Proteomic research in renal transplantation

Targeted Proteomic Analysis Detects Acute T Cell-Mediated Kidney Allograft Rejection in Belatacept-Treated Patients

BACKGROUND

There is an unmet need for reliable minimally invasive diagnostic biomarkers for immunological allograft monitoring and for the detection of acute kidney transplant rejection. Here, targeted proteomic analysis was applied to compare 92 proteins in sera of belatacept-treated patients who had biopsy-proven, acute T-cell-mediated rejection (aTCMR) with patients without aTCMR.

METHODS

Proximity extension immunoassay was used to measure 92 inflammation-related protein concentrations in the prerejection and rejection sera of 11 patients with aTCMR and 9 patients without aTCMR. This assay uses 2 matched oligonucleotide-labeled antibody probes for each protein and polymerase chain reaction to measure normalized protein expression values.

RESULTS

Five proteins (CD5, CD8A, NCR1, TNFRSF4, and TNFRSF9) were expressed significantly higher in samples with aTCMR compared with samples without aTCMR (adjusted P-value < 0.014) and had a good predictive capacity for aTCMR [area under the curve in a receiver-operator curve ranged from 0.83 to 0.91 (P < 0.014)]. These proteins are associated with CD8 cytotoxic T-cell and NK cell functions. Nonhierarchical clustering analysis showed distinct clustering of samples with aTCMR and samples without aTCMR. This clustering was not found in prerejection samples (1 month after transplantation). In prerejection samples, IFN-γ was expressed at a significantly lower level (normalized protein expression value median -0.15, interquartile range: -0.27 to 0.04) than in samples of patients without rejection (median 0.13, interquartile range: -0.07 to 0.15, adjusted P-value = 0.00367).

CONCLUSIONS

Targeted proteomic analysis with proximity extension immunoassay is a promising minimally invasive technique to diagnose aTCMR in kidney transplant recipients.

Plasma proteomics for the assessment of acute renal transplant rejection

Renal transplant is the best treatment for patients with chronical kidney disease however acute graft rejection is the major impediment to success in renal transplantation leading to loss of the organ the first year after transplantation. The aim of this study was to identify plasma proteins that may be early biomarkers of acute rejection of renal allograft, developing a diagnostic model that avoids the loss of the transplanted organ. Shotgun proteomics (LC-MS/MS) method was used to analyze a set of thirty-one plasma samples, including 06 from patients with acute graft rejection after transplantation (rejection group/Rej-group) and twenty-five from renal transplant patients with stable renal graft function (control group/Ct-group). As results nineteen proteins were upregulated in the rejection group compared to the control group, and two proteins were downregulated; and three were present exclusively in the rejection group. After analysis, we selected four proteins that were related to the acute phase response and that were strongly associated with each other: they are alpha-1 antitrypsin (A1AT), alpha-2 antiplasmin (A2AP), serum amyloid A (SAA) and apolipoprotein CIII (APOC3). We think that simultaneous monitoring of SAA and APOC3 can provide insights into a broad profile of signaling proteins and is highly valuable for the early detection of a possible acute renal graft rejection.

STATEMENT OF SIGNIFICANCE OF THE STUDY

In this study we did plasma shotgun patients with and without acute rejection of renal allograft. In a clinical setting an acute rejection is typically suspected upon an increase in plasma creatinine and renal biopsy. But these methods are late and unspecific; sometimes the rejection process is already advanced when there is an increase in serum creatinine. Therefore, it is necessary to find proteins that can predict the allograft rejection process. In our study were able to identify changes in the concentration of plasma protein belonging to a network of protein interaction processes the acute phase response. We believe, therefore, that development of a routine diagnosis of these proteins can detect early acute rejection of renal allograft process, thus preventing its loss.

