Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection.

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

De novo thrombotic microangiopathy after kidney transplantation in adults: Interplay between complement genetics and multiple endothelial injury.

De novo thrombotic microangiopathy (dnTMA), after renal transplantation may significantly alter graft outcomes. However, its pathogenesis and the role of complement alternative pathway dysregulation remain elusive. We studied all consecutive adult patients with a kidney allograft biopsy performed between January 2004 and March 2016 displaying dnTMA. Ninety-two patients were included. The median time of occurrence was 166 (IQR 25-811) days. The majority (82.6 %) had TMA localized only in the graft. Calcineurin inhibitor toxicity and antibody-mediated rejection (ABMR) were the 2 most frequent causes (54.3% and 37.0%, respectively). However, etiological factors were multiple in 37% patients. Interestingly, pathogenic variants in the genes of complement alternative pathway were significantly more frequent in the 42 tested patients than in healthy controls (16.7% vs 3.7% respectively, P < .008). The overall graft survival after biopsy was 66.0% at 5 years and 23.4% at 10 years, significantly worse than a matched cohort without TMA. Moreover, graft survival of patients with TMA and ABMR was worse than a matched cohort with ABMR without TMA. The 2 main prognostic factors were a positive C4d staining and a lower estimated glomerular filtration rate at diagnosis. DnTMA is a severe and multifactorial disease, induced by 1 or several endothelium-insulting conditions, mostly calcineurin inhibitor toxicity and ABMR.

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients.

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.

Long-Term Outcomes after Conversion to a Belatacept-Based Immunosuppression in Kidney Transplant Recipients.

BACKGROUND: Conversion to a belatacept-based immunosuppression is currently used as a calcineurin inhibitor (CNI) avoidance strategy when the CNI-based standard-of-care immunosuppression is not tolerated after kidney transplantation. However, there is a lack of evidence on the long-term benefit and safety after conversion to belatacept. METHODS: We prospectively enrolled 311 kidney transplant recipients from 2007 to 2020 from two referral centers, converted from CNI to belatacept after transplant according to a prespecified protocol. Patients were matched at the time of conversion to patients maintained with CNIs, using optimal matching. The primary end point was death-censored allograft survival at 7 years. The secondary end points were patient survival, eGFR, and safety outcomes, including serious viral infections, immune-related complications, antibody-mediated rejection, T-cell-mediated rejection, de novo anti-HLA donor-specific antibody, de novo diabetes, cardiovascular events, and oncologic complications. RESULTS: A total of 243 patients converted to belatacept (belatacept group) were matched to 243 patients maintained on CNIs (CNI control group). All recipient, transplant, functional, histologic, and immunologic parameters were well balanced between the two groups with a standardized mean difference below 0.05. At 7 years post-conversion to belatacept, allograft survival was 78% compared with 63% in the CNI control group ( P < 0.001 for log-rank test). The safety outcomes showed a similar rate of patient death (28% in the belatacept group versus 36% in the CNI control group), active antibody-mediated rejection (6% versus 7%), T-cell-mediated rejection (4% versus 4%), major adverse cardiovascular events, and cancer occurrence (9% versus 11%). A significantly higher rate of de novo proteinuria was observed in the belatacept group as compared with the CNI control group (37% versus 21%, P < 0.001). CONCLUSIONS: This real-world evidence study shows that conversion to belatacept post-transplant was associated with lower risk of graft failure and acceptable safety outcomes compared with patients maintained on CNIs. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Long-term Outcomes after Conversion to Belatacept, NCT04733131 .

Kidney Transplantation in Patients With AA Amyloidosis: Outcomes in a French Multicenter Cohort.

