T-cell Mediated Rejection Research Articles

316.1: Incidence and Effect on Survival of Delayed Graft Function in Donor-Deceased Kidney Transplants in Argentina: A Multicenter Analysis

Introduction: Delayed graft function (DGF) is a manifestation of acute kidney injury with attributes unique to the transplant process. DGF is associated with negative outcomes such as higher incidence of acute rejection, worse graft function and lower grafts and patients´ survival. Although the worldwide incidence of DGF is variable, a previous study showed that the incidence in Argentina is higher than the US and most countries in Europe. Therefore, the aim of our study was to identify the risk factors associated with DGF in Argentina and to evaluate the impact of DGF on grafts´ and patients´ survival. Methods: Retrospective multicenter cohort study of deceased-donor kidney transplant from 33 transplant centers in Argentina between 2015 and 2017. Demographic data and donor and recipient related variables were analyzed at baseline and at 3 and 5 years of follow-up. Data were obtained from SINTRA/ INCUCAI, the Argentinian procurement organization and from the transplant centers. Results: Between 2015 and 2017, 1886 single kidney transplants were performed in 33 centers. Recipient and donor characteristics are shown in Table 1. In the current study, the incidence of DGF was 62%. Univariate analysis demonstrated that higher donor creatinine, donor age, recipient time on dialysis, donor BMI, absence of induction and cold ischemia time were risk factors associated with DGF. Multiple organ donation and cause of death other than stroke were associated with reduced risk DGF. In the multivariable analysis donor age (0.02), higher donor creatinine (0.02), recipient time on dialysis (<0.01), cold ischemia time (<0.01), monorganic donor (<0.01)) were risk factors of DGF. Renal function was significatively better in patients without DGF throughout the 5 years follow -up (p<0.05). Patients with DGF had higher incidence of acute rejection in the first three months of follow-up, with T-cell mediated rejection being the most frequent. At 3 and 5 years of follow up there was no increased risk of rejection when both groups were compared. Graft survival and patient survival were lower in the group that developed DGF at 1, 3 and 5 years of follow-up (<0.01) (Figure 1). Conclusion: We confirmed the high incidence of DGF in our country. Furthermore, the analysis on the risk factors associated with DGF were not as much as different as in other countries where the incidence of DGF were lower. Further studies should be done to unravel the cause of this high incidence of DGF in Argentina. Heads of Transplant Centers: WalterJ, Raffaele P, Ciappa M, Paladini J, De la Fuente J, Novoa P, Soler Pujol G, Toselli L, Suso E, Ferreyra M, Fragale G, Reinoso S, Acosta F, Sgrosso J, Arriola M, Maldonado R, Acosta M, Prado R, Sedevich A, Martinez I, Di Pietrantonio S, Oddino J, Trimarchi H, Raimondi C, Gómez M, Dorado E, Palti G, Mele P, Maggiora E, Papaginovic Leiva M. Kidney Commitee: Ibañez J, Benitez ML, Leon L, Mesias M, Osella F.

315.8: The Molecular Nature of the Banff iIFTA Lesion

Introduction: Inflammation within areas of interstitial fibrosis and tubular atrophy (iIFTA) have been linked to adverse outcomes in kidney transplantation through an association with T-cell immunity leading to altered renal parenchymal structures. To date there is no literature that describes changes in the transcriptome in transplant recipients with iIFTA lesions. Further, molecular evidence for the progression of the banff iIFTA lesion, within the first year of transplantation, remains absent from the literature. Herein we define molecular changes within kidney allografts with an iIFTA lesion. We further characterise molecular signatures that accurately describe the progression of iIFTA at 12-months on a 3-month protocol biopsy. Methods: We performed RNA sequencing of 113 protocol biopsies with all samples scored by the same histopathologist. Differentially expressed genes were deemed significant if they had a Benjamini-Hochberg adjusted P < 0.05. We then performed a gene set enrichment analysis using the gene ontology database to identify biological pathways that were enriched in iIFTA lesions. We also compared the transcriptomic profiles of patients with antibody- and T-cell mediated rejection with the iIFTA lesion. We further interrogated the same cohort for the progression of their iIFTA score at 12-months. Differential gene expression, and pathway analysis were employed to identify risk genes in patients that developed high iIFTA at 12-months post-transplant. Results: Of the 113 biopsies with RNA sequencing, 37 demonstrated iIFTA by histopathology. Following transcriptomic analysis, 336 genes were differentially expressed in biopsies with an iIFTA diagnosis. The top tanking genes and pathways were all involved in the formation of immunoglobin and B-cell activation. Further, transcriptomic changes in the iIFTA lesion closely resembled those found in antibody-mediated rejection. Finally, we demonstrate that genomic information, from both peripheral blood and kidney biopsy 3-months post-transplant, provides better prediction power than clinical data in identifying patients with iIFTA lesions.Conclusion: RNA sequencing enabled us to identify novel transcriptomic changes in patients with iIFTA. This pathology is primarily driven by immune-based changes, closely resembling antibody-mediated rejection, which is at odds with the current concept of iIFTA mediated by T-cell activation. Further, this study aims to build a foundation for using molecular technology in identifying the progression of the Banff iIFTA lesion.

