Urinary CD4 + T Cells Predict Renal Relapse in ANCA-Associated Vasculitis.

SIGNIFICANCE STATEMENT: Early identification of patients at risk of renal flares in ANCA vasculitis is crucial. However, current clinical parameters have limitations in predicting renal relapse accurately. This study investigated the use of urinary CD4 + T lymphocytes as a predictive biomarker for renal flares in ANCA vasculitis. This study, including urine samples from 102 patients, found that the presence of urinary CD4 + T cells was a robust predictor of renal relapse within a 6-month time frame, with a sensitivity of 60% and a specificity of 97.8%. The diagnostic accuracy of urinary CD4 + T cells exceeded that of ANCA titers, proteinuria, and hematuria. Monitoring urinary CD4 + T lymphocytes could help assess the risk of future renal relapse, enabling early preventive measures and tailored treatment strategies. BACKGROUND: In ANCA-associated vasculitis, there is a lack of biomarkers for predicting renal relapse. Urinary T cells have been shown to differentiate active GN from remission in ANCA-associated vasculitis, but their predictive value for renal flares remains unknown. METHODS: The PRE-FLARED study was a prospective multicenter biomarker study including 102 individuals with ANCA-associated vasculitis in remission aimed to predict renal relapse by quantifying urinary CD4 + T-cell subsets using flow cytometry at baseline and monitoring clinical outcomes over a 6-month follow-up. RESULTS: Among the participants, ten experienced renal relapses, two had non-renal flares, and 90 remained in stable remission. The median baseline urinary CD4 + T-cell count was significantly higher in patients who relapsed compared with those in remission. Receiver operating characteristic curve analysis of urinary CD4 + T-cell counts showed an area under the curve value of 0.88 for predicting renal flares, outperforming ANCA titers, hematuria, and proteinuria. Using a cutoff of 490 CD4 + T cells per 100 ml urine, the sensitivity and specificity in identifying patients with future renal flares were 60% and 97.8%, respectively. In a post hoc analysis, combining urinary CD4 + T-cell counts with proteinase-3 ANCA levels suggested improved predictive performance in the PR3 + subgroup. In addition, the number of urinary CD4 + T cells showed a limited correlation with a decline in GFR and an increase in proteinuria over the follow-up period. CONCLUSIONS: This study concluded that urinary CD4 + T-cell counts could identify patients with ANCA-associated vasculitis at a substantial risk of renal relapse within 6 months. Combining these counts with ANCA levels further improved the prediction of relapse. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Urinary T Lymphocytes Predict Renal Flares in Patients With Inactive ANCA-associated Glomerulonephritis (PRE-FLARED), NCT04428398 .

Addition of formaldehyde releaser imidazolidinyl urea and MOPS buffer to urine samples enables delayed processing for flow cytometric analysis of urinary cells: A simple, two step conservation method of urinary cells for flow cytometry.

INTRODUCTION: Kidney diseases are a major health concern worldwide. Currently there is a large unmet need for novel biomarkers to non-invasively diagnose and monitor kidney diseases. Urinary cells are promising biomarkers and their analysis by flow cytometry has demonstrated its utility in diverse clinical settings. However, up to date this methodology depends on fresh samples, as cellular event counts and the signal-to-noise-ratio deter over time. Here we developed an easy-to-use two-step preservation method for conservation of urine samples for subsequent flow cytometry. METHODS: The protocol utilizes a combination of the formaldehyde releasing agent imidazolidinyl urea (IU) and MOPS buffer, leading to gentle fixation of urinary cells. RESULTS: The preservation method increases acceptable storing time of urine samples from several hours to up to 6 days. Cellular event counts and staining properties of cells remain comparable to fresh untreated samples. OUTLOOK: The hereby presented preservation method facilitates future investigations on flow cytometry of urinary cells as potential biomarkers and may enable broad implementation in clinical practice.

Urinary single-cell sequencing captures kidney injury and repair processes in human acute kidney injury.

Acute kidney injury (AKI) is a major health issue, the outcome of which depends primarily on damage and reparative processes of tubular epithelial cells. Mechanisms underlying AKI remain incompletely understood, specific therapies are lacking and monitoring the course of AKI in clinical routine is confined to measuring urine output and plasma levels of filtration markers. Here we demonstrate feasibility and potential of a novel approach to assess the cellular and molecular dynamics of AKI by establishing a robust urine-to-single cell RNA sequencing (scRNAseq) pipeline for excreted kidney cells via flow cytometry sorting. We analyzed 42,608 single cell transcriptomes of 40 urine samples from 32 patients with AKI and compared our data with reference material from human AKI post-mortem biopsies and published mouse data. We demonstrate that tubular epithelial cells transcriptomes mirror kidney pathology and reflect distinct injury and repair processes, including oxidative stress, inflammation, and tissue rearrangement. We also describe an AKI-specific abundant urinary excretion of adaptive progenitor-like cells. Thus, single cell transcriptomics of kidney cells excreted in urine provides noninvasive, unprecedented insight into cellular processes underlying AKI, thereby opening novel opportunities for target identification, AKI sub-categorization, and monitoring of natural disease course and interventions.

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.