RATIONALE & OBJECTIVE: Outcomes of kidney transplantation for patients with renal AA amyloidosis are uncertain, with reports of poor survival and high rates of disease recurrence. However, the data are inconclusive and mostly based on studies from the early 2000s and earlier. STUDY DESIGN: Retrospective multicenter cohort study. SETTING & PARTICIPANTS: We searched the French national transplant database to identify all patients with renal AA amyloidosis who underwent kidney transplantation between 2008 and 2018. EXPOSURES: Age, cause of amyloidosis, use of biotherapies, and C-reactive protein levels. OUTCOMES: Outcomes were all-cause mortality and allograft loss. We also reported amyloidosis allograft recurrence, occurrence of acute rejection episodes, as well as infectious, cardiovascular, and neoplastic disease events. ANALYTICAL APPROACH: Kaplan-Meier estimator for mortality and cumulative incidence function method for allograft loss. Factors associated with patient and allograft survival were investigated using a Cox proportional hazards model and a cause-specific hazards model, respectively. RESULTS: 86 patients who received kidney transplants for AA amyloidosis at 26 French centers were included. The median age was 49.4 years (IQR, 39.7-61.1). The main cause of amyloidosis was familial Mediterranean fever (37 cases; 43%). 16 (18.6%) patients received biotherapy after transplantation. Patient survival rates were 94.0% (95% CI, 89.1-99.2) at 1 year and 85.5% (77.8-94.0) at 5 years after transplantation. Cumulative incidences of allograft loss were 10.5% (4.0-17.0) at 1 year and 13.0% (5.8-20.1) at 5 years after transplantation. Histologically proven AA amyloidosis recurrence occurred in 5 transplants (5.8%). An infection requiring hospitalization developed in 55.8% of cases, and there was a 27.9% incidence of acute allograft rejection. Multivariable analysis showed that C-reactive protein concentration at the time of transplantation was associated with patient survival (HR, 1.01; 95% CI, 1.00-1.02; P=0.01) and allograft survival (HR, 1.68; 95% CI, 1.10-2.57; P=0.02). LIMITATIONS: The study lacked a control group, and the effect of biotherapies on transplantation outcomes could not be explored. CONCLUSIONS: This relatively contemporary cohort of patients who received a kidney transplant for AA amyloidosis experienced favorable rates of survival and lower recurrence rates than previously reported. These data support the practice of treating these patients with kidney transplantation for end-stage kidney disease. PLAIN-LANGUAGE SUMMARY: AA amyloidosis is a severe and rare disease. Kidney involvement is frequent and leads to end-stage kidney disease. Because of the involvement of other organs, these patients are often frail, which has raised concerns about their suitability for kidney transplantation. We reviewed all patients with AA amyloidosis nephropathy who underwent kidney transplantation in France in the recent era (2008-2018) and found that the outcomes after kidney transplantation were favorable, with 85.5% of patients still alive 5 years after transplantation, a survival rate that is comparable to the outcomes of patients receiving a transplant for other forms of kidney diseases. Recurrence of amyloidosis in the transplanted kidney was infrequent (5.8%). These data support the practice of kidney transplantation for patients with AA amyloidosis who experience kidney failure.

Hemifacial myohyperplasia is due to somatic muscular PIK3CA gain-of-function mutations and responds to pharmacological inhibition.

Hemifacial myohyperplasia (HFMH) is a rare cause of facial asymmetry exclusively involving facial muscles. The underlying cause and the mechanism of disease progression are unknown. Here, we identified a somatic gain-of-function mutation of PIK3CA in five pediatric patients with HFMH. To understand the physiopathology of muscle hypertrophy in this context, we created a mouse model carrying specifically a PIK3CA mutation in skeletal muscles. PIK3CA gain-of-function mutation led to striated muscle cell hypertrophy, mitochondria dysfunction, and hypoglycemia with low circulating insulin levels. Alpelisib treatment, an approved PIK3CA inhibitor, was able to prevent and reduce muscle hypertrophy in the mouse model with correction of endocrine anomalies. Based on these findings, we treated the five HFMH patients. All patients demonstrated clinical, esthetical, and radiological improvement with proof of target engagement. In conclusion, we show that HFMH is due to somatic alteration of PIK3CA and is accessible to pharmacological intervention.

Conversion From Intravenous In-Hospital Belatacept Injection to Subcutaneous Abatacept Injection in Kidney Transplant Recipients During the First COVID-19 Stay-at-Home Order in France.

The first COVID-19 stay-at-home order came into effect in France on 17 March 2020. Immunocompromised patients were asked to isolate themselves, and outpatient clinic visits were dramatically reduced. In order to avoid visits to the hospital by belatacept-treated kidney transplant recipients (KTRs) during the initial period of the pandemic, we promptly converted 176 KTRs at two French transplant centers from once-monthly 5 mg/kg in-hospital belatacept infusion to once-weekly 125 mg subcutaneous abatacept injection. At the end of follow-up (3 months), 171 (97.16%) KTRs survived with a functioning graft, 2 (1.14%) had died, and 3 (1.70%) had experienced graft loss. Two patients (1.1%) experienced acute T cell-mediated rejection. Nineteen patients (10.80%) discontinued abatacept; 47% of the KTRs found the use of abatacept less restrictive than belatacept, and 38% would have preferred to continue abatacept. Mean eGFR remained stable compared to baseline. Seven patients (3.9%) had COVID-19; among these, two developed severe symptoms but survived. Only one patient had a de novo DSA. Side effects of abatacept injection were uncommon and non-severe. Our study reports for the first time in a large cohort that once-weekly injection of abatacept appears to be feasible and safe in KTRs previously treated with belatacept.

