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

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

Mitochondrial genetic variation and risk of chronic kidney disease and acute kidney injury in UK Biobank participants.

Experimental models suggest an important role for mitochondrial dysfunction in the pathogenesis of chronic kidney disease (CKD) and acute kidney injury (AKI), but little is known regarding the impact of common mitochondrial genetic variation on kidney health. We sought to evaluate associations of inherited mitochondrial DNA (mtDNA) variation with risk of CKD and AKI in a large population-based cohort. We categorized UK Biobank participants who self-identified as white into eight distinct mtDNA haplotypes, which were previously identified based on their associations with phenotypes associated with mitochondrial DNA copy number, a measure of mitochondrial function. We used linear and logistic regression models to evaluate associations of these mtDNA haplotypes with estimated glomerular filtration rate by serum creatinine and cystatin C (eGFRCr-CysC, N = 362,802), prevalent (N = 416 cases) and incident (N = 405 cases) end-stage kidney disease (ESKD), AKI defined by diagnostic codes (N = 14,170 cases), and urine albumin/creatinine ratio (ACR, N = 114,662). The mean age was 57 ± 8 years and the mean eGFR was 90 ± 14 ml/min/1.73 m2. MtDNA haplotype was significantly associated with eGFR (p = 2.8E-12), but not with prevalent ESKD (p = 5.9E-2), incident ESKD (p = 0.93), AKI (p = 0.26), or urine ACR (p = 0.54). The association of mtDNA haplotype with eGFR remained significant after adjustment for diabetes mellitus and hypertension (p = 1.2E-10). When compared to the reference haplotype, mtDNA haplotypes I (ß = 0.402, standard error (SE) = 0.111; p = 2.7E-4), IV (ß = 0.430, SE = 0.073; p = 4.2E-9), and V (ß = 0.233, SE = 0.050; p = 2.7E-6) were each associated with higher eGFR. Among self-identified white UK Biobank participants, mtDNA haplotype was associated with eGFR, but not with ESKD, AKI or albuminuria.

MASLD and MASH at the crossroads of hepatology trials and cardiorenal metabolic trials.

Steatotic liver disease (SLD) is a worldwide public health problem, causing considerable morbidity and mortality. Patients with SLD are at increased risk for major adverse cardiovascular (CV) events, type 2 diabetes mellitus and chronic kidney disease. Conversely, patients with cardiometabolic conditions have a high prevalence of SLD. In addition to epidemiological evidence linking many of these conditions, there is evidence of shared pathophysiological processes. In December 2022, a unique multi-stakeholder, multi-specialty meeting, called MOSAIC (Metabolic multi Organ Science Accelerating Innovation in Clinical Trials) was convened to foster collaboration across metabolic, hepatology, nephrology and CV disorders. One of the goals of the meeting was to consider approaches to drug development that would speed regulatory approval of treatments for multiple disorders by combining liver and cardiorenal endpoints within a single study. Non-invasive tests, including biomarkers and imaging, are needed in hepatic and cardiorenal trials. They can be used as trial endpoints, to enrich trial populations, to diagnose and risk stratify patients and to assess treatment efficacy and safety. Although they are used in proof of concept and phase 2 trials, they are often not acceptable for regulatory approval of therapies. The challenge is defining the optimal combination of biomarkers, imaging and morbidity/mortality outcomes and ensuring that they are included in future trials while minimizing the burden on patients, trialists and trial sponsors. This paper provides an overview of some of the wide array of CV, liver and kidney measurements that were discussed at the MOSAIC meeting.

Associations of Baseline and Longitudinal Serum Uromodulin With Kidney Failure and Mortality: Results From the African American Study of Kidney Disease and Hypertension (AASK) Trial.