P8.045: Modern Medicine Needs Modern Technology Tools

Introduction: Early detection of subclinical rejection is critical to prevent the allograft loss. Currently used methods to detect subclinical rejection include surveillance biopsy protocol, serum creatinine level, eGFR or DSA; however, these methods have limited sensitivity and specificity to accurately detect subclinical rejection. Donor derived cell-free DNA (dd cf-DNA) is a non-invasive biomarker for allograft injury and has been shown to predict allograft rejection with higher sensitivity to detect subclinical rejection compare to some methods (1,2). Here, we show the value of dd cf-DNA in detecting early allograft rejection by presenting two cases where dd cf-DNA assay, AlloSure (CareDx) detected subclinical rejection while other indicators showed stable allograft function. Methods: Ochsner uses AlloSure (CareDx) for a surveillance for the high-risk patients. Results: Thirty-two years old Caucasian female with end stage kidney disease secondary to HIV infection underwent deceased-donor renal transplant in 2018 with KDPI 19% and cPRA 84%. Serum creatinine level had been stable at 1.1mg/dL to 1.2mg/dL post-transplant. This patient was monitored using AlloSure (CareDx) for 1-,2-,3-,4-,6- and 9-month post-transplant. AlloSure values for month 1 to 6 were <0.21, which indicates stable allograft function. However, at 9-month post-transplant, AlloSure value went up to 4.5%, which indicates possible allograft injury, while serum creatinine level remained stable at 1.2 mg/dL with low level of class 2 DSA (DR-1573). Despite stable creatinine level and low level DSA, we initiated biopsy because of sharp increase in AlloSure value. Biopsy revealed acute T-cell mediated rejection and acute vascular rejection. The second case is a 33 years-old Caucasian female with history of previous renal transplant. The first allograft failed in 2018 due to renal artery and vein thrombosis. The patient underwent deceased donor kidney transplant in 2019. Serum creatinine level was stable at 1.0 – 1.3 mg/dL and sharp increase in respectively. At month 3, AlloSure value went up to 0.78% but DSA was negative. We initiated biopsy based on increase in AlloSure value and it revealed acute antibody mediated rejection (ABMR) (Figure 1). The third case is a 56 years-old male with history of end-stage renal disease secondary to hypertension. The patient received deceased donor kidney transplant in 2017. He developed acute renal failure (Cr went up from 1.2 mg/dl to 1.7 mg/dL) few months after kidney transplant and his kidney biopsy showed acute antibody mediated rejection and T-cell mediated rejection which were treated. At 1-year post-transplant, serum creatinine level remained 1.2 mg/dL to 1.3 mg/dL. He was place on monthly Allosure surveillance. The first value was 1.9%, which indicate possible allograft injury. Monthly monitoring showed increase trend in AlloSure value up to 4.1% while Cr remained stable at 1.2 mg/dL-1.3 mg/dL. At that point, biopsy was performed, and it revealed acute antibody mediated rejection and chronic active antibody rejection. Patient was treated with for ABMR. In addition, monthly Tocilizumab was considered for chronic active antibody mediated rejection for 6 months. AlloSure values reflected the early detection of rejection in a patient with stable Cr as well as the efficacy of treatment with down trending values (Figure 2). Conclusion: For all 3 cases, biopsy would not have been initiated most likely due to stable creatinine level and weak or negative DSA. If this had gone untreated for long period of time, this would have led to significant decrease in graft survival. These cases demonstrate that normal serum creatinine does not mean patient has no active inflammatory process. When other indicators are normal/stable, AlloSure was able to detect early rejection. All three cases demonstrated the value of AlloSure as a monitoring tool for detection of early allograft rejection.

336.3: Clinical Utility of Donor-Derived Cell-Free DNA During the Period of Recovery of Renal Function After Kidney Transplantation

