Diagnosis of renal transplant rejection: Banff classification and beyond

Epithelial cell states associated with kidney and allograft injury

The kidney epithelium, with its intricate arrangement of highly specialized cell types, constitutes the functional core of the organ. Loss of kidney epithelium is linked to the loss of functional nephrons and a subsequent decline in kidney function. In kidney transplantation, epithelial injury signatures observed during post-transplantation surveillance are strong predictors of adverse kidney allograft outcomes. However, epithelial injury is currently neither monitored clinically nor addressed therapeutically after kidney transplantation. Several factors can contribute to allograft epithelial injury, including allograft rejection, drug toxicity, recurrent infections and postrenal obstruction. The injury mechanisms that underlie allograft injury overlap partially with those associated with acute kidney injury (AKI) and chronic kidney disease (CKD) in the native kidney. Studies using advanced transcriptomic analyses of single cells from kidney or urine have identified a role for kidney injury-induced epithelial cell states in exacerbating and sustaining damage in AKI and CKD. These epithelial cell states and their associated expression signatures are also observed in transplanted kidney allografts, suggesting that the identification and characterization of transcriptomic epithelial cell states in kidney allografts may have potential clinical implications for diagnosis and therapy.

Predicting Cellular Rejection of Renal Allograft Based on the Serum Proteomic Fingerprint

Kidney transplantation is an essential medical procedure that significantly enhances the survival rates and quality of life for patients with end-stage kidney disease. However, despite advancements in immunosuppressive therapies, allograft rejection remains a leading cause of organ loss. Notably, predictions of cellular rejection processes primarily rely on biopsy analysis, which is not routinely performed due to its invasive nature. The present work evaluates if the serum proteomic fingerprint, as acquired by Fourier Transform Infrared (FTIR) spectroscopy, can predict cellular rejection processes. We analyzed 28 serum samples, corresponding to 17 without cellular rejection processes and 11 associated with cellular rejection processes, as based on biopsy analyses. The leave-one-out-cross validation procedure of a Naïve Bayes model enabled the prediction of cellular rejection processes with high sensitivity and specificity (AUC > 0.984). The serum proteomic profile was obtained in a high-throughput mode and based on a simple, rapid, and economical procedure, making it suitable for routine analyses and large-scale studies. Consequently, the current method presents a high potential to predict cellular rejection processes translatable to clinical scenarios, and that should continue to be explored.

Assessment of CTLA-4 Gene Expression Levels on CD8+ T Cells in Renal Transplant Patients and Relation with Serum sCTLA-4 Levels

CTLA-4 (Cytotoxic T Lymphocyte Antigen-4) is an immune regulator molecule that is expressed on a variety of immune cells, including CD4+ and CD8+ T cells. After realizing the significance of this regulator molecule, researchers began to concentrate on its activation or inhibition in cancer. Even though there have been some studies on organ transplantation and autoimmunity, the role of the CTLA-4 molecule in renal transplantation has not been demonstrated. The goal of this study was to see how CTLA-4 gene expression and serum sCTLA-4 levels affected renal transplant patients. Peripheral blood samples were collected before and 1-3 months after renal transplantation from 29 recipients. CD8+ T lymphocytes were separated using magnetic beads and purity of the cells controlled by Flow cytometry. CTLA-4 mRNA levels were determined by Real-Time PCR while serum sCTLA-4 levels were assessed by ELISA. 55% of the patient had decreased level of CTLA-4 mRNA after transplantation when compared to pre-transplantation levels. Moreover 61% of the patient had lower serum sCTLA-4 levels after transplantation. sCTLA-4 levels were decreased 11% of the patients with rejection episode after transplantation when compared to stabile patients (5%). Kidney rejection is a complicated process influenced by numerous unknown factors. Several parameters should be evaluated together to precise rejection episodes or graft dysfunctions. Further research focused on the other immune checkpoint regulator molecules could give an opportunity to have an idea about the effect of these molecules on renal transplantation.

Kidney cortex shear wave motion simulations based on segmented biopsy histology

BACKGROUND AND OBJECTIVE

Biopsy stands as the gold standard for kidney transplant assessment, yet its invasive nature restricts frequent use. Shear wave elastography (SWE) is emerging as a promising alternative for kidney transplant monitoring. A parametric study involving 12 biopsy data sets categorized by standard biopsy scores (3 with normal histology, 3 with interstitial inflammation (i), 3 with interstitial fibrosis (ci), and 3 with tubular atrophy (ct)), was conducted to evaluate the interdependence between microstructural variations triggered by chronic allograft rejection and corresponding alterations in SWE measurements.

METHODS

Heterogeneous shear wave motion simulations from segmented kidney cortex sections were performed employing the staggered-grid finite difference (SGFD) method. The SGFD method allows the mechanical properties to be defined on a pixel-basis for shear wave motion simulation. Segmentation techniques enabled the isolation of four histological constituents: glomeruli, tubules, interstitium, and fluid. Baseline ex vivo Kelvin-Voigt mechanical properties for each constituent were drawn from established literature. The parametric evaluation was then performed by altering the baseline values individually. Shear wave velocity dispersion curves were measured with the generalized Stockwell transform in conjunction with slant frequency-wavenumber analysis (GST-SFK) algorithm. By fitting the curve within the 100-400 Hz range to the Kelvin-Voigt model, the rheological parameters, shear elasticity (µ1) and viscosity (µ2), were estimated. A time-to-peak algorithm was used to estimate the group velocity. The resultant in silico models emulated the heterogeneity of kidney cortex within the shear wave speed (SWS) reconstructions.

RESULTS

The presence of inflammation showed considerable spatial composition disparities compared to normal cases, featuring a 23 % increase in interstitial area and a 19 % increase in glomerular area. Concomitantly, there was a reduction of 12 % and 47 % in tubular and fluid areas, respectively. Consequently, mechanical changes induced by inflammation predominate in terms of rheological differentiation, evidenced by increased elasticity and viscosity. Mild tubular atrophy showed significant elevation in group velocity and µ1. Conversely, mild and moderate fibrosis exhibited negligible alterations across all parameters, compatible with relatively limited morphological impact.

CONCLUSIONS

This proposed model holds promise in enabling patient-specific simulations of the kidney cortex, thus facilitating exploration into how pathologies altering cortical morphology correlates to modifications in SWE-derived rheological measurements. We demonstrated that inflammation caused substantial changes in measured mechanical properties.

Using 1/2 Descending Time in CEUS to Identify Renal Allograft Rejection

RATIONALE AND OBJECTIVES

This study investigates the potential of quantitative Contrast-Enhanced Ultrasound (CEUS) parameters to distinguish between graft dysfunction due to rejection and non-rejection in kidney transplant recipients.

