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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.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.We found urine uromodulin to be correlated with serum creatinine (rho=-0.43;Higher urine uromodulin is independently associated with lower tubulointerstitial fibrosis in both human kidney biopsies and a mouse model of fibrosis.This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_08_10_CJN04360422.mp3.

Kidney fibrosis constitutes the shared final pathway of nearly all chronic nephropathies, but biomarkers for the non-invasive assessment of kidney fibrosis are currently not available. To address this, we characterize five candidate biomarkers of kidney fibrosis: Cadherin-11 (CDH11), Sparc-related modular calcium binding protein-2 (SMOC2), Pigment epithelium-derived factor (PEDF), Matrix-Gla protein, and Thrombospondin-2. Gene expression profiles in single-cell and single-nucleus RNA-sequencing (sc/snRNA-seq) datasets from rodent models of fibrosis and human chronic kidney disease (CKD) were explored, and Luminex-based assays for each biomarker were developed. Plasma and urine biomarker levels were measured using independent prospective cohorts of CKD: the Boston Kidney Biopsy Cohort, a cohort of individuals with biopsy-confirmed semiquantitative assessment of kidney fibrosis, and the Seattle Kidney Study, a cohort of patients with common forms of CKD. Ordinal logistic regression and Cox proportional hazards regression models were used to test associations of biomarkers with interstitial fibrosis and tubular atrophy and progression to end-stage kidney disease and death, respectively. Sc/snRNA-seq data confirmed cell-specific expression of biomarker genes in fibroblasts. After multivariable adjustment, higher levels of plasma CDH11, SMOC2, and PEDF and urinary CDH11 and PEDF were significantly associated with increasing severity of interstitial fibrosis and tubular atrophy in the Boston Kidney Biopsy Cohort. In both cohorts, higher levels of plasma and urinary SMOC2 and urinary CDH11 were independently associated with progression to end-stage kidney disease. Higher levels of urinary PEDF associated with end-stage kidney disease in the Seattle Kidney Study, with a similar signal in the Boston Kidney Biopsy Cohort, although the latter narrowly missed statistical significance. Thus, we identified CDH11, SMOC2, and PEDF as promising non-invasive biomarkers of kidney fibrosis.

Patients undergoing cardiac surgery are placed under intense physiologic stress. Blood and urine biomarkers measured peri-operatively may help identify patients at higher risk for adverse long-term kidney outcomes.We sought to determine independent associations of various biomarkers with development or progression of chronic kidney disease (CKD) following cardiac surgery. In this sub-study of the prospective cohort –TRIBE-AKI Study, we evaluated 613 adult patients undergoing cardiac surgery in Canada in our primary analysis and tested the association of 40 blood and urinary biomarkers with the primary composite outcome of CKD incidence or progression. In those with baseline estimated glomerular filtration rate (eGFR) over 60 mL/min/1.73m2, we defined CKD incidence as a 25% reduction in eGFR and an eGFR under 60. In those with baseline eGFR under 60 mL/min/1.73m2, we defined CKD progression as a 50% reduction in eGFR or eGFR under 15. Results were evaluated in a replication cohort of 310 patients from one study site in the United States. Over a median follow-up of 5.6 years, 172 patients developed the primary outcome. Each log increase in basic fibroblast growth factor (adjusted hazard ratio 1.52 [95% confidence interval 1.19, 1.93]), Kidney Injury Molecule-1 (1.51 [0.98, 2.32]), N-terminal pro–B-type natriuretic peptide (1.19 [1.01, 1.41]), and tumor necrosis factor receptor 1 (1.75 [1.18, 2.59]) were associated with outcome after adjustment for demographic factors, serum creatinine, and albuminuria. Similar results were noted in the replication cohort. Although there was no interaction by acute kidney injury in continuous analysis, mortality was higher in the no acute kidney injury group by biomarker tertile. Thus, elevated post-operative levels of blood biomarkers following cardiac surgery were independently associated with the development of CKD. These biomarkers can provide additional value in evaluating CKD incidence and progression after cardiac surgery.

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.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.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.