Background: The transplant of kidneys with high KDPI, and the incidence and duration of delayed graft function (DGF) are risk factors associated with incomplete recovery of kidney function (IRF). In both situations, kidney biopsies are essential to exclude the diagnosis of acute rejection (AR). Purpose: This study evaluates the clinical utility of monitoring donor-derived cell-free DNA (dd-cfDNA), a biomarker of kidney injury, in recipients of high Kidney Donor Profile Index (KDPI) transplants during the period of kidney function recovery. Methods: This is a single center, prospective, cohort study in recipients of high KDPI kidneys who developed delayed graft function (DGF), defined as the need for dialysis within the first week after transplantation. All patients received a single 3 mg/kg anti-thymocyte globulin dose, tacrolimus, mycophenolate, and prednisone. Blood samples were obtained at 14 (D14) and 30 (D30) days to measure the percentage (%) of dd-cfDNA. The dd-cfDNA > 1% is associated with increased probability for acute rejection (AR). Results: This preliminary analysis includes data from 69 patients. The median KDPI was 73% [IQR 47-87] and the mean cold ischemia time was 27± 7 hours. The incidence of DGF was 89.8% with a median duration of 6 (IQR 2 – 9) days. At D14 the median GFR was 12 ml/min/1.73 m2 (IQR 6-21) and the median dd-cfDNA levels were 0.43% (IQR 0.02-0.78), with 19 patients (28%) showing dd-cfDNA >1%. Surveillance biopsies during DGF were performed in 42 (61%) patients showing one T-cell mediated rejection IA (dd-cfDNA of 0.41%) and 4 borderline changes (dd-cfDNA 0.82%, 0.85%, 0.98%, 1.90%). Using dd-cfDNA >1% to guide the indication of the surveillance biopsy, we would have avoided 22 (52%) biopsies but missed 1 (2%) patient with AR. At D30, the median GFR was 36 ml/min/1.73 m2 (IQR 28-48) and the median dd-cfDNA levels were 0.40% (IQR 0.01-0.66), with 12 patients (19%) showing dd-cfDNA >1%. Surveillance biopsies performed in 21 (30.43%) patients with incomplete recovery of kidney function showed 4 borderline changes (dd-cfDNA 0.17%, 0.66%, 0.67%, and 2.80%). Using dd-cfDNA >1% to guide the indication of the surveillance biopsy, we would have avoided 12 (57%) biopsies without missing any AR episodes. Overall, 5 (7%) patients showed dd-cfDNA >1% at D14 and D30, but none of them showed biopsy confirmed AR. Conclusions: This preliminary analysis suggests that monitoring dd-cfDNA may assist clinical decision during the period of DGF and in kidney transplant recipients with incomplete recovery of graft function.

PIRCHE-II scores prove useful as a predictive biomarker among kidney transplant recipients with rejection: An analysis of indication and follow-up biopsies.

BackgroundIndication biopsies for deterioration of kidney allograft function often require follow-up biopsies to assess treatment response or lack of improvement. Immune-mediated injury, namely borderline rejection (BLR), T-cell mediated rejection (TCMR), or antibody-mediated rejection (ABMR), results from preformed or de novo alloreactivity due to donor and recipient HLA-mismatches. The impact of HLA-mismatches on alloreactivity is determined by highly immunogenic HLA-epitopes.MethodsWe analyzed 123 kidney transplant recipients (KTRs) from 2009 to 2019 who underwent a first indication and a follow-up biopsy. KTRs were divided into three groups according to the first biopsy: No rejection (NR)/BLR (n=68); TCMR (n=21); ABMR (n=34). The HLA-derived epitope-mismatches were calculated using the Predicted Indirectly Recognizable HLA-Epitopes (PIRCHE-II) algorithm.ResultsGroup NR/BLR: KTRs with higher total PIRCHE-II scores were more likely to develop TCMR in the follow-up biopsy (p=0.031). Interestingly, these differences were significant for both HLA-class I- (p=0.017) and HLA-class II-derived (p=0.017) PIRCHE-II scores. Group TCMR: KTRs with ongoing TCMR in the follow-up biopsy were more likely to show higher total PIRCHE-II scores (median 101.50 vs. 74.00). Group ABMR: KTRs with higher total PIRCHE-II scores were more likely to show an increase in the microvascular inflammation score in the follow-up biopsy. This difference was more pronounced for the HLA-class II-derived PIRCHE-II scores (median 70.00 vs. 31.76; p=0.086).ConclusionsPIRCHE-II scores may prove useful as a biomarker to predict the histopathological changes of immune-related injury from a first indication to a follow-up biopsy. This immunological risk stratification may contribute to individualized treatment strategies.

Genome-wide association study biomarkers in T-cell mediated rejection: selective effect according to the Banff classification.

A genome-wide association study (GWAS) in kidney transplant recipients reported the association of two polymorphisms located in the PTPRO gene and upstream of the CCDC67 (DEUP1) gene with increased risk of acute T cell-mediated rejection (TCMR). We aimed at replicating the assessment ofmentioned associations and additionally ascertaining the influence of treatment and clinical features of the patients. The polymorphisms, PTPRO-rs7976329 and CCDC67-rs10765602 were genotyped by TaqMan chemistry in 641 consecutive kidney transplant recipients. The diagnosis of rejection was confirmed by biopsy and categorized according to the Banff classification. Associations were evaluated by Chi-square test or Fisher's exact test when necessary and multivariate logistic regression. Considering the GWAS study we only replicated the association of the PTPRO-rs7976329*C allele in the Banff grade < II subjects. However, the homozygous mutant genotypes of both polymorphism seemed to increase the risk of TCMR Banff grade < II in the overall cohort and after stratification by Thymoglobulin induction therapy. In the multivariate analysis, we confirmed the association of PTPRO-rs7976329 with TCMR Banff grade < II, independently of the Thymoglobulin induction therapy and of CCDC67-rs10765602 only in the group of patients not receiving Thymoglobulin induction therapy. No association of these polymorphisms with TCMR Banff grade ≥ II was observed in either the overall cohort or in the subgroups stratified by Thymoglobulin therapy. Our study shows that the increased risk of TCMR related to polymorphisms PTPRO-rs7976329 and CCDC67-rs10765602 previously reported in a GWAS was replicated only in homozygous patients who presented TCMR Banff grade < II and for the minor allele of either polymorphism.