METHODS

In this retrospective study, 50 kidney transplant patients who presented elevated serum creatinine or proteinuria were analyzed. They were categorized as rejection or non-rejection based on biopsy outcomes. These classifications were applied in both derivation (n = 33) and validation cohorts (n = 17). Prior to the biopsy, all patients underwent a CEUS. Quantitative parameters derived from the CEUS were further analyzed for their consistency and reliability. Additionally, the relationship between the Banff scores, a standard for diagnosing transplant rejections, and these CEUS parameters was explored.

RESULTS

Significant differences between rejection and non-rejection groups were observed in the CEUS parameters of derivation cohorts. Specifically, Peak Intensity (PI), 1/2 Descending Time (DT/2), Area Under Curve (AUC), and Mean Transit Time (MTT) stood out. Sensitivity and specificity for these parameters were 76.5% and 87.5% for PI, 76.5% and 81.2% for DT/2, 76.5% and 87.5% for AUC, and 68.8% and 94.1% for MTT, respectively. DT/2 and MTT showed superior interobserver agreement compared to PI and AUC. When extrapolating the cutoff values from the derivation cohort to the validation group, DT/2 and AUC exhibited optimal diagnostic precision with positive and negative predictive values being 91.7% vs. 100% and 100% vs. 85.7%, respectively. Additionally, DT/2 effectively differentiated between mild and moderate to severe microvascular inflammation, pivotal in diagnosing antibody-mediated renal transplant rejection.

CONCLUSION

DT/2 from CEUS parameters presents as a reliable tool to differentiate rejection from non-rejection causes in renal transplant dysfunction. Yet, large-scale, multi-center studies are essential for further validation.

Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions

INTRODUCTION

Artificial intelligence (AI) integration in nephropathology has been growing rapidly in recent years, facing several challenges including the wide range of histological techniques used, the low occurrence of certain diseases, and the need for data sharing. This narrative review retraces the history of AI in nephropathology and provides insights into potential future developments.

METHODS

Electronic searches in PubMed-MEDLINE and Embase were made to extract pertinent articles from the literature. Works about automated image analysis or the application of an AI algorithm on non-neoplastic kidney histological samples were included and analyzed to extract information such as publication year, AI task, and learning type. Prepublication servers and reviews were not included.

RESULTS

Seventy-six (76) original research articles were selected. Most of the studies were conducted in the United States in the last 7 years. To date, research has been mainly conducted on relatively easy tasks, like single-stain glomerular segmentation. However, there is a trend towards developing more complex tasks such as glomerular multi-stain classification.

CONCLUSION

Deep learning has been used to identify patterns in complex histopathology data and looks promising for the comprehensive assessment of renal biopsy, through the use of multiple stains and virtual staining techniques. Hybrid and collaborative learning approaches have also been explored to utilize large amounts of unlabeled data. A diverse team of experts, including nephropathologists, computer scientists, and clinicians, is crucial for the development of AI systems for nephropathology. Collaborative efforts among multidisciplinary experts result in clinically relevant and effective AI tools.

Immune landscape of the kidney allograft in response to rejection

Preventing kidney graft dysfunction and rejection is a critical step in addressing the nationwide organ shortage and improving patient outcomes. While kidney transplants (KT) are performed more frequently, the overall number of patients on the waitlist consistently exceeds organ availability. Despite improved short-term outcomes in KT, comparable progress in long-term allograft survival has not been achieved. Major cause of graft loss at 5 years post-KT is chronic allograft dysfunction (CAD) characterized by interstitial fibrosis and tubular atrophy (IFTA). Accordingly, proactive prevention of CAD requires a comprehensive understanding of the immune mechanisms associated with either further dysfunction or impaired repair. Allograft rejection is primed by innate immune cells and carried out by adaptive immune cells. The rejection process is primarily facilitated by antibody-mediated rejection (ABMR) and T cell-mediated rejection (TCMR). It is essential to better elucidate the actions of individual immune cell subclasses (e.g. B memory, Tregs, Macrophage type 1 and 2) throughout the rejection process, rather than limiting our understanding to broad classes of immune cells. Embracing multi-omic approaches may be the solution in acknowledging these intricacies and decoding these enigmatic pathways. A transition alongside advancing technology will better allow organ biology to find its place in this era of precision and personalized medicine.

Evolution of human kidney allograft pathology diagnostics through 30 years of the Banff classification process

The second half of the previous century witnessed a tremendous rise in the number of clinical kidney transplants worldwide. This activity was, however, accompanied by many issues and challenges. An accurate diagnosis and appropriate management of causes of graft dysfunction were and still are, a big challenge. Kidney allograft biopsy played a vital role in addressing the above challenge. However, its interpretation was not standardized for many years until, in 1991, the Banff process was started to fill this void. Thereafter, regular Banff meetings took place every 2 years for the past 30 years. Marked changes have taken place in the interpretation of kidney allograft biopsies, diagnosis, and classification of rejection and other non-rejection pathologies from the original Banff 93 classification. This review attempts to summarize those changes for increasing the awareness and understanding of kidney allograft pathology through the eyes of the Banff process. It will interest the transplant surgeons, physicians, pathologists, and allied professionals associated with the care of kidney transplant patients.

Artificial Intelligence Advances in Transplant Pathology

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians' decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

Biomarkers for Kidney-Transplant Rejection: A Short Review Study

Kidney transplantation is the preferred treatment for end-stage renal failure, but the limited availability of donors and the risk of immune rejection pose significant challenges. Early detection of acute renal rejection is a critical step to increasing the lifespan of the transplanted kidney. Investigating the clinical, genetic, and histopathological markers correlated to acute renal rejection, as well as finding noninvasive markers for early detection, is urgently needed. It is also crucial to identify which markers are associated with different types of acute renal rejection to manage treatment effectively. This short review summarizes recent studies that investigated various markers, including genomics, histopathology, and clinical markers, to differentiate between different types of acute kidney rejection. Our review identifies the markers that can aid in the early detection of acute renal rejection, potentially leading to better treatment and prognosis for renal-transplant patients.

New Developments and Challenges in Liver Transplantation

Liver disease is increasing in incidence and is the third most common cause of premature death in the United Kingdom and fourth in the United States. Liver disease accounts for 2 million deaths globally each year. Three-quarters of patients with liver disease are diagnosed at a late stage, with liver transplantation as the only definitive treatment. Thomas E. Starzl performed the first human liver transplant 60 years ago. It has since become an established treatment for end-stage liver disease, both acute and chronic, including metabolic diseases and primary and, at present piloting, secondary liver cancer. Advances in surgical and anaesthetic techniques, refined indications and contra-indications to transplantation, improved donor selection, immunosuppression and prognostic scoring have allowed the outcomes of liver transplantation to improve year on year. However, there are many limitations to liver transplantation. This review describes the milestones that have occurred in the development of liver transplantation, the current limitations and the ongoing research aimed at overcoming these challenges.

