Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure.

BACKGROUND: Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate endpoints, and for patient management as clinical decision support tools. However, the impact of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes. METHODS: We included 11,046 kidney transplant recipients enrolled in 10 countries. We developed prediction models for long-term kidney graft failure prediction, without accounting (i.e., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine-Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modelling, and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance. RESULTS: Among 11,046 recipients in the derivation and validation cohorts, 1,497 (14%) lost their graft and 1,003 (9%) died with a functioning graft after a median follow-up post-risk evaluation of 4.7 years (IQR 2.7-7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan-Meier and Aalen-Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138 and 0.0135 for Cox, Fine-Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors over 65 years old), the findings suggest a trend towards moderately improved calibration when using a competing risk approach. CONCLUSIONS: Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

Subthreshold rejection activity in many kidney transplants currently classified as having no rejection.

Most kidney transplant patients who undergo biopsies are classified as having no rejection based on consensus thresholds. However, we hypothesized that because these patients have normal adaptive immune systems, T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) may exist as subthreshold activity in some transplants currently classified as no rejection. To examine this question, we studied genome-wide microarray results from 5086 kidney transplant biopsies (from 4170 patients). An updated molecular archetypal analysis designated 56% of biopsies as no rejection. Subthreshold molecular TCMR and/or ABMR activity molecular activity was detectable as elevated classifier scores in many biopsies classified as no rejection, with ABMR activity in many TCMR biopsies and TCMR activity in many ABMR biopsies. In biopsies classified as no rejection histologically and molecularly, molecular TCMR classifier scores correlated with increases in histologic TCMR features and molecular injury, lower estimated glomerular filtration rate, and higher risk of graft loss, and molecular ABMR activity correlated with increased glomerulitis and donor-specific antibody. No rejection biopsies with high subthreshold TCMR or ABMR activity had a higher probability of having TCMR or ABMR, respectively, diagnosed in a future biopsy. We conclude that many kidney transplant recipients have unrecognized subthreshold TCMR or ABMR activity, with significant implications for future problems.

Novel Potassium Binders for Early Postoperative Hyperkalemia in Kidney Transplant Recipients: A Single-Center Experience.

PURPOSE: Evaluate the safety/efficacy of novel potassium binders (patiromer, sodium zirconium cyclosilicate [SZ-9]) for early postoperative hyperkalemia following kidney transplantation. METHODS: Retrospective, single-center, cohort study of deceased-donor kidney recipients transplanted between 1/2018 and 12/2020. Potassium-binder use was evaluated from immediately posttransplant until discharge. Potassium binders were administered ≥2 hours before/after medications. RESULTS: A total of 179 patients were included, 24 (13%) of whom received potassium binders (16 [67%] patiromer, 7 [29%] SZ-9, 1 [4%] both) for a mean of 2.5 (±3.18) doses. Peak potassium levels were higher in the potassium-binder group (6.05 vs 5.35 mEq/L; P < .001). More patients on potassium binders transitioned to atovaquone than those on no binders (n = 21 [100%] vs n = 112 [75%], respectively; P = .005). Delayed graft function (DGF) was observed in 100 (56%) patients, with a higher proportion receiving potassium binders (18 [75%] vs 82 [53%], respectively; P = .042). There was no difference between groups in number of posttransplant dialysis sessions required in the general study population (P = .2), nor in the DGF group (P = .12). No difference was noted in the incidence of ileus (P = .2), or gastrointestinal symptoms (diarrhea, nausea, vomiting; P = .6). Of the 24 patients who received inpatient binders, 9 (37.5%) were discharged and remained on them for a mean of 46 (±49) days. CONCLUSION: Patiromer and SZ-9 appear safe in the early posttransplant period, but larger prospective trials are needed. Potassium-binder use does not appear to be associated with fewer dialysis sessions in DGF patients, however, they may be used as additional tools for lowering potassium in these patients.

Should Transplant Nephrology Pursue Recognition from the Accreditation Council for Graduate Medical Education (ACGME)?