Levels of donor-derived cell-free DNA and chemokines in BK polyomavirus-associated nephropathy.

BK polyomavirus-associated nephropathy (BKPyVAN) carries a risk of irreversible allograft injury. While detection of BK viremia and biopsy assessment are the current diagnostic gold standard, the diagnostic value of biomarkers reflecting tissue injury (donor-derived cell-free DNA [dd-cfDNA]) or immune activation (C-X-C motif chemokine ligand [CXCL]9 and CXCL10) remains poorly defined. For this retrospective study, 19 cases ofBKPyVANwere selected from the Vienna transplant cohort (biopsies performed between 2012 and 2019). Eight patients with T cell-mediated rejection (TCMR), 17 with antibody-mediated rejection (ABMR) and 10 patients without polyomavirus nephropathy or rejection served as controls. Fractions of dd-cfDNAwere quantified using next-generation sequencing and CXCL9 and CXCL10 were detected using multiplex immunoassays. BKPyVANwas associated with a slight increase in dd-cfDNA(median; interquartile range: .38% [.27%-1.2%] vs. .21% [.12%-.34%] in non-rejecting control patients; p=.005). Levels were far lower than in ABMR (1.2% [.82%-2.5%]; p=.004]), but not different from TCMR (.54% [.26%-3.56%]; p=.52). Within theBKPyVANcohort, we found no relationship between dd-cfDNAlevels and the extent of tubulo-interstitial infiltrates,BKPyVANclass and BK viremia/viruria, respectively. In some contrast to dd-cfDNA, concentrations of urinary CXCL9 and CXCL10 exceeded those detected in ABMR, but similar increases were also found in TCMR. BKPyVANcan induce moderate increases in dd-cfDNAand concomitant high urinary excretion of chemokines, but this pattern may be indistinguishable from that of TCMR. Our results argue against a significant value of these biomarkers to reliably distinguishBKPyVANfrom rejection.

Acute Antibody-mediated Rejection Coexisting With T Cell-mediated Rejection in Pediatric ABO-incompatible Transplantation.

Background.The management and outcome of ABO-incompatible (ABO-I) liver transplantation (LT) has been improving over the past few decades. Recently, the introduction of a pathological evaluation of acute antibody-mediated rejection (AMR) for liver allograft has provided a new recognition of allograft rejection in LT.Methods.One hundred and one pediatric ABO-I LTs performed in our institute were retrospectively analyzed. We assessed the clinical manifestations, diagnosis, and treatment of acute AMR, focusing on the recipient age and pathological findings.Results.Twelve cases (11.9%) of acute AMR related to ABO-I were observed. Nine cases developed mixed T cell–mediated rejection (TCMR)/AMR. These consisted of 6 patients in the younger age group for whom the preconditioning treatment was not indicated and 4 patients in the older age group to whom rituximab was administered as planned. Two patients in the older age group to whom preoperative rituximab was not administered as planned developed isolated AMR. Acute AMR in the older group required plasma exchange for treatment, regardless of the coexistence of TCMR. In contrast, those in the younger group were successfully treated by intravenous methylprednisolone pulse and intravenous immunoglobulin without plasma exchange, accounting for mild immune reaction.Conclusions.Acute ABO-I AMR can develop simultaneously with TCMR, even in young patients with a compromised humoral immune response following ABO-I LT. Establishing the accurate diagnosis of AMR with a pathological examination, including component 4d staining, is crucial for optimizing treatment.

Donor-derived Cell-free DNA Measurement in Kidney Transplant Patients Without Allograft Dysfunction: More Evidence and More Questions.

Donor-derived Cell-free DNA Measurement in Kidney Transplant Patients Without Allograft Dysfunction: More Evidence and More Questions.

Urinary CD8+HLA-DR+ T Cell Abundance Non-invasively Predicts Kidney Transplant Rejection.