Immunologic monitoring in kidney transplant recipients

Transplant biopsy has always been the gold standard for assessing the immune response to a kidney allograft (Chandraker A: Diagnostic techniques in the work-up of renal allograft dysfunction-an update. Curr Opin Nephrol Hypertens 8:723-728, 1999). A biopsy is not without risk and is unable to predict rejection and is only diagnostic once rejection has already occurred. However, in the past two decades, we have seen an expansion in assays that can potentially put an end to the "drug level" era, which until now has been one of the few tools available to clinicians for monitoring the immune response. A better understanding of the mechanisms of rejection and tolerance, and technological advances has led to the development of new noninvasive methods to monitor the immune response. In this article, we discuss these new methods and their potential uses in renal transplant recipients.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

Proteomic profiling of heterotopic heart-transplanted rats using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry: potential biomarkers and drug targets

OBJECTIVE

Methotrexate and rapamycin demonstrate an additive effect in prolonging cardiac allograft survival in a major histocompatibility complex mismatched rat model. The present study aimed to identify functional proteins involved in the allograft-protective effects of these two agents and reveal potential diagnostic markers for treating rejection.

METHODS

Serum samples from heterotopic heart-transplanted LEW(RT-1(1)) rats (either without immunosuppressive treatment or treated with methotrexate alone, rapamycin alone, or methotrexate and rapamycin combined) were analysed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein profiles obtained using a weak cation exchange ProteinChip® CM-10 array were then analysed using ProteinChip® Software.

RESULTS

Of 28 rejection-related proteins identified, isoelectric point and mass information from two potential candidate proteins matched information from the UniProtKB/Swiss-prot database, suggesting them to be complement component C3f fragment and complement component 4A (C4A, anaphylatoxin).

CONCLUSIONS

Proteomic analysis revealed 28 proteins as potential diagnostic markers of tissue rejection. Of these, 11 proteins may represent targets relating to the additive effects of methotrexate and rapamycin. Two protein peaks, with mass-to-charge ratios of 1950 Da and 8577 Da, may have potential for use in post-transplant diagnosis of rejection.

Proteomics and metabolomics in renal transplantation-quo vadis?

The improvement of long-term transplant organ and patient survival remains a critical challenge following kidney transplantation. Proteomics and biochemical profiling (metabolomics) may allow for the detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. Hence, these analytical strategies hold the promise to detect and monitor disease processes and drug effects before histopathological and pathophysiological changes occur. In addition, they will identify enriched populations and enable individualized drug therapy. However, proteomics and metabolomics have not yet lived up to such high expectations. Renal transplant patients are highly complex, making it difficult to establish cause-effect relationships between surrogate markers and disease processes. Appropriate study design, adequate sample handling, storage and processing, quality and reproducibility of bioanalytical multi-analyte assays, data analysis and interpretation, mechanistic verification, and clinical qualification (=establishment of sensitivity and specificity in adequately powered prospective clinical trials) are important factors for the success of molecular marker discovery and development in renal transplantation. However, a newly developed and appropriately qualified molecular marker can only be successful if it is realistic that it can be implemented in a clinical setting. The development of combinatorial markers with supporting software tools is an attractive goal.

Apolipoprotein A1 and C-terminal fragment of α-1 antichymotrypsin are candidate plasma biomarkers associated with acute renal allograft rejection

BACKGROUND

Current diagnostic methods of renal allograft rejection are neither sensitive nor specific. Needle biopsies are invasive and associated with patient morbidity. Thus, it is desirable to develop noninvasive tests to predict and diagnose rejection.

METHODS

Using a case-control approach, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry was used to identify plasma proteins associated with renal allograft rejection. From each rejection patient (n=16), two plasma samples (one near the biopsy date and the other at a time postbiopsy) were compared. Biopsy-confirmed nonrejection patients (n=48) were further analyzed as controls. Antibody-based quantitative enzyme-linked immunosorbent assay was performed to validate candidate biomarker apolipoprotein A1 (Apo A1) in a subset of the original and a second cohort of biopsy-confirmed rejection (n=40) and nonrejection (n=70) patients.