An automated histological classification system for precision diagnostics of kidney allografts.

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795 .

Race-free estimated glomerular filtration rate equation in kidney transplant recipients: development and validation study.

OBJECTIVE: To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients. DESIGN: Development and validation study SETTING: 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials). PARTICIPANTS: 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021. MAIN OUTCOME MEASURE: The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. RESULTS: The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient's creatinine level, age, and sex (https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/). CONCLUSION: A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys. TRIAL REGISTRATION: ClinicalTrials.gov NCT05229939.

Subclinical rejection-free diagnostic after kidney transplantation using blood gene expression.

We previously established a six-gene-based blood score associated with operational tolerance in kidney transplantation which was decreased in patients developing anti-HLA donor-specific antibodies (DSA). Herein, we aimed to confirm that this score is associated with immunological events and risk of rejection. We measured this using quantitative PCR (qPCR) and NanoString methods from an independent multicenter cohort of 588 kidney transplant recipients with paired blood samples and biopsies at one year after transplantation validating its association with pre-existing and de novo DSA. From 441 patients with protocol biopsy, there was a significant decrease of the score of tolerance in 45 patients with biopsy-proven subclinical rejection (SCR), a major threat associated with pejorative allograft outcomes that prompted an SCR score refinement. This refinement used only two genes, AKR1C3 and TCL1A, and four clinical parameters (previous experience of rejection, previous transplantation, sex of recipient and tacrolimus uptake). This refined SCR score was able to identify patients unlikely to develop SCR with a C-statistic of 0.864 and a negative predictive value of 98.3%. The SCR score was validated in an external laboratory, with two methods (qPCR and NanoString), and on 447 patients from an independent and multicenter cohort. Moreover, this score allowed reclassifying patients with discrepancies between the DSA presence and the histological diagnosis of antibody mediated rejection unlike kidney function. Thus, our refined SCR score could improve detection of SCR for closer and noninvasive monitoring, allowing early treatment of SCR lesions notably for patients DSA-positive and during lowering of immunosuppressive treatment.

Cardiovascular Outcomes in De Novo Kidney Transplant Recipients Receiving Everolimus and Reduced Calcineurin Inhibitor or Standard Triple Therapy: 24-month Post Hoc Analysis From TRANSFORM Study.

BACKGROUND: The comparative impact of everolimus (EVR)-based regimens versus standard of care (mycophenolic acid+standard calcineurin inhibitor [MPA+sCNI]) on cardiovascular outcomes in de novo kidney transplant recipients (KTRs) is poorly understood. The incidence of major adverse cardiac events (MACEs) in KTRs receiving EVR+reduced CNI (rCNI) or MPA+sCNI from the TRANSplant eFficacy and safety Outcomes with an eveRolimus-based regiMen study was evaluated. METHODS: The incidence of MACE was determined for all randomized patients receiving at least 1 dose of the study drug. Factors associated with MACEs were determined by logistic regression. Risk of MACE out to 3 y post-study was calculated using the Patient Outcome in Renal Transplantation equation. RESULTS: MACE occurred in 81 of 1014 (8.0%; EVR+rCNI) versus 89 of 1012 (8.8%; MPA+sCNI) KTRs (risk ratio, 0.91 [95% confidence interval [CI], 0.68-1.21]). The incidence of circulatory death, myocardial infarction, revascularization, or angina was similar between the arms. Incidence of MACE was similar between EVR+rCNI and MPA+sCNI arms with a higher incidence in prespecified risk groups: older age, pretransplant diabetes (15.1% versus 15.9%), statin use (8.5% versus 10.8%), and low estimated glomerular filtration rate (Month 2 estimated glomerular filtration rate <30 versus >60 mL/min/1.73 m 2 ; odds ratio, 2.23 [95% CI, 1.02-4.86]; P = 0.044), respectively. Predicted risk of MACE within 3 y of follow-up did not differ between the treatment arms. CONCLUSIONS: Cardiovascular morbidity and mortality were similar between de novo KTRs receiving EVR+rCNI and MPA+sCNI. EVR+rCNI is a viable alternative to the current standard of care in KTRs.

CMV-related anterior and intermediate uveitis in a kidney transplant recipient treated with belatacept.