Early detection of kidney transplant (KT) rejection remains a challenge in patient care. Non-invasive biomarkers hold high potential to detect rejection, adjust immunosuppression, and monitor KT patients. So far, no approach has fully satisfied requirements to innovate routine monitoring of KT patients. In this two-center study we analyzed a total of 380 urine samples. T cells and tubular epithelial cells were quantified in KT patients with graft deterioration using flow cytometry. Epigenetic urine cell quantification was used to confirm flow cytometric results. Moreover, a cohort of KT patients was followed up during the first year after transplantation, tracking cell subsets over time. Abundance of urinary cell counts differed in patients with and without rejection. Most strikingly, various T cell subsets were enriched in patients with T cell-mediated rejection (TCMR) compared to patients without TCMR. Among T cell subsets, CD8+HLA-DR+ T cells were most distinctive (AUC = 0.91, Spec.: 95.9%, Sens.: 76.5%). Epigenetic analysis confirmed T cell and tubular epithelial cell quantities as determined by flow cytometry. Urinary T cell abundance in new KT patients decreased during their first year after transplantation. In conclusion urinary T cells reflect intrarenal inflammation in TCMR. T cell subsets yield high potential to monitor KT patients and detect rejection. Hereby we present a promising biomarker to non-invasively diagnose TCMR.

The impact of human leukocyte antigen mismatch on recipient outcomes in living-donor liver transplantation.

Donor-recipient human leukocyte antigen (HLA) compatibility has not been considered to significantly affect liver transplantation (LT) outcomes; however, its significance in living-donor LT (LDLT), which is mostly performed between blood relatives, remains unclear. This retrospective cohort study included 1954 LDLTs at our institution (1990-2020). The primary and secondary endpoints were recipient survival and the incidence of T cell-mediated rejection (TCMR) after LDLT, respectively, according to the number of HLA mismatches at all five loci: HLA-A, HLA-B, HLA-C, HLA-DR, and HLA-DQ. Subgroup analyses were also performed in between-siblings that characteristically have widely distributed 0-10 HLA mismatches. A total of 1304 cases of primary LDLTs were finally enrolled, including 631 adults (recipient age at LT ≥18 years) and 673 children (<18 years). In adult-to-adult LDLT, the more HLA mismatches at each locus, the significantly worse the recipient survival was (p=0.03, 0.01, 0.03, 0.001, and <0.001 for HLA-A, HLA-B, HLA-C, HLA-DR, and HLA-DQ, respectively). This trend was more pronounced when multiple loci were combined (all p < 0.001 for A + B + DR, A + B + C, DR + DQ, and A + B + C + DR + DQ). Notably, a total of three or more HLA-B + DR mismatches was an independent risk factor for both TCMR (hazard ratio [HR] 2.66, 95% confidence interval [CI] 1.21-5.87; p=0.02) and recipient survival (HR 2.44, 95% CI 1.11-5.35; p=0.03) in between-siblings. By contrast, HLA mismatch did not affect pediatric LDLT outcomes at any locus or in any combinations; however, it should be noted that all donor-recipient relationships are parent-to-child that characteristically possesses one or less HLA mismatch at each locus and maximally five or less mismatches in total. In conclusion, HLA mismatch significantly affects not only TCMR development but also recipient survival in adult LDLT, but not in children.

Tacrolimus CYP3A Single-Nucleotide Polymorphisms and Preformed T- and B-Cell Alloimmune Memory Improve Current Pretransplant Rejection-Risk Stratification in Kidney Transplantation.

Achieving fast immunosuppression blood exposure after kidney transplantation is key to abrogating both preformed and de novo anti-donor humoral and cellular alloresponses. However, while tacrolimus (TAC) is the cornerstone immunosuppressant inhibiting adaptive alloimmunity, its blood exposure is directly impacted by different single-nucleotide polymorphisms (SNPs) in CYP3A TAC-metabolizing enzymes. Here, we investigated how functional TAC-CYP3A genetic variants (CYP3A4*22/CYP3A5*3) influence the main baseline clinical and immunological risk factors of biopsy-proven acute rejection (BPAR) by means of preformed donor-specific antibodies (DSAs) and donor-specific alloreactive T cells (DSTs) in a large European cohort of 447 kidney transplants receiving TAC-based immunosuppression. A total of 70 (15.7%) patients developed BPAR. Preformed DSAs and DSTs were observed in 12 (2.7%) and 227 (50.8%) patients, respectively. According to the different CYP3A4*22 and CYP3A5*3 functional allele variants, we found 4 differential new clusters impacting fasting TAC exposure after transplantation; 7 (1.6%) were classified as high metabolizers 1 (HM1), 71 (15.9%) as HM2, 324 (72.5%) as intermediate (IM), and 45 (10.1%) as poor metabolizers (PM1). HM1/2 showed significantly lower TAC trough levels and higher dose requirements than IM and PM (p < 0.001) and more frequently showed TAC underexposure (<5 ng/ml). Multivariate Cox regression analyses revealed that CYP3A HM1 and IM pharmacogenetic phenotypes (hazard ratio (HR) 12.566, 95% CI 1.99–79.36, p = 0.007, and HR 4.532, 95% CI 1.10–18.60, p = 0.036, respectively), preformed DSTs (HR 3.482, 95% CI 1.99–6.08, p < 0.001), DSAs (HR 4.421, 95% CI 1.63–11.98, p = 0.003), and delayed graft function (DGF) (HR 2.023, 95% CI 1.22–3.36, p = 0.006) independently predicted BPAR. Notably, a significant interaction between T-cell depletion and TAC underexposure was observed, showing a reduction of the BPAR risk (HR 0.264, 95% CI 0.08–0.92, p = 0.037). Such variables except for DSAs displayed a higher predictive risk for the development of T cell-mediated rejection (TCMR). Refinement of pretransplant monitoring by incorporating TAC CYP3A SNPs with preformed DSAs as well as DSTs may improve current rejection-risk stratification and help induction treatment decision-making.