Background We previously demonstrated that urine interleukin (IL)-9 and tumor necrosis factor (TNF)-α can distinguish acute interstitial nephritis (AIN) from other causes of acute kidney injury. Here we evaluated the role of these biomarkers to prognosticate kidney function in patients with AIN. Methods In a cohort of participants with biopsy-proven, adjudicated AIN, we tested the association of histological features and urine biomarkers (IL-9 and TNF-α) with estimated glomerular filtration rate measured 6 months after diagnosis (6 m-eGFR) controlling for eGFR before AIN and albuminuria. We also evaluated subgroups in whom corticosteroid use was associated with 6 m-eGFR. Results In the 51 (93%) of the 55 participants with complete data, median (interquartile range) eGFR before and 6 m after AIN were 41 (27–69) and 28 (13–47) mL/min/1.73 m2, respectively. Patients with higher severity of interstitial fibrosis had lower 6 m-eGFR, whereas those with higher tubulointerstitial infiltrate had higher 6 m-eGFR. IL-9 levels were associated with lower 6 m-eGFR only in the subset of patients who did not receive corticosteroids [6m-eGFR per doubling of IL-9, −6.0 (−9.4 to −2.6) mL/min/1.73 m2]. Corticosteroid use was associated with higher 6 m-eGFR [20.9 (0.2, 41.6) mL/min/1.73 m2] only in those with urine IL-9 above the median (>0.66 ng/g) but not in others. Conclusions Urine IL-9 was associated with lower 6 m-eGFR only in participants not treated with corticosteroids. Corticosteroid use was associated with higher 6 m-eGFR in those with high urine IL-9. These findings provide a framework for IL-9-guided clinical trials to test efficacy of immunosuppressive therapy in patients with AIN.

Background Timely prediction of AKI in children can allow for targeted interventions, but the wealth of data in the electronic health record poses unique modeling challenges. Methods We retrospectively reviewed the electronic medical records of all children younger than 18 years old who had at least two creatinine values measured during a hospital admission from January 2014 through January 2018. We divided the study population into derivation, and internal and external validation cohorts, and used five feature selection techniques to select 10 of 720 potentially predictive variables from the electronic health records. Model performance was assessed by the area under the receiver operating characteristic curve in the validation cohorts. The primary outcome was development of AKI (per the Kidney Disease Improving Global Outcomes creatinine definition) within a moving 48-hour window. Secondary outcomes included severe AKI (stage 2 or 3), inpatient mortality, and length of stay. Results Among 8473 encounters studied, AKI occurred in 516 (10.2%), 207 (9%), and 27 (2.5%) encounters in the derivation, and internal and external validation cohorts, respectively. The highest-performing model used a machine learning-based genetic algorithm, with an overall receiver operating characteristic curve in the internal validation cohort of 0.76 [95% confidence interval (CI), 0.72 to 0.79] for AKI, 0.79 (95% CI, 0.74 to 0.83) for severe AKI, and 0.81 (95% CI, 0.77 to 0.86) for neonatal AKI. To translate this prediction model into a clinical risk-stratification tool, we identified high- and low-risk threshold points. Conclusions Using various machine learning algorithms, we identified and validated a time-updated prediction model of ten readily available electronic health record variables to accurately predict imminent AKI in hospitalized children.

BackgroundIn 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.MethodsIn 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.ResultsOf 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, pConclusionIn 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.

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.Prospective cohort.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.We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge.The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated.Cox proportional hazard models.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.Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups.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.

Morphometric estimates of mean glomerular volume (MGV) have clinical implications, over and above histologic data. However, MGV estimation is time-consuming, could waste tissue sections and requires expertise limiting its utility in retrospective clinical studies.MethodsWe evaluated MGV using both plastic and paraffin-embedded tissue from control and FSGS mice (n=10 each) using the gold-standard Disector/Cavalieri technique (Vglom-Cav) and other reported techniques [2- or 3-profile technique, Weibel-Gomez method (W-G)]. Within Vglom-Cav we examined the precision of MGV estimation while using MGVs obtained from 5- or 10-individual glomeruli measurements vs the true mean (20 glomeruli).ResultsIn both FSGS and controls, we identified an acceptable precision of 10-glomerular sampling vs true MGV within Vglom-Cav technique [88 (79-94) % of MGV obtained were within 10% of the true MGV]. The 5-glomerular sampling was less precise [70 (56, 81) % of MGV obtained were within 10% of true MGV]. In plastic based techniques, 2- or 3-profile MGVs showed greater concordance with Vglom-Cav, than W-G MGV. The new 3-profile technique offered incremental benefit to the existing 2-profile method (improved Lin’s concordance in control and FSGS animals). We observed a consistent reduction of Vglom values within control animals (52+/-0.06%) in paraffin-embedded tissue (vs corresponding methods in plastic) demonstrating a clear shrinkage artefact due to tissue processing. FSGS glomeruli showed significantly less and more variable shrinkage artefact likely due to glomerular fibrosis.ConclusionWe report the precision of 5- or 10-glomerular sampling for MGV estimation using controls and FSGS animals. We demonstrate and quantify the shrinkage bias in MGV during tissue processing for paraffin-embedding that also differentiated control animals and FSGS. Our findings have implications for experimental studies using glomerular morphometry.

