Immune monitoring and biomarkers to predict chronic allograft dysfunction

Transforming kidney transplant monitoring with urine CXCL9 and CXCL10: practical clinical implementation

In kidney transplant recipients, urine CXCL9 and CXCL10 (uCXCL9/10) chemokines have reached a sufficiently high level of evidence to be recommended by the European Society of Organ Transplantation for the monitoring of immune quiescence. To assess the risk of acute rejection (AR), the advantage of uCXCL9/10 is their cost-effectiveness and their high diagnostic performance. Here, we evaluated the feasibility of a next-generation immunoassay for quantifying uCXCL9/10 levels. It demonstrated high efficiency with minimal workflow and a 90-min time to result. Preanalytical studies indicated stability of uCXCL9/10 levels and analytical studies confirmed excellent linearity and precision. In a cohort of 1048 samples collected at biopsy, the results correlated significantly with ELISA quantification and were integrated into a previously validated 8-parameter urine chemokine model. The next generation immunoassay achieved an accuracy of 0.84 for AR diagnosis. This study validates this technology as a robust, locally available and unexpensive platform and marks a significant step towards the widespread implementation of uCXCL9/10, for immune quiescence monitoring. Therefore, we developed an open-access web application using uCXCL9/10 to calculate AR risk and improve clinical decision-making to perform biopsy, ushering in a new era in kidney transplantation, where personalized, data-driven care becomes the norm.

Dynamic Behaviour of Donor Specific Antibodies in the Early Period Following HLA Incompatible Kidney Transplantation

In HLA-incompatible kidney transplantation, monitoring donor-specific antibodies (DSA) plays a crucial role in providing appropriate treatment and increases kidney survival times. This work aimed to determine if early post-transplant DSA dynamics inform graft outcome over and above other predictive factors. Eighty-eight cases were classified by unsupervised machine learning into five distinct DSA response groups: no response, fast modulation, slow modulation, rise to sustained and sustained. Fast modulation dynamics gave an 80% rate for early acute rejection, whereas the sustained group was associated with the lowest rejection rates (19%). In complete contrast, the five-year graft failure was lowest in the modulation groups (4–7%) and highest in the sustained groups (25–31%). Multivariable analysis showed that a higher pre-treatment DSA level, male gender and absence of early acute rejection were strongly associated with a sustained DSA response. The modulation group had excellent five-year outcomes despite higher rates of early rejection episodes. This work further develops an understanding of post-transplant DSA dynamics and their influence on graft survival following HLA-incompatible kidney transplantation.

Emerging biomarkers in kidney transplantation and challenge of clinical implementation

PURPOSE OF REVIEW

Despite improvement in short-term outcomes after kidney transplantation, long-term outcomes remain suboptimal. Conventional biomarkers are limited in their ability to reliably identify early immunologic and nonimmunologic injury. Novel biomarkers are needed for noninvasive diagnosis of subclinical injury, prediction of response to treatment, and personalization of the care of kidney transplant recipients.

RECENT FINDINGS

Recent biotechnological advances have led to the discovery of promising molecular biomarker candidates. However, translating potential biomarkers from bench to clinic is challenging, and many potential biomarkers are abandoned prior to clinical implementation. Despite these challenges, several promising urine, blood, and tissue novel molecular biomarkers have emerged and are approaching incorporation into clinical practice.

SUMMARY

This article highlights the challenges in adopting biomarker-driven posttransplant management and reviews several promising emerging novel biomarkers that are approaching clinical implementation.

Donor-specific ELISPOT assay for predicting acute rejection and allograft function after kidney transplantation: A systematic review and meta-analysis