Kidney transplant is not only the best treatment for patients with advanced kidney disease but it also reduces health care expenditure. The management of transplant patients is complex as they require special care by transplant nephrologists who have expertise in assessing transplant candidates, understand immunology and organ rejection, have familiarity with perioperative complications, and have the ability to manage the long-term effects of chronic immunosuppression. This skill set at the intersection of multiple disciplines necessitates additional training in Transplant Nephrology. Currently, there are more than 250,000 patients with a functioning kidney allograft and over 100,000 waitlisted patients awaiting kidney transplant, with a burgeoning number added to the kidney transplant wait list every year. In 2022, more than 40,000 patients were added to the kidney wait list and more than 25,000 received a kidney transplant. The Advancing American Kidney Health Initiative, passed in 2019, is aiming to double the number of kidney transplants by 2030 creating a need for additional transplant nephrologists to help care for them. Over the past decade, there has been a decline in the Nephrology-as well Transplant Nephrology-workforce due to a multitude of reasons. The American Society of Transplantation Kidney Pancreas Community of Practice created a workgroup to discuss the Transplant Nephrology workforce shortage. In this article, we discuss the scope of the problem and how the Accreditation Council for Graduate Medical Education recognition of Transplant Nephrology Fellowship could at least partly mitigate the Transplant Nephrology work force crisis.

Recurrence of membranous nephropathy after kidney transplantation: A multicenter retrospective cohort study.

Membranous nephropathy (MN) is a leading cause of kidney failure worldwide and frequently recurs after transplant. Available data originated from small retrospective cohort studies or registry analyses; therefore, uncertainties remain on risk factors for MN recurrence and response to therapy. Within the Post-Transplant Glomerular Disease Consortium, we conducted a retrospective multicenter cohort study examining the MN recurrence rate, risk factors, and response to treatment. This study screened 22,921 patients across 3 continents and included 194 patients who underwent a kidney transplant due to biopsy-proven MN. The cumulative incidence of MN recurrence was 31% at 10 years posttransplant. Patients with a faster progression toward end-stage kidney disease were at higher risk of developing recurrent MN (hazard ratio [HR], 0.55 per decade; 95% confidence interval [CI], 0.35-0.88). Moreover, elevated pretransplant levels of anti-phospholipase A2 receptor (PLA2R) antibodies were strongly associated with recurrence (HR, 18.58; 95% CI, 5.37-64.27). Patients receiving rituximab for MN recurrence had a higher likelihood of achieving remission than patients receiving renin-angiotensin-aldosterone system inhibition alone. In sum, MN recurs in one-third of patients posttransplant, and measurement of serum anti-PLA2R antibody levels shortly before transplant could aid in risk-stratifying patients for MN recurrence. Moreover, patients receiving rituximab had a higher rate of treatment response.

Impact of Deceased-donor Acute Kidney Injury on Kidney Transplantation.

Even as record numbers of deceased donors are undergoing organ recovery, the global transplant community continues to struggle with a shortage of donor organs and a high organ discard rate. Acute kidney injury (AKI) occurs in many hospitalized patients, including up to 25% of patients in critical condition. Registry studies have shown a significant increase in nonrecovery or organ discard rates in AKI donors, despite most studies reporting similar clinical outcomes compared with non-AKI donors. This review aims to capture the salient information learned from these studies and to summarize the efforts that have been made to gain a more granular understanding of how kidneys from donors with AKI behave posttransplant. In particular, we reviewed the studies that analyzed the clinical outcomes in different stages of AKI and AKI in marginal donors, such as kidney donor profile index of >85%, older donors, and donation after circulatory death donors. We summarized studies investigating molecular biomarkers, transcriptomics, and possible future therapeutic targets for postdonation AKI.

Performance and Advancement of the Kidney Solid Organ Response Test.

BACKGROUND: The kidney solid organ response test (kSORT) has been investigated for the prediction of acute rejection in kidney transplant recipients with conflicting results. We aimed to investigate if the kSORT assay score is associated with rejection or immune quiescence. METHODS: The blinded association between rejection and kSORT > 9 were investigated. Optimization of kSORT prediction was evaluated after unblinding to determine the optimal prediction cutoff value of kSORT score. Additionally, the predictive capability of the kSORT gene set was assessed using blinded normalized gene expression data from microarray (Affymetrix) and qPCR assays. RESULTS: Of the 95 blood samples analyzed, 18 patients had blood samples before transplant, 77 patients after transplant and 71 had clinically indicated biopsies of which 15 biopsies showed acute rejection and 16 showed chronic active antibody-mediated rejection. When 31 patients with rejection were compared to the remaining 64 patients, positive predictive value (PPV) was 54.29% and negative predictive value (NPV) was 75% when stratified using a kSORT score > 9, and PPV was 57.89% and NPV was 78.95% when stratified using a kSORT score > 5. Using the kSORT assay for detection of rejection showed an area under the curve value of 0.71. Microarray data improved prediction accuracy with PPV of 53% and NPV of 84% compared to qPCR results (PPV and NPV were 36% and 66%), respectively. CONCLUSIONS: The kSORT assay has the potential to be used as a predictive tool for active rejection and/or immune quiescence, but additional studies will be useful in improving and refining the kSORT assay, in particular the prediction algorithm.