Association of Predicted HLA T-Cell Epitope Targets and T-Cell–Mediated Rejection After Kidney Transplantation

The relationship between human leukocyte antigen (HLA) molecular mismatches and T-cell-mediated rejection (TCMR) is unknown. We investigated the associations between the different donor HLA-derived T-cell targets and the occurrence of TCMR and borderline histologic changes suggestive of TCMR after kidney transplantation. Retrospective cohort study. All kidney transplant recipients at a single center between 2004 and 2013 with available biopsy data and a DNA sample for high-resolution HLA donor/recipient typing (N = 893). Scores calculated by the HLA matching algorithm PIRCHE-II and HLA eplet mismatches. TCMR, borderline changes suggestive of TCMR, and allograft failure. Multivariable cause-specific hazards models were fit to characterize the association between HLA epitopes targets and study outcomes. We found 277 patients developed TCMR, and 134 developed only borderline changes suggestive of TCMR on at least 1 biopsy. In multivariable analyses, only the PIRCHE-II scores for HLA-DRB1 and HLA-DQB1 were independently associated with the occurrence of TCMR and with allograft failure; this was not the case for HLA class I molecules. If restricted to rejection episodes within the first 3 months after transplantation, only the T-cell epitope targets originating from the donor's HLA-DRB1 and HLA-DQB1, but not class I molecules, were associated with the early acute TCMR. Also, the median PIRCHE-II score for HLA class II was statistically different between the patients with TCMR compared to the patients without TCMR (129 [IQR, 60-240] vs 201 [IQR, 96-298], respectively; P< 0.0001). These differences were not observed for class I PIRCHE-II scores. Observational clinical data and residual confounding. In the absence of HLA-DSA, HLA class II but not class I mismatches are associated with early episodes of acute TCMR and allograft failure. This suggests that current immunosuppressive therapies are largely able to abort the most deleterious HLA class I-directed alloimmune processes; however, alloresponses against HLA-DRB1 and HLA-DQB1 molecular mismatches remain insufficiently suppressed. Genetic differences in the human leukocyte antigen (HLA) complex between kidney transplant donors and recipients play a central role in T-cell-mediated rejection (TCMR), which can lead to failure of the transplanted kidney. Evaluating this genetic disparity (mismatch) in the HLA complex at the molecular (epitope) level could contribute to better prediction of the immune response to the donor organ posttransplantation. We investigated the associations of the different donor HLA-derived T-cell epitope targets and scores obtained from virtual crossmatch algorithms with the occurrence of TCMR, borderline TCMR, and graft failure after kidney transplantation after taking into account the influence of donor-specific anti-HLA antibodies. This study illustrates the greater importance of the molecular mismatches in class II molecules compared to class I HLA molecules.

Causes of Kidney Graft Failure in a Cohort of Recipients With a Very Long-Time Follow-Up After Transplantation.

BackgroundBiopsy-proven causes of graft loss many years after kidney transplantation are scarcely documented.MethodsPatients transplanted between 1995 and 2005 (n = 737) in a single center were followed on a regular basis until 2021. The recipients were divided according to age at transplantation into 3 groups; 18–39 years (young), 40–55 years (middle age), and older than 55 years (elderly). For cause biopsies of renal transplants were clustered into the categories, rejection, IFTA, return original disease, and diagnosis of de novo kidney disease.ResultsRejection was the main cause of graft failure censored for death at every time period after transplantation. The incidence of T cell-mediated rejection (TCMR) became rare 6 years after transplantation while the cumulative incidence of antibody-mediated rejection (ABMR) increased over time (1.1% per year). ABMR was not diagnosed anymore beyond 15 years of follow-up in recipients without pre-transplant donor-specific antibodies (DSA). An episode of TCMR was associated with an increased incidence of ABMR diagnosis in the short-term but did not increase the overall incidence of AMBR not in the long-term. Death as a cause of graft failure was an important competitive risk factor long after transplantation and resulted in a significantly lower frequency of rejection-related graft loss in the elderly group (11 vs. 23% in the young group at 15 year follow-up).ConclusionRejection is a major cause of graft loss but recipient’s age, time after transplantation, and the presence of DSA before transplantation determine the relative contribution to overall graft loss and the type of rejection involved.