Acute rejection remains an important problem after kidney transplantation. Enzyme-linked immunosorbent spot (ELISPOT) assay has been investigated extensively and has shown promising results as a predictor of allograft rejection. The objective of this study was to systematically review and analyze the predictive value of the donor-specific ELISPOT assay to identify recipients at risk for acute rejection. Electronic databases were searched for studies reporting donor-specific ELISPOT and kidney transplantation outcomes. Odds ratio (OR) for acute rejection was calculated, along with standardized mean difference (SMD) of cytokine producing-cells between recipients with and without acute rejection. Pooled estimates were calculated using random-effect models. The positive ELISPOT cutoff frequencies were extracted from each study. From 665 articles found, 32 studies were included in the meta-analysis. IFN-γ was the most investigated cytokine (30 out of 32 studies). Patients with positive pre-transplantation donor-reactive IFN-γ ELISPOT had an OR of 3.3 for acute rejection (95%-CI 2.1 to 5.1), and OR of 6.8 (95%-CI 2.5 to 18.9) for post-transplantation ELISPOT. Recipients with rejection had significantly higher frequencies of pre- and post-transplantation cytokine producing-cells (SMD 0.47, 95%-CI 0.07 to 0.87 and SMD 3.68, 95%-CI 1.04 to 6.32, respectively). Pre-transplantation ELISPOT had a positive predictive value of 43% and a negative predictive value of 81% for acute rejection. A positive ELISPOT result was associated with a lower estimated glomerular filtration rate (SMD -0.59, 95%-CI -0.83 to -0.34). In conclusion, patients with a high frequency of donor-reactive IFN-γ ELISPOT are at higher risk for acute rejection. The donor-specific IFN-γ ELISPOT assay can serve as an immune-monitoring tool in kidney transplantation.

Impact of Proinflammatory Cytokine Gene Polymorphisms and Circulating CD3 on Long-Term Renal Allograft Outcome in Egyptian Patients

The extant study aimed to explore the influence of two cytokines TNF-α - 308 and IFN-γ + 874 gene polymorphism on development of renal transplant rejection and to investigate the feasibility of Th1 cytotoxic immune reaction (CD3). It includes 152 kidney recipients were divided into two subgroups: 76 stable graft functions (SGF) and 76 allograft dysfunctions (AD) compared with 56 healthy individuals as control group. TNF-α - 308 G > A and IFN-γ + 874 A > T genetic polymorphisms were characterized using ARMS-PCR technique. CD3 protein expression was measured using ELISA Kit. The effect on transplant outcome was analyzed where, statistically significant differences of TNF-a-308 G/A were observed between AD group when compared to SGF group (OR = 0.296, 95% CI = 0.091-0.965, p = .031) in AG genotype (intermediate producer genotype). Also, AD group displayed a statistically significant increase of IFN-γ + 874 TT (high producer genotype) when compared to SGF group (OR = 0.290, 95% CI = 0.127-0.665, p = .003). The expression of CD3⁺ T lymphocytes in recipients with allograft dysfunction was statistically higher than that with stable allograft function and control groups (732 ± 76, 235 ± 51 and 442 ± 50) respectively and (p ≤ 0.001). In conclusion, IFN-γ + 874 T and TNF-α - 308 A alleles are risk alleles for renal transplant rejection and these two single nucleotide polymorphisms (SNPs) may be implicated in the tendency of rejection after renal transplantation. CD3 may be used as non-invasive biomarker in monitoring of rejection and avoid exposing patients for biopsy risks and sampling error.

The Small RNA Repertoire of Small Extracellular Vesicles Isolated From Donor Kidney Preservation Fluid Provides a Source for Biomarker Discovery for Organ Quality and Posttransplantation Graft Function

Supplemental Digital Content is available in the text.

Delayed graft function (DGF) after kidney transplantation is negatively associated with long-term graft function and survival. Kidney function after transplantation depends on multiple factors, both donor- and recipient-associated. Prediction of posttransplantation graft function would allow timely intervention to optimize patient care and survival. Currently, graft-based predictions can be made based on histological and molecular analyses of 0-hour biopsy samples. However, such analyses are currently not implemented, as biopsy samples represent only a very small portion of the entire graft and are not routinely analyzed in all transplantation centers. Alternatives are thus required.

High urinary interleukin-2 in late post-transplant period portends a risk of decline in kidney allograft function: a preliminary study

BACKGROUND

Predictive factors for the rate of decline in kidney allograft function beyond the first post-transplant year have not been thoroughly studied. We aimed to determine whether a single measurement of serum and urinary interleukin 2, interleukin 8 and interleukin 10 at 1-15 years after kidney transplantation could predict a decline in estimated glomerular filtration rate (eGFR) over a 2-year period.