Pathophysiology of Rejection in Kidney Transplantation

Kidney transplantation has been the optimal treatment for end-stage kidney disease for almost 70 years, with increasing frequency over this period. Despite the prevalence of the procedure, allograft rejection continues to impact transplant recipients, with consequences ranging from hospitalization to allograft failure. Rates of rejection have declined over time, which has been largely attributed to developments in immunosuppressive therapy, understanding of the immune system, and monitoring. Developments in these therapies, as well as an improved understanding of rejection risk and the epidemiology of rejection, are dependent on a foundational understanding of the pathophysiology of rejection. This review explains the interconnected mechanisms behind antibody-mediated and T-cell-mediated rejection and highlights how these processes contribute to outcomes and can inform future progress.

The Flow Cytometric Analysis of Peripheral Blood Lymphocytes and Expression of HLA II Molecules in Lymphocyte During Acute Rejection After Renal Transplantation

Objective

To investigate the changes in the proportion of peripheral blood lymphocytes and the expression of HLA II molecules in lymphocytes during acute rejection after renal transplantation.

Methods

Thirty-five patients who had undergone renal transplantation were selected. Eighteen patients with clinical and pathological confirmed acute rejection were selected as the test group, and twelve patients without clinical acute rejection symptoms were selected as the control group. Flow cytometry analysis was used to determine the proportion of peripheral blood lymphocytes. The mRNA and protein expression of HLA II molecules on peripheral blood lymphocytes were detected using real-time fluorescence quantification and immunoblotting, respectively.

Results

The proportion of T lymphocytes, B lymphocytes, and CD4CD8 double positive T cells in the Control Group were 67.48% ± 5.35%, 10.82% ± 1.26%, and 0.88% ± 0.06%, respectively, and in the Test Group were 87.52% ± 6.28%, 3.36% ± 0.26%, and 0.34% ± 0.03%, with a significant difference respectively. The mRNA and protein expressions of HLA II molecules of peripheral blood B lymphocytes in the control group were significantly higher that these in the test group.

Conclusion

The proportion of peripheral blood T lymphocytes, B lymphocytes, CD4CD8 double positive T cells, and the expression of HLA II molecules of peripheral blood lymphocytes can all indicate the occurrence of acute renal transplantation rejection, which were exceedingly useful to clinicians in judging the acute rejection of renal transplantation in the early stages.

Development and validation of urinary exosomal microRNA biomarkers for the diagnosis of acute rejection in kidney transplant recipients

Introduction

Acute rejection (AR) continues to be a significant obstacle for short- and long-term graft survival in kidney transplant recipients. Herein, we aimed to examine urinary exosomal microRNAs with the objective of identifying novel biomarkers of AR.

Materials and methods

Candidate microRNAs were selected using NanoString-based urinary exosomal microRNA profiling, meta-analysis of web-based, public microRNA database, and literature review. The expression levels of these selected microRNAs were measured in the urinary exosomes of 108 recipients of the discovery cohort using quantitative real-time polymerase chain reaction (qPCR). Based on the differential microRNA expressions, AR signatures were generated, and their diagnostic powers were determined by assessing the urinary exosomes of 260 recipients in an independent validation cohort.

Results

We identified 29 urinary exosomal microRNAs as candidate biomarkers of AR, of which 7 microRNAs were differentially expressed in recipients with AR, as confirmed by qPCR analysis. A three-microRNA AR signature, composed of hsa-miR-21-5p, hsa-miR-31-5p, and hsa-miR-4532, could discriminate recipients with AR from those maintaining stable graft function (area under the curve [AUC] = 0.85). This signature exhibited a fair discriminative power in the identification of AR in the validation cohort (AUC = 0.77).

Conclusion

We have successfully demonstrated that urinary exosomal microRNA signatures may form potential biomarkers for the diagnosis of AR in kidney transplantation recipients.

Quantitative ultrasound for non-invasive evaluation of subclinical rejection in renal transplantation

OBJECTIVES

This study aimed to investigate the predictive efficacy of shear-wave elastography, superb microvascular imaging (SMI), and CEUS for allograft rejection in kidney transplants without graft dysfunction.

METHODS

From January 2021 to November 2021, 72 consecutive patients who underwent both allograft biopsy and ultrasound were evaluated. Blood test results were obtained within a week of the ultrasound examinations, which were performed before the protocol biopsy. Resistive index (RI), tissue viscoelasticity, vascular index, and quantitative CEUS parameters were measured. Patients were divided based on biopsy results into the rejection and non-rejection groups.

RESULTS

Among the 72 patients, 21 patients had pathological characteristics of acute rejection. RI of allograft was significantly higher in the rejection group (p = 0.007), compared to the non-rejection group. There were no significant between-group differences in vascular indices of SMI, mean elasticity, and mean viscosity. Meanwhile, among the parameters obtained by the time-intensity curve on CEUS, the cortical and medullary ratios of average contrast signal intensity, peak enhancement, wash-in area AUC, wash-in perfusion index, wash-out AUC, and wash-in and wash-out AUC were significantly different between the two groups (p < 0.05). In the receiver operating characteristic curve analysis for predicting allograft rejection, the AUC was 0.853 for the combination of six CEUS parameters, RI, and blood urea nitrogen.

CONCLUSIONS

Among non-invasive quantitative ultrasound measurements, CEUS parameters are the most useful for diagnosing subclinical allograft rejection. Furthermore, the combination of CEUS parameters, RI, and blood urea nitrogen may be helpful for the early detection of renal allograft rejection.

KEY POINTS

• Among non-invasive quantitative ultrasound measurements, CEUS parameters are the most useful for the diagnosis of subclinical allograft rejection. • On CEUS, the C/M ratios of MeanLin, PE, WiAUC, WiPI, WoAUC, and WiWoAUC are significantly lower in the rejection group; the combination of these showed reliable predictive performance for rejection. • The combination of CEUS parameters, RI, and BUN has a high predictive capability for subclinical allograft rejection.