IntroductionAKI is a heterogeneous syndrome defined via serum creatinine and urine output criteria. However, these markers are insufficient to capture the biological complexity of AKI and not necessarily inform on future risk of kidney and clinical events.MethodsData from ASSESS-AKI was obtained and analyzed to uncover different clinical and biological signatures within AKI. We utilized a set of unsupervised machine learning algorithms incorporating a comprehensive panel of systemic and organ-specific biomarkers of inflammation, injury, and repair/health integrated into electronic data. Furthermore, the association of these novel biomarker-enriched subphenotypes with kidney and cardiovascular events and death was determined. Clinical and biomarker concentration differences among subphenotypes were evaluated via classic statistics. Kaplan-Meier and cumulative incidence curves were obtained to evaluate longitudinal outcomes.ResultsAmong 1538 patients from ASSESS-AKI, we included 748 AKI patients in the analysis. The median follow-up time was 4.8 years. We discovered 4 subphenotypes via unsupervised learning. Patients with AKI subphenotype 1 (‘injury’ cluster) were older (mean age ± SD): 71.2 ± 9.4 (pConclusionWe discovered four clinically meaningful AKI subphenotypes with statistical differences in biomarker composites that associate with longitudinal risks of adverse clinical events. Our approach is a novel look at the potential mechanisms underlying AKI and the putative role of biomarkers investigation.

BackgroundThe role of plasma soluble tumor necrosis factor receptor (sTNFR)1 and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown.MethodsWe measured sTNFR1 and sTNFR2 obtained 3 months post-discharge using samples from Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) and AKI Risk in Derby (ARID) that enrolled patients with and without AKI. The associations between biomarkers with longitudinal kidney disease incidence and progression, heart failure and death were evaluated. Analyses were adjusted for demographics and key covariates at the 3-month visit.ResultsAmong 1474 participants with plasma biomarker measurements, 19% developed kidney disease progression, 14% had later heart failure, and 21% died over a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs per doubling in concentration were 2.9 (2.2-3.9) for sTNFR1 and 1.9 (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 adjusted HRs per doubling in concentration were 1.9 (1.4-2.5) for sTNFR1 and 1.5 (1.2-2.0) for sTNFR2. For mortality, the adjusted HRs were 3.3 (2.5-4.3) for sTNFR1 and 2.5 (2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar for the magnitude of association between biomarkers and outcomes.ConclusionPlasma sTNFR1 and sTNFR2 measured 3 months after 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.Significance StatementSoluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 associate with kidney outcomes in patients with chronic kidney disease with and without diabetes mellitus. However, their role in the post-hospitalization stage is unknown. High sTNFR1 and sTNFR2 obtained 3 months after discharge associate with kidney events, heart failure hospitalizations, and death among patients who did and did not have acute kidney injury (AKI). Furthermore, sTNFRs provide discriminative value at the time of predicting kidney events. These findings were demonstrated in two large independent prospective cohorts. sTNFR1 and sTNFR2 may detect patients at risk of future adverse events even when patients do not meet the clinical criteria for AKI or exhibit biochemical abnormalities.

IntroductionBiomarkers of acute kidney injury (AKI) are often indexed to urine creatinine (UCr) or urine osmolarity (UOsm) to control for urine concentration. We evaluated how these approaches affect the biomarker-outcome association in patients with AKI.MethodsThe Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury Study was a cohort of hospitalized patients with and without AKI between 2009 and 2015. Using Cox proportional hazards regression, we assessed the associations and predictions (C-statistics) of urine biomarkers with a composite outcome of incident chronic kidney disease (CKD) and CKD progression. We used 4 approaches to account for urine concentration: indexing and adjusting for UCr and UOsm.ResultsAmong 1538 participants, 769 (50%) had AKI and 300 (19.5%) developed composite CKD outcome at median follow-up of 4.7 years. UCr and UOsm during hospitalization were inversely associated with the composite CKD outcome. The associations and predictions with CKD were significantly strengthened after indexing or adjusting for UCr or UOsm for urine kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), and monocyte chemoattractant protein-1 (MCP-1) in patients with AKI. There was no significant improvement with indexing or adjusting UCr or UOsm for albumin, neutrophil gelatinase-associated lipocalin (NGAL), and chitinase 3-like 1 (YKL-40). Uromodulin's (UMOD) inverse association with the outcome was significantly blunted after indexing but not adjusting for UCr or UOsm.ConclusionUCr and UOsm during hospitalization are inversely associated with development and progression of CKD. Indexing or adjusting for UCr or UOsm strengthened associations and improved predictions for CKD for only some biomarkers. Incorporating urinary concentration should be individualized for each biomarker in research and clinical applications.

