Rationale and Design of a Phase 2, Double-blind, Placebo-Controlled, Randomized Trial Evaluating AMP Kinase-Activation by Metformin in Focal Segmental Glomerulosclerosis.

Introduction: Focal segmental glomerulosclerosis (FSGS), the most common primary glomerular disease leading to end-stage kidney disease (ESKD), is characterized by podocyte injury and depletion, whereas minimal change disease (MCD) has better outcomes despite podocyte injury. Identifying mechanisms capable of preventing podocytopenia during injury could transform FSGS to an "MCD-like" state. Preclinical data have reported conversion of an MCD-like injury to one with podocytopenia and FSGS by inhibition of AMP-kinase (AMPK) in podocytes. Conversely, in FSGS, AMPK-activation using metformin (MF) mitigated podocytopenia and azotemia. Observational studies also support beneficial effects of MF on proteinuria and chronic kidney disease (CKD) outcomes in diabetes. A randomized controlled trial (RCT) to test MF in podocyte injury with FSGS has not yet been conducted. Methods: We report the rationale and design of phase 2, double-blind, placebo-controlled RCT evaluating the efficacy and safety of MF as adjunctive therapy in FSGS. By randomizing 30 patients with biopsy-confirmed FSGS to MF or placebo (along with standard immunosuppression), we will study mechanistic biomarkers that correlate with podocyte injury or depletion and evaluate outcomes after 6 months. We specifically integrate novel urine, blood, and tissue markers as surrogates for FSGS progression along with unbiased profiling strategies. Results and Conclusion: Our phase 2 trial will provide insight into the potential efficacy and safety of MF as adjunctive therapy in FSGS-a crucial step to developing a larger phase 3 study. The mechanistic assays here will guide the design of other FSGS trials and contribute to understanding AMPK activation as a potential therapeutic target in FSGS. By repurposing an inexpensive agent, our results will have implications for FSGS treatment in resource-poor settings.

Urinary Plasminogen as a Marker of Disease Progression in Human Glomerular Disease.

RATIONALE & OBJECTIVE: Glomerular disorders have a highly variable clinical course, and biomarkers that reflect the molecular mechanisms underlying their progression are needed. Based on our previous work identifying plasminogen as a direct cause of podocyte injury, we designed this study to test the association between urine plasmin(ogen) (ie, plasmin and its precursor plasminogen) and end-stage kidney disease (ESKD). STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 1,010 patients enrolled in the CureGN Cohort with biopsy-proven glomerular disease (focal segmental glomerulosclerosis, membranous nephropathy, and immunoglobulin A nephropathy). PREDICTORS: The main predictor was urine plasmin(ogen) at baseline. Levels were measured by an electrochemiluminescent immunoassay developed de novo. Traditional clinical and analytical characteristics were used for adjustment. The ratio of urine plasmin(ogen)/expected plasmin(ogen) was evaluated as a predictor in a separate model. OUTCOME: Progression to ESKD. ANALYTICAL APPROACH: Cox regression was used to examine the association between urinary plasmin(ogen) and time to ESKD. Urinary markers were log2 transformed to approximate normal distribution and normalized to urinary creatinine (Log2uPlasminogen/cr, Log2 urinary protein/cr [UPCR]). Expected plasmin(ogen) was calculated by multiple linear regression. RESULTS: Adjusted Log2uPlasminogen/cr was significantly associated with ESKD (HR per doubling Log2 uPlasminogen/cr 1.31 [95% CI, 1.22-1.40], P<0.001). Comparison of the predictive performance of the models including Log2 uPlasminogen/cr, Log2 UPCR, or both markers showed the plasmin(ogen) model superiority. The ratio of measured/expected urine plasmin(ogen) was independently associated with ESKD: HR, 0.41 (95% CI, 0.22-0.77) if ratio<0.8 and HR 2.42 (95% CI, 1.54-3.78) if ratio>1.1 (compared with ratio between 0.8 and 1.1). LIMITATIONS: Single plasmin(ogen) determination does not allow for the study of changes over time. The use of a cohort of mostly white patients and the restriction to patients with 3 glomerular disorders limits the external validity of our analysis. CONCLUSIONS: Urinary plasmin(ogen) and the ratio of measured/expected plasmin(ogen) are independently associated with ESKD in a cohort of patients with glomerular disease. Taken together with our previous experimental findings, urinary plasmin(ogen) could be a useful biomarker in prognostic decision making and a target for the development of novel therapies in patients with proteinuria and glomerular disease. PLAIN-LANGUAGE SUMMARY: Glomerular diseases are an important cause of morbidity and mortality in patients of all ages. Knowing the individual risk of progression to dialysis or transplantation would help to plan the follow-up and treatment of these patients. Our work studies the usefulness of urinary plasminogen as a marker of progression in this context, since previous studies indicate that plasminogen may be involved in the mechanisms responsible for the progression of these disorders. Our work in a sample of 1,010 patients with glomerular disease demonstrates that urinary plasminogen (as well as the ratio of measured to expected plasminogen) is associated with the risk of progression to end-stage kidney disease. Urine plasminogen exhibited good performance and, if further validated, could enable risk stratification for timely interventions in patients with proteinuria and glomerular disease.

