An atlas of healthy and injured cell states and niches in the human kidney.

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Rationale and design of the Nephrotic Syndrome Study Network (NEPTUNE) Match in glomerular diseases: designing the right trial for the right patient, today.

Glomerular diseases are classified using a descriptive taxonomy that is not reflective of the heterogeneous underlying molecular drivers. This limits not only diagnostic and therapeutic patient management, but also impacts clinical trials evaluating targeted interventions. The Nephrotic Syndrome Study Network (NEPTUNE) is poised to address these challenges. The study has enrolled >850 pediatric and adult patients with proteinuric glomerular diseases who have contributed to deep clinical, histologic, genetic, and molecular profiles linked to long-term outcomes. The NEPTUNE Knowledge Network, comprising combined, multiscalar data sets, captures each participant's molecular disease processes at the time of kidney biopsy. In this editorial, we describe the design and implementation of NEPTUNE Match, which bridges a basic science discovery pipeline with targeted clinical trials. Noninvasive biomarkers have been developed for real-time pathway analyses. A Molecular Nephrology Board reviews the pathway maps together with clinical, laboratory, and histopathologic data assembled for each patient to compile a Match report that estimates the fit between the specific molecular disease pathway(s) identified in an individual patient and proposed clinical trials. The NEPTUNE Match report is communicated using established protocols to the patient and the attending nephrologist for use in their selection of available clinical trials. NEPTUNE Match represents the first application of precision medicine in nephrology with the aim of developing targeted therapies and providing the right medication for each patient with primary glomerular disease.

Association of COVID-19 Versus COVID-19 Vaccination With Kidney Function and Disease Activity in Primary Glomerular Disease: A Report of the Cure Glomerulonephropathy Study.

RATIONALE & OBJECTIVE: Patients with glomerular disease (GN) may be at increased risk of severe COVID-19, yet concerns over vaccines causing disease relapse may lead to vaccine hesitancy. We examined the associations of COVID-19 with longitudinal kidney function and proteinuria and compared these with similar associations with COVID-19 vaccination. STUDY DESIGN: Observational cohort study from July 1, 2021, to January 1, 2023. SETTING & PARTICIPANTS: A prospective observational study network of 71 centers from North America and Europe (CureGN) with children and adults with primary minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA nephropathy. EXPOSURE: COVID-19 and COVID-19 vaccination. OUTCOME: Repeated measure of estimated glomerular filtration rate (eGFR); recurrent time-to-event outcome of GN disease worsening as defined by doubling of the urinary protein-creatinine ratio (UPCR) to at least 1.5g/g or increase in dipstick urine protein by 2 ordinal levels to 3+(300mg/dL) or above. ANALYTICAL APPROACH: Interrupted time series analysis for eGFR. Prognostic matched sequential stratification recurrent event analysis for GN disease worsening. RESULTS: Among 2,055 participants, 722 (35%) reported COVID-19 infection; of these, 92 (13%) were hospitalized, and 3 died (<1%). The eGFR slope before COVID-19 infection was-1.40mL/min/1.73m2 (± 0.29 SD); within 6 months after COVID-19 infection, the eGFR slope was-4.26mL/min/1.73m2 (± 3.02 SD), which was not significantly different (P=0.34). COVID-19 was associated with increased risk of worsening GN disease activity (HR, 1.35 [95% CI, 1.01-1.80]). Vaccination was not associated with a change in eGFR (-1.34mL/min/1.73m2±0.15 SD vs-2.16mL/min/1.73m2±1.74 SD; P=0.6) or subsequent GN disease worsening (HR 1.02 [95% CI, 0.79-1.33]) in this cohort. LIMITATIONS: Infrequent or short follow-up. CONCLUSIONS: Among patients with primary GN, COVID-19 infection was severe for 1 in 8 cases and was associated with subsequent worsening of GN disease activity, as defined by proteinuria. By contrast, vaccination against COVID-19 was not associated with change in disease activity or kidney function decline. These results support COVID-19 vaccination for patients with GN. PLAIN-LANGUAGE SUMMARY: In this cohort study of 2,055 patients with minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA nephropathy, COVID-19 resulted in hospitalization or death for 1 in 8 cases and was associated with a 35% increase in risk for worsening proteinuria. By contrast, vaccination did not appear to adversely affect kidney function or proteinuria. Our data support vaccination for COVID-19 in patients with glomerular disease.