Introduction Animal models of renal ischemia-reperfusion injury (IRI) demonstrate that interferon (IFN)-γ producing T-helper (Th)-1 cells worsen acute kidney injury (AKI), whereas interleukin (IL)-4– and IL-13–producing Th2 cells lead to repair. We tested the association of these cytokines with AKI and mortality in patients who underwent cardiac surgery. Methods In 1444 participants of a multicenter, prospective, observational cohort, we measured 10 plasma biomarkers before and after cardiac surgery (IFN-γ, IL-4, IL-13, tumor necrosis factor [TNF]-α, IL-1β, IL-2, IL-6, IL-8, IL-10, and IL-12p70) and combined these biomarkers using principal component analysis (PCA). We also tested independent associations of Th1 (IFN-γ) and Th2 (IL-4 and IL-13) biomarkers with clinical outcomes of postoperative AKI and 1-year mortality. Results AKI occurred in 492 participants (34%), and 1-year mortality occurred in 81 participants (6%). Within 6 hours after surgery, IFN-γ, IL-4, and IL-13 increased 2.1-, 6.0-, and 4.6-fold, respectively, from their preoperative levels. Patients with higher levels of IFN-γ had higher odds of AKI (adjusted odds ratio per log change, 1.35 [1.13, 1.6]) and mortality (1.51 [1.17, 1.94]). Patients with higher levels of IL-4 and IL-13 also had higher odds of AKI (1.26 [1.09, 1.46] and 1.4 [1.16, 1.69], respectively) and mortality (1.46 [1.18, 1.82] and 1.71 [1.27, 2.31], respectively). Adding biomarkers to the clinical variables through use of PCA improved the area under the curve by 0.01 for AKI and 0.04 for mortality, resulting in final areas under the curve of 0.85 (0.83–0.87) and 0.76 (0.70–0.81), respectively. Conclusion Both Th1 and Th2 cytokines increased immediately after cardiac surgery and were associated with AKI and 1-year mortality. Our findings indicate activation of both Th1 and Th2 pathways after cardiac surgery rather than predominance of either pathway., Graphical abstract

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.

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.

BACKGROUND Assessment 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. METHODS We 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. RESULTS Over 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. CONCLUSION Urinary 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 REGISTRATION ClinicalTrials.gov NCT00774137. FUNDING The 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 objective While COVID-19 infection has been associated with acute kidney injury (AKI), it is unclear whether this association is independent of traditional risk factors such as hypotension, nephrotoxin exposure, and inflammation. We tested the independent association of COVID-19 with AKI. Study Design Multicenter, observational, cohort study. Setting and participants Patients admitted to one of six hospitals within the Yale-New Haven Health System between 3/10/2020 and 8/31/2020 and tested for SARS-CoV-2 via nasopharyngeal PCR test. Exposure Positive test for SARS-CoV-2. Outcome AKI by Kidney Disease: Improving Global Outcomes criteria. Analytic approach Evaluated the association of COVID-19 with AKI after controlling for time-invariant factors at admission (e.g., demographics, comorbidities) and time-varying factors updated continuously during hospitalization (e.g., vital signs, medications, laboratory results, respiratory failure) using time-updated Cox proportional hazard models. Results Of the 22,122 patients hospitalized between, 2,600 tested positive and 19,522 tested negative for SARS-CoV-2. Compared to patients who tested negative, patients with COVID-19 had more AKI [30.6% vs. 18.2%, absolute risk difference 12.5 (95% CI, 10.6, 14.3)%] and dialysis-requiring AKI (8.5% vs. 3.6%) and lower recovery from AKI (58% vs. 69.8%]. Compared to patients who tested negative, patients with COVID-19 had higher inflammatory markers (C-reactive protein, ferritin), and greater use of vasopressors and diuretics. Compared to patients who tested negative, patients with COVID-19 had higher rate of AKI in univariable analysis (HR, 1.84 [1.73, 1.95]). In fully adjusted model controlling for demographics, comorbidities, vital signs, medications, and laboratory results, COVID-19 remained associated with a high rate of AKI (adjusted HR, 1.40 [1.29-1.53]). Limitations Possibility of residual confounding. Conclusions COVID-19 is associated with high rates of AKI not fully explained by adjustment for known risk factors. This suggests the presence of mechanisms of AKI not accounted for in this analysis, which may include a direct effect of COVID-19 on the kidney or other unmeasured mediators. Future studies should evaluate the possible unique pathways by which COVID-19 may cause AKI., One-third of patients hospitalized with COVID-19 experience acute kidney injury (AKI), which is higher than in other hospitalized patients. Patients with COVID-19 carry many well-known risk factors for AKI including severe lung disease requiring mechanical ventilation, shock and significant inflammation. Whether higher rates of AKI in COVID-19 are above what could be expected in patients with similar risk factors is unknown. We compared AKI rates between those with and without COVID-19 after controlling for risk factors for AKI both before and during hospitalization. We found that COVID-19 was independently associated with high rates of AKI. This indicates that some of the AKI risk in patients with COVID-19 is unexplained by traditional AKI risk factors and is unique to this disease.

