|Year : 2019 | Volume
| Issue : 2 | Page : 69-77
Renal allograft dysfunction: An update on immunological graft injury
Praveen Kumar Etta, MV Rao
Department of Nephrology and Renal Transplantation, Asian Institute of Nephrology and Urology, Hyderabad, Telangana, India
|Date of Submission||20-Dec-2018|
|Date of Acceptance||01-Mar-2019|
|Date of Web Publication||28-Jun-2019|
Dr. Praveen Kumar Etta
Department of Nephrology and Renal Transplantation, Asian Institute of Nephrology and Urology, Hyderabad - 500 082, Telangana
Source of Support: None, Conflict of Interest: None
Renal transplantation is the treatment of choice in most patients with end-stage renal disease, especially with improvement in surgical techniques and immunosuppressive regimens; however, the long-term graft survival remains to be improved. Immunological graft injury leading to rejection plays a major role in long-term graft loss. With pretransplant immunological evaluation using various crossmatch tests, identification of donor-specific antibodies, a better understanding of renal allograft pathology and its standardization with the Banff classification having regular updates led to prevention, early and accurate diagnosis of rejection and its histological differentiation. Some newer biomarkers are in pipeline may enable early and accurate identification of graft pathology noninvasively.
Keywords: Allograft, crossmatch, rejection, renal transplantation
|How to cite this article:|
Etta PK, Rao M V. Renal allograft dysfunction: An update on immunological graft injury. Indian J Transplant 2019;13:69-77
| Introduction|| |
Renal transplantation (RT) is the best modality of renal replacement therapy as it offers survival and quality of life benefit over dialysis in patients with end-stage renal disease. Evolution of stronger and potent immunosuppressive agents and diagnostic techniques dramatically decreased the incidence of acute rejections in the past few decades, but the negative impact on graft survival persisted. Despite therapy, rejection episodes have a negative impact on both short- and long-term graft survivals. These are a major predictor of interstitial fibrosis/tubular atrophy (IF/TA), formerly called chronic allograft nephropathy, which is responsible for most of the death-censored graft loss over long term. Recent studies suggest that antibody-mediated injury, which is not controlled by the currently used immunosuppressive agents, plays an important role in long-term graft loss. Optimizing immunosuppression to both prevent rejection and minimize drug toxicity remains a challenge. In this review, we have briefly summarized newer advances in the field of transplant immunology with reference to renal allograft dysfunction.
| Evaluation of Renal Allograft Dysfunction|| |
Early recognition, diagnosis, and management of allograft dysfunction are important as it is usually reversible. Persistent dysfunction without timely intervention may lead to irreversible graft loss. The causes of renal allograft dysfunction vary with the time after transplantation, and it can result from a variety of immunological and nonimmunological events including drug toxicity. A thorough history, clinical examination, laboratory studies, including drug levels in blood and/or allograft biopsy can establish the diagnosis in most of the cases. Here, we have briefly discussed the evolution in the diagnosis of renal allograft rejection, its pathology, classification, and newer advances in this field.
| Alloimmune Response and Rejection|| |
After transplantation, the recipient immune system reacts to the human leukocyte antigen (HLA) and other alloantigens leading to stimulation of adaptive immune response mediated by T-cells or antibodies. Immune system activation leads to the release of proinflammatory mediators with subsequent recruitment of the effector cells and allograft injury. Most episodes of acute rejection occur within the first 6 months to 1 year after RT. Risk factors for the development of rejection include the presence of donor-specific antibodies (DSAs), HLA mismatches, pediatric recipient, elderly donor, African–American ethnicity, blood group incompatibility, prolonged cold ischemia time, delayed graft function, medication nonadherence and prior sensitization identified with high panel reactive antibody (PRA), prior transplant, multiple pregnancies, and blood transfusions.
There are two principal histologic forms of rejection: T-cell-mediated (cellular) rejection (TCMR) and antibody-mediated rejection (ABMR). ABMR and TCMR may coexist at the same time in the allograft. Subclinical rejection is defined as the presence of acute rejection on biopsy, without graft dysfunction. It is primarily detected by a protocol or surveillance biopsy. It usually involves a form of TCMR, though subclinical ABMR can also occur.
Most patients with acute rejection are asymptomatic; diagnosis is suggested only by an increase in the serum creatinine, worsening of hypertension or proteinuria and it is confirmed by allograft biopsy. However, occasionally, patients present with fever, malaise, oliguria, and graft pain and/or tenderness. A rising serum creatinine level, however, is a relatively late phenomenon and usually indicates the presence of significant histologic damage. Biopsy accurately grades the severity of rejection, differentiate between TCMR and ABMR, and determine the degree of irreversible kidney damage (IF/TA). The outcome of rejection depends on several factors such as the timing of rejection, severity, and number of acute rejections, and degree of recovery after treatment.
| Pathology of Renal Allograft Rejection|| |
Till the early 1990s, there was considerable heterogeneity among pathologists in the characterization of renal allograft biopsies. Hence, it was felt that standardization of allograft pathology was necessary to allow comparisons of the efficacy of different therapies and to help guide treatment. Initial classification systems that have been introduced include the Banff classification and the Cooperative Clinical Trials in Transplantation (CCTT) classification.