RATIONALE & OBJECTIVE: Uromodulin (UMOD) is the most abundant protein found in urine and has emerged as a promising biomarker of tubule health. Circulating UMOD is also detectable, but at lower levels. We evaluated whether serum UMOD levels were associated with the risks of incident kidney failure with replacement therapy (KFRT) and mortality. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Participants in AASK (the African American Study of Kidney Disease and Hypertension) with available stored serum samples from the 0-, 12-, and 24-month visits for biomarker measurement. PREDICTORS: Baseline log-transformed UMOD and change in UMOD over 2 years. OUTCOMES: KFRT and mortality. ANALYTICAL APPROACH: Cox proportional hazards and mixed-effects models. RESULTS: Among 500 participants with baseline serum UMOD levels (mean age, 54y; 37% female), 161 KFRT events occurred during a median of 8.5 years. After adjusting for baseline demographic factors, clinical factors, glomerular filtration rate, log-transformed urine protein-creatinine ratio, and randomized treatment groups, a 50% lower baseline UMOD level was independently associated with a 35% higher risk of KFRT (adjusted HR, 1.35; 95% CI, 1.07-1.70). For annual UMOD change, each 1-standard deviation lower change was associated with a 67% higher risk of KFRT (adjusted HR, 1.67; 95% CI, 1.41-1.99). Baseline UMOD and UMOD change were not associated with mortality. UMOD levels declined more steeply for metoprolol versus ramipril (P<0.001) as well as for intensive versus standard blood pressure goals (P = 0.002). LIMITATIONS: Small sample size and limited generalizability. CONCLUSIONS: Lower UMOD levels at baseline and steeper declines in UMOD over time were associated with a higher risk of subsequent KFRT in a cohort of African American adults with chronic kidney disease and hypertension. PLAIN-LANGUAGE SUMMARY: Prior studies of uromodulin (UMOD), the most abundant protein in urine, and kidney disease have focused primarily on urinary UMOD levels. The present study evaluated associations of serum UMOD levels with the risks of kidney failure with replacement therapy (KFRT) and mortality in a cohort of African American adults with hypertension and chronic kidney disease. It found that participants with lower levels of UMOD at baseline were more likely to experience KFRT even after accounting for baseline kidney measures. Similarly, participants who experienced steeper annual declines in UMOD also had a heightened risk of kidney failure. Neither baseline nor annual change in UMOD was associated with mortality. Serum UMOD is a promising biomarker of kidney health.

Urinary Biomarkers and Kidney Injury in VA NEPHRON-D: Phenotyping Acute Kidney Injury in Clinical Trials.

RATIONALE & OBJECTIVE: Urinary biomarkers of injury, inflammation, and repair may help phenotype acute kidney injury (AKI) observed in clinical trials. We evaluated the differences in biomarkers between participants randomized to monotherapy or to combination renin-angiotensin-aldosterone system (RAAS) blockade in VA NEPHRON-D, where an increased proportion of observed AKI was acknowledged in the combination arm. STUDY DESIGN: Longitudinal analysis. SETTING & PARTICIPANTS: A substudy of the VA NEPHRON-D trial. PREDICTOR: Primary exposure was the treatment arm (combination [RAAS inhibitor] vs monotherapy). AKI is used as a stratifying variable. OUTCOME: Urinary biomarkers, including albumin, EGF (epidermal growth factor), MCP-1 (monocyte chemoattractant protein-1), YKL-40 (chitinase 3-like protein 1), and KIM-1 (kidney injury molecule-1). ANALYTICAL APPROACH: Biomarkers measured at baseline and at 12 months in trial participants were compared between treatment groups and by AKI. AKI events occurring during hospitalization were predefined safety end points in the original trial. The results were included in a meta-analysis with other large chronic kidney disease trials to assess global trends in biomarker changes. RESULTS: In 707 participants followed for a median of 2.2 years, AKI incidence was higher in the combination (20.7%) versus the monotherapy group (12.7%; relative risk [RR], 1.64 [95% CI, 1.16-2.30]). Compared with the monotherapy arm, in the combination arm the urine biomarkers at 12 months were either unchanged (MCP-1: RR, -3% [95% CI, -13% to 9%], Padj=0.8; KIM-1: RR, -10% [95% CI, -20% to 1%], Padj=0.2; EGF, RR-7% [95% CI, -12% to-1%], Padj=0.08) or lower (albuminuria: RR, -24% [95% CI, -37% to-8%], Padj=0.02; YKL: RR, -40% to-44% [95% CI, -58% to-25%], Padj<0.001). Pooled meta-analysis demonstrated reduced albuminuria in the intervention arm across 3 trials and similar trajectories in other biomarkers. LIMITATIONS: Biomarker measurement was limited to 2 time points independent of AKI events. CONCLUSIONS: Despite the increased risk of serum creatinine-defined AKI, combination RAAS inhibitor therapy was associated with unchanged or decreased urinary biomarkers at 12 months. This suggests a possible role for kidney biomarkers to further characterize kidney injury in clinical trials. PLAIN-LANGUAGE SUMMARY: The VA NEPHRON-D trial investigated inhibition of the renin-angiotensin-aldosterone system (RAAS) hormonal axis on kidney outcomes in a large population of diabetic chronic kidney disease patients. The trial was stopped early due to increased events of serum creatinine-defined acute kidney injury in the combination therapy arm. Urine biomarkers can serve as an adjunct to serum creatinine in identifying kidney injury. We found that urinary biomarkers in the combination therapy group were not associated with a pattern of harm and damage to the kidney, despite the increased number of kidney injury events in that group. This suggests that serum creatinine alone may be insufficient for defining kidney injury and supports further exploration of how other biomarkers might improve identification of kidney injury in clinical trials.