Machine learning does not outperform traditional statistical modelling for kidney allograft failure prediction.

Machine learning (ML) models have recently shown potential for predicting kidney allograft outcomes. However, their ability to outperform traditional approaches remains poorly investigated. Therefore, using large cohorts of kidney transplant recipients from 14 centers worldwide, we developed ML-based prediction models for kidney allograft survival and compared their prediction performances to those achieved by a validated Cox-Based Prognostication System (CBPS). In a French derivation cohort of 4000 patients, candidate determinants of allograft failure including donor, recipient and transplant-related parameters were used as predictors to develop tree-based models (RSF, RSF-ERT, CIF), Support Vector Machine models (LK-SVM, AK-SVM) and a gradient boosting model (XGBoost). Models were externally validated with cohorts of 2214 patients from Europe, 1537 from North America, and 671 from South America. Among these 8422 kidney transplant recipients, 1081 (12.84%) lost their grafts after a median post-transplant follow-up time of 6.25 years (Inter Quartile Range 4.33-8.73). At seven years post-risk evaluation, the ML models achieved a C-index of 0.788 (95% bootstrap percentile confidence interval 0.736-0.833), 0.779 (0.724-0.825), 0.786 (0.735-0.832), 0.527 (0.456-0.602), 0.704 (0.648-0.759) and 0.767 (0.711-0.815) for RSF, RSF-ERT, CIF, LK-SVM, AK-SVM and XGBoost respectively, compared with 0.808 (0.792-0.829) for the CBPS. In validation cohorts, ML models' discrimination performances were in a similar range of those of the CBPS. Calibrations of the ML models were similar or less accurate than those of the CBPS. Thus, when using a transparent methodological pipeline in validated international cohorts, ML models, despite overall good performances, do not outperform a traditional CBPS in predicting kidney allograft failure. Hence, our current study supports the continued use of traditional statistical approaches for kidney graft prognostication.

Deceased-Donor Acute Kidney Injury and Acute Rejection in Kidney Transplant Recipients: A Multicenter Cohort.

RATIONALE & OBJECTIVE: Donor acute kidney injury (AKI) activates innate immunity, enhances HLA expression in the kidney allograft, and provokes recipient alloimmune responses. We hypothesized that injury and inflammation that manifested in deceased-donor urine biomarkers would be associated with higher rates of biopsy-proven acute rejection (BPAR) and allograft failure after transplantation. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: 862 deceased donors for 1,137 kidney recipients at 13 centers. EXPOSURES: We measured concentrations of interleukin 18 (IL-18), kidney injury molecule 1 (KIM-1), and neutrophil gelatinase-associated lipocalin (NGAL) in deceased donor urine. We also used the Acute Kidney Injury Network (AKIN) criteria to assess donor clinical AKI. OUTCOMES: The primary outcome was a composite of BPAR and graft failure (not from death). A secondary outcome was the composite of BPAR, graft failure, and/or de novo donor-specific antibody (DSA). Outcomes were ascertained in the first posttransplant year. ANALYTICAL APPROACH: Multivariable Fine-Gray models with death as a competing risk. RESULTS: Mean recipient age was 54 ± 13 (SD) years, and 82% received antithymocyte globulin. We found no significant associations between donor urinary IL-18, KIM-1, and NGAL and the primary outcome (subdistribution hazard ratio [HR] for highest vs lowest tertile of 0.76 [95% CI, 0.45-1.28], 1.20 [95% CI, 0.69-2.07], and 1.14 [95% CI, 0.71-1.84], respectively). In secondary analyses, we detected no significant associations between clinically defined AKI and the primary outcome or between donor biomarkers and the composite outcome of BPAR, graft failure, and/or de novo DSA. LIMITATIONS: BPAR was ascertained through for-cause biopsies, not surveillance biopsies. CONCLUSIONS: In a large cohort of kidney recipients who almost all received induction with thymoglobulin, donor injury biomarkers were associated with neither graft failure and rejection nor a secondary outcome that included de novo DSA. These findings provide some reassurance that centers can successfully manage immunological complications using deceased-donor kidneys with AKI.