The Banff classification represented the first attempt to formulate an international, consensus-based and structured classification system for the diagnosis and categorization of renal allograft pathology. In this regard, the first Banff meeting was held at Banff, Alberta, Canada in 1991 and the first publication appeared in 1993 (Banff '93). Subsequent follow-up meetings have taken place every 2 years, and the Banff schema has undergone considerable evolution over the past 25 years [Table 1]. The Banff '93 and the CCTT systems were both incorporated into the Banff '97 classification. Banff has introduced a numerical grading system for each of the renal compartments-interstitium (i), tubules (t), vessels (v), and glomeruli (g).
|Table 1: The evolution of the Banff classification of renal allograft pathology|
Click here to view
Hyperacute rejection (HAR) occurs immediately after transplant. It is mediated by high titer of preformed anti-donor antibodies: anti-HLA, anti-ABO, or other non-HLA antibodies. It results in an irreversible vascular rejection, intravascular thrombosis, and graft necrosis; and graft nephrectomy is usually indicated. Accelerated acute rejection (AAR) can occur within 24 h to several days after transplant. It represents an anamnestic response by memory B and plasma cells from prior sensitization. These types of rejections are rarely seen now due to better pretransplant immunologic evaluation. The borderline rejection was defined by inflammation in 10%–25% of the interstitium (i1) with mild tubulitis (t1, 1–4 mononuclear cells/tubular cross section). This might be considered as “very mild acute rejection,” without clear clinical significance.
The presence of linear staining for C4d, a degradation product of the complement pathway that binds covalently to the endothelium, is highly suggestive of ABMR. C4d serves as an immunologic footprint of complement activation and ABMR. Some patients have morphologic evidence of ABMR and a positive DSA with little or no C4d staining. The concept of C4d-negative ABMR was introduced in a retrospective study of 1036 allograft biopsies from 1320 RT recipients (RTRs); only 36% of cases with transplant glomerulopathy (TG) had C4d-positive staining, despite the presence of DSAs in 73% of cases. Additional evidence for C4d-negative ABMR came from a molecular study in which gene expression microarrays were performed in 173 indication biopsies to examine endothelial activation and injury transcripts (ENDATs). High expression of ENDATs correlated with histologic lesions of ABMR but not TCMR. Among renal allografts with high ENDATs, positive DSA and morphologic evidence of chronic ABMR, 60% were C4d-negative. In C4d-negative ABMR, DSA binding to endothelial cells may cause injury through complement independent mechanisms-the innate immune cells such as neutrophils, macrophages, and natural killer cells can bind to Fc fragments of DSAs, trigger degranulation, and release lytic enzymes, which cause tissue injury and cell death (antibody-dependent cell cytotoxicity); DSAs can also cause graft injury by direct activation of endothelial proliferation through increased vascular endothelial growth factor production, upregulating fibroblast growth factor receptor, and increasing its ligand binding as well as other signaling pathways for cellular recruitment. Diagnostic criteria for C4d-negative ABMR were incorporated into the 2013 Banff update.,
Patients with the first two criteria for the diagnosis of ABMR, but no evidence of DSAs is typically managed as patients with ABMR. It was agreed that C4d staining in at least 10% of peritubular capillaries (C4d2 or C4d3) by IF on frozen sections or in any peritubular capillaries by immunoperoxidase on paraffin sections (C4d score >0) should be regarded as sufficient for the diagnosis of ABMR in the presence of tissue injury, regardless of whether detectable DSAs are present. Cases in which C4d staining is positive, but DSA cannot be detected may result from DSA being below the level of detection due to immunoadsorption by the graft or it can also be due to the presence of non-HLA antibodies. This issue has been, particularly discussed in the 2017 Banff conference. Although molecular diagnostics were first introduced into the Banff classification in 2013, recent 2017 Banff has recommended indications for the use of these tests in renal allograft biopsy diagnosis [Table 2]. Hidalgo et al. introduced DSA-specific transcript set (DSAST) of messenger RNA (mRNA) differentially expressed in biopsy specimens and showed DSASTs to be more of a marker for ABMR than for the presence of DSAs. Loupy et al. showed that adding the results of the ABMR classifier to histologic findings significantly improved their ability to diagnose ABMR, independently from C4d and DSA. DSASTs, ABMR classifier, and TCMR classifier may help in the diagnosis of rejection in atypical cases.