Analysis of the human kidney transcriptome and plasma proteome identifies markers of proximal tubule maladaptation to injury.

Acute kidney injury (AKI) is a major risk factor for long-term adverse outcomes, including chronic kidney disease. In mouse models of AKI, maladaptive repair of the injured proximal tubule (PT) prevents complete tissue recovery. However, evidence for PT maladaptation and its etiological relationship with complications of AKI is lacking in humans. We performed single-nucleus RNA sequencing of 120,985 nuclei in kidneys from 17 participants with AKI and seven healthy controls from the Kidney Precision Medicine Project. Maladaptive PT cells, which exhibited transcriptomic features of dedifferentiation and enrichment in pro-inflammatory and profibrotic pathways, were present in participants with AKI of diverse etiologies. To develop plasma markers of PT maladaptation, we analyzed the plasma proteome in two independent cohorts of patients undergoing cardiac surgery and a cohort of marathon runners, linked it to the transcriptomic signatures associated with maladaptive PT, and identified nine proteins whose genes were specifically up- or down-regulated by maladaptive PT. After cardiac surgery, both cohorts of patients had increased transforming growth factor-ß2 (TGFB2), collagen type XXIII-α1 (COL23A1), and X-linked neuroligin 4 (NLGN4X) and had decreased plasminogen (PLG), ectonucleotide pyrophosphatase/phosphodiesterase 6 (ENPP6), and protein C (PROC). Similar changes were observed in marathon runners with exercise-associated kidney injury. Postoperative changes in these markers were associated with AKI progression in adults after cardiac surgery and post-AKI kidney atrophy in mouse models of ischemia-reperfusion injury and toxic injury. Our results demonstrate the feasibility of a multiomics approach to discovering noninvasive markers and associating PT maladaptation with adverse clinical outcomes.

APOBEC-1 deletion enhances cisplatin-induced acute kidney injury.

Cisplatin (CP) induces acute kidney injury (AKI) whereby proximal tubules undergo regulated necrosis. Repair is almost complete after a single dose. We now demonstrate a role for Apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (Apobec-1) that is prominently expressed at the interface between acute and chronic kidney injury (CKD), in the recovery from AKI. Apobec-1 knockout (KO) mice exhibited greater mortality than in wild type (WT) and more severe AKI in both CP- and unilateral ischemia reperfusion (IR) with nephrectomy. Specifically, plasma creatinine (pCr) 2.6 ± 0.70 mg/dL for KO, n = 10 and 0.16 ± 0.02 for WT, n = 6, p < 0.0001 in CP model and 1.34 ± 0.22 mg/dL vs 0.75 ± 0.06, n = 5, p < 0.05 in IR model. The kidneys of Apobec-1 KO mice showed increased necrosis, increased expression of KIM-1, NGAL, RIPK1, ASCL4 and increased lipid accumulation compared to WT kidneys (p < 0.01). Neutrophils and activated T cells were both increased, while macrophages were reduced in kidneys of Apobec-1 KO animals. Overexpression of Apobec-1 in mouse proximal tubule cells protected against CP-induced cytotoxicity. These findings suggest that Apobec-1 mediates critical pro-survival responses to renal injury and increasing Apobec-1 expression could be an effective strategy to mitigate AKI.

Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis.

BackgroundAcute tubulointerstitial nephritis (AIN) is one of the few causes of acute kidney injury with diagnosis-specific treatment options. However, due to the need to obtain a kidney biopsy for histological confirmation, AIN diagnosis can be delayed, missed, or incorrectly assumed. Here, we identify and validate urinary CXCL9, an IFN-γ-induced chemokine involved in lymphocyte chemotaxis, as a diagnostic biomarker for AIN.MethodsIn a prospectively enrolled cohort with pathologist-adjudicated histological diagnoses, termed the discovery cohort, we tested the association of 180 immune proteins measured by an aptamer-based assay with AIN and validated the top protein, CXCL9, using sandwich immunoassay. We externally validated these findings in 2 cohorts with biopsy-confirmed diagnoses, termed the validation cohorts, and examined mRNA expression differences in kidney tissue from patients with AIN and individuals in the control group.ResultsIn aptamer-based assay, urinary CXCL9 was 7.6-fold higher in patients with AIN than in individuals in the control group (P = 1.23 × 10-5). Urinary CXCL9 measured by sandwich immunoassay was associated with AIN in the discovery cohort (n = 204; 15% AIN) independently of currently available clinical tests for AIN (adjusted odds ratio for highest versus lowest quartile: 6.0 [1.8-20]). Similar findings were noted in external validation cohorts, where CXCL9 had an AUC of 0.94 (0.86-1.00) for AIN diagnosis. CXCL9 mRNA expression was 3.9-fold higher in kidney tissue from patients with AIN (n = 19) compared with individuals in the control group (n = 52; P = 5.8 × 10-6).ConclusionWe identified CXCL9 as a diagnostic biomarker for AIN using aptamer-based urine proteomics, confirmed this association using sandwich immunoassays in discovery and external validation cohorts, and observed higher expression of this protein in kidney biopsies from patients with AIN.FundingThis study was supported by National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) awards K23DK117065 (DGM), K08DK113281 (KM), R01DK128087 (DGM), R01DK126815 (DGM and LGC), R01DK126477 (KNC), UH3DK114866 (CRP, DGM, and FPW), R01DK130839 (MES), and P30DK079310 (the Yale O'Brien Center). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes.

BACKGROUND: AKI is a heterogeneous syndrome. Current subphenotyping approaches have only used limited laboratory data to understand a much more complex condition. METHODS: We focused on patients with AKI from the Assessment, Serial Evaluation, and Subsequent Sequelae in AKI (ASSESS-AKI). We used hierarchical clustering with Ward linkage on biomarkers of inflammation, injury, and repair/health. We then evaluated clinical differences between subphenotypes and examined their associations with cardiorenal events and death using Cox proportional hazard models. RESULTS: We included 748 patients with AKI: 543 (73%) of them had AKI stage 1, 112 (15%) had AKI stage 2, and 93 (12%) had AKI stage 3. The mean age (±SD) was 64 (13) years; 508 (68%) were men; and the median follow-up was 4.7 (Q1: 2.9, Q3: 5.7) years. Patients with AKI subphenotype 1 ( N =181) had the highest kidney injury molecule (KIM-1) and troponin T levels. Subphenotype 2 ( N =250) had the highest levels of uromodulin. AKI subphenotype 3 ( N =159) comprised patients with markedly high pro-brain natriuretic peptide and plasma tumor necrosis factor receptor-1 and -2 and low concentrations of KIM-1 and neutrophil gelatinase-associated lipocalin. Finally, patients with subphenotype 4 ( N =158) predominantly had sepsis-AKI and the highest levels of vascular/kidney inflammation (YKL-40, MCP-1) and injury (neutrophil gelatinase-associated lipocalin, KIM-1). AKI subphenotypes 3 and 4 were independently associated with a higher risk of death compared with subphenotype 2 and had adjusted hazard ratios of 2.9 (95% confidence interval, 1.8 to 4.6) and 1.6 (95% confidence interval, 1.01 to 2.6, P = 0.04), respectively. Subphenotype 3 was also independently associated with a three-fold risk of CKD and cardiovascular events. CONCLUSIONS: We discovered four AKI subphenotypes with differing clinical features and biomarker profiles that are associated with longitudinal clinical outcomes.

Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

Pre-operative kidney biomarkers and risks for death, cardiovascular and chronic kidney disease events after cardiac surgery: the TRIBE-AKI study.

BACKGROUND: Soluble tumor necrosis factor receptor (sTNFR)1, sTNFR2, and plasma kidney injury molecule-1 (KIM-1) are associated with kidney events in patients with and without diabetes. However, their associations with clinical outcomes when obtained pre-operatively have not been explored. METHODS: The TRIBE-AKI cohort study is a prospective, multicenter, cohort study of high-risk adults undergoing cardiac surgery. We assessed the associations between pre-operative concentrations of plasma sTNFR1, sTNFR2, and KIM-1 and post-operative long-term outcomes including mortality, cardiovascular events, and chronic kidney disease (CKD) incidence or progression after discharge. RESULTS: Among 1378 participants included in the analysis with a median follow-up period of 6.7 (IQR 4.0-7.9) years, 434 (31%) patients died, 256 (19%) experienced cardiovascular events and out of 837 with available long-term kidney function data, 30% developed CKD. After adjustment for clinical covariates, each log increase in biomarker concentration was independently associated with mortality with 95% CI adjusted hazard ratios (aHRs) of 3.0 (2.3-4.0), 2.3 (1.8-2.9), and 2.0 (1.6-2.4) for sTNFR1, sTNFR2, and KIM-1, respectively. For cardiovascular events, the 95% CI aHRs were 2.1 (1.5-3.1), 1.9 (1.4-2.6) and 1.6 (1.2-2.1) for sTNFR1, sTNFR2 and KIM-1, respectively. For CKD events, the aHRs were 2.2 (1.5-3.1) for sTNFR1, 1.9 (1.3-2.7) for sTNFR2, and 1.7 (1.3-2.3) for KIM-1. Despite the associations, each of the biomarkers alone or in combination failed to result in robust discrimination on an absolute basis or compared to a clinical model. CONCLUSION: sTNFR1, sTNFR2, and KIM-1 were independently associated with longitudinal outcomes after discharge from a cardiac surgery hospitalization including death, cardiovascular, and CKD events when obtained pre-operatively in high-risk individuals. Pre-operative plasma biomarkers could serve to assist during the evaluation of patients in whom cardiac surgery is planned.

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.

Urine Uromodulin as a Biomarker of Kidney Tubulointerstitial Fibrosis.

BACKGROUND AND OBJECTIVES: Uromodulin, produced exclusively in the kidney's thick ascending limb, is a biomarker of kidney tubular health. However, the relationship between urine uromodulin and histologic changes in the kidney tubulointerstitium has not been characterized. In this study, we test the association of urine uromodulin with kidney histologic findings in humans and mice. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We investigated the independent association of urine uromodulin measured at the time of kidney biopsy with histologic features in 364 participants at two academic medical centers from 2015 to 2018 using multivariable linear regression models. This relationship was further examined by comparison of uromodulin staining in murine models of kidney fibrosis and repair. RESULTS: We found urine uromodulin to be correlated with serum creatinine (rho=-0.43; P<0.001), bicarbonate (0.20; P<0.001), and hemoglobin (0.11; P=0.03) at the time of biopsy but not with urine albumin (-0.07; P=0.34). Multivariable models controlling for prebiopsy GFR, serum creatinine at biopsy, and urine albumin showed higher uromodulin to be associated with lower severity of interstitial fibrosis/tubular atrophy and glomerulosclerosis (interstitial fibrosis/tubular atrophy: -3.5% [95% confidence intervals, -5.7% to -1.2%] and glomerulosclerosis: -3.3% [95% confidence intervals, -5.9% to -0.6%] per two-fold difference in uromodulin). However, when both interstitial fibrosis/tubular atrophy and glomerulosclerosis were included in multivariable analysis, only interstitial fibrosis/tubular atrophy was independently associated with uromodulin (interstitial fibrosis/tubular atrophy: -2.5% [95% confidence intervals, -4.6% to -0.4%] and glomerulosclerosis: -0.9% [95% confidence intervals, -3.4% to 1.5%] per two-fold difference in uromodulin). In mouse kidneys, uromodulin staining was found to be lower in the fibrotic model than in normal or repaired models. CONCLUSIONS: Higher urine uromodulin is independently associated with lower tubulointerstitial fibrosis in both human kidney biopsies and a mouse model of fibrosis. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_08_10_CJN04360422.mp3.