Precision nephrology identified tumor necrosis factor activation variability in minimal change disease and focal segmental glomerulosclerosis.

The diagnosis of nephrotic syndrome relies on clinical presentation and descriptive patterns of injury on kidney biopsies, but not specific to underlying pathobiology. Consequently, there are variable rates of progression and response to therapy within diagnoses. Here, an unbiased transcriptomic-driven approach was used to identify molecular pathways which are shared by subgroups of patients with either minimal change disease (MCD) or focal segmental glomerulosclerosis (FSGS). Kidney tissue transcriptomic profile-based clustering identified three patient subgroups with shared molecular signatures across independent, North American, European, and African cohorts. One subgroup had significantly greater disease progression (Hazard Ratio 5.2) which persisted after adjusting for diagnosis and clinical measures (Hazard Ratio 3.8). Inclusion in this subgroup was retained even when clustering was limited to those with less than 25% interstitial fibrosis. The molecular profile of this subgroup was largely consistent with tumor necrosis factor (TNF) pathway activation. Two TNF pathway urine markers were identified, tissue inhibitor of metalloproteinases-1 (TIMP-1) and monocyte chemoattractant protein-1 (MCP-1), that could be used to predict an individual's TNF pathway activation score. Kidney organoids and single-nucleus RNA-sequencing of participant kidney biopsies, validated TNF-dependent increases in pathway activation score, transcript and protein levels of TIMP-1 and MCP-1, in resident kidney cells. Thus, molecular profiling identified a subgroup of patients with either MCD or FSGS who shared kidney TNF pathway activation and poor outcomes. A clinical trial testing targeted therapies in patients selected using urinary markers of TNF pathway activation is ongoing.

Kidney Biopsy Features Most Predictive of Clinical Outcomes in the Spectrum of Minimal Change Disease and Focal Segmental Glomerulosclerosis.

BACKGROUND: Heterogeneity in disease course and treatment response among patients with MCD/FSGS necessitates a granular evaluation of kidney tissue features. This study aimed to identify histologic and ultrastructural descriptors of structural changes most predictive of clinical outcomes in the Nephrotic Syndrome Study Network (NEPTUNE). METHODS: Forty-eight histologic (37 glomerular, 9 tubulointerstitial, 2 vascular) and 20 ultrastructural descriptors were quantified by applying the NEPTUNE Digital Pathology Scoring System to NEPTUNE kidney biopsies. Outcomes included time from biopsy to disease progression, first complete remission of proteinuria, and treatment response. Relative importance of pathology and clinical predictors was obtained from random forest models, and predictive discrimination was assessed. RESULTS: Among 224 participants (34% Black, 24% Hispanic), model performance was excellent, with predictive discrimination of 0.9 for disease progression, 0.85 for complete remission, and 0.81 for treatment response. The most predictive descriptors of outcomes included both conventional-e.g., global sclerosis or segmental sclerosis and interstitial fibrosis/tubular atrophy-and novel features, including adhesion, interstitial foam cells, deflation, periglomerular fibrosis, mononuclear white blood cells, endothelial cell abnormalities, microvillous transformation, and acute tubular injury. CONCLUSIONS: The most predictive descriptors of clinical outcomes among MCD/FSGS patients reflected structural changes in multiple renal compartments. Reporting these descriptors should be standardized to guide prognostication of proteinuric glomerular diseases.

Molecular programs associated with glomerular hyperfiltration in early diabetic kidney disease.