INTRODUCTION: Belatacept is associated with a higher incidence of cytomegalovirus (CMV) disease and atypical presentations. Ocular manifestations are rare, representing up to 5% of disease manifestations and previous cases consisted in isolated retinitis. CASE DESCRIPTION: Herein, we report the case of an 81-year-old kidney transplant recipient who developed an anterior and intermediate uveitis under belatacept therapy. The diagnosis was established using quantitative CMV polymerase chain reaction assays in the aqueous humor. Belatacept was interrupted and oral and topical valganciclovir treatments were instituted. Lesions however extended, leading to intensify the treatment by intra-venous and intra-vitreal ganciclovir injections. Visual acuity stabilized and ocular inflammation was finally controlled after 3 months. CONCLUSION: Clinicians should be aware of CMV infection as a cause of anterior uveitis under belatacept-based regimen, even in the absence of symptoms suggestive of systemic CMV replication.

Performance of creatinine-based equations to estimate glomerular filtration rate in White and Black populations in Europe, Brazil and Africa.

BACKGROUND: A new Chronic Kidney Disease Epidemiology Collaboration equation without the race variable has been recently proposed (CKD-EPIAS). This equation has neither been validated outside USA nor compared with the new European Kidney Function Consortium (EKFC) and Lund-Malmö Revised (LMREV) equations, developed in European cohorts. METHODS: Standardized creatinine and measured glomerular filtration rate (GFR) from the European EKFC cohorts (n = 13 856 including 6031 individuals in the external validation cohort), from France (n = 4429, including 964 Black Europeans), from Brazil (n = 100) and from Africa (n = 508) were used to test the performances of the equations. A matched analysis between White Europeans and Black Africans or Black Europeans was performed. RESULTS: In White Europeans (n = 9496), both the EKFC and LMREV equations outperformed CKD-EPIAS (bias of -0.6 and -3.2, respectively versus 5.0 mL/min/1.73 m², and accuracy within 30% of 86.9 and 87.4, respectively, versus 80.9%). In Black Europeans and Black Africans, the best performance was observed with the EKFC equation using a specific Q-value (= concentration of serum creatinine in healthy males and females). These results were confirmed in matched analyses, which showed that serum creatinine concentrations were different in White Europeans, Black Europeans and Black Africans for the same measured GFR, age, sex and body mass index. Creatinine differences were more relevant in males. CONCLUSION: In a European and African cohort, the performances of CKD-EPIAS remain suboptimal. The EKFC equation, using usual or dedicated population-specific Q-values, presents the best performance in the whole age range in the European and African populations included in this study.

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.

Modulation of Monocyte Response by MicroRNA-15b/106a/374a During Antibody-mediated Rejection in Kidney Transplantation.

BACKGROUND: Increasing evidence suggest that microRNAs are involved in the physiopathology of acute or chronic renal disease. In kidney transplantation, as key regulators of cellular homeostasis, microRNAs may be involved in the regulation of immune cell function and the allograft response. Here, we investigated the change in circulating microRNA expression profile and their involvement in the profound transcriptional changes associated with antibody-mediated rejection (AMR). METHODS: Blood samples were collected at the time of the 710 kidney allograft biopsies at 4 European transplant centers. Messenger RNA and microRNA profiling analyses were performed in a discovery-to-validation study within 3 independent cohorts encompassing N = 126, N = 135, and N = 416 patients, respectively. RESULTS: Compared with samples with no AMR, 14 microRNAs were significantly decreased in AMR samples. Among them, expression levels of microRNA-15b, microRNA-106a, and microRNA-374a gradually decreased with the severity of AMR lesions. From their in silico-predicted target genes, a high proportion proved to be significantly upregulated in the paired transcriptomic analysis. Gene ontology analyses of microRNA-15b/-106a/-374a suggested enrichment in myeloid-related pathways, which was further refined by in silico and ex vivo transcriptomic analyses, showing a specific origin from classical CD14 + monocytes. Finally, human CD14 + monocytes were subjected to transduction by antago-microRNAs to mimic AMR pathology. MicroRNA-15b/-106a/-374a impairment resulted in cellular activation with an increased expression of CD69, CRIM1, IPO7, and CAAP1, direct and common targets of the 3 microRNAs. CONCLUSIONS: Together, our data provide new insights into circulating microRNAs as markers and key players in AMR, and they suggest monocyte involvement in this process.

Outcomes in kidney transplant recipients treated with immediate-release tacrolimus capsules versus extended-release tacrolimus capsules: A cohort study.