Protocol Biopsy After Kidney Transplant: Clinical Application and Efficacy to Detect Allograft Rejection

Background Kidney transplant rejection is a major cause of graft dysfunction and failure. In recent years, there has been increased interest in renal allograft protocol biopsies to allow earlier detection of acute or chronic graft dysfunction or rejection to improve long-term graft survival and reduce graft failure. This study aimed to determine if renal allograft protocol biopsies performed within the first 12 months after transplantation help detect subclinical graft dysfunction or rejection. Methods We performed a retrospective analysis utilizing SUNY Upstate University Hospital data from January 2016 to March 2022 to assess transplant outcomes and biopsies. The study population was divided into two subgroups: non-protocol biopsies and protocol biopsies within the 12 months post-transplant. Results A total of 332 patients met our inclusion criteria and were included in the study. Patients were divided into two subgroups: 135 patients (40.6%) in the protocol biopsy group and 197 patients (59.4%) with non-protocol indication biopsies during the first year after the transplant. The overall number of rejection episodes reported was eight episodes (4.6%) in the protocol biopsy group and 56 episodes (18.3%) in the non-protocol indication biopsy group, which was significantly higher in the non-protocol biopsy group (P=0.001). Antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR) diagnoses were significantly higher in the non-protocol biopsy group (P=0.03 and P=0.03, respectively). We also mentioned a trend in terms of mixed antibody-mediated rejection and T-cell-mediated rejection diagnosis (P=0.07). One year after the rejection, the mean glomerular filtration rate (GFR) was 56.78 mL/min/1.73m² in the protocol biopsy group and 49.14 mL/min/1.73m² in the non-protocol indication biopsy group, and there was no significant difference anymore (P=0.11). The patient survival rate was not significantly higher in the protocol biopsy group compared to the non-protocol indication biopsy group (P=0.42). Conclusion This study suggests that performing protocol biopsies does not significantly benefit rejection rates, graft survival, or renal function within the first 12 months post-transplant. Given these results and the small but non-zero risk of complications associated with protocol biopsies, they should be reserved for those patients at high risk of rejection. It may be more feasible and beneficial to utilize less invasive tests, such as DSA and dd-cfDNA testing, for early diagnosis of a rejection episode.

Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives

Antibody-mediated rejection (ABMR) is the major cause of chronic allograft dysfunction and loss in kidney transplantation. The immunological mechanisms of ABMR that have been featured in the latest studies indicate a highly complex interplay between various immune and nonimmune cell types. Clinical diagnostic standards have long been criticized for being arbitrary and the lack of accuracy. Transcriptomic approaches, including microarray and RNA sequencing of allograft biopsies, enable the identification of differential gene expression and the continuous improvement of diagnostics. Given that conventional bulk transcriptomic approaches only reflect the average gene expression but not the status at the single-cell level, thereby ignoring the heterogeneity of the transcriptome across individual cells, single-cell RNA sequencing is rising as a powerful tool to provide a high-resolution transcriptome map of immune cells, which allows the elucidation of the pathogenesis and may facilitate the development of novel strategies for clinical treatment of ABMR.

Combined impact of the inter and intra-patient variability of tacrolimus blood level on allograft outcomes in kidney transplantation

Introduction

Tacrolimus (TAC) has been widely used as an immunosuppressant after kidney transplantation (KT); however, the combined effects of intra-patient variability (IPV) and inter-patient variability of TAC-trough level (C0) in blood remain controversial. This study aimed to determine the combined impact of TAC-IPV and TAC inter-patient variability on allograft outcomes of KT.

Methods

In total, 1,080 immunologically low-risk patients who were not sensitized to donor human leukocyte antigen (HLA) were enrolled. TAC-IPV was calculated using the time-weighted coefficient variation (TWCV) of TAC-C0, and values &gt; 30% were classified as high IPV. Concentration-to-dose ratio (CDR) was used for calculating TAC inter-patient variability, and CDR &lt; 1.05 ng•mg/mL was classified as rapid metabolizers (RM). TWCV was calculated based on TAC-C0 up to 1 year after KT, and CDR was calculated based on TAC-C0 up to 3 months after KT. Patients were classified into four groups according to TWCV and CDR: low IPV/non-rapid metabolizer (NRM), high IPV/NRM, low IPV/RM, and high IPV/RM. Subgroup analysis was performed for pre-transplant panel reactive antibody (PRA)-positive and -negative patients (presence or absence of non-donor-specific HLA-antibodies). Allograft outcomes, including deathcensored graft loss (DCGL) and biopsy-proven allograft rejection (BPAR), were compared.

Results

The incidences of DCGL, BPAR, and overall graft loss were the highest in the high-IPV/RM group. In addition, a high IPV/RM was identified as an independent risk factor for DCGL. The hazard ratio of high IPV/RM for DCGL and the incidence of active antibody-mediated rejection were considerably increased in the PRA-positive subgroup.

Discussion

High IPV combined with RM (inter-patient variability) was closely related to adverse allograft outcomes, and hence, more attention must be given to pre-transplant PRA-positive patients.

Assessing the Global Impact on the Mouse Kidney After Traumatic Brain Injury: A Transcriptomic Study

Purpose

In this study, we use animal models combined with bioinformatics strategies to investigate the potential changes in overall renal transcriptional expression after traumatic brain injury.

Methods

Microarray analysis was performed after kidney acquisition using unilateral controlled cortical impact as the primary mouse TBI model. Multi-oriented gene set enrichment analysis was performed for differentially expressed genes.

Results

The results showed that TBI affected the gene set associated with mitochondria function in kidney cells, and a negative enrichment of gene sets associated with immune cell migration and epidermal development was also observed. Analysis of the disease phenotype gene set revealed that differential expression of mitochondria-related genes was associated with lactate metabolism. Alternatively, activation and adhesion of immune cells associated with the complement system may promote autoinflammation in kidney tissue. The simulated immune cell infiltration analysis showed an increase in the proportion of activated memory CD4 T cells and a decrease in the proportion of resting memory CD4 T cells, suggesting that activated memory CD4 T cell infiltration may be involved in the inflammation of renal tissue and cause damage to renal cells, such as principal cells, mesangial cells and loops of Henle cells.

Conclusion

This study is the first to reveal the effects of brain trauma on the kidney. TBI may affect the expression of mitochondria function-related gene sets in renal cells by increasing lactate. It may also affect renal mesangial cells by inducing increased infiltration of immune cells through mechanisms related to complement system activation or autoimmune antibodies.

Shifting Clinical Trial Endpoints in Kidney Transplantation: The Rise of Composite Endpoints and Machine Learning to Refine Prognostication

The measurement of outcomes in kidney transplantation has been more accurately documented than almost any other surgical procedure result in recent decades. With significant improvements in short- and long-term outcomes related to optimized immunosuppression, outcomes have gradually shifted away from conventional clinical endpoints (ie, patient and graft survival) to surrogate and composite endpoints. This article reviews how outcomes measurements have evolved in the past 2 decades in the setting of increased data collection and summarizes recent advances in outcomes measurements pertaining to clinical, histopathological, and immune outcomes. Finally, we discuss the use of composite endpoints and Bayesian concepts, specifically focusing on the integrative box risk prediction score, in conjunction with machine learning to refine prognostication.