Hyperfiltration is a state of high glomerular filtration rate (GFR) observed in early diabetes that damages glomeruli, resulting in an iterative process of increasing filtration load on fewer and fewer remaining functional glomeruli. To delineate underlying cellular mechanisms of damage associated with hyperfiltration, transcriptional profiles of kidney biopsies from Pima Indians with type 2 diabetes with or without early-stage diabetic kidney disease were grouped into two hyperfiltration categories based on annual iothalamate GFR measurements. Twenty-six participants with a peak GFR measurement within two years of biopsy were categorized as the hyperfiltration group, and 26 in whom biopsy preceded peak GFR by over two years were considered pre-hyperfiltration. The hyperfiltration group had higher hemoglobin A1c, higher urine albumin-to-creatinine ratio, increased glomerular basement membrane width and lower podocyte density compared to the pre-hyperfiltration group. A glomerular 1240-gene transcriptional signature identified in the hyperfiltration group was enriched for endothelial stress response signaling genes, including endothelin-1, tec-kinase and transforming growth factor-ß1 pathways, with the majority of the transcripts mapped to endothelial and inflammatory cell clusters in kidney single cell transcriptional data. Thus, our analysis reveals molecular pathomechanisms associated with hyperfiltration in early diabetic kidney disease involving putative ligand-receptor pairs with downstream intracellular targets linked to cellular crosstalk between endothelial and mesangial cells.

Quantification of Glomerular Structural Lesions: Associations With Clinical Outcomes and Transcriptomic Profiles in Nephrotic Syndrome.

RATIONALE & OBJECTIVE: The current classification system for focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) does not fully capture the complex structural changes in kidney biopsies nor the clinical and molecular heterogeneity of these diseases. STUDY DESIGN: Prospective observational cohort study. SETTING & PARTICIPANTS: 221 MCD and FSGS patients enrolled in the Nephrotic Syndrome Study Network (NEPTUNE). EXPOSURE: The NEPTUNE Digital Pathology Scoring System (NDPSS) was applied to generate scores for 37 glomerular descriptors. OUTCOME: Time from biopsy to complete proteinuria remission, time from biopsy to kidney disease progression (40% estimated glomerular filtration rate [eGFR] decline or kidney failure), and eGFR over time. ANALYTICAL APPROACH: Cluster analysis was used to group patients with similar morphologic characteristics. Glomerular descriptors and patient clusters were assessed for associations with outcomes using adjusted Cox models and linear mixed models. Messenger RNA from glomerular tissue was used to assess differentially expressed genes between clusters and identify genes associated with individual descriptors driving cluster membership. RESULTS: Three clusters were identified: X (n = 56), Y (n = 68), and Z (n = 97). Clusters Y and Z had higher probabilities of proteinuria remission (HRs of 1.95 [95% CI, 0.99-3.85] and 3.29 [95% CI, 1.52-7.13], respectively), lower hazards of disease progression (HRs of 0.22 [95% CI, 0.08-0.57] and 0.11 [95% CI, 0.03-0.45], respectively), and lower loss of eGFR over time compared with X. Cluster X had 1,920 genes that were differentially expressed compared with Y+Z; these reflected activation of pathways of immune response and inflammation. Six descriptors driving the clusters individually correlated with clinical outcomes and gene expression. LIMITATIONS: Low prevalence of some descriptors and biopsy at a single time point. CONCLUSIONS: The NDPSS allows for categorization of FSGS/MCD patients into clinically and biologically relevant subgroups, and uncovers histologic parameters associated with clinical outcomes and molecular signatures not included in current classification systems.

Rationale and design of the Kidney Precision Medicine Project.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Study Design and Baseline Characteristics of the CARDINAL Trial: A Phase 3 Study of Bardoxolone Methyl in Patients with Alport Syndrome.