RESULTS

Greater serum concentrations of interleukin 8 and interleukin 10 in 30 recipients of kidney allograft at enrollment were associated with lower eGFR after 1 year (beta = - 0.616, p = 0.002 and beta = - 0.393, p = 0.035, respectively), whereas serum concentrations of interleukin 8 also demonstrated significant association with eGFR after 2 years of follow-up (beta = - 0.594, p = 0.003). Higher urinary interleukin 2 concentrations were associated with lower eGFR at baseline (rho = - 0.368, p = 0.049) and after the first (beta = - 0.481, p = 0.008) and the second year (beta = - 0.502, p = 0.006) of follow-up. Higher urinary interleukin 2 concentrations predicted certain decline in eGFR of ≥ 25% from baseline after 1 year of follow-up in logistic regression: odds ratio = 2.94, confidence interval 1.06-8.18, p = 0.038. When combined with time after transplantation, urinary interleukin 2 demonstrated good accuracy in predicting rapid decline in eGFR by > -5 mL/min/1.73 m2/year (area under the receiver-operator characteristic curve: 0.855, confidence interval 0.687-1.000, and p = 0.008).

CONCLUSIONS

Our findings suggest that urinary interleukin 2 in the late period after kidney transplantation has promise in identifying patients who are at risk for progressive loss of graft function in a short-time perspective and need closer monitoring.

Proteins in Preservation Fluid as Predictors of Delayed Graft Function in Kidneys from Donors after Circulatory Death

BACKGROUND AND OBJECTIVES

Kidney transplantation is the preferred treatment for ESRD, and donor kidney shortage urges proper donor-recipient matching. Zero-hour biopsies provide predictive values for short- and long-term transplantation outcomes, but are invasive and may not reflect the entire organ. Alternative, more representative methods to predict transplantation outcome are required. We hypothesized that proteins accumulating in preservation fluid during cold ischemic storage can serve as biomarkers to predict post-transplantation graft function.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Levels of 158 proteins were measured in preservation fluids from kidneys donated after circulatory death (Maastricht category III) collected in two Dutch centers (University Medical Center Utrecht and Erasmus Medical Center Rotterdam) between 2013 and 2015. Five candidate biomarkers identified in a discovery set of eight kidneys with immediate function (IF) versus eight with delayed graft function (DGF) were subsequently analyzed in a verification set of 40 additional preservation fluids to establish a prediction model.

RESULTS

Variables tested for their contribution to a prediction model included five proteins (leptin, periostin, GM-CSF, plasminogen activator inhibitor-1, and osteopontin) and two clinical parameters (recipient body mass index [BMI] and dialysis duration) that distinguished between IF and DGF in the discovery set. Stepwise multivariable logistic regression provided a prediction model on the basis of leptin and GM-CSF. Receiver operating characteristic analysis showed an area under the curve (AUC) of 0.87, and addition of recipient BMI generated a model with an AUC of 0.89, outperforming the Kidney Donor Risk Index and the DGF risk calculator, showing AUCs of 0.55 and 0.59, respectively.

CONCLUSIONS

We demonstrate that donor kidney preservation fluid harbors biomarkers that, together with information on recipient BMI, predict short-term post-transplantation kidney function. Our approach is safe, easy, and performs better than current prediction algorithms, which are only on the basis of clinical parameters.

High Urinary Aspartate Aminotransferase in the Late Posttransplant Period Predicts Rapid, Progressive Decline in Kidney Allograft Function

OBJECTIVES

Scant information is available on factors for predicting the rate of decline in kidney allograft function beyond 1 year posttransplant.We investigated whether urinary enzymes (alanine aminotransferase, alkaline phosphatase, aspartate aminotransferase, N-acetyl-β-D-hexosaminidase, and ε-glutamyl transpeptidase) in the late postoperative period can predict the decline in estimated glomerular filtration rate.

MATERIALS AND METHODS

In 79 kidney allograft recipients 1 to 17 years after kidney transplant, we assessed a value of urinary enzymes single measurement for predicting the slope of estimated glomerular filtration rate, rapid decline in estimated glomerular filtration rate (> 5 mL/min/1.73 m² /y), and significant decline in estimated glomerular filtration rate (≥ 25% from baseline) during a 2-year period.