Kidney Transplant Outcomes From Deceased Donors Who Received Dialysis.

Importance: Recipient outcomes after kidney transplant from deceased donors who received dialysis prior to kidney donation are not well described. Objective: To compare outcomes of transplant recipients who received kidneys from deceased donors who underwent dialysis prior to kidney donation vs recipients of kidneys from deceased donors who did not undergo dialysis. Design, Setting, and Participants: A retrospective cohort study was conducted including data from 58 US organ procurement organizations on deceased kidney donors and kidney transplant recipients. From 2010 to 2018, 805 donors who underwent dialysis prior to kidney donation were identified. The donors who underwent dialysis prior to kidney donation were matched 1:1 with donors who did not undergo dialysis using a rank-based distance matrix algorithm; 1944 kidney transplant recipients were evaluated. Exposure: Kidney transplants from deceased donors who underwent dialysis prior to kidney donation compared with kidney transplants from deceased donors who did not undergo dialysis. Main Outcomes and Measures: The 4 study outcomes were delayed graft function (defined as receipt of dialysis by the kidney recipient ≤1 week after transplant), all-cause graft failure, death-censored graft failure, and death. Results: From 2010 to 2018, 1.4% of deceased kidney donors (805 of 58 155) underwent dialysis prior to kidney donation. Of these 805 individuals, 523 (65%) donated at least 1 kidney. A total of 969 kidneys (60%) were transplanted and 641 kidneys (40%) were discarded. Among the donors with kidneys transplanted, 514 (mean age, 33 years [SD, 10.8 years]; 98 had hypertension [19.1%] and 36 had diabetes [7%]) underwent dialysis prior to donation and were matched with 514 (mean age, 33 years [SD, 10.9 years]; 98 had hypertension [19.1%] and 36 had diabetes [7%]) who did not undergo dialysis. Kidney transplants from donors who received dialysis prior to donation (n = 954 kidney recipients) were associated with a higher risk of delayed graft function compared with kidney transplants from donors who did not receive dialysis (n = 990 kidney recipients) (59.2% vs 24.6%, respectively; adjusted odds ratio, 4.17 [95% CI, 3.28-5.29]). The incidence rates did not significantly differ at a median follow-up of 34.1 months for all-cause graft failure (43.1 kidney transplants per 1000 person-years from donors who received dialysis prior to donation vs 46.9 kidney transplants per 1000 person-years from donors who did not receive dialysis; adjusted hazard ratio [HR], 0.90 [95% CI, 0.70-1.15]), for death-censored graft failure (22.5 vs 20.6 per 1000 person-years, respectively; adjusted HR, 1.18 [95% CI, 0.83-1.69]), or for death (24.6 vs 30.8 per 1000 person-years; adjusted HR, 0.76 [95% CI, 0.55-1.04]). Conclusions and Relevance: Compared with receiving a kidney from a deceased donor who did not undergo dialysis, receiving a kidney from a deceased donor who underwent dialysis prior to kidney donation was associated with a significantly higher incidence of delayed graft function, but no significant difference in graft failure or death at follow-up.