Acute interstitial nephritis (AIN) is a well-known cause of acute kidney disease (AKD) and CKD and is associated with progression to ESKD (1⇓⇓⇓⇓–6). Accordingly, it represents an important problem for clinicians caring for these patients. AIN is primarily an immune-mediated kidney injury triggered by use of certain medications, in particular antibiotics, PPIs, NSAIDs, and immune checkpoint inhibitors (ICPIs), or by autoimmune diseases, such as Sjogren syndrome, sarcoidosis, IgG4-related tubulointerstitial disease, and TINU. In developed countries, medications are the most common cause of AIN (>70%), whereas the number approximates 50% in developing countries. Infectious agents are a less common cause of AIN, except in developing countries. The overall incidence of AIN in kidney biopsy registries is 2%–5%, whereas AIN is observed in approximately 15%–20% of patients with AKI or AKD who undergo kidney biopsy (1⇓–3). The actual number is likely higher as many patients with AKI/AKD do not undergo biopsy and are presumed to have acute tubular injury (ATI). Importantly, diagnosing AIN clinically is often quite challenging, making kidney biopsy a frequent requirement to definitively confirm the diagnosis and guide therapy (Figure 1). Furthermore, delayed or missed AIN diagnosis leads to ongoing inflammation with resulting interstitial fibrosis, tubular atrophy, and permanent kidney damage, which may be the explanation for CKD occurring in 40%–60% of patients after an episode of AIN (4,5). Approximately 2% of CKD is considered to be due to AIN, which is equivalent to 10 million prevalent worldwide cases. Furthermore, AIN is the primary cause of ESKD in 3%–4% of incident patients (6). It is one of the few potentially treatable causes of AKI if identified and treated early. In view of these data, three key challenges that limit the diagnosis and management of patients suspected of having …

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 kidney donor biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomics 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 ten 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.

SARS-CoV-2 infection has so far affected over 42 million people worldwide, causing over 1.1 million deaths. With the large majority of SARS-CoV-2 infected individuals being asymptomatic, major concerns have been raised about possible long-term consequences of the infection. We developed an antigen capture assay to detect SARS-CoV-2 spike protein in urine samples from COVID-19 patients whose diagnosis was confirmed by PCR from nasopharyngeal swabs (NP-PCR+). The study used a collection of 233 urine samples from 132 participants from Yale New Haven Hospital and the Children’s Hospital of Philadelphia obtained during the pandemic (106 NP-PCR+ and 26 NP-PCR-) as well as a collection of 20 urine samples from 20 individuals collected before the pandemic. Our analysis identified 23 out of 91 (25%) NP-PCR+ adult participants with SARS-CoV-2 spike S1 protein in urine (Ur-S+). Interestingly, although all NP-PCR+ children were Ur-S-, 1 NP-PCR-child was found to be positive for spike protein in urine. Of the 23 Ur-S+ adults, only 1 individual showed detectable viral RNA in urine. Our analysis further showed that 24% and 21% of NP-PCR+ adults have high levels of albumin and cystatin C in urine, respectively. Among individuals with albuminuria (>0.3 mg/mg of creatinine) statistical correlation could be found between albumin and spike protein in urine. Together, our data showe that 1 of 4 of SARS-CoV-2 infected individuals develop renal abnormalities such as albuminuria. Awareness about the long-term impact of these findings is warranted.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect any human host, but kidney transplant recipients (KTR) are considered more susceptible on the basis of previous experience with other viral infections. We evaluated rates of hospital complications between SARS-CoV-2–positive KTR and comparator groups. METHODS: We extracted data from the electronic health record on patients who were hospitalized with SARS-CoV-2, testing at six hospitals from March 4 through September 9, 2020. We compared outcomes between SARS-CoV-2–positive KTR and controls: SARS-CoV-2–positive non-KTR, SARS-CoV-2–negative KTR, and SARS-CoV-2–negative non-KTR. RESULTS: Of 31,540 inpatients, 3213 tested positive for SARS-CoV-2. There were 32 SARS-CoV-2–positive and 224 SARS-CoV-2–negative KTR. SARS-CoV-2–positive KTR had higher ferritin levels (1412; interquartile range, 748–1749 versus 553; interquartile range, 256–1035; P