Role of time from transplantation to biopsy in histologic ABMR: A single center report.

BACKGROUND: Allograft biopsies with lesions of Antibody-Mediated Rejection (ABMR) with Microvascular Inflammation (MVI) have shown heterogeneous etiologies and outcomes. METHODS: To examine factors associated with outcomes in biopsies that meet histologic ABMR criteria, we retrospectively evaluated for-cause biopsies at our center between 2011 and 2017. We included biopsies that met the diagnosis of ABMR by histology, along with simultaneous evaluation for anti-Human Leukocyte Antigen (HLA) donor-specific antibodies (DSA). We evaluated death-censored graft loss (DCGL) and used a principal component analysis (PCA) approach to identify key predictors of outcomes. RESULTS: Out of the histologic ABMR cohort (n = 118), 70 were DSA-positive ABMR, while 48 had no DSA. DSA(+)ABMR were younger and more often female recipients. DSA(+)ABMR occurred significantly later post-transplant than DSA(-)ABMR suggesting time-dependence. DSA(+)ABMR had higher inflammatory scores (i,t), chronicity scores (ci, ct) and tended to have higher MVI scores. Immunodominance of DQ-DSA in DSA(+)ABMR was associated with higher i+t scores. Clinical/histologic factors significantly associated with DCGL after biopsy were inputted into the PCA. Principal component-1 (PC-1), which contributed 34.8% of the variance, significantly correlated with time from transplantation to biopsy, ci/ct scores and DCGL. In the PCA analyses, i, t scores, DQ-DSA, and creatinine at biopsy retained significant correlations with GL-associated PCs. CONCLUSIONS: Time from transplantation to biopsy plays a major role in the prognosis of biopsies with histologic ABMR and MVI, likely due to ongoing chronic allograft injury over time.

Analysis of Cross-sectional and Longitudinal HLA and Anti-viral Responses After COVID Infection in Renal Allograft Recipients: Differences and Correlates.

BACKGROUND: Characterization of anti-HLA versus anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) immune globulin isotypes in organ transplant recipients after coronavirus disease 2019 (COVID-19) infection has not been reported. We aimed to determine changes in anti-HLA antibodies in renal transplant patients with COVID-19 and compare the immunoglobulin and epitope-binding pattern versus anti-SARS-CoV-2 antibodies. METHODS: This is a cross-sectional study of 46 kidney transplant recipients including 21 with longitudinal sampling. Using a semi-quantitative multiplex assay, we determined immunoglobulin (Ig) M, IgA, IgG, and IgG1-2-3-4 antibodies against Class I and Class II HLA, and 5 SARS-CoV-2 epitopes including the nucleocapsid protein and multiple regions of the spike protein. RESULTS: Fourteen of 46 (30%) patients had donor-specific anti-HLA antibodies (donor-specific antibody [DSA]), 12 (26%) had non-DSA anti-HLA antibodies and 45 (98%) had anti-SARS-CoV-2 antibodies. Most DSAs targeted HLA-DQ (71%), with a dominant IgG isotype and IgG1 subtype prevalence (93%), and/or IgG3 (64%), followed by IgG2 (36%). Comparatively, there was a higher prevalence of IgA (85% versus 14%, P = 0.0001) and IgM (87%, versus 36%, P = 0.001) in the anti-SARS-CoV-2 antibody profile, when compared to DSAs, respectively. Anti-SARS-CoV-2 antibody profile was characterized by increased prevalence of IgM and IgA, when compared to DSAs. The median calculated panel reactive antibody before COVID-19 diagnosis (24%) tended to decrease after COVID-19 diagnosis (10%) but it was not statistically significant ( P = 0.1). CONCLUSIONS: Anti-HLA antibody strength and calculated panel reactive antibody in kidney transplant recipients after COVID-19 do not significantly increase after infection. Although the IgG isotype was the dominant form in both HLA and SARS-CoV-2 antigens, the alloimmune response had a low IgA pattern, whereas anti-SARS-CoV-2 antibodies were high IgA/IgM.