Untargeted metabolomics of perfusate and their association with hypothermic machine perfusion and allograft failure.

Although hypothermic machine perfusion (HMP) is associated with improved kidney graft viability and function, the underlying biological mechanisms are unknown. Untargeted metabolomic profiling may identify potential metabolites and pathways that can help assess allograft viability and contribute to organ preservation. Therefore, in this multicenter study, we measured all detectable metabolites in perfusate collected at the beginning and end of deceased-donor kidney perfusion and evaluated their associations with graft failure. In our cohort of 190 kidney transplants, 33 (17%) had death-censored graft failure over a median follow-up of 5.0 years (IQR 3.0-6.1 years). We identified 553 known metabolites in perfusate and characterized their experimental and biological consistency through duplicate samples and unsupervised clustering. After perfusion-time adjustment and false discovery correction, six metabolites in post-HMP perfusate were significantly associated with death-censored graft failure, including alpha-ketoglutarate, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, 1-carboxyethylphenylalanine, and three glycerol-phosphatidylcholines. All six metabolites were associated with an increased risk of graft failure (Hazard Ratio per median absolute deviation range 1.04-1.45). Four of six metabolites also demonstrated significant interaction with donation after cardiac death with notably greater risk in the donation after cardiac death group (Hazard Ratios up to 1.69). Discarded kidneys did not have significantly different levels of any death-censored graft failure-associated metabolites. On interrogation of pathway analysis, production of reactive oxygen species and increased metabolism of fatty acids were upregulated in kidneys that subsequently developed death-censored graft failure. Thus, further understanding the role of these metabolites may inform the HMP process and help improve the objective evaluation of allograft offers, thereby reducing the discard of potentially viable organs.

Microbiome modulation after severe acute kidney injury accelerates functional recovery and decreases kidney fibrosis.

Targeting gut microbiota has shown promise to prevent experimental acute kidney injury (AKI). However, this has not been studied in relation to accelerating recovery and preventing fibrosis. Here, we found that modifying gut microbiota with an antibiotic administered after severe ischemic kidney injury in mice, particularly with amoxicillin, accelerated recovery. These indices of recovery included increased glomerular filtration rate, diminution of kidney fibrosis, and reduction of kidney profibrotic gene expression. Amoxicillin was found to increase stool Alistipes, Odoribacter and Stomatobaculum species while significantly depleting Holdemanella and Anaeroplasma. Specifically, amoxicillin treatment reduced kidney CD4+T cells, interleukin (IL)-17 +CD4+T cells, and tumor necrosis factor-α double negative T cells while it increased CD8+T cells and PD1+CD8+T cells. Amoxicillin also increased gut lamina propria CD4+T cells while decreasing CD8+T and IL-17+CD4+T cells. Amoxicillin did not accelerate repair in germ-free or CD8-deficient mice, demonstrating microbiome and CD8+T lymphocytes dependence for amoxicillin protective effects. However, amoxicillin remained effective in CD4-deficient mice. Fecal microbiota transplantation from amoxicillin-treated to germ-free mice reduced kidney fibrosis and increased Foxp3+CD8+T cells. Amoxicillin pre-treatment protected mice against kidney bilateral ischemia reperfusion injury but not cisplatin-induced AKI. Thus, modification of gut bacteria with amoxicillin after severe ischemic AKI is a promising novel therapeutic approach to accelerate recovery of kidney function and mitigate the progression of AKI to chronic kidney disease.

The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events.

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients.

Deceased-Donor Acute Kidney Injury and Acute Rejection in Kidney Transplant Recipients: A Multicenter Cohort.