The inflammation in areas of IF/TA (i-IFTA) is the morphologic correlate of active injury and predicts disease progression. The impact of i-IFTA on graft outcomes was first suggested by the finding of Mengel et al. that total cortical inflammation (Banff ti score) was more predictive of graft loss than inflammation in nonsclerotic areas of cortex (Banff i score). The long-term deterioration of kidney allograft function study also showed a strong association between the severity of i-IFTA and graft loss, far stronger than that of IFTA alone.
| Human Leukocyte Antigen and Epitope Matching|| |
The major histocompatibility complex (MHC) encodes both HLA class I and HLA class II antigens. HLA class 1 antigens (A, B, and C) are expressed on all nucleated cells; the epitopes reside only in the polymorphic α-chain. HLA class 2 antigens (DR, DQ, and DP) are normally restricted to antigen-presenting cells (dendritic cells, B cells, and macrophages), but they can be upregulated and expressed after inflammatory insults, such as ischemia-reperfusion injury, infection, and rejection. Each class 2 antigen consists of one α-chain and one β-chain, and both chains are polymorphic.
The importance of HLA matching is well known. The degree of HLA mismatch influences long-term graft survival and risk of rejection. The newer concept is epitope matching. During antigen-antibody binding, the DSA binds to a limited area of the HLA molecule comprising a 15–25 amino acid sequence. This specific binding area of the HLA is called an “epitope.” While some of these epitopes are unique to a single HLA (private epitopes), others are shared among numerous antigens (public epitopes). Using epitopes as the focus in HLA typing allows more precision compared to the traditional HLA molecule-based matching. Epitope-based matching has been shown to be more predictive of crossmatch (XM) results and subsequent graft outcome compared to HLA molecule matching. Use of epitopes and eplets may also help in determining permissible mismatches.
| Crossmatch Testing|| |
XM testing of potential renal donors against potential RTRs has been performed for over 45 years and is a mandatory component of the pretransplant workup. XM test was developed in an attempt to identify recipients who are likely to develop acute vascular rejection of a graft from a given donor. Since the first demonstration by Patel and Terasaki that performed HLA-DSA in RTRs caused HAR, there has been an imperative to test all potential recipients prospectively for HLA antibodies to avoid transplanting incompatible grafts. In their seminal work, they described the outcomes of 30 such transplants; 24 patients lost their grafts immediately to HAR while another three lost their grafts within 3 months.
Preformed antibodies cause rejection by binding to HLA antigens expressed on the endothelium of vessels in the transplanted kidney, resulting in activation of the complement cascade with resultant thrombosis and infarction of the graft. Almost a third of patients who are waitlisted for RT may have a degree of anti-HLA antibodies detected. Many modifications in the XM testing have been evolved with focus on increasing the sensitivity and specificity of the test to identify DSA in a particular recipient. These tests are either cell-based assays or solid phase immunoassays (SPI). Although the single-antigen bead (SAB) assay has very high sensitivity for antibody detection, the complement-dependent cytotoxicity XM (CDC-XM) still remains the gold standard test for the detection of preformed antibodies before RT. Different types of commonly used tests are briefly summarized below.
| Complement-Dependent Cytotoxicity Crossmatch|| |
CDC-XM was pioneered by Terasaki et al. in the 1960s. If DSA is present and binds to donor cells, the complement cascade will be activated through the classical pathway resulting in lysis of the lymphocytes. The proportion of lysed cells is assessed, and the XM is graded. DSAs that are not complement-fixing can give false-negative result. An auto-XM or a repeat assay with dithiothreitol (DTT) is useful to identify false-positive assays. The addition of antihuman globulin enhances the sensitivity of the assay by cross-linking the antibodies.
| Flow Cytometry Crossmatch|| |
Flow cytometry XM (FC-XM) involves adding recipient serum to donor lymphocytes and then incubating them with fluorescein-labeled antibodies against human immunoglobulin G (IgG). The strength of the fluorescence can be measured and expressed as “channel shifts” above the control sample. FC-XM is more sensitive for detecting DSA compared with CDC-XM. FC-XM detects DSA independent of complement fixation. Positive FC-XM with negative CDC-XM is likely to be caused by a noncomplement fixing antibody or a low-level antibody.
| Luminex and Virtual Crossmatch|| |
The Luminex technology consists of a series of polystyrene microspheres (beads) coated with HLA antigens and containing fluorochromes of differing intensity embedded within the bead. Recipient serum potentially containing anti-HLA antibodies is added to a mixture of synthetic beads. Beads may be coated with multiple HLA antigens (screening beads) or a single-HLA antigen (SAB assay) for defining the specificity of antibodies more precisely. Positive results can then be graded semiquantitatively on the basis of the degree of fluorescence of the positive bead (MFI and mean fluorescence index). SAB detects only anti-HLA DSA and not the nonanti-HLA DSA. It may have a “gray zone” for MFI up to 4000 with a sensitivity of 54% and a specificity of 100%. It may fail to detect anti-Cw and anti-DP/DQ antibodies and have a lower sensitivity for anti-A and B Class-1 antibodies. False positive or high titers may be reported due to the presence of antibodies to denatured HLA molecules. DSAs targeting one of the shared epitopes may be diluted across the beads. False negative or low titers can also occur in the presence of inhibitors or “prozone effect.” Studies suggested that serum titration studies, freeze/thaw cycles, heat inactivation, DTT or ethylenediaminetetraacetic acid treatment may resolve “prozone.”