RESULTS

Twenty-two proteins/peptides showed significant differences between rejection and postrejection samples. Peptides 5191 Da and 4467 Da detected rejection with 100% sensitivity and 94% specificity. The 4467 Da peptide was identified as the C-terminal fragment of α-1 antichymotrypsin and a 28 kDa protein was determined as Apo A1. Both protein levels were significantly lower at rejection compared with postrejection. Protein levels of nonrejection patients were similar to the postrejection samples. Apo A1 enzyme-linked immunosorbent assay results showed significantly lower Apo A1 levels (P=0.001 for the original and P=4.14E-11 for the second cohort) at the time of rejection compared with nonrejection which coincides with the SELDI findings.

CONCLUSIONS

Together α-1 antichymotrypsin, Apo A1, and the unidentified 5191 Da peptide provide a plasma molecular profile, and this is associated with acute cellular renal allograft rejection.

Diagnosis of C4d+ Renal Allograft Acute Humoral Rejection by Urine Protein Fingerprint Analysis

This study aimed to develop urine protein fingerprint models for the diagnosis of acute rejection (AR) and complement split product positive (C4d+) acute humoral rejection (AHR) following renal allograft transplantation. Urine samples from 101 renal transplant recipients were analysed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry combined with bioinformatics. The patients comprised 36 with stable allograft function (stable group), 10 with acute tubular necrosis (ATN) and 55 with AR (20 with C4d- acute cellular rejection [ACR] and 15 with C4d+ AHR). The ATN group was differentiated from the stable group with a sensitivity and specificity of 100% (pattern 1). The stable group was differentiated from the AR group with a specificity of 86.4% and a sensitivity of 85.4% (pattern 2). The C4d- ACR subgroup was differentiated from the C4d+ AHR subgroup with a specificity and sensitivity of 95% and 80%, respectively (pattern 3). It is concluded that urine protein fingerprint analysis can provide a noninvasive tool to diagnose AR and C4d+ AHR.

Standardized preprocessing of urine for proteome analysis

Proteome/peptidome profiling of human urine is a promising tool for the discovery of novel disease-associated biomarkers. However, a wide range of preanalytic variables influence the results of proteome/peptidome analysis regardless of the method used. We present a validated pretreatment protocol, which allows standardization of preanalytic modalities and facilitates reproducible peptidome profiling of human urine by means of magnetic bead (MB) separation in combination with MALDI-TOF MS. Such a procedure is necessary for generating consistent and reliable data from which meaningful results may be obtained for biomarker discovery and general proteomic experiments.

Urinary Peptide patterns in native kidneys and kidney allografts

BACKGROUND

The use of biopsies to determine kidney health after kidney transplantation is an invasive procedure with some risk to the patient. Consequently, a noninvasive test for transplanted kidney health would provide a significant advantage over current clinical practice.

METHODS

Urines from kidney donors before nephrectomy, pretransplant patients with native kidney disease, and posttransplant kidney recipients were examined for protein biomarkers to diagnose or prognose kidney disease. Proteins were extracted by C4 reverse phase affinity and analyzed by matrix assisted laser desorption/ionization time-of-flight mass spectrometry.

RESULTS

Urine from individuals with healthy kidneys showed few components other than two ubiquitous saposin B glycoisoforms. Patients with kidney disease lacked saposin B and showed new components in two patterns: the most common contained beta-2 microglobulin (B2M, m/z=11,732) plus one or more peaks at m/z=10,350, 9480, 4337, and 4180. Pattern 2 lacked beta-2 microglobulin but contained several degradation products of alpha-1 antitrypsin. Other pathologic components included urinary protein 1 (m/z=15,835), transthyretin (m/z=13,880), and a component at m/z=13,350.

CONCLUSIONS

Patients with acute rejection showed profiles that ranged from those of kidney donors to those of advanced kidney disease. The range of patterns may be useful for analysis of transplant patients without complications and persons with developing kidney disease before or after transplant.