RATIONALE & OBJECTIVE: Donor acute kidney injury (AKI) activates innate immunity, enhances HLA expression in the kidney allograft, and provokes recipient alloimmune responses. We hypothesized that injury and inflammation that manifested in deceased-donor urine biomarkers would be associated with higher rates of biopsy-proven acute rejection (BPAR) and allograft failure after transplantation. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: 862 deceased donors for 1,137 kidney recipients at 13 centers. EXPOSURES: We measured concentrations of interleukin 18 (IL-18), kidney injury molecule 1 (KIM-1), and neutrophil gelatinase-associated lipocalin (NGAL) in deceased donor urine. We also used the Acute Kidney Injury Network (AKIN) criteria to assess donor clinical AKI. OUTCOMES: The primary outcome was a composite of BPAR and graft failure (not from death). A secondary outcome was the composite of BPAR, graft failure, and/or de novo donor-specific antibody (DSA). Outcomes were ascertained in the first posttransplant year. ANALYTICAL APPROACH: Multivariable Fine-Gray models with death as a competing risk. RESULTS: Mean recipient age was 54 ± 13 (SD) years, and 82% received antithymocyte globulin. We found no significant associations between donor urinary IL-18, KIM-1, and NGAL and the primary outcome (subdistribution hazard ratio [HR] for highest vs lowest tertile of 0.76 [95% CI, 0.45-1.28], 1.20 [95% CI, 0.69-2.07], and 1.14 [95% CI, 0.71-1.84], respectively). In secondary analyses, we detected no significant associations between clinically defined AKI and the primary outcome or between donor biomarkers and the composite outcome of BPAR, graft failure, and/or de novo DSA. LIMITATIONS: BPAR was ascertained through for-cause biopsies, not surveillance biopsies. CONCLUSIONS: In a large cohort of kidney recipients who almost all received induction with thymoglobulin, donor injury biomarkers were associated with neither graft failure and rejection nor a secondary outcome that included de novo DSA. These findings provide some reassurance that centers can successfully manage immunological complications using deceased-donor kidneys with AKI.

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.

Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is a heterogeneous clinical syndrome with varying causes, pathophysiology, and outcomes. We incorporated plasma and urine biomarker measurements to identify AKI subgroups (subphenotypes) more tightly linked to underlying pathophysiology and long-term clinical outcomes. STUDY DESIGN: Multicenter cohort study. SETTING & PARTICIPANTS: 769 hospitalized adults with AKI matched with 769 without AKI, enrolled from December 2009 to February 2015 in the ASSESS-AKI Study. PREDICTORS: 29 clinical, plasma, and urinary biomarker parameters used to identify AKI subphenotypes. OUTCOME: Composite of major adverse kidney events (MAKE) with a median follow-up period of 4.7 years. ANALYTICAL APPROACH: Latent class analysis (LCA) and k-means clustering were applied to 29 clinical, plasma, and urinary biomarker parameters. Associations between AKI subphenotypes and MAKE were analyzed using Kaplan-Meier curves and Cox proportional hazard models. RESULTS: Among 769 AKI patients both LCA and k-means identified 2 distinct AKI subphenotypes (classes 1 and 2). The long-term risk for MAKE was higher with class 2 (adjusted HR, 1.41 [95% CI, 1.08-1.84]; P=0.01) compared with class 1, adjusting for demographics, hospital level factors, and KDIGO stage of AKI. The higher risk of MAKE among class 2 was explained by a higher risk of long-term chronic kidney disease progression and dialysis. The top variables that were different between classes 1 and 2 included plasma and urinary biomarkers of inflammation and epithelial cell injury; serum creatinine ranked 20th out of the 29 variables for differentiating classes. LIMITATIONS: A replication cohort with simultaneously collected blood and urine sampling in hospitalized adults with AKI and long-term outcomes was unavailable. CONCLUSIONS: We identify 2 molecularly distinct AKI subphenotypes with differing risk of long-term outcomes, independent of the current criteria to risk stratify AKI. Future identification of AKI subphenotypes may facilitate linking therapies to underlying pathophysiology to prevent long-term sequalae after AKI. PLAIN-LANGUAGE SUMMARY: Acute kidney injury (AKI) occurs commonly in hospitalized patients and is associated with high morbidity and mortality. The AKI definition lumps many different types of AKI together, but subgroups of AKI may be more tightly linked to the underlying biology and clinical outcomes. We used 29 different clinical, blood, and urinary biomarkers and applied 2 different statistical algorithms to identify AKI subtypes and their association with long-term outcomes. Both clustering algorithms identified 2 AKI subtypes with different risk of chronic kidney disease, independent of the serum creatinine concentrations (the current gold standard to determine severity of AKI). Identification of AKI subtypes may facilitate linking therapies to underlying biology to prevent long-term consequences after AKI.