Virtual XM (VXM) refers to the comparison of the anti-HLA antibodies of the recipient as defined by Luminex, with the HLA of the donor. In VXM, both donor HLA typing and SAB assay are utilized together. It is not precisely an XM in the sense of mixing serum and lymphocytes. A patient will not be offered a kidney from the deceased donor who expresses an unacceptable HLA antigen (positive VXM).
| Panel Reactive Antibody|| |
In the PRA test, the recipient's serum is tested for antibodies against a panel of lymphocytes from approximately 100 blood donors from the local population. It estimates the likelihood of positive XM to potential donors and is extremely useful in providing information about the sensitization of a recipient. PRA is done similar to cell-based assays of XM and the antigen specificity of antibodies is not known. With PRA that identifies several antibodies to a potential cluster of donors, the XM will identify if a recipient had antibodies to a specific donor of interest.
| Calculated Panel Reactive Antibody|| |
This is similar to SPI (VXM) and the test is performed against a fixed panel of HLA antigens from the past organ donors, to determine the antigen specificity against which an individual produces antibody. These antigens are called unacceptable antigens. It is reported as the percentage PRA. The calculated PRA is calculated separately for Class I HLA and Class II HLA antigens.
| Donor-Specific Antibodies|| |
The presence of DSAs in patients with renal allograft dysfunction can provide significant diagnostic and prognostic information. The ability to detect DSAs and diagnose ABMR has improved markedly with the addition of flow cytometric analysis and SPI such as Luminex (SAB assay) to standard cytotoxicity assays.
| Human Leukocyte Antigen-Donor-Specific Antibody by Luminex|| |
Donor lysate-based solid phase XM (SPC) on the Luminex platform can be used for detecting DSA. This test uses donor lysate and identifies anti-HLA antibodies for class I and class II and their titers, but fails to give the HLA specificities. The beads conjugated with monoclonal antibodies which are identification for HLA class-I and class-II are mixed with donor lysate and then with recipient serum to identify the DSA. The SAB assay is more sensitive and specific than the lysate based SPC assay. A study reported that the sensitivity of SPC was 89% for Class I and 68% for Class II antibodies. A recent study showed SPC on the Luminex platform can detect class I antibodies with MFI of 2300 or more and detect Class II antibodies with MFI of 1300 or more as in the SAB assay technique. Hence, SPC can be used as a screening test for HLA-DSA using donor lymphocytes.
Preformed DSAs (predominantly against HLA Class 1 and complement-fixing IgG1 or IgG3) in sensitized patients can trigger HAR, AAR, and early active ABMR. De novo DSAs (predominantly directed to HLA Class 2 and noncomplement binding IgG2 or IgG4) are associated with late active ABMR, chronic ABMR, and TG. Posttransplant screening for the development of DSAs may also permit the early detection of active ABMR and allograft dysfunction, particularly in high-risk patients. The complement activation contributes to allograft damage in most cases of ABMR; there are SPI assays that have been modified to detect complement-binding antibodies.
| C1q, C3d and C4d-Binding Assays|| |
The C1q-assay is a newer modification to the Luminex-based test. SAB assay may detect both complement dependent and noncomplement dependent antibodies. The clinical significance of such DSA detected on Luminex in the presence of a negative CDC-XM remains inconclusive. This resulted in the search for a test that is both sensitive to detect low titer DSA and specific to identify complement fixing ability that is considered crucial in antibody-mediated graft injury. The C1q-assay is designed to selectively identify only the DSA that bind C1q and thereby activate the complement pathway, with the same degree of sensitivity as the original Luminex test but with enhanced specificity for complement fixing. Patients with C1q-binding HLA DSAs also had inferior 5-year graft survival compared with patients with non-C1q-binding DSAs. Patients with non-C1q-binding HLA DSAs had lower graft survival and worse histologic features than those without DSAs. This may be of therapeutic importance also. Complement inhibitors may be considered as part of treatment for rejection mediated by C1q-binding DSA, and they are unlikely to be beneficial in treating rejection caused by C1q-nonbinding DSA.