Blood Transcriptomes of SARS-CoV-2-Infected Kidney Transplant Recipients Associated with Immune Insufficiency Proportionate to Severity.

BACKGROUND: Among patients with COVID-19, kidney transplant recipients (KTRs) have poor outcomes compared with non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort. METHODS: We ascertained clinical data by chart review. A single sample of blood was collected for transcriptome analysis. Total RNA was poly-A selected and RNA was sequenced to evaluate transcriptome changes. We also measured cytokines and chemokines of serum samples collected during acute infection. RESULTS: A total of 64 patients with COVID-19 in KTRs were enrolled, including 31 with acute COVID-19 (<4 weeks from diagnosis) and 33 with post-acute COVID-19 (>4 weeks postdiagnosis). In the blood transcriptome of acute cases, we identified genes in positive or negative association with COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways but downregulation of T cell and adaptive immune activation pathways. This finding was independent of lymphocyte count, despite reduced immunosuppressant use in most KTRs. Compared with acute cases, post-acute cases showed "normalization" of these enriched pathways after 4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of immunosuppression. Analysis of the non-KTR cohort with COVID-19 showed significant overlap with KTRs in these functions. Serum inflammatory cytokines followed an opposite trend (i.e., increased with disease severity), indicating that blood lymphocytes are not the primary source. CONCLUSIONS: The blood transcriptome of KTRs affected by COVID-19 shows decreases in T cell and adaptive immune activation pathways during acute disease that, despite reduced immunosuppressant use, associate with severity. These pathways show recovery after acute illness.

Survey of Salary and Job Satisfaction of Transplant Nephrologists in the United States.

BACKGROUND AND OBJECTIVES: There are no standardized benchmarks to measure productivity and compensation of transplant nephrologists in the United States, and consequently, criteria set for general nephrologists are often used. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A web-based survey was sent to 809 nephrologists who were members of the American Society of Transplantation to gather data on measures of productivity, compensation, and job satisfaction. Factors associated with higher total compensation and job satisfaction were examined. RESULTS: Of 365 respondents, 260 were actively practicing in the United States and provided data on compensation. Clinical productivity was assessed variably, and although 194 (76%) had their work relative value units (wRVUs) reported to them, only 107 (44%) had an established RVU target. Two hundred thirty-four respondents (90%) had fixed base compensation, and 172 (66%) received a bonus on the basis of clinical workload (68%), academic productivity (31%), service (32%), and/or teaching responsibility (31%). Only 127 respondents (49%) filled out time studies, and 92 (35%) received some compensation for nonbillable transplant activity. Mean total compensation (base salary and bonus) was $274,460±$91,509. The unadjusted mean total compensation was higher with older age and was higher for men; Hispanic and White respondents; adult care transplant nephrologists; residents of the western United States; US medical school graduates; nonuniversity hospital employees; and those with an administrative title, higher academic rank, and a higher number of years in practice. Two hundred and nine respondents (80%) thought their compensation was unfair, and 180 (70%) lacked a clear understanding of how they were compensated. One hundred forty-five respondents (55%) reported being satisfied or highly satisfied with their job. Job satisfaction was greater among those with higher amounts of compensation and US medical school graduates. CONCLUSIONS: We report significant heterogeneity in the assessment of productivity and compensation for transplant nephrologists and the association of compensation with job satisfaction.

Pretransplant kidney transcriptome captures intrinsic donor organ quality and predicts 24-month outcomes.

With the development of novel prognostic tools derived from omics technologies, transplant medicine is entering the era of precision medicine. Currently, there are no established predictive biomarkers for posttransplant kidney function. A total of 270 deceased donor pretransplant kidney biopsies were collected and posttransplant function was prospectively monitored. This study first assessed the utility of pretransplant gene expression profiles in predicting 24-month outcomes in a training set (n = 174). Nearly 600 differentially expressed genes were associated with 24-month graft function. Grafts that progressed to low function at 24 months exhibited upregulated immune responses and downregulated metabolic processes at pretransplantation. Using penalized logistic regression modeling, a 55 gene model area under the receiver operating curve (AUROC) for 24-month graft function was 0.994. Gene expression for a subset of candidate genes was then measured in an independent set of pretransplant biopsies (n = 96) using quantitative polymerase chain reaction. The AUROC when using 13 genes with three donor characteristics (age, race, body mass index) was 0.821. Subsequently, a risk score was calculated using this combination for each patient in the validation cohort, demonstrating the translational feasibility of using gene markers as prognostic tools. These findings support the potential of pretransplant transcriptomic biomarkers as novel instruments for improving posttransplant outcome predictions and associated management.