RESULTS

At baseline, patients with estimated glomerular filtration rate < 60 mL/min/1.73 m² (n = 54) differed from those with estimated glomerular filtration rate ≥ 60 mL/min/1.73 m² (n = 25) only in their lower median urinary alanine aminotransferase:creatinine ratio (expressed as U/L:mmol/L): 0.055 versus 0.222 (P = .011). Higher urinary activity of aspartate aminotransferase at baseline predicted the negative-slope value for estimated glomerular filtration rate (beta, -0.279; standard error, 0.131; P = .037) and decline in estimated glomerular filtration rate of > 5 mL/min/1.73 m ²/year (odds ratio, 2.06; 95% confidence interval, 1.10-3.83; P = .023) over 2 years. It also predicted the drop in estimated glomerular filtration rate ≥ 25% after 1 year (odds ratio, 2.62; 95% confidence interval, 1.07-6.37; P = .034) and 2 years (odds ratio, 2.75; 95% confidence interval, 1.12-6.73; P =.027). Combined with time after transplant, urinary aspartate aminotransferase had good power for predicting an estimated glomerular filtration rate decrease ≥ 25% after 2 years of follow-up.

CONCLUSIONS

Higher urinary activity of aspartate aminotransferase in the late posttransplant period is useful for identifying transplant patients who are at risk for progressive loss of graft function.

Computational Models for Transplant Biomarker Discovery

Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist. Current advent of genomics and proteomics profiling called "omics" provides new resources to develop novel biomarkers for clinical routine. Establishing such a marker system heavily depends on appropriate applications of computational algorithms and software, which are basically based on mathematical theories and models. Understanding these theories would help to apply appropriate algorithms to ensure biomarker systems successful. Here, we review the key advances in theories and mathematical models relevant to transplant biomarker developments. Advantages and limitations inherent inside these models are discussed. The principles of key -computational approaches for selecting efficiently the best subset of biomarkers from high--dimensional omics data are highlighted. Prediction models are also introduced, and the integration of multi-microarray data is also discussed. Appreciating these key advances would help to accelerate the development of clinically reliable biomarker systems.

Pre- and Posttransplant IgA Anti-Fab Antibodies to Predict Long-term Kidney Graft Survival

OBJECTIVES

Immunologic factors are reliable markers for allograft monitoring, because of their seminal role in rejection process. One of these factors is the immunoglobulin (Ig)A anti-Fab of the IgG antibody. This study aimed to evaluate the predictive value of pre- and posttransplant levels of this marker for kidney allograft function and survival.

METHODS

Sera samples of 59 living unrelated donor kidney recipients were collected before and after transplantation (days 7, 14, and 30) and investigated for IgA anti-Fab of IgG antibody levels using enzyme-linked immunosorbent assay in relation with allograft outcome.

RESULTS

Among 59 patients, 15 cases (25%) including 10 with acute rejection and 5 with chronic rejection episodes showed graft failure during a mean of 5 years of follow-up. High posttransplant levels of IgA anti-Fab antibodies were observed more frequently in patients with stable graft function (SGF) compared with patients with graft failure (P = 2 × 10(-6)). None of patients with acute or chronic rejection episodes had high levels of IgA anti-Fab antibodies at day 30 posttransplant compared with the SGF group (P = 10(-6) and P = .01, respectively). In addition, high levels of IgA anti-Fab antibody correlated with lesser concentration of serum creatinine at 1 month posttransplantation (P = .01). Five-year graft survival was associated with high levels of pre- and posttransplant IgA anti-Fab antibodies (P = .02 and P = .003, respectively).

CONCLUSIONS

Our findings indicate the protective effect of higher levels of IgA anti-Fab antibodies regarding to kidney allograft outcomes and long-term graft survival.

The histology of kidney transplant failure: a long-term follow-up study

BACKGROUND

The relative impact on renal allograft outcome of specific histological diagnoses versus nonspecific chronic histological damage remains unclear.