The presence of C3d-binding DSAs at the time of ABMR is a strong independent predictor of allograft loss as concluded in a recent study. The authors have observed C3d-binding is a more sensitive marker than C1q-assay. C3d-and C1q-binding assays analyze different steps of the classic complement pathway. The complement system indeed activates through a triggered-enzyme cascade, in which the activation of a small number of complement proteins at the start is hugely amplified by each successive enzymatic reaction. C1q is the first component of the classical complement pathway, and it is, therefore, not surprising that a C1q-binding assay would exhibit a lower sensitivity than a C3d-binding assay. Another possible explanation could lie in the regulatory mechanisms preventing uncontrolled amplification of the complement cascade. By limiting C3 convertase formation even when substantial amounts of C1q bind to antibodies, they could reduce the specificity of a C1q-binding assay. In contrast, the presence of C3d on DSA proves the efficient cleavage of C3 and is, therefore, more closely related to the pathogenic processes damaging the graft. In one study, preformed DSAs able to bind C4d were reported to predict ABMR and graft loss, though the XM was negative before transplant.
| Immunoglobulin G Subclass of Human Leukocyte Antigen-Donor-Specific Antibody|| |
Serum IgG molecules can be divided into four subclasses (IgG1-IgG4) with varying capacity to activate complement and recruit effector cells through the Fc receptor (IgG3> IgG1> IgG2> IgG4). Recent evidence showed that complement binding IgG3 subclass of DSA was more pathogenic and was associated with active ABMR, shorter time to rejection, increased microcirculation injury, and C4d deposition. Noncomplement binding IgG4 DSA was associated with subclinical or chronic ABMR, late allograft injury with increased TG and IF/TA lesions.
| Human Leukocyte Antigen-DQ and Human Leukocyte Antigen-DP Antibodies|| |
HLA typing and matching in relation to transplant immunology mainly consider only antigens in HLA-A, B, and DR loci. However, the majority of de novo DSAs after RT are Class 2 antibodies, especially HLA-DQ. Thus, Class II HLA mismatches between donor and recipient are associated with the higher generation of DSAs in the posttransplant period.
Unlike Class I molecules, HLA Class II antigens are composed of two chains (α and β) encoded by two distinct genes (A and B). While the DQ and DP antigens have two (α and β) polymorphic chains, the α chain of HLA-DR is virtually nonpolymorphic and therefore does not contribute to differences between HLA-DR alleles. HLA-DQ antibodies are likely the most commonly developed de novo DSA after RT and recent evidence support strong correlation between the presence of donor-specific HLA-DQ antibodies and rejection.,
| Nonhuman Leukocyte Antigen Antibodies|| |
Non-HLA antibodies comprise an evolving field in transplant immunology. Non-HLA DSA antibodies can also result in rejection and C4d deposition. In cases where there are no detectable DSAs but a biopsy specimen meeting criteria for ABMR [microvascular inflammation (MVI) score ≥1 and C4d-positive; MVI score ≥2 and C4d-negative], testing for non-HLA antibodies is strongly advised. These mainly include anti-angiotensin II type 1 receptor (anti-AT1R) antibodies, anti-endothelin-1 type A receptor (ETAR) antibodies and anti-endothelial cell antibodies (AECAs). Four antigenic targets expressed on endothelial cells were identified in a recent study: endoglin, Fms-like tyrosine kinase-3 ligand (FLT3 ligand), EGF-like repeats and discoidin I-like domains 3 (EDIL3), and intercellular adhesion molecule 4 (ICAM4). MHC1-related chains A and B (MICA and MICB) are minor histocompatibility molecules expressed on endothelial cells, and their antibodies can trigger ABMR. H-Y antigens encoded by Y chromosome in male and may cause rejection in male-to-female transplant. Other non-HLA antibodies identified in few studies include antibodies against agrin, vimentin, type IV collagen, fibronectin, perlecan, Kα-tubulin, protein kinase Cζ, and glutathione S-transferase T1.
| Novel Biomarkers of Rejection|| |
Histologic evaluation of renal allograft remains the gold standard for the diagnosis of rejection. Its limitations include: it is an invasive procedure and not without complications; sampling errors may jeopardize their diagnostic utility; the procedures are costly and labor intensive. In addition, pathologists frequently vary in their interpretation of biopsy findings. There is a need for innovative, robust and ideally, noninvasive methods to predict and diagnose acute and chronic graft injury. The development of “omics” methods (e.g., genomics, transcriptomics, proteomics, metabolomics) in the field of RT has paved the way for the development of several candidate biomarkers., However, the specific role of these biomarkers is still not well established.
| Donor-Derived Cell-Free DNA|| |
Plasma level of donor-derived cell-free DNA (dd-cfDNA), which is released into the bloodstream by dead cells in the injured allograft, may be elevated in patients with acute rejection. In one study, plasma levels of dd-cfDNA were correlated with allograft rejection; hence, dd-cfDNA may serve as a noninvasive biomarker for the diagnosis of rejection.
| Kidney Solid Organ Response Test|| |
The kidney solid organ response test is a microarray-based assay that was developed to detect patients at high risk for acute rejection. The test, performed on a peripheral blood sample, employs quantitative polymerase chain reaction to measure the relative mRNA expression levels of 17 genes known to be associated with acute rejection or leukocyte trafficking. The assay was able to predict patients at high risk of acute rejection in a large multicenter study of RTR.