Immune checkpoint inhibitors and kidney disease.

PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICIs) have changed the landscape of cancer treatment. However, use of ICIs can be limited by inflammatory toxicities referred to as immune-related adverse events (irAEs). ICI-associated acute kidney injury (ICI-associated AKI) affects 3-5% of ICI users. RECENT FINDINGS: With the rapidly growing indication of ICI, knowledge of ICI-associated kidney toxicity has also expanded from case series to large multicentre cohort studies. In this review, we discuss the clinical features, risk factors, clinicopathological correlations and prognosis of ICI-associated AKI from the most recent rigorously conducted retrospective cohort studies. We also discuss recent advances in diagnostic biomarker investigation, treatment and the unique challenge faced in the kidney transplant population. SUMMARY: With more comprehensive understanding of the clinical features and risk factors, ICI-associated AKI is commonly diagnosed clinically, especially given the inherent challenges performing a kidney biopsy in the cancer population; however, this highlights the urgent need for improved noninvasive diagnostic biomarkers to aid diagnosis and prognosis. Prospective studies are needed to better define the optimal treatment of ICI-associated AKI and to minimize the risk of graft loss in patients with kidney transplant who require ICIs.

Urine testing to differentiate glomerular from tubulointerstitial diseases on kidney biopsy.

Background: Differentiating between glomerular and tubulointerstitial diseases can guide selection of appropriate patients for kidney biopsy. The aim of this study is to identify urine tests that can differentiate between these histological diagnoses. Methods: In this sub-study of a prospectively enrolled cohort of participants with urine samples concurrent with their kidney biopsy, we tested the association of 24 features on urinalysis, urine sediment microscopy, and biomarkers of glomerular and tubular injury and inflammation with histological diagnosis of glomerular or tubulointerstitial disease. We selected a combination of features associated with glomerular disease using stepwise forward and backward regression, and LASSO algorithm after dividing the cohort into training (70%) and test (30%) sets. Results: Of 359 participants, 121 had glomerular, 89 had tubulointerstitial diseases, and 149 were classified as mixed. Compared to patients with tubulointerstitial diseases, those with glomerular diseases had more dipstick hematuria (3+ vs. 1+, P < 0.001) and urine albumin (1.25 vs. 0.09 mg/mg, P < 0.001). Patients with glomerular diseases had higher levels of tubular health biomarkers (Uromodulin, 1.22 vs. 0.92, P = 0.03). In a multivariable model, higher urine albumin, dipstick blood, and urine uromodulin were independently associated with higher odds of glomerular diseases (test set AUC, 0.81 (0.69, 0.93)). Conclusion: Urine tests, including urine albumin, dipstick blood, and urine uromodulin, were associated with the histological diagnosis of glomerular disease. These findings can help clinicians differentiate between glomerular and tubulointerstitial diseases and guide clinical decisions regarding a kidney biopsy.

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.

Mortality after acute kidney injury and acute interstitial nephritis in patients prescribed immune checkpoint inhibitor therapy.