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.

Overcoming barriers in the design and implementation of clinical trials for acute kidney injury: a report from the 2020 Kidney Disease Clinical Trialists meeting.

Acute kidney injury (AKI) is a growing epidemic and is independently associated with increased risk of death, chronic kidney disease (CKD) and cardiovascular events. Randomized-controlled trials (RCTs) in this domain are notoriously challenging and many clinical studies in AKI have yielded inconclusive findings. Underlying this conundrum is the inherent heterogeneity of AKI in its etiology, presentation and course. AKI is best understood as a syndrome and identification of AKI subphenotypes is needed to elucidate the disease's myriad etiologies and to tailor effective prevention and treatment strategies. Conventional RCTs are logistically cumbersome and often feature highly selected patient populations that limit external generalizability and thus alternative trial designs should be considered when appropriate. In this narrative review of recent developments in AKI trials based on the Kidney Disease Clinical Trialists (KDCT) 2020 meeting, we discuss barriers to and strategies for improved design and implementation of clinical trials for AKI patients, including predictive and prognostic enrichment techniques, the use of pragmatic trials and adaptive trials.

Biomarkers of eGFR decline after cardiac surgery in children: findings from the ASSESS-AKI study.

BACKGROUND: Children who require surgery for congenital heart disease have increased risk for long-term chronic kidney disease (CKD). Clinical factors as well as urine biomarkers of tubular health and injury may help improve the prognostication of estimated glomerular filtration rate (eGFR) decline. METHODS: We enrolled children from 1 month to 18 years old undergoing cardiac surgery in the ASSESS-AKI cohort. We used mixed-effect models to assess the association between urinary biomarkers (log2-transformed uromodulin, NGAL, KIM-1, IL-18, L-FABP) measured 3 months after cardiac surgery and cyanotic heart disease with the rate of eGFR decline at annual in-person visits over 4 years. RESULTS: Of the 117 children enrolled, 30 (24%) had cyanotic heart disease. During 48 months of follow-up, the median eGFR in the subgroup of children with cyanotic heart disease was lower at all study visits as compared with children with acyanotic heart disease (p = 0.01). In the overall cohort, lower levels of both urine uromodulin and IL-18 after discharge were associated with eGFR decline. After adjustment for age, RACHS-1 surgical complexity score, proteinuria, and eGFR at the 3-month study visit, lower concentrations of urine uromodulin and IL-18 were associated with a monthly decline in eGFR (uromodulin ß = 0.04 (95% CI: 0.00-0.09; p = 0.07) IL-18 ß = 0.07 (95% CI: 0.01-0.13; p = 0.04), ml/min/1.73 m2 per month). CONCLUSIONS: At 3 months after cardiac surgery, children with lower urine uromodulin and IL-18 concentrations experienced a significantly faster decline in eGFR. Children with cyanotic heart disease had a lower median eGFR at all time points but did not experience faster eGFR decline. A higher-resolution version of the Graphical abstract is available as Supplementary information.

Systematic Review and Meta-Analysis of Plasma and Urine Biomarkers for CKD Outcomes.