| Molecular Microscope Diagnostic System|| |
The Molecular Microscope Diagnostic System is a microarray-based system that analyzes mRNA expression patterns in transplant biopsy tissue and may be helpful in diagnosing TCMR, particularly in situ ations where histology is ambiguous or potentially misleading.
| Quantification of MicroRNAs|| |
In one recent study, the combined measurement of five microRNAs (miRNAs) (miR-15B, miR-16, miR-103A, miR-106A, and miR-107) in peripheral blood samples enhanced the sensitivity and specificity for the diagnosis of severe T-cell-mediated vascular rejection.
| Urinary Cell Messenger RNA Profiling|| |
Studies of urinary cell mRNA profiling identified several potential mRNAs (e.g., perforin, granzyme B, interferon [IFN] inducible protein-10 [IP-10], CD3), the levels of which predicted the diagnosis of acute TCMR., A three-gene signature of CD3-epsilon mRNA, IP-10 mRNA, and 18S ribosomal RNA (rRNA) was able to distinguish between renal biopsy specimens showing acute TCMR and those without rejection in a large, multicenter study of RTR.
| Urinary MicroRNA Profiling|| |
In a study that profiled urinary miRNAs of stable RTR and those with acute TCMR, miR-10a, miR-10b, and miR-210 were strongly deregulated in the urine of patients with acute TCMR. Combination of miRNA profiling of biopsy and urine samples could be used to monitor graft function and predict progression to chronic allograft dysfunction. Fifty-six miRNAs were identified as differentially expressed in biopsy samples with IF/TA; five of these (miR-142-3p, miR-204, miR-107, miR-211, and miR-32) were confirmed using an independent set of samples. Differential expression of miR-142-3p, miR-204, and miR-211 in the urine of patients with IF/TA was also observed.
| Urinary Proteins|| |
Various proteins and peptides differentially expressed in patients with acute rejection have been identified, including fragments of collagens, beta-2-microglobulin, alpha-1-antichymotrypsin, and uromodulin. Elevated urinary levels of chemokine CXCL9 and CXCL10 have been associated with acute TCMR in few studies. One study found that urinary concentration of chemokine CCL2, also known as monocyte chemoattractant protein 1 at 6 months posttransplant was a predictor of severe IF/TA and graft dysfunction at 2 years posttransplant. Urine mass spectrometry is also promising for the diagnosis of acute rejection and may allow for the diagnosis of subclinical rejection.
| Functional Cell-Based Immune Monitoring|| |
Alloreactive memory T cells are central mediators of renal allograft rejection, and monitoring the activity of these cells may help to identify RTRs who are at risk for acute rejection. The IFN-gamma enzyme-linked immunospot assay, which measures IFN-gamma secretion by recipient T cells in response to donor antigens, has been used to assess anti-donor T-cell alloreactivity in vitro.
| Other Tests|| |
Newer imaging modalities such as positron emission tomography coupled with computed tomography and magnetic resonance spectroscopy to assess high-energy phosphates metabolism may identify rejection episodes noninvasively.
| Conclusions|| |
Renal allograft dysfunction is a complex process involving both immunological and nonimmunological processes including drug toxicity, distinguishing them is important in the management and graft salvage. Since the recognition of the association between preformed alloantibodies and HAR, our knowledge of transplant immunology has improved enormously. This, in turn, led to improved clinical outcomes of RT. Clinical phenotypes of rejection are determined by the complex characteristics of DSA like HLA class, specificity, strength, IgG subclass, complement binding capacity and cellular immune mechanisms. Although few novel assays are valuable in the research setting, it is not yet clear whether they will be of utility in the clinical setting. The ultimate goals are not only to improve our ability to predict graft outcomes but also to better guide therapy, leading to improved patient outcomes compared with the current standard of care.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Koo J, Wang HL. Acute, chronic, and humoral rejection: Pathologic features under current immunosuppressive regimes. Surg Pathol Clin 2018;11:431-52.
Colvin RB, Cohen AH, Saiontz C, Bonsib S, Buick M, Burke B, et al.
Evaluation of pathologic criteria for acute renal allograft rejection: Reproducibility, sensitivity, and clinical correlation. J Am Soc Nephrol 1997;8:1930-41.
Solez K, Axelsen RA, Benediktsson H, Burdick JF, Cohen AH, Colvin RB, et al.
International standardization of criteria for the histologic diagnosis of renal allograft rejection: The Banff working classification of kidney transplant pathology. Kidney Int 1993;44:411-22.
Bhowmik DM, Dinda AK, Mahanta P, Agarwal SK. The evolution of the Banff classification schema for diagnosing renal allograft rejection and its implications for clinicians. Indian J Nephrol 2010;20:2-8.
] [Full text]
Sis B, Campbell PM, Mueller T, Hunter C, Cockfield SM, Cruz J, et al.