INTRODUCTION: Alport syndrome is a rare genetic disorder that affects as many as 60,000 persons in the USA and a total of 103,000 persons (<5 per 10,000) in the European Union [1, 2]. It is the second most common inherited cause of kidney failure and is characterized by progressive loss of kidney function that often leads to end-stage kidney disease. Currently, there are no approved disease-specific agents for therapeutic use. We designed a phase 3 study (CARDINAL; NCT03019185) to evaluate the safety, tolerability, and efficacy of bardoxolone methyl in patients with Alport syndrome. METHODS: The CARDINAL phase 3 study is an international, multicenter, double-blind, placebo-controlled, randomized registrational trial. Eligible patients were of ages 12-70 years with confirmed genetic or histologic diagnosis of Alport syndrome, eGFR 30-90 mL/min/1.73 m2, and urinary albumin to creatinine ratio (UACR) ≤3,500 mg/g. Patients with B-type natriuretic peptide values >200 pg/mL at baseline or with significant cardiovascular histories were excluded. Patients were randomized 1:1 to bardoxolone methyl or placebo, with stratification by baseline UACR. RESULTS: A total of 371 patients were screened, and 157 patients were randomly assigned to receive bardoxolone methyl (n = 77) or placebo (n = 80). The average age at screening was 39.2 years, and 23 (15%) were <18 years of age. Of the randomized population, 146 (93%) had confirmed genetic diagnosis of Alport syndrome, and 62% of patients had X-linked mode of inheritance. Mean baseline eGFR was 62.7 mL/min/1.73 m2, and the geometric mean UACR was 141.0 mg/g. The average annual rate of eGFR decline prior to enrollment in the study was -4.9 mL/min/1.73 m2 despite 78% of the patient population receiving ACE inhibitor (ACEi) or ARB therapy. DISCUSSION/CONCLUSION: CARDINAL is one of the largest interventional, randomized controlled trials in Alport syndrome conducted to date. Despite the use of ACEi or ARB, patients were experiencing significant loss of kidney function prior to study entry.

Ultrastructural Characterization of Proteinuric Patients Predicts Clinical Outcomes.

BACKGROUND: The analysis and reporting of glomerular features ascertained by electron microscopy are limited to few parameters with minimal predictive value, despite some contributions to disease diagnoses. METHODS: We investigated the prognostic value of 12 electron microscopy histologic and ultrastructural changes (descriptors) from the Nephrotic Syndrome Study Network (NEPTUNE) Digital Pathology Scoring System. Study pathologists scored 12 descriptors in NEPTUNE renal biopsies from 242 patients with minimal change disease or FSGS, with duplicate readings to evaluate reproducibility. We performed consensus clustering of patients to identify unique electron microscopy profiles. For both individual descriptors and clusters, we used Cox regression models to assess associations with time from biopsy to proteinuria remission and time to a composite progression outcome (≥40% decline in eGFR, with eGFR<60 ml/min per 1.73 m2, or ESKD), and linear mixed models for longitudinal eGFR measures. RESULTS: Intrarater and interrater reproducibility was >0.60 for 12 out of 12 and seven out of 12 descriptors, respectively. Individual podocyte descriptors such as effacement and microvillous transformation were associated with complete remission, whereas endothelial cell and glomerular basement membrane abnormalities were associated with progression. We identified six descriptor-based clusters with distinct electron microscopy profiles and clinical outcomes. Patients in a cluster with more prominent foot process effacement and microvillous transformation had the highest rates of complete proteinuria remission, whereas patients in clusters with extensive loss of primary processes and endothelial cell damage had the highest rates of the composite progression outcome. CONCLUSIONS: Systematic analysis of electron microscopic findings reveals clusters of findings associated with either proteinuria remission or disease progression.

Proteomic Analysis Identifies Distinct Glomerular Extracellular Matrix in Collapsing Focal Segmental Glomerulosclerosis.

BACKGROUND: The mechanisms leading to extracellular matrix (ECM) replacement of areas of glomerular capillaries in histologic variants of FSGS are unknown. This study used proteomics to test the hypothesis that glomerular ECM composition in collapsing FSGS (cFSGS) differs from that of other variants. METHODS: ECM proteins in glomeruli from biopsy specimens of patients with FSGS not otherwise specified (FSGS-NOS) or cFSGS and from normal controls were distinguished and quantified using mass spectrometry, verified and localized using immunohistochemistry (IHC) and confocal microscopy, and assessed for gene expression. The analysis also quantified urinary excretion of ECM proteins and peptides. RESULTS: Of 58 ECM proteins that differed in abundance between cFSGS and FSGS-NOS, 41 were more abundant in cFSGS and 17 in FSGS-NOS. IHC showed that glomerular tuft staining for cathepsin B, cathepsin C, and annexin A3 in cFSGS was significantly greater than in other FSGS variants, in minimal change disease, or in membranous nephropathy. Annexin A3 colocalized with cathepsin B and C, claudin-1, phosphorylated ERK1/2, and CD44, but not with synaptopodin, in parietal epithelial cells (PECs) infiltrating cFSGS glomeruli. Transcripts for cathepsins B and C were increased in FSGS glomeruli compared with normal controls, and urinary excretion of both cathepsins was significantly greater in cFSGS compared with FSGS-NOS. Urinary excretion of ECM-derived peptides was enhanced in cFSGS, although in silico analysis did not identify enhanced excretion of peptides derived from cathepsin B or C. CONCLUSIONS: ECM differences suggest that glomerular sclerosis in cFSGS differs from that in other FSGS variants. Infiltration of activated PECs may disrupt ECM remodeling in cFSGS. These cells and their cathepsins may be therapeutic targets.