Point-of-care non-invasive enzyme-cleavable nanosensors for acute transplant rejection detection

Accurate and non-invasive monitoring of allograft posttransplant is essential for early detection of acute cellular rejection and determines the long-term survival of the graft. Clinically, tissue biopsy is the most effective approach for diagnosing transplant rejection. Nonetheless, the procedure is invasive and potentially triggers organ failure. This work aims to design and apply GzmB-responsive nanosensors (GBRNs) that can readily size-change in graft tissues. Subsequently, we investigate the activity of serine protease granzyme B by generating a direct colorimetric urinary readout for non-invasive detection of transplant rejection in under 1 h. In preclinical heart graft mice models of transplant rejection, GBRNs were cleaved by GzmB and excreted by the kidneys via accurate nanometre-size glomerular filtration. By exploiting the catalytic activity of ultrasmall gold nanoclusters, GBRNs urinalysis promotes ultrasensitive surveillance of rejection episodes with a receiver operator characteristic curve area under the curve of 0.896 as well as a 95% confidence interval of about 0.7701-1.000. Besides, the catalytic activity of gold nanoclusters in urine can be detected at point-of-care testing to predict the immunity responses in mice with insufficient immunosuppressive therapy. Therefore, this non-invasive, sensitive, and quantitative method is a robust and informative approach for rapid and routine monitoring of transplant allografts without invasive biopsy.

Omics-based biomarkers for diagnosis and prediction of kidney allograft rejection

Kidney transplantation is the preferred treatment for patients with end-stage kidney disease, because it prolongs survival and improves quality of life. Allograft biopsy is the gold standard for diagnosing allograft rejection. However, it is invasive and reactive, and continuous monitoring is unrealistic. Various biomarkers for diagnosing allograft rejection have been developed over the last two decades based on omics technologies to overcome these limitations. Omics technologies are based on a holistic view of the molecules that constitute an individual. They include genomics, transcriptomics, proteomics, and metabolomics. The omics approach has dramatically accelerated biomarker discovery and enhanced our understanding of multifactorial biological processes in the field of transplantation. However, clinical application of omics-based biomarkers is limited by several issues. First, no large-scale prospective randomized controlled trial has been conducted to compare omics-based biomarkers with traditional biomarkers for rejection. Second, given the variety and complexity of injuries that a kidney allograft may experience, it is likely that no single omics approach will suffice to predict rejection or outcome. Therefore, integrated methods using multiomics technologies are needed. Herein, we introduce omics technologies and review the latest literature on omics biomarkers predictive of allograft rejection in kidney transplant recipients.

Increasing Incidence of Inadequate Kidney Biopsy Samples Over Time: A 16-Year Retrospective Analysis From a Large National Renal Biopsy Laboratory

Introduction

Renal biopsy remains an essential tool for the diagnosis and treatment of patients with medical kidney disease. Recently, there has been a perceived change in the number of inadequate samples. The aim of this study was to determine the native renal biopsy miss rate from 2005 to 2020 at Arkana Laboratories, a nationwide kidney biopsy service.

Methods

From 2005 to 2020, a total of 123,372 native kidney biopsies were received from >2500 nephrologists practicing across 44 US states. The miss rate was determined by age and year. In a subset of biopsies received in 2005 and 2018, the biopsy operator was determined, nephrologist or radiologist. Furthermore, the miss rate, needle gauge, biopsy depth by operator, and biopsy core width by gauge were measured.

Results

The miss rate increased markedly from 2% in 2005 to 14% in 2020. Radiologists performed 5% of biopsies in 2005 and 95% in 2018 using smaller diameter (18g/20g) needles 92% of the time. Glomeruli per centimeter of core biopsy and mean core width were significantly lower with smaller needles. The miss rate deep was significantly lower for nephrologists and remained consistent within operator between the 2 time points. The miss rate did not correlate with the increasing age of the population who had biopsies.

Conclusion

This increase in kidney biopsy miss rate significantly affects patient care in the management of medical kidney disease. Its correlation with the complete reversal in operators suggests an urgent need for interaction with and training of radiologists in this critical technique.

Surfing the Big Data Wave: Omics Data Challenges in Transplantation

In both research and care, patients, caregivers, and researchers are facing a leap forward in the quantity of data that are available for analysis and interpretation, marking the daunting "big data era." In the biomedical field, this quantitative shift refers mostly to the -omics that permit measuring and analyzing biological features of the same type as a whole. Omics studies have greatly impacted transplantation research and highlighted their potential to better understand transplant outcomes. Some studies have emphasized the contribution of omics in developing personalized therapies to avoid graft loss. However, integrating omics data remains challenging in terms of analytical processes. These data come from multiple sources. Consequently, they may contain biases and systematic errors that can be mistaken for relevant biological information. Normalization methods and batch effects have been developed to tackle issues related to data quality and homogeneity. In addition, imputation methods handle data missingness. Importantly, the transplantation field represents a unique analytical context as the biological statistical unit is the donor-recipient pair, which brings additional complexity to the omics analyses. Strategies such as combined risk scores between 2 genomes taking into account genetic ancestry are emerging to better understand graft mechanisms and refine biological interpretations. The future omics will be based on integrative biology, considering the analysis of the system as a whole and no longer the study of a single characteristic. In this review, we summarize omics studies advances in transplantation and address the most challenging analytical issues regarding these approaches.

Advanced Tertiary Lymphoid Tissues in Protocol Biopsies are Associated with Progressive Graft Dysfunction in Kidney Transplant Recipients

BACKGROUND

Tertiary lymphoid tissues (TLTs) are ectopic lymphoid tissues found in chronically inflamed organs. Although studies have documented TLT formation in transplanted kidneys, the clinical relevance of these TLTs remains controversial. We examined the effects of TLTs on future graft function using our histologic TLT maturity stages and the association between TLTs and Banff pathologic scores. We also analyzed the risk factors for the development of TLTs.

METHODS

Serial protocol biopsy samples (0 hour, 1, 6, and 12 months) without rejection were retrospectively analyzed from 214 patients who underwent living donor kidney transplantation. TLTs were defined as lymphocyte aggregates with signs of proliferation and their stages were determined by the absence (stage I) or presence (stage II) of follicular dendritic cells.