Transplant glomerulopathy, late antibody-mediated rejection and the ABCD tetrad in kidney allograft biopsies for cause. Am J Transplant 2007;7:1743-52.
Sis B, Halloran PF. Endothelial transcripts uncover a previously unknown phenotype: C4d-negative antibody-mediated rejection. Curr Opin Organ Transplant 2010;15:42-8.
Haas M, Sis B, Racusen LC, Solez K, Glotz D, Colvin RB, et al.
Banff 2013 meeting report: Inclusion of c4d-negative antibody-mediated rejection and antibody-associated arterial lesions. Am J Transplant 2014;14:272-83.
Roufosse C, Simmonds N, Clahsen-van Groningen M, Haas M, Henriksen KJ, Horsfield C, et al.
A2018 reference guide to the Banff classification of renal allograft pathology. Transplantation 2018;102:1795-814.
Haas M. The revised (2013) Banff classification for antibody-mediated rejection of renal allografts: Update, difficulties, and future considerations. Am J Transplant 2016;16:1352-7.
Haas M, Loupy A, Lefaucheur C, Roufosse C, Glotz D, Seron D, et al.
The Banff 2017 kidney meeting report: Revised diagnostic criteria for chronic active T cell-mediated rejection, antibody-mediated rejection, and prospects for integrative endpoints for next-generation clinical trials. Am J Transplant 2018;18:293-307.
Hidalgo LG, Sis B, Sellares J, Campbell PM, Mengel M, Einecke G, et al.
NK cell transcripts and NK cells in kidney biopsies from patients with donor-specific antibodies: Evidence for NK cell involvement in antibody-mediated rejection. Am J Transplant 2010;10:1812-22.
Loupy A, Lefaucheur C, Vernerey D, Chang J, Hidalgo LG, Beuscart T, et al.
Molecular microscope strategy to improve risk stratification in early antibody-mediated kidney allograft rejection. J Am Soc Nephrol 2014;25:2267-77.
Mengel M, Reeve J, Bunnag S, Einecke G, Jhangri GS, Sis B, et al.
Scoring total inflammation is superior to the current Banff inflammation score in predicting outcome and the degree of molecular disturbance in renal allografts. Am J Transplant 2009;9:1859-67.
Mannon RB, Matas AJ, Grande J, Leduc R, Connett J, Kasiske B, et al.
Inflammation in areas of tubular atrophy in kidney allograft biopsies: A potent predictor of allograft failure. Am J Transplant 2010;10:2066-73.
Wiebe C, Pochinco D, Blydt-Hansen TD, Ho J, Birk PE, Karpinski M, et al.
Class II HLA epitope matching-A strategy to minimize de novo
donor-specific antibody development and improve outcomes. Am J Transplant 2013;13:3114-22.
Patel R, Terasaki PI. Significance of the positive crossmatch test in kidney transplantation. N
Engl J Med 1969;280:735-9.
Mulley WR, Kanellis J. Understanding crossmatch testing in organ transplantation: A case-based guide for the general nephrologist. Nephrology (Carlton) 2011;16:125-33.
Bettinotti MP, Zachary AA, Leffell MS. Clinically relevant interpretation of solid phase assays for HLA antibody. Curr Opin Organ Transplant 2016;21:453-8.
Vincent L. Improving crossmatch techniques and graft outcomes. Indian J Nephrol 2018;28:491-2.
] [Full text]
Guillaume N, Mazouz H, Piot V, Presne C, Westeel PF. Correlation between luminex donor-specific crossmatches and levels of donor-specific antibodies in pretransplantation screening. Tissue Antigens 2013;82:16-20.
Billen EV, Christiaans MH, van den Berg-Loonen EM. Clinical relevance of luminex donor-specific crossmatches: Data from 165 renal transplants. Tissue Antigens 2009;74:205-12.
Zhang R. Donor-specific antibodies in kidney transplant recipients. Clin J Am Soc Nephrol 2018;13:182-92.
Loupy A, Lefaucheur C, Vernerey D, Prugger C, Duong van Huyen JP, Mooney N, et al.
Complement-binding anti-HLA antibodies and kidney-allograft survival. N
Engl J Med 2013;369:1215-26.
Sicard A, Ducreux S, Rabeyrin M, Couzi L, McGregor B, Badet L, et al.
Detection of C3d-binding donor-specific anti-HLA antibodies at diagnosis of humoral rejection predicts renal graft loss. J Am Soc Nephrol 2015;26:457-67.
Lawrence C, Willicombe M, Brookes PA, Santos-Nunez E, Bajaj R, Cook T, et al.
Preformed complement-activating low-level donor-specific antibody predicts early antibody-mediated rejection in renal allografts. Transplantation 2013;95:341-6.
Lefaucheur C, Viglietti D, Bentlejewski C, Duong van Huyen JP, Vernerey D, Aubert O, et al.