High-Throughput Sequencing of Complementarity Determining Region 3 in the Heavy Chain of B-Cell Receptor in Renal Transplant Recipients: A Preliminary Report.

Background: Graft failure resulting from rejection or any other adverse event usually originates from an aberrant and/or exaggerated immune response and is often catastrophic in renal transplantation. So, it is essential to monitor patients’ immune status for detecting a rejection/graft failure early on. Methods: We monitored the sequence change of complementary determining region 3 (CDR3) in B-cell receptor (BCR) immunoglobulin heavy-chain (IGH) immune repertoire (iR) in 14 renal transplant patients using next-generation sequencing (NGS), correlating its diversity to various clinical events occurring after transplantation. BCR-IGH-CDR3 in peripheral blood mononuclear cells was sequenced along the post-transplantation course by NGS using the iRweb server. Results: Datasets covering VDJ regions of BCR-IGH-CDR3 indicated clonal diversity (D50) variations along the post-transplant course. Furthermore, principal component analysis showed the clustering of these sequence variations. A total of 544 shared sequences were identified before transplantation. D50 remained low in three patients receiving rituximab. Among them, one’s D50 resumed after 3 m, indicating graft tolerance. The D50 rapidly increased after grafting and decreased thereafter in four patients without rejection, decreased in two patients with T-cell-mediated rejection (TCMR) and exhibited a sharp down-sliding after 3 m in two patients receiving donations after cardiac death (DCD). In another two patients with TCMR, D50 was low just before individual episodes, but either became persistently low or returned to a plateau, depending on the failure or success of the immunosuppressive treatments. Shared CDR3 clonal expansions correlated to D50 changes. Agglomerative hierarchical clustering showed a commonly shared CDR3 sequence and at least two different clusters in five patients. Conclusions: Clonal diversity in BCR-IGH-CDR3 varied depending on clinical courses of 14 renal transplant patients, including B-cell suppression therapy, TCMR, DCD, and graft tolerance. Adverse events on renal graft failure might lead to different clustering of BCR iR. However, these preliminary data need further verification in further studies for the possible applications of iR changes as genetic expression biomarkers or laboratory parameters to detect renal graft failure/rejection earlier.

The impact of methodological choices when developing predictive models using urinary metabolite data.

The continuous evolution of metabolomics over the past two decades has stimulated the search for metabolic biomarkers of many diseases. Metabolomic data measured from urinary samples can provide rich information of the biological events triggered by organ rejection in pediatric kidney transplant recipients. With additional validation, metabolic markers can be used to build clinically useful diagnostic tools. However, there are many methodological steps ranging from data processing to modeling that can influence the performance of the resulting metabolomic classifiers. In this study we focus on the comparison of various classification methods that can handle the complex structure of metabolomic data, including regularized classifiers, partial least squares discriminant analysis, and nonlinear classification models. We also examine the effectiveness of a physiological normalization technique widely used in the clinical and biochemical literature but not extensively analyzed and compared in urine metabolomic studies. While the main objective of this work is to interrogate metabolomic data of pediatric kidney transplant recipients to improve the diagnosis of T cell-mediated rejection (TCMR), we also analyze three independent datasets from other disease conditions to investigate the generalizability of our findings.

Clinical Significances of Anti-Collagen Type I and Type III Antibodies in Antibody-Mediated Rejection.

It is important to determine the clinical significance of non-human leukocyte antigen (HLA) antibodies and their association with antibody-mediated rejection (ABMR) of kidney allografts. We collected post-transplant sera from 68 ABMR patients, 67 T-cell mediated rejection (TCMR) patients, and 83 control subjects without rejection, and determined the titers of 39 non-HLA antibodies including antibodies for angiotensin II receptor type I and MICA. We compared all these non-HLA antibody titers among the study groups. Then, we investigated their association with the risk of death-censored graft failure in ABMR cases. Among the antibodies evaluated, anti-collagen type I (p = 0.001) and type III (p < 0.001) antibody titers were significantly higher in ABMR cases than in both TCMR cases and no-rejection controls. Both anti-collagen type I [per 1 standard deviation (SD), adjusted odds ratio (OR), 11.72 (2.73-76.30)] and type III [per 1 SD, adjusted OR, 6.22 (1.91-31.75)] antibodies were significantly associated with the presence of ABMR. Among ABMR cases, a higher level of anti-collagen type I [per 1 SD, adjusted hazard ratio (HR), 1.90 (1.32-2.75)] or type III per 1 SD, [adjusted HR, 1.57 (1.15-2.16)] antibody was associated with a higher risk of death-censored graft failure. In conclusion, post-transplant anti-collagen type I and type III antibodies may be novel non-HLA antibodies related to ABMR of kidney allografts.