Machine learning, the kidney, and genotype-phenotype analysis.

With biomedical research transitioning into data-rich science, machine learning provides a powerful toolkit for extracting knowledge from large-scale biological data sets. The increasing availability of comprehensive kidney omics compendia (transcriptomics, proteomics, metabolomics, and genome sequencing), as well as other data modalities such as electronic health records, digital nephropathology repositories, and radiology renal images, makes machine learning approaches increasingly essential for analyzing human kidney data sets. Here, we discuss how machine learning approaches can be applied to the study of kidney disease, with a particular focus on how they can be used for understanding the relationship between genotype and phenotype.

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2-infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19-related kidney damage.

Incorporating longitudinal biomarkers for dynamic risk prediction in the era of big data: A pseudo-observation approach.

Longitudinal biomarker data are often collected in studies, providing important information regarding the probability of an outcome of interest occurring at a future time. With many new and evolving technologies for biomarker discovery, the number of biomarker measurements available for analysis of disease progression has increased dramatically. A large amount of data provides a more complete picture of a patient's disease progression, potentially allowing us to make more accurate and reliable predictions, but the magnitude of available data introduces challenges to most statistical analysts. Existing approaches suffer immensely from the curse of dimensionality. In this article, we propose methods for making dynamic risk predictions using repeatedly measured biomarkers of a large dimension, including cases when the number of biomarkers is close to the sample size. The proposed methods are computationally simple, yet sufficiently flexible to capture complex relationships between longitudinal biomarkers and potentially censored events times. The proposed approaches are evaluated by extensive simulation studies and are further illustrated by an application to a data set from the Nephrotic Syndrome Study Network.

Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research.

BACKGROUND: The rarity of pediatric glomerular disease makes it difficult to identify sufficient numbers of participants for clinical trials. This leaves limited data to guide improvements in care for these patients. METHODS: The authors developed and tested an electronic health record (EHR) algorithm to identify children with glomerular disease. We used EHR data from 231 patients with glomerular disorders at a single center to develop a computerized algorithm comprising diagnosis, kidney biopsy, and transplant procedure codes. The algorithm was tested using PEDSnet, a national network of eight children's hospitals with data on >6.5 million children. Patients with three or more nephrologist encounters (n=55,560) not meeting the computable phenotype definition of glomerular disease were defined as nonglomerular cases. A reviewer blinded to case status used a standardized form to review random samples of cases (n=800) and nonglomerular cases (n=798). RESULTS: The final algorithm consisted of two or more diagnosis codes from a qualifying list or one diagnosis code and a pretransplant biopsy. Performance characteristics among the population with three or more nephrology encounters were sensitivity, 96% (95% CI, 94% to 97%); specificity, 93% (95% CI, 91% to 94%); positive predictive value (PPV), 89% (95% CI, 86% to 91%); negative predictive value, 97% (95% CI, 96% to 98%); and area under the receiver operating characteristics curve, 94% (95% CI, 93% to 95%). Requiring that the sum of nephrotic syndrome diagnosis codes exceed that of glomerulonephritis codes identified children with nephrotic syndrome or biopsy-based minimal change nephropathy, FSGS, or membranous nephropathy, with 94% sensitivity and 92% PPV. The algorithm identified 6657 children with glomerular disease across PEDSnet, ≥50% of whom were seen within 18 months. CONCLUSIONS: The authors developed an EHR-based algorithm and demonstrated that it had excellent classification accuracy across PEDSnet. This tool may enable faster identification of cohorts of pediatric patients with glomerular disease for observational or prospective studies.

Using All Longitudinal Data to Define Time to Specified Percentages of Estimated GFR Decline: A Simulation Study.