Incomplete repair after acute kidney injury (AKI) is associated with progressive loss of tubular cell function and development of chronic kidney disease (CKD). Here, we compared mice subjected to either unilateral ischemia-reperfusion kidney injury with contralateral nephrectomy (IRI/CL-NX, in which tubule repair predominates) or unilateral IRI with contralateral kidney intact (U-IRI, in which fibrosis and atrophy predominates) to investigate the mechanism(s) underlying transition to CKD following AKI. The initial injury and early recruitment and activation of macrophages, dendritic cells (DCs), neutrophils, and T cells were similar through day 7 but markedly diverged afterwards between the two models. By day 14, kidneys subjected to U-IRI had greater numbers of macrophages with higher expression of Ccl2, Ccl7, Ccl8, Ccl12, and Cxcl16. These chemokines correlated with a second wave of Ccr1-positive neutrophils and Cxcr6-positive T cells, resulting in a proinflammatory milieu, accompanied by increased expression of tubular cell injury, oxidative stress and major histocompatibility complex genes. This second wave of immune dysfunction led to a distinct profile of tubule injury with morphologic kidney atrophy and a decreased proportion of differentiated tubule cells. Combined depletion of neutrophils and T cells beginning on day 5 after U-IRI was found to reduce tubular cell loss and the associated kidney atrophy. In kidney biopsy samples from patients with AKI, the number of interstitial T cells and neutrophils negatively correlated with 6-month recovery of GFR. Together, our findings demonstrate that macrophage persistence after AKI promotes a T cell- and neutrophil-mediated proinflammatory milieu that leads to progressive tubule damage.

Importance False negative SARS-CoV-2 tests can lead to spread of infection in the inpatient setting to other patients and healthcare workers. However, the population of patients with COVID who are admitted with false negative testing is unstudied. Objective To characterize and develop a model to predict true SARS-CoV-2 infection among patients who initially test negative for COVID by PCR. Design Retrospective cohort study. Setting Five hospitals within the Yale New Haven Health System between 3/10/2020 and 9/1/2020. Participants Adult patients who received diagnostic testing for SARS-CoV-2 virus within the first 96 hours of hospitalization. Exposure We developed a logistic regression model from readily available electronic health record data to predict SARS-CoV-2 positivity in patients who were positive for COVID and those who were negative and never retested. Main outcomes and measures This model was applied to patients testing negative for SARS-CoV-2 who were retested within the first 96 hours of hospitalization. We evaluated the ability of the model to discriminate between patients who would subsequently retest negative and those who would subsequently retest positive. Results We included 31,459 hospitalized adult patients; 2,666 of these patients tested positive for COVID and 3,511 initially tested negative for COVID and were retested. Of the patients who were retested, 61 (1.7%) had a subsequent positive COVID test. The model showed that higher age, vital sign abnormalities, and lower white blood cell count served as strong predictors for COVID positivity in these patients. The model had moderate performance to predict which patients would retest positive with a test set area under the receiver-operator characteristic (ROC) of 0.76 (95% CI 0.70–0.83). Using a cutpoint for our risk prediction model at the 90th percentile for probability, we were able to capture 35/61 (57%) of the patients who would retest positive. This cutpoint amounts to a number-needed-to-retest range between 15 and 77 patients. Conclusion and relevance We show that a pragmatic model can predict which patients should be retested for COVID. Further research is required to determine if this risk model can be applied prospectively in hospitalized patients to prevent the spread of SARS-CoV-2 infections.