RESULTS

Only 4% of patients exhibited TLTs at the 0-hour biopsy. Prevalence increased to almost 50% at the 1-month biopsy, and then slightly further for 12 months. The proportion of advanced stage II TLTs increased gradually, reaching 19% at the 12-month biopsy. Presence of stage II TLTs was associated with higher risk of renal function decline after transplantation compared with patients with no TLT or stage I TLTs. Stage II TLTs were associated with more severe tubulitis and interstitial fibrosis/tubular atrophy at 12 months and predicted poorer graft function independently from the degree of interstitial inflammation. Pretransplantation rituximab treatment dramatically attenuated the development of stage II TLTs.

CONCLUSIONS

TLTs are commonly found in clinically stable transplanted kidneys. Advanced stage II TLTs are associated with progressive graft dysfunction, independent of interstitial inflammation.

Urinary Proteomics in Kidney Transplantation

Although kidney transplantation is the best treatment option for end stage kidney disease, it is still associated with long-term graft failure. One of the greater challenges for transplant professionals is the ability to identify grafts with a high risk of failure before initial decline of eGFR with irreversible graft changes. Transplantation medicine is facing an emerging need for novel disease end point-specific biomarkers, with practical application in preventive screening, early diagnostic, and improved prognostic and therapeutic utility. The aim of our review was to evaluate the clinical application of urinary proteomics in kidney transplant recipients at risk for any type of future graft failure.

C4d Deposition after Allogeneic Renal Transplantation in Rats Is Involved in Initial Apoptotic Cell Clearance

In the context of transplantation, complement activation is associated with poor prognosis and outcome. While complement activation in antibody-mediated rejection is well-known, less is known about complement activation in acute T cell-mediated rejection (TCMR). There is increasing evidence that complement contributes to the clearance of apoptotic debris and tissue repair. In this regard, we have analysed published human kidney biopsy transcriptome data clearly showing upregulated expression of complement factors in TCMR. To clarify whether and how the complement system is activated early during acute TCMR, experimental syngeneic and allogeneic renal transplantations were performed. Using an allogeneic rat renal transplant model, we also observed upregulation of complement factors in TCMR in contrast to healthy kidneys and isograft controls. While staining for C4d was positive, staining with a C3d antibody showed no C3d deposition. FACS analysis of blood showed the absence of alloantibodies that could have explained the C4d deposition. Gene expression pathway analysis showed upregulation of pro-apoptotic factors in TCMR, and apoptotic endothelial cells were detected by ultrastructural analysis. Monocytes/macrophages were found to bind to and phagocytise these apoptotic cells. Therefore, we conclude that early C4d deposition in TCMR may be relevant to the clearance of apoptotic cells.

Intrapatient Variability in Tacrolimus Trough Levels Over 2 Years Affects Long-Term Allograft Outcomes of Kidney Transplantation

This study aimed to determine the impact of tacrolimus (TAC) trough level (C0) intrapatient variability (IPV) over a period of 2 years after kidney transplantation (KT) on allograft outcomes. In total, 1,143 patients with low immunologic risk were enrolled. The time-weighted coefficient variability (TWCV) of TAC-C0 was calculated, and patients were divided into tertile groups (T1: < 24.6%, T2: 24.6%–33.7%, T3: ≥ 33.7%) according to TAC-C0-TWCV up to post-transplant 1^st year. They were classified into the low/low, low/high, high/low, and high/high groups based on a TAC-C0-TWCV value of 33.7% during post-transplant 0–1^st and 1^st–2^nd years. The allograft outcomes among the three tertile and four TAC-C0-TWCV groups were compared. The T3 group had the highest rate of death-censored allograft loss (DCGL), and T3 was considered an independent risk factor for DCGL. The low/low group had the lowest and the high/high group had the highest risk for DCGL. Moreover, patients with a mean TAC-C0 of ≥5 ng/ml in the high/high group were at the highest risk for DCGL. Thus, TAC-IPV can significantly affect allograft outcomes even with a high mean TAC-C0. Furthermore, to improve allograft outcomes, a low TAC-IPV should be maintained even after the first year of KT.

Declining trend of preemptive kidney transplantation and impact of pretransplant dialysis: a Korean nationwide prospective cohort study

We evaluated the temporal trend of preemptive kidney transplantation (KT) and the effect of pretransplant dialysis duration on post-transplant outcomes. This was a nationwide cohort study of the first-time 3392 living donor KT (LDKT) recipients (2014-2019). The annual changes in proportion of preemptive KT, factors associated with preemptive KT, and post-transplant outcomes were analyzed. Preemptive KT was performed in 816 (24.1%) patients. Annual trend analysis revealed gradual decrease in preemptive KT over time (P = 0.042). Among the underlying causes of preemptive KT, the proportion of diabetes increased and that of glomerulonephritis decreased during the study period. Glomerulonephritis as the primary renal disease was a predictor of preemptive KT. Patients with pretransplant dialysis >6 months showed increased graft failure risk than preemptive KT in the subdistribution of hazard model for competing risk (adjusted hazard ratio [aHR], 2.53; 95% confidence interval [CI], 1.09-5.87; P = 0.031) and in propensity score-matched analysis (aHR, 2.45; 95% CI, 1.02-5.92; P = 0.034); however, pretransplant dialysis ≤6 months showed comparable graft survival with preemptive KT in both analyses. Preemptive KT declined over successive years, associated with an increase in diabetes and a decrease in glomerulonephritis as underlying causes of KT. Short period of dialysis less than 6 months does not affect graft survival compared with preemptive KT; however, longer dialysis decreases graft survival.

Kidney transplantation in highly sensitized recipients

In kidney transplantation (KT), overcoming donor shortage is particularly challenging in patients with preexisting donor-specific antibodies (DSAs) against human leukocyte antigen (HLA), called HLA-incompatible KT (HLAi KT), carrying the risk of rejection and allograft loss. Thus, it is necessary to accurately evaluate the degree of sensitization before HLAi KT, and undertake appropriate pretreatment strategies. To determine the degree of sensitization, complement-dependent cytotoxicity has been the only method employed; the development of a method using flow cytometry further improved the test sensitivity. However, these tests present disadvantages, including the need for living cells, with a solid-phase assay developed to resolve this problem. Currently, the method using Luminex (Luminex Corp.) is widely used in clinical practice. As this method measures DSAs using single antigen beads, it is possible to classify immunological risks by measuring the type and amount of DSAs. Furthermore, there have been major advances in methods that involve DSA removal before HLAi KT. In the early stages of desensitization, plasmapheresis and intravenous immunoglobulins were the main treatment methods employed; however, the introduction of CD20 monoclonal antibody and proteasome inhibitors further increased the success rate of desensitization. Currently, HLAi KT has been established as an important transplant method, but an understanding of DSAs and a novel desensitization treatment are warranted.