INTRODUCTION: Prior randomized trials and observational studies have generally reported similar outcomes in kidney transplant recipients (KTRs) treated with immediate-release tacrolimus (IR-TAC) versus extended-release tacrolimus (ER-TAC). However, many of these previous studies focused on patients with low immunological risks, had small sample sizes and brief follow-up periods, and excluded outcomes associated with graft loss, such as chronic rejection. METHODS: To address these limitations, we conducted a cohort study of 848 KTRs at a single transplantation center who had generally high immunological risks and were treated with either IR-TAC capsules (589 patients, 65.9%) or ER-TAC capsules (289 patients, 34.1%). All patients received their designated maintenance immunosuppressive regimen for at least 3 months post-transplantation. Afterwards, tacrolimus formulation was at the discretion of each patient's transplant nephrologist. For the two treatment groups, we compared the hazards of experiencing a composite outcome of acute or chronic antibody-mediated rejection (AMR), acute or chronic T-cell-mediated rejection, de novo DSA, and/or graft loss over a 3-year period starting at 3 months post-transplantation. RESULTS: In a multivariable Cox proportional hazards regression model, KTRs treated with IR-TAC capsules had an increased hazard of experiencing the composite outcome when compared to patients treated with ER-TAC capsules; however, this result was not significant (adj HR 1.24, 95% CI .92-1.68, p = .163). Similar results were obtained with inverse probability of treatment weighting (IPTW) using a propensity score (adj HR 1.25, 95% CI .93-1.68, p = .146). CONCLUSION: These findings suggest that when compared to IR-TAC capsules, ER-TAC capsules do not reduce the hazard of poor outcomes in KTRs with generally high immunological risks.

PIK3CA gain-of-function mutation in adipose tissue induces metabolic reprogramming with Warburg-like effect and severe endocrine disruption.

PIK3CA-related overgrowth syndrome (PROS) is a genetic disorder caused by somatic mosaic gain-of-function mutations of PIK3CA. Clinical presentation of patients is diverse and associated with endocrine disruption. Adipose tissue is frequently involved, but its role in disease development and progression has not been elucidated. Here, we created a mouse model of PIK3CA-related adipose tissue overgrowth that recapitulates patient phenotype. We demonstrate that PIK3CA mutation leads to GLUT4 membrane accumulation with a negative feedback loop on insulin secretion, a burst of liver IGFBP1 synthesis with IGF-1 sequestration, and low circulating levels. Mouse phenotype was mainly driven through AKT2. We also observed that PIK3CA mutation induces metabolic reprogramming with Warburg-like effect and protein and lipid synthesis, hallmarks of cancer cells, in vitro, in vivo, and in patients. We lastly show that alpelisib is efficient at preventing and improving PIK3CA-adipose tissue overgrowth and reversing metabolomic anomalies in both animal models and patients.

Comparison of artificial intelligence and human-based prediction and stratification of the risk of long-term kidney allograft failure.

BACKGROUND: Clinical decisions are mainly driven by the ability of physicians to apply risk stratification to patients. However, this task is difficult as it requires complex integration of numerous parameters and is impacted by patient heterogeneity. We sought to evaluate the ability of transplant physicians to predict the risk of long-term allograft failure and compare them to a validated artificial intelligence (AI) prediction algorithm. METHODS: We randomly selected 400 kidney transplant recipients from a qualified dataset of 4000 patients. For each patient, 44 features routinely collected during the first-year post-transplant were compiled in an electronic health record (EHR). We enrolled 9 transplant physicians at various career stages. At 1-year post-transplant, they blindly predicted the long-term graft survival with probabilities for each patient. Their predictions were compared with those of a validated prediction system (iBox). We assessed the determinants of each physician's prediction using a random forest survival model. RESULTS: Among the 400 patients included, 84 graft failures occurred at 7 years post-evaluation. The iBox system demonstrates the best predictive performance with a discrimination of 0.79 and a median calibration error of 5.79%, while physicians tend to overestimate the risk of graft failure. Physicians' risk predictions show wide heterogeneity with a moderate intraclass correlation of 0.58. The determinants of physicians' prediction are disparate, with poor agreement regardless of their clinical experience. CONCLUSIONS: This study shows the overall limited performance and consistency of physicians to predict the risk of long-term graft failure, demonstrated by the superior performances of the iBox. This study supports the use of a companion tool to help physicians in their prognostic judgement and decision-making in clinical care.

The ability to predict the risk of a particular event is key to clinical decision-making, for example when predicting the risk of a poor outcome to help decide which patients should receive an organ transplant. Computer-based systems may help to improve risk prediction, particularly with the increasing volume and complexity of patient data available to clinicians. Here, we compare predictions of the risk of long-term kidney transplant failure made by clinicians with those made by our computer-based system (the iBox system). We observe that clinicians' overall performance in predicting individual long-term outcomes is limited compared to the iBox system, and demonstrate wide variability in clinicians' predictions, regardless of level of experience. Our findings support the use of the iBox system in the clinic to help clinicians predict outcomes and make decisions surrounding kidney transplants.