RATIONALE & OBJECTIVE: The standard method to calculate time to the event of a specified percentage decline in estimated glomerular filtration rate (eGFR) uses 2 eGFR assessments, 1 at baseline and 1 at the event time. However, event times may be inaccurate due to eGFR variability and restriction of events to study visit times. We propose a novel method for calculating time to a specified percentage decline in eGFR that uses all available longitudinal eGFR assessments. STUDY DESIGN: Simulation study and comparison of methods in 2 observational cohorts. SETTINGS & PARTICIPANTS: Simulation data and study participants in the Nephrotic Syndrome Study Network (NEPTUNE) and Clinical Phenotyping and Resource Biobank Core (C-PROBE). EXPOSURE: Analytical method for calculating time to a specified percentage decline in eGFR: standard 2-point method versus a regression method incorporating all available longitudinally assessed eGFR assessments. OUTCOME: Time to percentage decline in eGFR. ANALYTIC APPROACH: A 2-point method used only the baseline eGFR and first eGFR below the decline threshold. The comparison method used ordinary linear regression incorporating all longitudinal eGFR assessments to define the baseline measure and 40% decline threshold. Time to a 40% decline in eGFR was defined as the time when the regression line crossed the decline threshold. The 2 outcome calculation methods were compared using simulations to assess the accuracy of estimated event times and power to detect event time differences between groups. Comparison of event times calculated using each method was also implemented using data from NEPTUNE and C-PROBE. RESULTS: The regression method incorporating all eGFR assessments was more accurate than the 2-point method in estimating event times in simulation analyses, particularly when eGFR variability was high, there was a greater correlation among successive eGFR values, or there were more missing data. This method was also more powerful in detecting differences between groups. Using NEPTUNE and C-PROBE data, the standard method estimated a more rapid rate of events, some likely representing transient reductions in kidney function, and was less likely to give accurate estimates in the presence of nonlinear eGFR trajectories. LIMITATIONS: Computations required for our proposed method currently limit its use to research rather than clinical applications. CONCLUSIONS: A regression method using all longitudinal eGFR values to estimate time to a percentage decline in eGFR increases accuracy and power over traditional methods, representing a potential improvement in the ability to discover treatment or biomarker effects on kidney disease progression.

CureGN Study Rationale, Design, and Methods: Establishing a Large Prospective Observational Study of Glomerular Disease.

RATIONALE & OBJECTIVES: Glomerular diseases, including minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, and immunoglobulin A (IgA) nephropathy, share clinical presentations, yet result from multiple biological mechanisms. Challenges to identifying underlying mechanisms, biomarkers, and new therapies include the rarity of each diagnosis and slow progression, often requiring decades to measure the effectiveness of interventions to prevent end-stage kidney disease (ESKD) or death. STUDY DESIGN: Multicenter prospective cohort study. SETTING & PARTICIPANTS: Cure Glomerulonephropathy (CureGN) will enroll 2,400 children and adults with minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA nephropathy (including IgA vasculitis) and a first diagnostic kidney biopsy within 5 years. Patients with ESKD and those with secondary causes of glomerular disease are excluded. EXPOSURES: Clinical data, including medical history, medications, family history, and patient-reported outcomes, are obtained, along with a digital archive of kidney biopsy images and blood and urine specimens at study visits aligned with clinical care 1 to 4 times per year. OUTCOMES: Patients are followed up for changes in estimated glomerular filtration rate, disease activity, ESKD, and death and for nonrenal complications of disease and treatment, including infection, malignancy, cardiovascular, and thromboembolic events. ANALYTICAL APPROACH: The study design supports multiple longitudinal analyses leveraging the diverse data domains of CureGN and its ancillary program. At 2,400 patients and an average of 2 years' initial follow-up, CureGN has 80% power to detect an HR of 1.4 to 1.9 for proteinuria remission and a mean difference of 2.1 to 3.0mL/min/1.73m2 in estimated glomerular filtration rate per year. LIMITATIONS: Current follow-up can only detect large differences in ESKD and death outcomes. CONCLUSIONS: Study infrastructure will support a broad range of scientific approaches to identify mechanistically distinct subgroups, identify accurate biomarkers of disease activity and progression, delineate disease-specific treatment targets, and inform future therapeutic trials. CureGN is expected to be among the largest prospective studies of children and adults with glomerular disease, with a broad goal to lessen disease burden and improve outcomes.