Assessing causality by means of the Naranjo scale in a paediatric patient with life threatening respiratory failure after alemtuzumab administration: a case report

Background

Alemtuzumab is a T cell depleting antibody agent used as induction immunosuppressant therapy in solid organ transplant recipients. In addition, it is being increasingly used to treat severe or glucocorticoid-resistant graft rejection. Despite the effectiveness of the treatment, severe adverse events have been reported related to alemtuzumab administration. We present a similar event illustrating the severity of this adverse drug reaction (ADR) and we highlight the structure causality assessment provides in approaching such a case.

Case presentation

We report a case of life-threatening respiratory failure after alemtuzumab administration in a 17 year old paediatric kidney transplant recipient. He developed near fatal severe respiratory and circulatory failure based on acute respiratory distress syndrome (ARDS) with diffuse alveolar oedema and haemoptysis hours after his second alemtuzumab administration. As it was questionable whether alemtuzumab could be regarded as the origin of his reaction and in order to assess the causality of this reaction as well as to structure clinical reasoning, we applied a widely used ADR probability scale to systematically review our case.

Discussion and conclusions

Our case shows a severe ADR after alemtuzumab administration. It illustrates the importance of proper causality assessment, the structure it provides and the benefit of a clinical pharmacology consultation when a severe reaction is suspected to be an ADR. By taking our case as an example, we demonstrate the added value of structured causality assessment to clinical reasoning and in generating differential diagnoses.

Thrombotic Microangiopathy After Kidney Transplantation: An Underdiagnosed and Potentially Reversible Entity

Thrombotic microangiopathy is a rare but serious complication that affects kidney transplant recipients. It appears in 0.8–14% of transplanted patients and negatively affects graft and patient survival. It can appear in a systemic form, with hemolytic microangiopathic anemia, thrombocytopenia, and renal failure, or in a localized form, with progressive renal failure, proteinuria, or arterial hypertension. Post-transplant thrombotic microangiopathy is classified as recurrent atypical hemolytic uremic syndrome or de novo thrombotic microangiopathy. De novo thrombotic microangiopathy accounts for the majority of cases. Distinguishing between the 2 conditions can be difficult, given there is an overlap between them. Complement overactivation is the cornerstone of all post-transplant thrombotic microangiopathies, and has been demonstrated in the context of organ procurement, ischemia-reperfusion phenomena, immunosuppressive drugs, antibody-mediated rejection, viral infections, and post-transplant relapse of antiphospholipid antibody syndrome. Although treatment of the causative agents is usually the first line of treatment, this approach might not be sufficient. Plasma exchange typically resolves hematologic abnormalities but does not improve renal function. Complement blockade with eculizumab has been shown to be an effective therapy in post-transplant thrombotic microangiopathy, but it is necessary to define which patients can benefit from this therapy and when and how eculizumab should be used.

Impact of acute kidney injury in deceased donors with high Kidney Donor Profile Index on posttransplant clinical outcomes: a multicenter cohort study

BACKGROUND

This study evaluated the impact of acute kidney injury (AKI) on posttransplant clinical outcomes for deceased donor (DD) kidney transplantation (KT) using the Kidney Donor Profile Index (KDPI) system.

METHODS

Overall, 657 kidney transplant recipients (KTRs) receiving kidneys from 526 DDs from four transplant centers were included. We divided them into the high and low KDPI donor groups by 65%, the KDPI score, and both groups were subdivided into the AKI-DDKT and non-AKI-DDKT subgroups according to AKI in DDs.

RESULTS

There was no significant difference in the incidence of delayed graft function (DGF) between the high and low KDPI-KTR groups; however, the AKI-DDKT subgroup showed significantly higher incidence of DGF than the non-AKI-DDKT subgroup in both groups (p = 0.001, p < 0.001, respectively). The death-censored graft survival rate was significantly lower in the high KDPI-KTR group than in the low KDPI-KTR group (p = 0.005). Only in the high KDPI-KTR group, the death-censored graft survival rate was significantly lower in the KT from DDs with AKI stage 3 than KT from DDs with non-AKI or AKI stage 1 or 2 (p = 0.040). The interaction between AKI stage 3 in DDs and high KDPI on the allograft outcome was significant (p = 0.002).

CONCLUSION

KTs from DDs with AKI stage 3 showed an adverse impact on the allograft outcome in the high KDPI-KTR group. Therefore, DDs with a high KDPI score should be managed carefully so that severe AKI does not occur prior to KT.

Effect of Everolimus with Low-Dose Tacrolimus on Development of New-Onset Diabetes After Transplantation and Allograft Function in Kidney Transplantation: A Multicenter, Open-Label, Randomized Trial

Background

This randomized controlled trial aimed to investigate the effect of everolimus (EVL) with low-dose tacrolimus (Tac) on the development of post-transplantation diabetes mellitus (PTDM) in kidney transplantation (KT).

Material/Methods

Seventy-seven kidney transplant patients from 4 transplant centers were included. Patients were randomized to the “EVL group” (n=38) and the “TAC group” (n=39). The target Tac trough level was 2 to 5 ng/mL in the EVL group and 5 to 10 ng/mL in the TAC group.

Results

The 1-year cumulative incidence of PTDM in all patients was 7.8%, and no difference was found between the 2 groups (P=0.0819). Insulin resistance measured with the homeostatic model assessment for insulin resistance showed a significant increase only in the TAC group (1.11 to 1.30, P=0.0492). Allograft rejection rate and estimated glomerular filtration rate (eGFR) follow-ups every 3 months were not significantly different between the 2 groups. However, the EVL group showed a significant increase in the mean eGFR at 9 months and 12 months after KT compared to the baseline value (P=0.0242 and 0.0491, respectively).

The EVL group showed lower insulin resistance and higher allograft function in comparison to the TAC group.

Conclusions

EVL-based immunosuppressive therapy with lower Tac exposure could be a safer alternative for maintenance treatment.

Imaging in Renal Transplants: An Update

Renal transplantation has become the best treatment for the patients with chronic renal insufficiency. The surgical procedures, immunosuppressive regiments and patient follow-up have evolved especially in the last 10 years. However, the diagnosis for renal transplantation dysfunction remained the same in these years. Serum creatinine levels and estimated glomerular filtration rate calculated by serum creatinine based equations are used in routine patient follow-up. Pelvic ultrasonography and color Doppler ultrasonography are used as a first-line imaging method. Assessment of allograft functions both qualitatively and quantitatively are possible using nuclear medicine procedures. Surgical complications, acute tubular necrosis, subacute and/or acute rejection, infections, toxicity due to immunosuppressive medications, complications relating the collecting system, chronic rejection are the main causes for renal function impairment. The imaging procedures can diagnose the worsening of renal transplant function; however, they still lack the ability to differentiate types of rejection as histopathology or differentiate rejection from other causes of allograft dysfunction. The transplant biopsy gives detailed diagnosis for allograft dysfunction, guide the treatment and therefore it is the preferred diagnostic choice in recent years. On recent years, literature on radionuclide imaging is focused on perfusion analysis for the early diagnosis of renal transplant dysfunction and prognostic use of perfusion parameters, and then this article will focus on these studies and their outcome.