Clinically adjudicated deceased donor acute kidney injury and graft outcomes.

BACKGROUND: Acute kidney injury (AKI) in deceased donors is not associated with graft failure (GF). We hypothesize that hemodynamic AKI (hAKI) comprises the majority of donor AKI and may explain this lack of association. METHODS: In this ancillary analysis of the Deceased Donor Study, 428 donors with available charts were selected to identify those with and without AKI. AKI cases were classified as hAKI, intrinsic (iAKI), or mixed (mAKI) based on majority adjudication by three nephrologists. We evaluated the associations between AKI phenotypes and delayed graft function (DGF), 1-year eGFR and GF. We also evaluated differences in urine biomarkers among AKI phenotypes. RESULTS: Of the 291 (68%) donors with AKI, 106 (36%) were adjudicated as hAKI, 84 (29%) as iAKI and 101 (35%) as mAKI. Of the 856 potential kidneys, 669 were transplanted with 32% developing DGF and 5% experiencing GF. Median 1-year eGFR was 53 (IQR: 41-70) ml/min/1.73m2. Compared to non-AKI, donors with iAKI had higher odds DGF [aOR (95%CI); 4.83 (2.29, 10.22)] and had lower 1-year eGFR [adjusted B coefficient (95% CI): -11 (-19, -3) mL/min/1.73 m2]. hAKI and mAKI were not associated with DGF or 1-year eGFR. Rates of GF were not different among AKI phenotypes and non-AKI. Urine biomarkers such as NGAL, LFABP, MCP-1, YKL-40, cystatin-C and albumin were higher in iAKI. CONCLUSION: iAKI was associated with higher DGF and lower 1-year eGFR but not with GF. Clinically phenotyped donor AKI is biologically different based on biomarkers and may help inform decisions regarding organ utilization.

Blood transcriptomes of SARS-CoV-2 infected kidney transplant recipients demonstrate immune insufficiency.

BACKGROUND: Kidney transplant recipients (KTRs) with COVID-19 have poor outcomes compared to non-KTRs. To provide insight into management of immunosuppression during acute illness, we studied immune signatures from the peripheral blood during and after COVID-19 infection from a multicenter KTR cohort.□. METHODS: Clinical data were collected by chart review. PAXgene blood RNA was poly-A selected and RNA sequencing was performed to evaluate transcriptome changes. RESULTS: A total of 64 cases of COVID-19 in KTRs were enrolled, including 31 acute cases (< 4 weeks from diagnosis) and 33 post-acute cases (>4 weeks). In the blood transcriptome of acute cases, we identified differentially expressed genes (DEGs) in positive or negative association COVID-19 severity scores. Functional enrichment analyses showed upregulation of neutrophil and innate immune pathways, but downregulation of T-cell and adaptive immune-activation pathways proportional to severity score. This finding was independent of lymphocyte count and despite reduction in immunosuppression (IS) in most KTRs. Comparison with post-acute cases showed "normalization" of these enriched pathways after >4 weeks, suggesting recovery of adaptive immune system activation despite reinstitution of IS. The latter analysis was adjusted for COVID-19 severity score and lymphocyte count. DEGs associated with worsening disease severity in a non-KTR cohort with COVID-19 (GSE152418) showed significant overlap with KTRs in these identified enriched pathways. CONCLUSION: Blood transcriptome of KTRs affected by COVID-19 shows decrease in T-cell and adaptive immune activation pathways during acute disease that associate with severity despite IS reduction and show recovery after acute illness. SIGNIFICANCE STATEMENT: Kidney transplant recipients (KTRs) are reported to have worse outcomes with COVID-19, and empiric reduction of maintenance immunosuppression is pursued. Surprisingly, reported rates of acute rejection have been low despite reduced immunosuppression. We evaluated the peripheral blood transcriptome of 64 KTRs either during or after acute COVID-19. We identified transcriptomic signatures consistent with suppression of adaptive T-cell responses which significantly associated with disease severity and showed evidence of recovery after acute disease, even after adjustment for lymphocyte number. Our transcriptomic findings of immune-insufficiency during acute COVID-19 provide an explanation for the low rates of acute rejection in KTRs despite reduced immunosuppression. Our data support the approach of temporarily reducing T -cell-directed immunosuppression in KTRs with acute COVID-19.

Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study.

BACKGROUND: Kidney allograft failure is a common cause of end-stage renal disease. We aimed to develop a dynamic artificial intelligence approach to enhance risk stratification for kidney transplant recipients by generating continuously refined predictions of survival using updates of clinical data. METHODS: In this observational study, we used data from adult recipients of kidney transplants from 18 academic transplant centres in Europe, the USA, and South America, and a cohort of patients from six randomised controlled trials. The development cohort comprised patients from four centres in France, with all other patients included in external validation cohorts. To build deeply phenotyped cohorts of transplant recipients, the following data were collected in the development cohort: clinical, histological, immunological variables, and repeated measurements of estimated glomerular filtration rate (eGFR) and proteinuria (measured using the proteinuria to creatininuria ratio). To develop a dynamic prediction system based on these clinical assessments and repeated measurements, we used a Bayesian joint models-an artificial intelligence approach. The prediction performances of the model were assessed via discrimination, through calculation of the area under the receiver operator curve (AUC), and calibration. This study is registered with ClinicalTrials.gov, NCT04258891. FINDINGS: 13 608 patients were included (3774 in the development cohort and 9834 in the external validation cohorts) and contributed 89 328 patient-years of data, and 416 510 eGFR and proteinuria measurements. Bayesian joint models showed that recipient immunological profile, allograft interstitial fibrosis and tubular atrophy, allograft inflammation, and repeated measurements of eGFR and proteinuria were independent risk factors for allograft survival. The final model showed accurate calibration and very high discrimination in the development cohort (overall dynamic AUC 0·857 [95% CI 0·847-0·866]) with a persistent improvement in AUCs for each new repeated measurement (from 0·780 [0·768-0·794] to 0·926 [0·917-0·932]; p<0·0001). The predictive performance was confirmed in the external validation cohorts from Europe (overall AUC 0·845 [0·837-0·854]), the USA (overall AUC 0·820 [0·808-0·831]), South America (overall AUC 0·868 [0·856-0·880]), and the cohort of patients from randomised controlled trials (overall AUC 0·857 [0·840-0·875]). INTERPRETATION: Because of its dynamic design, this model can be continuously updated and holds value as a bedside tool that could refine the prognostic judgements of clinicians in everyday practice, hence enhancing precision medicine in the transplant setting. FUNDING: MSD Avenir, French National Institute for Health and Medical Research, and Bettencourt Schueller Foundation.

Delayed Kinetics of IgG, but Not IgA, Antispike Antibodies in Transplant Recipients following SARS-CoV-2 Infection.

BACKGROUND: Kidney transplant recipients are at increased risk of severe outcomes during COVID-19. Antibodies against the virus are thought to offer protection, but a thorough characterization of anti-SARS-CoV-2 immune globulin isotypes in kidney transplant recipients following SARS-CoV-2 infection has not been reported. METHODS: We performed a cross-sectional study of 49 kidney transplant recipients and 42 immunocompetent controls at early (≤14 days) or late (>14 days) time points after documented SARS-CoV-2 infection. Using a validated semiquantitative Luminex-based multiplex assay, we determined the abundances of IgM, IgG, IgG1-4, and IgA antibodies against five distinct viral epitopes. RESULTS: Kidney transplant recipients showed lower levels of total IgG antitrimeric spike (S), S1, S2, and receptor binding domain (RBD) but not nucleocapsid (NC) at early versus late time points after SARS-CoV-2 infection. Early levels of IgG antispike protein epitopes were also lower than in immunocompetent controls. Anti-SARS-CoV-2 antibodies were predominantly IgG1 and IgG3, with modest class switching to IgG2 or IgG4 in either cohort. Later levels of IgG antispike, S1, S2, RBD, and NC did not significantly differ between cohorts. There was no significant difference in the kinetics of either IgM or IgA antispike, S1, RBD, or S2 on the basis of timing after diagnosis or transplant status. CONCLUSIONS: Kidney transplant recipients mount early anti-SARS-CoV-2 IgA and IgM responses, whereas IgG responses are delayed compared with immunocompetent individuals. These findings might explain the poor outcomes in transplant recipients with COVID-19. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/JASN/2021_11_23_briggsgriffin112321.mp3.