Interstitial fibrosis scored on whole-slide digital imaging of kidney biopsies is a predictor of outcome in proteinuric glomerulopathies.

Background: Interstitial fibrosis (IF), tubular atrophy (TA) and interstitial inflammation (II) are known determinants of progression of renal disease. Standardized quantification of these features could add value to current classification of glomerulopathies. Methods: We studied 315 participants in the Nephrotic Syndrome Study Network (NEPTUNE) study, including biopsy-proven minimal change disease (MCD = 98), focal segmental glomerulosclerosis (FSGS = 121), membranous nephropathy (MN = 59) and IgA nephropathy (IgAN = 37). Cortical IF, TA and II were quantified (%) on digitized whole-slide biopsy images, by five pathologists with high inter-reader agreement (intra-class correlation coefficient >0.8). Tubulointerstitial messenger RNA expression was measured in a subset of patients. Multivariable Cox proportional hazards models were fit to assess association of IF with the composite of 40% decline in estimated glomerular filtration rate (eGFR) and end-stage renal disease (ESRD) and separately as well, and with complete remission (CR) of proteinuria. Results: IF was highly correlated with TA (P < 0.001) and II (P < 0.001). Median IF varied by diagnosis: FSGS 17, IgAN 21, MN 7, MCD 1 (P < 0.001). IF was strongly correlated with baseline eGFR (P < 0.001) and proteinuria (P = 0.002). After adjusting for clinical pathologic diagnosis, age, race, global glomerulosclerosis, baseline proteinuria, eGFR and medications, each 10% increase in IF was associated with a hazard ratio of 1.29 (P < 0.03) for ESRD/40% eGFR decline, but was not significantly associated with CR. A total of 981 genes were significantly correlated with IF (|r| > 0.4, false discovery rate (FDR) < 0.01), including upstream regulators such as tumor necrosis factor, interferon gamma (IFN-gamma), and transforming growth factor beta 1 (TGF-B1), and signaling pathways for antigen presentation and hepatic fibrosis. Conclusions: The degree of IF is associated with risk of eGFR decline across different types of proteinuric glomerulopathy, correlates with inflammatory and fibrotic gene expression, and may have predictive value in assessing risk of progression.

Integrative Genomics Identifies Novel Associations with APOL1 Risk Genotypes in Black NEPTUNE Subjects.

APOL1 variants have been associated with renal phenotypes in blacks. To refine clinical outcomes and discover mechanisms of APOL1-associated kidney injury, we analyzed clinical and genomic datasets derived from 90 black subjects in the Nephrotic Syndrome Study Network (NEPTUNE), stratified by APOL1 risk genotype. Ninety subjects with proteinuria ≥0.5 g/d were enrolled at first biopsy for primary nephrotic syndrome and followed. Clinical outcomes were determined, and renal histomorphometry and sequencing of Mendelian nephrotic syndrome genes were performed. APOL1 variants were genotyped, and glomerular and tubulointerstitial transcriptomes from protocol renal biopsy cores were analyzed for differential and correlative gene expression. Analyses were performed under the recessive model (high-risk genotype defined by two risk alleles). APOL1 high-risk genotype was significantly associated with a 17 ml/min per 1.73 m(2) lower eGFR and a 69% reduction in the probability of complete remission at any time, independent of histologic diagnosis. Neither APOL1 risk group was enriched for Mendelian mutations. On renal biopsy, high-risk genotype was associated with increased fractional interstitial area, interstitial fibrosis, and tubular atrophy. Risk genotype was not associated with intrarenal APOL1 mRNA expression levels. Differential expression analysis demonstrated an increased steady-state level of five genes associated with the high-risk genotype (CXCL9, CXCL11, and UBD in glomerulus; SNOR14B and MUC13 in tubulointerstitium). APOL1 tubulointerstitial coexpression analysis showed coexpression of APOL1 mRNA levels with a group of intrarenal transcripts that together were associated with increased interstitial fibrosis and tubular atrophy. These data indicate the high-risk APOL1 genotype confers renal risk across histopathologic diagnoses.