Donor-Derived Cell-Free DNA in Kidney Transplantation as a Potential Rejection Biomarker: A Systematic Literature Review

Kidney transplantation (KTx) is the best treatment method for end-stage kidney disease. KTx improves the patient's quality of life and prolongs their survival time; however, not all patients benefit fully from the transplantation procedure. For some patients, a problem is the premature loss of graft function due to immunological or non-immunological factors. Circulating cell-free DNA (cfDNA) is degraded deoxyribonucleic acid fragments that are released into the blood and other body fluids. Donor-derived cell-free DNA (dd-cfDNA) is cfDNA that is exogenous to the patient and comes from a transplanted organ. As opposed to an invasive biopsy, dd-cfDNA can be detected by a non-invasive analysis of a sample. The increase in dd-cfDNA concentration occurs even before the creatinine level starts rising, which may enable early diagnosis of transplant injury and adequate treatment to avoid premature graft loss. In this paper, we summarise the latest promising results related to cfDNA in transplant patients.

Analyses of AUC(0–12) and C0 Compliances within Therapeutic Ranges in Kidney Recipients Receiving Cyclosporine or Tacrolimus

The AUC (area under the concentration time curve) is considered the pharmacokinetic exposure parameter best associated with clinical effects. Unfortunately, no prospective studies of clinical outcomes have been conducted in adult transplant recipients to investigate properly the potential benefits of AUC_(0–12) monitoring compared to the C₀-guided therapy. The aim of the present study was to compare two methods, C₀ (through level) and AUC_(0–12) (area under the concentration time curve), for assessing cyclosporine and tacrolimus concentrations. The study included 340 kidney recipients. The AUC_(0–12) was estimated using a Bayesian estimator and a three-point limited sampling strategy. Therapeutic drug monitoring of tacrolimus performed by using AUC_(0–12) and C₀ showed that tacrolimus in most cases is overdosed when considering C₀, while determination of the AUC_(0–12) showed that tacrolimus is effectively dosed for 27.8–40.0% of patients receiving only tacrolimus and for 25.0–31.9% of patients receiving tacrolimus with MMF (mycophenolate mofetil). In the 1–5 years post-transplantation group, 10% higher CsA (cyclosporine) dose was observed, which was proportionate with a 10% higher AUC_(0–12) exposure value. This indicates good compatibility of the dosage and the AUC(0–12) method. The Bland–Altman plot demonstrated that C₀ and AUC_(0–12) might be interchangeable methods, while the ROC (receiver operating characteristic) curve analysis of the C₀/AUC_(0–12) ratio in the tacrolimus-receiving patient group demonstrated reliable performance to predict IFTA (interstitial fibrosis and tubular atrophy) after kidney transplantation, with an ROC curve of 0.660 (95% confidence interval (CI): 0.576–0.736), p < 0.01. Moreover, AUC_(0–12) and C₀ of tacrolimus depend on concomitant medication and adjustment of the therapeutic range for AUC_(0–12) might influence the results.

Renoprotective Effects of Alpha-1 Antitrypsin against Tacrolimus-Induced Renal Injury

The protective effects of alpha-1 antitrypsin (AAT) in tacrolimus (TAC)-induced renal injury was evaluated in a rat model. The TAC group rats were subcutaneously injected with 2 mg/kg TAC every day for four weeks. The TAC with AAT group was cotreated with daily subcutaneous injections of TAC and intraperitoneal injections of AAT (80 mg/kg) for four weeks. The effects of AAT on TAC-induced renal injury were evaluated using serum biochemistry, histopathology, and Western blotting. The TAC injection significantly increased renal interstitial fibrosis, inflammation, and apoptosis as compared to the control treatment. The histopathological examination showed that cotreatment of TAC and AAT attenuated interstitial fibrosis (collagen, fibronectin, and α-SMA staining), and α-SMA expression in Western blotting was also decreased. Immunohistochemical staining for inflammation (osteopontin and ED-1 staining) revealed improved interstitial inflammation in the TAC with AAT group compared to that in the TAC group. The TAC treatment increased renal apoptosis compared to the control treatment, based on the results of increased immunohistochemical staining of terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL), increased caspase-3 activity, and lower Bcl-2 to Bad expression ratio. However, AAT cotreatment significantly changed these markers and consequently showed decreased apoptosis. AAT protects against TAC-induced renal injury via antifibrotic, anti-inflammatory, and antiapoptotic effects.

Deceased vs. living donor kidney transplantation in prediction of acute renal allograft rejection using Tc-99m DTPA renal scan

OBJECTIVES

No data are available regarding different prognostic values of Tc-99m diethylenetriaminepentaacetic acid (DTPA) renal scan in kidney transplantation (KT) recipients according to two distinct donor types: deceased donor KT (DDKT) and living donor KT (LDKT). We evaluated whether the interpretation of Tc-99m DTPA renal scan should be different by the donor type in predicting acute renal allograft rejection (AR).

METHODS

One hundred and seven KT recipients (61 DDKT and 46 LDKT) were included in this study. Tc-99m DTPA renal scan was performed 1 week after KT. AR was defined as pathological evidence of renal allograft rejection during the first 6 months of KT. Clinical factors and Tc-99m DTPA renal scan findings were compared between patients with and without AR. To further analyze the effect of the donor type, they were again compared within DDKT and LDKT recipients, respectively.

RESULTS

AR occurred in 15 patients (7 DDKT and 8 LDKT recipients). Among all patients, time to peak uptake (TTP) of the cortex (TTP_CX) measured by Tc-99m DTPA renal scan was independently predictive of AR. Moreover, TTP_KD (TTP of the whole transplanted kidney) and TTP_CX were the only predictors of AR among DDKT recipients. The most accurate predictors were TTP_CX and kidney area on renal scan for DDKT and LDKT, respectively. However, these parameters could not predict AR for the opposite donor type.

CONCLUSIONS

AR could be effectively predicted by Tc-99m DTPA renal scan obtained at 1 week post-KT. Different parameters should be applied according to the donor type in the prediction of AR.