METHODS

All 1,197 renal allograft recipients who were transplanted at a single center between 1991 and 2001 were included. All posttransplant renal allograft indication biopsies performed in this cohort during follow-up (mean, 14.5±2.80 years after transplantation) were rescored according to the current histological criteria and associated with death-censored graft outcome.

RESULTS

In this cohort, 1,365 allograft indication biopsies were performed. Specific diagnoses were present in 69.4% of graft biopsies before graft loss, but 30.6% of grafts did not have specific diagnoses in the last biopsy before graft loss. Only 14.6% of the patients did never have any specific disease diagnosed before graft loss. Extensive interstitial fibrosis and tubular atrophy without a clear cause was identified as the single cause of graft loss in only 6.9% of the cases. Acute T-cell-mediated rejection and changes suggestive of acute antibody-mediated rejection, diagnosed after the first year posttransplant, associated independently with graft survival. Transplant glomerulopathy increased over time after transplantation and represented a major risk for graft loss, as well as de novo or recurrent glomerular pathologies and polyomavirus nephropathy. Chronic histological injury associated with graft outcome, independent of specific diagnoses.

CONCLUSION

Renal allograft loss is multifactorial. Chronic histological damage and specific diseases had additive and independent impact on graft outcome. Chronic damage should be taken into account in prognostication of renal allograft outcome and could be implemented in treatment algorithms for specific diseases of kidney allografts.

Evaluation of molecular profiles in calcineurin inhibitor toxicity post-kidney transplant: input to chronic allograft dysfunction

The molecular basis of calcineurin inhibitor toxicity (CNIT) in kidney transplantation (KT) and its contribution to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA) were evaluated by: (1) identifying specific CNIT molecular pathways that associate with allograft injury (cross-sectional study) and (2) assessing the contribution of the identified CNIT signature in the progression to CAD with IF/TA (longitudinal study). Kidney biopsies from well-selected transplant recipients with histological diagnosis of CNIT (n = 14), acute rejection (n = 13) and CAD with IF/TA (n = 10) were evaluated. Normal allografts (n = 18) were used as controls. To test CNIT contribution to CAD progression, an independent set of biopsies (n = 122) from 61 KT patients collected at 3 and ~12 months post-KT (range = 9-18) were evaluated. Patients were classified based on 2-year post-KT graft function and histological findings as progressors (n = 30) or nonprogressors to CAD (n = 31). Molecular signatures characterizing CNIT samples were identified. Patients classified as progressors showed an overlap of 7% and 22% with the CNIT signature at 3 and at ~12 months post-KT, respectively, while the overlap was <1% and 1% in nonprogressor patients, showing CNIT at the molecular level as a nonimmunological factor involved in the progression to CAD.

Distinct metabolic profile of primary focal segmental glomerulosclerosis revealed by NMR-based metabolomics

Background

Primary focal segmental glomerulosclerosis (FSGS) is pathological entity which is characterized by idiopathic steroid-resistant nephrotic syndrome (SRNS) and progression to end-stage renal disease (ESRD) in the majority of affected individuals. Currently, there is no practical noninvasive technique to predict different pathological types of glomerulopathies. In this study, the role of urinary metabolomics in the diagnosis and pathogenesis of FSGS was investigated.

Methods

NMR-based metabolomics was applied for the urinary metabolic profile in the patients with FSGS (n = 25), membranous nephropathy (MN, n = 24), minimal change disease (MCD, n = 14) and IgA nephropathy (IgAN, n = 26), and healthy controls (CON, n = 35). The acquired data were analyzed using principal component analysis (PCA) followed by orthogonal projections to latent structure discriminant analysis (OPLS-DA). Model validity was verified using permutation tests.

Results

FSGS patients were clearly distinguished from healthy controls and other three types of glomerulopathies with good sensitivity and specificity based on their global urinary metabolic profiles. In FSGS patients, urinary levels of glucose, dimethylamine and trimethylamine increased compared with healthy controls, while pyruvate, valine, hippurate, isoleucine, phenylacetylglycine, citrate, tyrosine, 3-methylhistidine and β-hydroxyisovalerate decreased. Additionally, FSGS patients had lower urine N-methylnicotinamide levels compared with other glomerulopathies.