BACKGROUND: In patients receiving immune checkpoint inhibitor (ICI) therapy, acute kidney injury (AKI) is common, and can occur either from kidney injury unrelated to ICI use or from immune activation resulting in acute interstitial nephritis (AIN). In this study, we test the hypothesis that occurrence of AIN indicates a favorable treatment response to ICI therapy and therefore among patients who develop AKI while on ICI therapy, those with AIN will demonstrate greater survival compared with others with AKI. METHODS: In this observational cohort study, we included participants initiated on ICI therapy between 2013 and 2019. We tested the independent association of AKI and estimated AIN (eAIN) with mortality up to 1 year after therapy initiation as compared with those without AKI using time-varying Cox proportional hazard models controlling for demographics, comorbidities, cancer type, stage, and therapy, and baseline laboratory values. We defined eAIN as those with a predicted probability of AIN >90th percentile derived from a recently validated diagnostic model. RESULTS: Of 2207 patients initiated on ICIs, 617 (28%) died at 1 year and 549 (25%) developed AKI. AKI was independently associated with higher mortality (adjusted HR, 2.28 (95% CI 1.90 to 2.72)). Those AKI patients with eAIN had more severe AKI as reflected by a higher peak serum creatinine (3.3 (IQR 2.1-6.1) vs 1.4 (1.2-1.9) mg/dL, p<0.001) but exhibited lower mortality than those without eAIN in univariable analysis (HR 0.43 (95% CI 0.21 to 0.89)) and after adjusting for demographics, comorbidities, and cancer type and severity (adjusted HR 0.44 (95% CI 0.21 to 0.93)). CONCLUSION: In patients treated with ICI, mortality was higher in those with AKI unrelated to ICI but lower in those where the underlying etiology was AIN. Future studies could evaluate the association of biopsy-proven or biomarker-proven AIN with mortality in those receiving ICI therapy.

Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data.

BACKGROUND: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. METHODS: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. RESULTS: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. CONCLUSIONS: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.

Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is common in patients with coronavirus disease 2019 (COVID-19) and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers and adverse kidney outcomes among patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. EXPOSURE: 19 urinary biomarkers of injury, inflammation, and repair. OUTCOME: Composite of KDIGO (Kidney Disease: Improving Global Outcomes) stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. ANALYTICAL APPROACH: Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. RESULTS: Out of 153 patients, 24 (15.7%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR, 1.34 [95% CI, 1.14-1.57]), monocyte chemoattractant protein (MCP-1) (HR, 1.42 [95% CI, 1.09-1.84]), and kidney injury molecule 1 (KIM-1) (HR, 2.03 [95% CI, 1.38-2.99]) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR, 0.61 [95% CI, 0.47-0.79]). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. LIMITATIONS: Small sample size with low number of composite outcome events. CONCLUSIONS: Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery.

Urinary EGF and MCP-1 and risk of CKD after cardiac surgery.

BACKGROUNDAssessment of chronic kidney disease (CKD) risk after acute kidney injury (AKI) is based on limited markers primarily reflecting glomerular function. We evaluated markers of cell integrity (EGF) and inflammation (monocyte chemoattractant protein-1, MCP-1) for predicting long-term kidney outcomes after cardiac surgery.METHODSWe measured EGF and MCP-1 in postoperative urine samples from 865 adults who underwent cardiac surgery at 2 sites in Canada and the United States and assessed EGF and MCP-1's associations with the composite outcome of CKD incidence or progression. We used single-cell RNA-Seq (scRNA-Seq) of AKI patient biopsies to perform transcriptomic analysis of programs corregulated with the associated genes.RESULTSOver a median (IQR) follow-up of 5.8 (4.2-7.1) years, 266 (30.8%) patients developed the composite CKD outcome. Postoperatively, higher levels of urinary EGF were protective and higher levels of MCP-1 were associated with the composite CKD outcome (adjusted HR 0.83, 95% CI 0.73-0.95 and 1.10, 95% CI 1.00-1.21, respectively). Intrarenal scRNA-Seq transcriptomes in patients with AKI-defined cell populations revealed concordant changes in EGF and MCP-1 levels and underlying molecular processes associated with loss of EGF expression and gain of CCL2 (encoding MCP-1) expression.CONCLUSIONUrinary EGF and MCP-1 were each independently associated with CKD after cardiac surgery. These markers may serve as noninvasive indicators of tubular damage, supported by tissue transcriptomes, and provide an opportunity for novel interventions in cardiac surgery.TRIAL REGISTRATIONClinicalTrials.gov NCT00774137.FUNDINGThe NIH funded the TRIBE-AKI Consortium and Kidney Precision Medicine Project. Yale O'Brien Kidney Center, American Heart Association, Patterson Trust Fund, Dr. Adam Linton Chair in Kidney Health Analytics, Canadian Institutes of Health Research, ICES, Ontario Ministry of Health and Long-Term Care, Academic Medical Organization of Southwestern Ontario, Schulich School of Medicine & Dentistry, Western University, Lawson Health Research Institute, Chan Zuckerberg Initiative Human Cell Atlas Kidney Seed Network.

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.