Objective To determine whether electronic health record alerts for acute kidney injury would improve patient outcomes of mortality, dialysis, and progression of acute kidney injury. Design Double blinded, multicenter, parallel, randomized controlled trial. Setting Six hospitals (four teaching and two non-teaching) in the Yale New Haven Health System in Connecticut and Rhode Island, US, ranging from small community hospitals to large tertiary care centers. Participants 6030 adult inpatients with acute kidney injury, as defined by the Kidney Disease: Improving Global Outcomes (KDIGO) creatinine criteria. Interventions An electronic health record based “pop-up” alert for acute kidney injury with an associated acute kidney injury order set upon provider opening of the patient’s medical record. Main outcome measures A composite of progression of acute kidney injury, receipt of dialysis, or death within 14 days of randomization. Prespecified secondary outcomes included outcomes at each hospital and frequency of various care practices for acute kidney injury. Results 6030 patients were randomized over 22 months. The primary outcome occurred in 653 (21.3%) of 3059 patients with an alert and in 622 (20.9%) of 2971 patients receiving usual care (relative risk 1.02, 95% confidence interval 0.93 to 1.13, P=0.67). Analysis by each hospital showed worse outcomes in the two non-teaching hospitals (n=765, 13%), where alerts were associated with a higher risk of the primary outcome (relative risk 1.49, 95% confidence interval 1.12 to 1.98, P=0.006). More deaths occurred at these centers (15.6% in the alert group v 8.6% in the usual care group, P=0.003). Certain acute kidney injury care practices were increased in the alert group but did not appear to mediate these outcomes. Conclusions Alerts did not reduce the risk of our primary outcome among patients in hospital with acute kidney injury. The heterogeneity of effect across clinical centers should lead to a re-evaluation of existing alerting systems for acute kidney injury. Trial registration ClinicalTrials.gov NCT02753751 .

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is diagnosed based on changes in serum creatinine concentration, a late marker of this syndrome. Algorithms that predict elevated risk for AKI are of great interest, but no studies have incorporated such an algorithm into the electronic health record to assist with clinical care. We describe the experience of implementing such an algorithm. STUDY DESIGN: Prospective observational cohort study. SETTING & PARTICIPANTS: 2,856 hospitalized adults in a single urban tertiary-care hospital with an algorithm-predicted risk for AKI in the next 24 hours >15%. Alerts were also used to target a convenience sample of 100 patients for measurement of 16 urine and 6 blood biomarkers. EXPOSURE: Clinical characteristics at the time of pre-AKI alert. OUTCOME: AKI within 24 hours of pre-AKI alert (AKI(24)). ANALYTICAL APPROACH: Descriptive statistics and univariable associations. RESULTS: At enrollment, mean predicted probability of AKI(24) was 19.1%; 18.9% of patients went on to develop AKI(24). Outcomes were generally poor among this population, with 29% inpatient mortality among those who developed AKI(24) and 14% among those who did not (P < 0.001). Systolic blood pressure < 100 mm Hg (28% of patients with AKI(24) vs 18% without), heart rate > 100 beats/min (32% of patients with AKI(24) vs 24% without), and oxygen saturation < 92% (15% of patients with AKI(24) vs 6% without) were all more common among those who developed AKI(24). Of all biomarkers measured, only hyaline casts on urine microscopy (72% of patients with AKI(24) vs 25% without) and fractional excretion of urea nitrogen (20% [IQR, 12%−36%] among patients with AKI(24) vs 34% [IQR, 25%−44%] without) differed between those who did and did not develop AKI(24). LIMITATIONS: Single-center study, reliance on serum creatinine level for AKI diagnosis, small number of patients undergoing biomarker evaluation. CONCLUSIONS: A real-time AKI risk model was successfully integrated into the EHR.

Rationale and Objective Acute kidney injury (AKI) is common in patients with 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 with adverse kidney outcomes among patients hospitalized with COVID-19. Study Design Prospective cohort study. Setting and Participants Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. Exposures 19 urinary biomarkers of injury, inflammation, and repair. Outcomes Composite of KDIGO 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. Analytic 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. Two-fold 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. Conclusion 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., Graphical abstract