Conclusions

NMR-based metabonomic approach is amenable for the noninvasive diagnosis and differential diagnosis of FSGS as well as other glomerulopathies, and it could indicate the possible mechanisms of primary FSGS.

Early post-transplant immune monitoring can predict long-term kidney graft survival: soluble CD30 levels, anti-HLA antibodies and IgA-anti-Fab autoantibodies

This study aimed to investigate the predictive power of anti-HLA antibodies, sCD30 levels and IgA-anti-Fab autoantibody before and early after transplantation in relation to long-term kidney allograft survival. Pre- and post-transplant sera samples of 59 living-unrelated donor kidney recipients were tested for above risk factors by enzyme-linked immunoabsorbent assay. 15 out of 59 cases experienced rejection episodes (failure group). Pre- and post-transplant high sCD30 levels were significantly associated with graft failure (P=0.02 and P=0.004) and decreased 4 year graft survival (P = 0.009 and P = 0.001). Higher frequency of post-transplant HLA class-II antibody in the absence of class-I antibody was observed in failure group (P=0.007). Patients with post-transplant HLA class-I and class-II antibodies either alone or in combination showed significant lower 4 year graft survival. Recipients with high sCD30 levels in the presence of HLA class-I or class-II antibodies within 2 weeks post-transplant had poor graft survival (P = 0.004 and P = 0.002, respectively). High levels of post-transplant IgA-anti-Fab antibody was more frequent in functioning-graft patients (P = 0.00001), correlated with decreased serum creatinine levels (P = 0.01) and associated with improved graft survival (P = 0.008). Our findings indicate the deleterious effect of early post-transplant HLA antibodies and increased sCD30 levels dependently and protective effect of IgA-anti-Fab antibodies on long-term renal graft outcomes.

Renal ischemia-reperfusion injury amplifies the humoral immune response

Renal transplant recipients who experience delayed graft function have increased risks of rejection and long-term graft failure. Ischemic damage is the most common cause of delayed graft function, and although it is known that tissue inflammation accompanies renal ischemia, it is unknown whether renal ischemia affects the production of antibodies by B lymphocytes, which may lead to chronic humoral rejection and allograft failure. Here, mice immunized with a foreign antigen 24-96 hours after renal ischemia-reperfusion injury developed increased levels of antigen-specific IgG1 compared with sham-treated controls. This amplified IgG1 response did not follow unilateral ischemia, and it did not occur in response to a T-independent antigen. To test whether innate immune activation in the kidney after ischemia affects the systemic immune response to antigen, we repeated the immunization experiment using mice deficient in factor B that lack a functional alternative pathway of complement. Renal ischemia-reperfusion injury did not cause amplification of the antigen-specific antibodies in these mice, suggesting that the increased immune response requires a functional alternative pathway of complement. Taken together, these data suggest that ischemic renal injury leads to a rise in antibody production, which may be harmful to renal allografts, possibly explaining a mechanism underlying the link between delayed graft function and long-term allograft failure.

Immunologic monitoring in transplantation revisited

PURPOSE OF REVIEW

Tailoring immunosuppressive drugs to an individual's needs is crucial to improve long-term outcomes of organ transplant patients. The purpose of this review is to summarize the data on promising biomarkers able to detect the risk of acute or chronic rejection and to discuss the potential issues for their implementation in the clinic.

RECENT FINDINGS

Multiple publications have indicated that circulating antibodies targeting human leukocyte antigen (HLA) and non-HLA antigens as well as donor-specific memory T cells are associated with accelerated graft failure. Other studies published within the year show that specific genomic and proteomic signatures obtained from urine, blood, and graft tissue correlate with acute rejection in kidney and heart transplant patients.

SUMMARY

The development of reliable biomarkers is crucial for individualizing therapy aimed at extending allograft survival and improving patient health. Emerging data indicate that monitoring assays, likely used in panels, have the potential to be diagnostic and possibly predictive of long-term outcome. In addition to ongoing discovery efforts, progress in the field will require multicenter validation, assay standardization, and commercialization so as to efficiently deliver reliable testing strategies to the practicing clinician.

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.

