantification (iTRAQ) technology to quantitate plasma protein relative concentrations in precise cohorts of patients with and without biopsy-confirmed acute rejection (BCAR). Plasma samples were depleted of the 14 most abundant plasma proteins to enhance detection sensitivity. A total of 18 plasma proteins that encompassed processes related to inflammation, complement activation, blood coagulation, and wound repair exhibited significantly different relative concentrations between patient cohorts with and without BCAR (p value <0.05). Twelve proteins with a fold-change >or=1.15 were selected for diagnostic purposes: seven were increased (titin, lipopolysaccharide-binding protein, peptidase inhibitor 16, complement factor D, mannose-binding lectin, protein Z-dependent protease and beta(2)-microglobulin) and five were decreased (kininogen-1, afamin, serine protease inhibitor, phosphatidylcholine-sterol acyltransferase, and sex hormone-binding globulin) in patients with BCAR. The first three principal components of these proteins showed clear separation of cohorts with and without BCAR. Performance improved with the inclusion of sequential proteins, reaching a primary asymptote after the first three (titin, kininogen-1, and lipopolysaccharide-binding protein). Longitudinal monitoring over the first 3 months post-transplant based on ratios of these three proteins showed clear discrimination between the two patient cohorts at time of rejection. The score then declined to baseline following treatment and resolution of the rejection episode and remained comparable between cases and controls throughout the period of quiescent follow-up. Results were validated using ELISA where possible, and initial cross-validation estimated a sensitivity of 80% and specificity of 90% for classification of BCAR based on a four-protein ELISA classifier. This study provides evidence that protein concentrations in plasma may provide a relevant measure for the occurrence of BCAR and offers a potential tool for immunologic monitoring.

Development of a cross-platform biomarker signature to detect renal transplant tolerance in humans

Identifying transplant recipients in whom immunological tolerance is established or is developing would allow an individually tailored approach to their posttransplantation management. In this study, we aimed to develop reliable and reproducible in vitro assays capable of detecting tolerance in renal transplant recipients. Several biomarkers and bioassays were screened on a training set that included 11 operationally tolerant renal transplant recipients, recipient groups following different immunosuppressive regimes, recipients undergoing chronic rejection, and healthy controls. Highly predictive assays were repeated on an independent test set that included 24 tolerant renal transplant recipients. Tolerant patients displayed an expansion of peripheral blood B and NK lymphocytes, fewer activated CD4+ T cells, a lack of donor-specific antibodies, donor-specific hyporesponsiveness of CD4+ T cells, and a high ratio of forkhead box P3 to alpha-1,2-mannosidase gene expression. Microarray analysis further revealed in tolerant recipients a bias toward differential expression of B cell-related genes and their associated molecular pathways. By combining these indices of tolerance as a cross-platform biomarker signature, we were able to identify tolerant recipients in both the training set and the test set. This study provides an immunological profile of the tolerant state that, with further validation, should inform and shape drug-weaning protocols in renal transplant recipients.