Background and objectives Patients are informed of the risk of kidney biopsy–related complications using data from nonhospitalized patients, which may underestimate the risk for hospitalized patients. We evaluated the rate and risk factors of kidney biopsy–related complications in hospitalized patients with acute kidney disease (AKD) to better estimate the risk in this population. Design, setting, participants, & measurements We used data from the Yale biopsy cohort to evaluate rates of kidney biopsy–related complications including adjudicated procedure-related bleeding requiring blood transfusions or angiographic interventions, medium- or large-sized hematomas, reimaging after biopsy including abdominal ultrasonography or computed tomography, and death in hospitalized patients with AKD (including AKI). We evaluated univariable and multivariable association of risk factors with transfusions. We compared rates of complications between hospitalized and nonhospitalized patients. Results Between 2015 and 2017, 159 hospitalized patients underwent a kidney biopsy for AKD evaluation, of which 80 (51%) had stage 1 AKI, 42 (27%) had stage 2 (or higher) AKI, and 27 (17%) had AKD (without AKI). Of these, 12 (8%; 95% confidence interval [95% CI], 5% to 15%) required a transfusion, three (2%; 95% CI, 1% to 5%) required an intervention, 11 (7%; 95% CI, 4% to 12%) had hematoma, and 31 (20%; 95% CI, 14% to 26%) required reimaging after biopsy. Of the four (3%; 95% CI, 1% to 6%) deaths during hospitalization, none were related to the biopsy. Female sex, lower platelet count, and higher BUN were associated with postbiopsy transfusions on univariable and multivariable analyses. Trainee as proceduralist and larger needle gauge were associated with transfusions in univariable, but not multivariable, analysis. Nonhospitalized patients had lower rates of transfusion than hospitalized patients, although the latter also had lower prebiopsy hemoglobin and greater surveillance after biopsy. Conclusions Hospitalized patients experience higher risk of postbiopsy complications than previously reported and several factors, such as lower platelet count, female sex, and higher BUN, are associated with this risk.

Introduction As part of the precision medicine initiative, the National Institutes of Health/National Institute of Diabetes and Digestive Kidney Diseases has proposed collecting human kidney tissue to discover novel therapeutic targets from patients with kidney diseases. Patient attitudes on participating in kidney biopsy−based research are largely unknown. Methods We evaluated attitudes toward donating kidney tissue to research among participants who had experienced a clinically indicated kidney biopsy, through a survey conducted 9 months (interquartile range, 5−13 months) after their biopsy. Results Of the 177 participants contacted, 117 (66%) participated in the survey. A total of 85 participants (73%) reported that they would allow additional needle passes during a clinically indicated biopsy to donate kidney tissue for research. As reasons for participating in such a study, the participants reported the desire to help others and to contribute to science, and the lack of additional burden while participating in such a study. In a multivariable logistic model, older and African American participants had lower odds of allowing an additional pass for research (odds ratio: age ≥65 years [vs. ≤40], 0.15 [95% confidence interval, 0.03−0.73]; African Americans (vs. all others), 0.15 [95% confidence interval, 0.05−0.44]). However, participants’ self-reported biopsy complications such as pain, anxiety, and hematuria did not affect their willingness to allow additional passes. A total of 23 participants (20%) stated that they would agree to undergo a biopsy for research even if it was not clinically indicated. Conclusion Among patients who had experienced a kidney biopsy, a majority were amenable to additional needle passes to donate kidney tissue for research during a future, clinically indicated biopsy, whereas a minority would undergo a biopsy for research purpose only.

BACKGROUND AND OBJECTIVES: Drug-induced acute interstitial nephritis represents an emerging cause of acute kidney disease, especially among polymedicated elderly patients. Although corticosteroids are frequently used, controversy exists about the timing of initiation, efficacy, safety, and duration of treatment. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We performed a retrospective study of 182 patients with biopsy-proven drug-induced acute interstitial nephritis from 13 Spanish centers. Exposure was defined as the length of corticosteroid treatment. The main outcome was the level of serum creatinine at month 6, with respect to baseline values. RESULTS: The most common offending agents were nonsteroidal anti-inflammatory drugs (27%). In 30% of patients, the offending drug could not be identified. The median time to suspected drug withdrawal was 11 days (interquartile range, 5–22). All patients presented with acute kidney disease and were treated with corticosteroids. The mean initial dose of prednisone was 0.8±0.2 mg/kg per day. High-dose corticosteroid treatment was maintained for 2 weeks (interquartile range, 1–4). After 6 months, the mean recovered GFR was 34±26 ml/min per 1.73 m(2) and ten patients required maintenance dialysis. Use of high-dose corticosteroids for 3 weeks or treatment duration >8 weeks were not associated with better recovery of kidney function. In the multivariable analysis, delayed onset of steroid treatment (odds ratio, 1.02; 95% confidence interval, 1.0 to 1.04) and the presence of interstitial fibrosis of >50% on the kidney biopsy specimen (odds ratio, 8.7; 95% confidence interval, 2.7 to 27.4) were both associated with serum creatinine level at month 6 of >75%, with respect to baseline values. CONCLUSIONS: High-dose corticosteroid treatment for 3 weeks or prolonged treatment for >8 weeks were not associated with greater kidney function recovery in drug-induced acute interstitial nephritis. A delay in the initiation of corticosteroids resulted in worse recovery of kidney function.