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

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

MicroRNAs as biomarkers in solid organ transplantation

Important progress has been made in improving short-term outcomes in solid organ transplantation. However, long-term outcomes have not improved during the last decades. There is a critical need for biomarkers of donor quality, early diagnosis of graft injury and treatment response. MicroRNAs (miRNAs) are a class of small single-stranded noncoding RNAs that function through translational repression of specific target mRNAs. MiRNA expression has been associated with different diseases and physiological conditions. Moreover, miRNAs have been detected in different biological fluids and these circulating miRNAs can distinguish diseased individuals from healthy controls. The noninvasive nature of circulating miRNA detection, their disease specificity and the availability of accurate techniques for detecting and monitoring these molecules has encouraged a pursuit of miRNA biomarker research and the evaluation of specific applications in the transplant field. miRNA expression might develop as excellent biomarkers of allograft injury and function. In this minireview, we summarize the main accomplishments of recently published reports focused on the identification of miRNAs as biomarkers in organ quality, ischemia-reperfusion injury, acute rejection, tolerance and chronic allograft dysfunction emphasizing their mechanistic and clinical potential applications and describing their methodological limitations.

The implications of acute rejection for allograft survival in contemporary U.S. kidney transplantation

BACKGROUND

We examined the frequency and clinical impact of acute rejection (AR) in contemporary U.S. kidney transplantation.

METHODS

Data for Medicare-insured kidney transplant recipients in 2000 to 2007 (n=48,179) were drawn from the United States Renal Data System. AR events were ascertained from Organ Procurement and Transplantation Network reports. AR was subclassified as antibody (Ab)-treated AR or other management (non-Ab-treated AR). Associations of AR with subsequent all-cause graft loss were estimated with time-varying Cox regression. Covariates included recipient, donor, and transplant factors in the United Network for Organ Sharing Kidney Allocation Review Committee survival model.

RESULTS

The frequencies of non-Ab-treated AR per 100 graft-years at risk among standard criteria donor recipients over the first 6, 12, 24, and 36 months after transplantation were 9.93, 8.43, 5.71, and 4.70, respectively. Non-Ab-treated AR was consistently more than twice as common as Ab-treated AR by risk period and donor type. Development of Ab-treated AR predicted a greater risk of graft loss than non-Ab-treated AR. The relative risk for graft loss from Ab-treated AR continuously increased with later timing of AR after transplantation, whereas risk associated with non-Ab-treated AR peaked for events reported in months 13 to 24 after kidney transplantation. Regardless of the diagnosis time, the relative risk of graft loss was higher in the first 89 days after a given AR report compared with 90 days and beyond.

CONCLUSIONS

AR events recognized later after transplantation have more serious graft loss implications, especially within the first 89 days after AR reporting. This observation may reflect reduced intensity of monitoring, delays in diagnosis, or clinicopathologic features of late AR.

Changes of progesterone-induced blocking factor in patients after kidney transplantation

The prediction of graft rejection can play an important part in graft survival. Analysis of immune reactions has shown that graft rejection shares mechanisms with recurrent abortions during pregnancy. Progesterone-induced blocking factor (PIBF), a mediator of progesterone that blocks natural killer cell activity in peripheral blood, produces antiabortive effects. The aim of this study was to examine the PIBF concentration in the urine of transplanted recipients. The study included 116 white adults (70 men and 46 women) of median age 49.3 years, who had undergone kidney transplantations. The median duration after transplantation was 3.46 years. The average period between renal disease and our measurement was 12.3 years, and the median interval between graft rejection and our study was 1.75 years. Urine samples were used to measure PIBF concentrations by an enzyme-linked immunsorbent assay. PIBF urinary concentrations decreased significantly in patients who experienced ≥1 rejection episode (31.8±2.2 ng/mL) compared with those without any episode (22.7±1.2 ng/ml; P<.01). Moreover, the urinary PIBF level was significantly lower among patients who had increased creatinine and urea nitrogen levels in blood samples (P<.05 and P<.01, respectively). Decreased PIBF values in kidney transplant patients followed previous rejection episodes. A close negative correlation was observed between urinary PIBF concentrations and blood levels of creatinine and urea nitrogen. These findings suggested that PIBF detection may predict graft rejection in transplant recipients.

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.