IgG donor-specific anti-human HLA antibody subclasses and kidney allograft antibody-mediated injury. J Am Soc Nephrol 2016;27:293-304.
DeVos JM, Gaber AO, Knight RJ, Land GA, Suki WN, Gaber LW, et al.
Donor-specific HLA-DQ antibodies may contribute to poor graft outcome after renal transplantation. Kidney Int 2012;82:598-604.
Willicombe M, Brookes P, Sergeant R, Santos-Nunez E, Steggar C, Galliford J, et al. De novo
DQ donor-specific antibodies are associated with a significant risk of antibody-mediated rejection and transplant glomerulopathy. Transplantation 2012;94:172-7.
Dragun D, Müller DN, Bräsen JH, Fritsche L, Nieminen-Kelhä M, Dechend R, et al.
Angiotensin II type 1-receptor activating antibodies in renal-allograft rejection. N
Engl J Med 2005;352:558-69.
Jackson AM, Sigdel TK, Delville M, Hsieh SC, Dai H, Bagnasco S, et al.
Endothelial cell antibodies associated with novel targets and increased rejection. J Am Soc Nephrol 2015;26:1161-71.
Zou Y, Stastny P, Süsal C, Döhler B, Opelz G. Antibodies against MICA antigens and kidney-transplant rejection. N
Engl J Med 2007;357:1293-300.
Salvadori M, Tsalouchos A. Biomarkers in renal transplantation: An updated review. World J Transplant 2017;7:161-78.
Erpicum P, Hanssen O, Weekers L, Lovinfosse P, Meunier P, Tshibanda L, et al.
Non-invasive approaches in the diagnosis of acute rejection in kidney transplant recipients, part II: Omics analyses of urine and blood samples. Clin Kidney J 2017;10:106-15.
Bloom RD, Bromberg JS, Poggio ED, Bunnapradist S, Langone AJ, Sood P, et al.
Cell-free DNA and active rejection in kidney allografts. J Am Soc Nephrol 2017;28:2221-32.
Roedder S, Sigdel T, Salomonis N, Hsieh S, Dai H, Bestard O, et al.
The kSORT assay to detect renal transplant patients at high risk for acute rejection: Results of the multicenter AART study. PLoS Med 2014;11:e1001759.
Halloran PF, Pereira AB, Chang J, Matas A, Picton M, De Freitas D, et al.
Potential impact of microarray diagnosis of T cell-mediated rejection in kidney transplants: The INTERCOM study. Am J Transplant 2013;13:2352-63.
Matz M, Fabritius K, Lorkowski C, Dürr M, Gaedeke J, Durek P, et al.
Identification of T cell-mediated vascular rejection after kidney transplantation by the combined measurement of 5 specific microRNAs in blood. Transplantation 2016;100:898-907.
Suthanthiran M, Schwartz JE, Ding R, Abecassis M, Dadhania D, Samstein B, et al.
Urinary-cell mRNA profile and acute cellular rejection in kidney allografts. N
Engl J Med 2013;369:20-31.
Li B, Hartono C, Ding R, Sharma VK, Ramaswamy R, Qian B, et al.
Noninvasive diagnosis of renal-allograft rejection by measurement of messenger RNA for perforin and granzyme B in urine. N
Engl J Med 2001;344:947-54.
Lorenzen JM, Volkmann I, Fiedler J, Schmidt M, Scheffner I, Haller H, et al.
Urinary miR-210 as a mediator of acute T-cell mediated rejection in renal allograft recipients. Am J Transplant 2011;11:2221-7.
Scian MJ, Maluf DG, David KG, Archer KJ, Suh JL, Wolen AR, et al.
MicroRNA profiles in allograft tissues and paired urines associate with chronic allograft dysfunction with IF/TA. Am J Transplant 2011;11:2110-22.
Schaub S, Nickerson P, Rush D, Mayr M, Hess C, Golian M, et al.
Urinary CXCL9 and CXCL10 levels correlate with the extent of subclinical tubulitis. Am J Transplant 2009;9:1347-53.
Ho J, Wiebe C, Gibson IW, Hombach-Klonisch S, Gao A, Rigatto C, et al.
Elevated urinary CCL2: Cr at 6 months is associated with renal allograft interstitial fibrosis and inflammation at 24 months. Transplantation 2014;98:39-46.
Rush D, Somorjai R, Deslauriers R, Shaw A, Jeffery J, Nickerson P, et al.
Subclinical rejection – A potential surrogate marker for chronic rejection – May be diagnosed by protocol biopsy or urine spectroscopy. Ann Transplant 2000;5:44-9.
Hricik DE, Rodriguez V, Riley J, Bryan K, Tary-Lehmann M, Greenspan N, et al.
Enzyme linked immunosorbent spot (ELISPOT) assay for interferon-gamma independently predicts renal function in kidney transplant recipients. Am J Transplant 2003;3:878-84.
[Table 1], [Table 2]