Proteomics studies after hematopoietic stem cell transplantation

Complex biological samples hold significant information on the health status and on development of disease. Approximately 35,000 human genes give rise to more than 1,000,000 functional entities at the protein level. Thus, the proteome provides a much richer source of information than the genome for describing the state of health or disease of humans. The composition body fluids comprise a rich source of information on changes of protein and peptide expression. Here we describe the application of capillary electrophoresis (CE) coupled online to an electrospray-ionization time-of-flight mass spectrometer (ESI-TOF-MS) to analyze human urine for the identification of biomarkers specific for complications after allogeneic hematopoietic stem cell transplantation (HSCT). Sequencing of native proteins/peptides is necessary for the identification of possible new therapeutic targets.

Diagnosis of renal allograft subclinical rejection by urine protein fingerprint analysis

AIMS

This study aimed to find new biomarkers and establish urine protein fingerprint model for diagnosis of renal allograft subclinical rejection (SCR).

METHODS

A total of 73 urine samples were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) combined with bioinformatics tools.

RESULTS

Firstly, 22 urine samples from recipients of stable graft function proved by protocol biopsies and 27 from subclinical rejection gruop were analyzed by SELDI-TOF-MS and Zhejiang University Cancer Institute-ProteinChip Data Analysis System (ZUCI-PDAS). The diagnostic pattern comprised of 4 biomarkers could differentiate SCR group from stable group with sensitivity of 81.5% and specificity of 81.8%. The remaining 14 samples from stable group and 10 samples from SCR were analyzed on the second day as an independent test set. The independent tests yielded a specificity of 71.4% and sensitivity of 90%.

CONCLUSIONS

Urine protein fingerprint analysis by SELDI-TOF-MS combined with bioinformatics can help to discover new biomarkers and provide a non-invasive tool to diagnosis of SCR.

Recent progress in urinary proteomics

Urinary proteomics has become one of the most attractive subdisciplines in clinical proteomics as the urine is an ideal source for the discovery of noninvasive biomarkers for kidney and nonkidney diseases. This field has been growing rapidly as indicated by >80 original research articles on urinary proteome analyses appearing since 2001, of which 28 (approximately 1/3) had been published within the year 2006. The most common technologies used in recent urinary proteome studies remain gel-based methods (1-DE, 2-DE and 2-D DIGE), whereas LC-MS/MS, SELDI-TOF MS, and CE-MS are other commonly used techniques. In addition, mass spectrometric immunoassay (MSIA) and array technology have also been applied. This review provides an extensive but concise summary of recent applications of urinary proteomics. Proteomic analyses of dialysate and ultrafiltrate fluids derived from renal replacement therapy (or artificial kidney) are also discussed.

Human body fluid proteome analysis

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

Protein biomarkers associated with acute renal failure and chronic kidney disease

Acute renal failure (ARF) as well as chronic kidney disease (CKD) are currently categorized according to serum creatinine concentrations. Serum creatinine, however, has shortcomings because of its low predictive values. The need for novel markers for the early diagnosis and prognosis of renal diseases is imminent, particularly for markers reflecting intrinsic organ injury in stages when glomerular filtration is not impaired. This review summarizes protein markers discussed in the context of ARF as well as CKD, and provides an overview on currently available discovery results following 'omics' techniques. The identified set of candidate marker proteins is discussed in their cellular and functional context. The systematic review of proteomics and genomics studies revealed 56 genes to be associated with acute or chronic kidney disease. Context analysis, i.e. correlation of biological processes and molecular functions of reported kidney markers, revealed that 15 genes on the candidate list were assigned to the most significant ontology groups: immunity and defence. Other significantly enriched groups were cell communication (14 genes), signal transduction (22 genes) and apoptosis (seven genes). Among 24 candidate protein markers, nine proteins were also identified by gene expression studies. Next generation candidate marker proteins with improved diagnostic and prognostic values for kidney diseases will be derived from whole genome scans and protemics approaches. Prospective validation still remains elusive for all proposed candidates.