Th17-Immune Response in Patients With Membranous Nephropathy Is Associated With Thrombosis and Relapses

International audienceAlternative strategies targeting dysregulated cytokine balance could be considered for these patients at high risk of relapse

Th17-Immune Response in Patients With Membranous Nephropathy Is Associated With Thrombosis and Relapses: Th17-Immune Response in Patients With Membranous Nephropathy Is Associated With Thrombosis and Relapses

International audienceExciting times for the field of renal autoimmune diseases have begun. In 2021, for the first time, two new drugs belimumab (1) and voclosporin ( 2) are approved for the treatment of lupus nephritis (LN) (1, 2). Other novel targeted therapies demonstrate clinical efficacy in large, randomized trials, such as avacopan for ANCA-associated vasculitis (AAV) (3), imlifidase for Goodpasture’s disease and iptacopan for IgA nephropathy (IgAN). Pathogenic molecules are specifically targeted by new drugs that help to uncover novel aspects of disease mechanisms leading to glomerulonephritis. Simultaneously, the field is boosted by novel big data technologies on the single cell levels such as high-sensitive multi-color flow cytometry, single-cell genomics (single-cell RNA sequencing - scRNAseq), single cell metabolomics and proteomics. The novel treatment options in renal autoimmune diseases almost simultaneously require new immunomonitoring tools. ‘Immunomonitoring’includes the wide range of approaches to monitoring immune responses by the cellular immune system (e.g. T-cells, B-cells, plasma cells, dendritic cells, neutrophils etc.), or by the humoral immune system (e.g. cytokines, (auto-)antibodies, urinary markers, etc.). Monitoring relevant immune responses in patients with renal autoimmune diseases helps us to better understand a) the underpinning immunological pathophysiology of these diseases; b) the beneficial effects of novel treatments on autoimmunity; and c) can potentially help doctors and patients guide a personalized treatment strategy, adding information on immunological (non-)response to a clinical (non-) response treatment and on disease prognosis. In the present Research Topic, we have been able to collect for you a vast amount of research addressing novel ways and the roleof immunomonitoring in the broad range of renal autoimmune disease including LN, AAV, IgAN, idiopathic membranous nephropathy (iMN) and complement-mediated disease (CMD)

Optimization of Rituximab Therapy in Adult Patients With PLA2R1-Associated Membranous Nephropathy With Artificial Intelligence

International audienceIntroduction: Rituximab is a first-line treatment for membranous nephropathy. Nephrotic syndrome limits rituximab exposure due to urinary drug loss. Rituximab underdosing (serum level <2 μg/ml at month-3) is a risk factor for treatment failure. We developed a machine learning algorithm to predict the risk of underdosing based on patients’ characteristics at rituximab infusion. We investigated the relationship between the predicted risk of underdosing and the cumulative dose of rituximab required to achieve remission.Methods: Rituximab concentrations were measured at month-3 in 92 sera from adult patients with primary membranous nephropathy, split into a training (75%) and a testing set (25%). A forward-backward machine-learning procedure determined the best combination of variables to predict rituximab underdosing in the training data set, which was tested in the test set. The performances were evaluated for accuracy, sensitivity, and specificity in 10-fold cross-validation training and test sets.Results: The best variables combination to predict rituximab underdosing included age, gender, body surface area (BSA), anti-phospholipase A2 receptor type 1 (anti-PLA2R1) antibody titer on day-0, serum albumin on day-0 and day-15, and serum creatinine on day-0 and day-15. The accuracy, sensitivity, and specificity were respectively 79.4%, 78.7%, and 81.0% (training data set), and 79.2%, 84.6% and 72.7% (testing data set). In both sets, the algorithm performed significantly better than chance (P < 0.05). Patients with an initial high probability of underdosing experienced a longer time to remission with higher rituximab cumulative doses required to achieved remission.Conclusion: This algorithm could allow for early intensification of rituximab regimen in patients at high estimated risk of underdosing to increase the likelihood of remission

Cohort study: “Outcomes of kidney transplantation in patients with prosthetic heart valves”

International audienceThe number of kidney transplant candidates with prosthetic heart valves (PHVs) is increasing. Yet, outcomes of kidney transplantation in these patients are still unclear. This is the first report of post-transplant outcomes in patients with PHVs at time of kidney transplantation. We conducted a matched cohort study among recipients from the multicentric and prospective DIVAT cohort to compare the outcomes in patients with left-sided PHVs at time of transplantation and a group of recipients without PHV matched according to age, dialysis time, initial disease, pretransplant DSA, diabetes, and cardiovascular events. Of 23 018 patients, 92 patients with PHVs were included and compared to 276 patients without PHV. Delayed graft function and postoperative bleeding occurred more frequently in patients with PHVs. Kidney graft survival was similar between groups. 5-year overall survival was 68.5% in patients with PHV vs. 87.9% in patients without PHV [HR, 2.72 (1.57-4.70), P = 0.0004]. Deaths from infection, endocarditis, and bleeding were more frequent in patients with PHV. Mechanical valves, but not bioprosthetic valves, were independent risk factors for mortality [HR, 2.89 (1.68-4.97), P = 0.0001]. Patients with PHV have high mortality rates after kidney transplantation. These data suggest that mechanical valves, but not biological valves, increase risks of post-transplant mortality