A Decentralized Kidney Transplant Biopsy Classifier for Transplant Rejection Developed Using Genes of the Banff-Human Organ Transplant Panel.

IntroductionA decentralized and multi-platform-compatible molecular diagnostic tool for kidney transplant biopsies could improve the dissemination and exploitation of this technology, increasing its clinical impact. As a first step towards this molecular diagnostic tool, we developed and validated a classifier using the genes of the Banff-Human Organ Transplant (B-HOT) panel extracted from a historical Molecular Microscope® Diagnostic system microarray dataset. Furthermore, we evaluated the discriminative power of the B-HOT panel in a clinical scenario.Materials and MethodsGene expression data from 1,181 kidney transplant biopsies were used as training data for three random forest models to predict kidney transplant biopsy Banff categories, including non-rejection (NR), antibody-mediated rejection (ABMR), and T-cell-mediated rejection (TCMR). Performance was evaluated using nested cross-validation. The three models used different sets of input features: the first model (B-HOT Model) was trained on only the genes included in the B-HOT panel, the second model (Feature Selection Model) was based on sequential forward feature selection from all available genes, and the third model (B-HOT+ Model) was based on the combination of the two models, i.e. B-HOT panel genes plus highly predictive genes from the sequential forward feature selection. After performance assessment on cross-validation, the best-performing model was validated on an external independent dataset based on a different microarray version.ResultsThe best performances were achieved by the B-HOT+ Model, a multilabel random forest model trained on B-HOT panel genes with the addition of the 6 most predictive genes of the Feature Selection Model (ST7, KLRC4-KLRK1, TRBC1, TRBV6-5, TRBV19, and ZFX), with a mean accuracy of 92.1% during cross-validation. On the validation set, the same model achieved Area Under the ROC Curve (AUC) of 0.965 and 0.982 for NR and ABMR respectively.DiscussionThis kidney transplant biopsy classifier is one step closer to the development of a decentralized kidney transplant biopsy classifier that is effective on data derived from different gene expression platforms. The B-HOT panel proved to be a reliable highly-predictive panel for kidney transplant rejection classification. Furthermore, we propose to include the aforementioned 6 genes in the B-HOT panel for further optimization of this commercially available panel.

Immune Subsets From Ficoll Density Gradient Separation in Kidney Transplant Recipients.

Immune Subsets From Ficoll Density Gradient Separation in Kidney Transplant Recipients.

Serum Soluble B Cell-Activating Factor Is a Non-Invasive Biomarker of Antibody-Mediated Rejection in Kidney Allograft With Satisfactory Risk Stratification Performance But Negligible Diagnostic Value.

ObjectivesB cell-activating factor (BAFF), which is critical in the activation and differentiation of B cells, is a candidate diagnostic and predictive biomarker for antibody-mediated rejection (ABMR). We aimed to investigate the value of serum soluble BAFF (sBAFF) for the diagnosis and risk stratification of ABMR after kidney transplantation.MethodsIn the diagnostic study, sBAFF level among ABMR (n = 25), T cell-mediated rejection (TCMR) (n = 14), 4 other pathological lesions (n = 21), and stable allograft function group (n = 15) were compared. In the nested case-control study, kidney allograft recipients with de novo donor-specific antibody (DSA) or ABMR (n = 16) vs. stable allograft function (n = 7) were enrolled, and sBAFF was measured preoperatively, at D7, M1, M3, M6, M9, M12, M18 posttransplant and at allograft biopsy.ResultsThere was no significant difference in sBAFF level at biopsy between ABMR and non-ABMR groups. Longitudinal study showed that the sBAFF levels decreased dramatically at D7 in both groups. The sBAFF level in the DSA group started to increase within M1, while in the stable group, it maintained a low level until M3 and M6. The sBAFF levels of the DSA group were significantly higher than that of the stable group at M1 [1,013.23 (633.97, 1,277.38) pg/ml vs. 462.69 (438.77, 586.48) pg/ml, P = 0.005], M3 [1,472.07 (912.79, 1,922.08) pg/ml vs. 561.63 (489.77, 630.00) pg/ml, P = 0.002], and M6 [1,217.95 (965.25, 1,321.43) pg/ml vs. 726.93 (604.77, 924.60) pg/ml, P = 0.027]. sBAFF levels at M3 had the best predictive value for the DSA/ABMR with the area under the receiver operating characteristic (AUROC) curve value of 0.908. The predictive performance of the maximum (max) change rate from D7 to the peak within M3 was also excellent (AUROC 0.949, P = 0.580).ConclusionWe clarified by a diagnostic study that sBAFF is not a diagnostic biomarker for ABMR in kidney transplantation and revealed by a nested case-control study that sBAFF values at M3 posttransplant and dynamic changes in sBAFF within M3 posttransplant have a good predictive value for the DSA/ABMR. It provides a useful tool for early screening of low-risk patients with negative preoperative DSA for the risk of developing postoperative DSA in kidney allograft recipients.