BACKGROUND: Sensitive and specific biomarkers are needed to provide better biologic insight into the risk of incident and progressive CKD. However, studies have been limited by sample size and design heterogeneity. METHODS: In this assessment of the prognostic value of preclinical plasma and urine biomarkers for CKD outcomes, we searched Embase (Ovid), MEDLINE ALL (Ovid), and Scopus up to November 30, 2020, for studies exploring the association between baseline kidney biomarkers and CKD outcomes (incident CKD, CKD progression, or incident ESKD). We used random-effects meta-analysis. RESULTS: After screening 26,456 abstracts and 352 full-text articles, we included 129 studies in the meta-analysis for the most frequently studied plasma biomarkers (TNFR1, FGF23, TNFR2, KIM-1, suPAR, and others) and urine biomarkers (KIM-1, NGAL, and others). For the most frequently studied plasma biomarkers, pooled RRs for CKD outcomes were 2.17 (95% confidence interval [95% CI], 1.91 to 2.47) for TNFR1 (31 studies); 1.21 (95% CI, 1.15 to 1.28) for FGF-23 (30 studies); 2.07 (95% CI, 1.82 to 2.34) for TNFR2 (23 studies); 1.51 (95% CI, 1.38 to 1.66) for KIM-1 (18 studies); and 1.42 (95% CI, 1.30 to 1.55) for suPAR (12 studies). For the most frequently studied urine biomarkers, pooled RRs were 1.10 (95% CI, 1.05 to 1.16) for KIM-1 (19 studies) and 1.12 (95% CI, 1.06 to 1.19) for NGAL (19 studies). CONCLUSIONS: Studies of preclinical biomarkers for CKD outcomes have considerable heterogeneity across study cohorts and designs, limiting comparisons of prognostic performance across studies. Plasma TNFR1, FGF23, TNFR2, KIM-1, and suPAR were among the most frequently investigated in the setting of CKD outcomes.

Longitudinal TNFR1 and TNFR2 and Kidney Outcomes: Results from AASK and VA NEPHRON-D.

BACKGROUND: Higher baseline levels of soluble TNF receptors (TNFR1 and TNFR2) have been associated with progressive CKD. Whether longitudinal changes in these biomarkers of inflammation are also associated with worse kidney outcomes has been less studied. METHODS: We evaluated associations of longitudinal changes in TNFR1 and TNFR2 with ESKD in the African American Study of Kidney Disease and Hypertension (AASK; 38% female; 0% diabetes) and kidney function decline (first occurrence of ≥30 ml/min per 1.73 m2 or ≥50% eGFR decline if randomization eGFR ≥60 or <60 ml/min per 1.73 m2, respectively; ESKD) in the Veterans Affairs Nephropathy in Diabetes trial (VA NEPHRON-D; 99% male; 100% diabetes) using Cox models. Biomarkers were measured from samples collected at 0-, 12-, and 24-month visits for AASK (serum) and 0- and 12-month visits for VA NEPHRON-D (plasma). Biomarker slopes (AASK) were estimated using linear mixed-effects models. Covariates included sociodemographic/clinical factors, baseline biomarker level, and kidney function. RESULTS: There were 129 ESKD events over a median of 7.0 years in AASK (n=418) and 118 kidney function decline events over a median of 1.5 years in VA NEPHRON-D (n=754). In AASK, each 1 SD increase in TNFR1 and TNFR2 slope was associated with 2.98- and 1.87-fold higher risks of ESKD, respectively. In VA NEPHRON-D, each 1 SD increase in TNFR1 and TNFR2 was associated with 3.20- and 1.43-fold higher risks of kidney function decline, respectively. CONCLUSIONS: Among individuals with and without diabetes, longitudinal increases in TNFR1 and TNFR2 were each associated with progressive CKD, independent of initial biomarker level and kidney function.

Acute Kidney Injury Associates with Long-Term Increases in Plasma TNFR1, TNFR2, and KIM-1: Findings from the CRIC Study.

BACKGROUND: Some markers of inflammation-TNF receptors 1 and 2 (TNFR1 and TNFR2)-are independently associated with progressive CKD, as is a marker of proximal tubule injury, kidney injury molecule 1 (KIM-1). However, whether an episode of hospitalized AKI may cause long-term changes in these biomarkers is unknown. METHODS: Among adult participants in the Chronic Renal Insufficiency Cohort (CRIC) study, we identified 198 episodes of hospitalized AKI (defined as peak/nadir inpatient serum creatinine values ≥1.5). For each AKI hospitalization, we found the best matched non-AKI hospitalization (unique patients), using prehospitalization characteristics, including eGFR and urine protein/creatinine ratio. We measured TNFR1, TNFR2, and KIM-1 in banked plasma samples collected at annual CRIC study visits before and after the hospitalization (a median of 7 months before and 5 months after hospitalization). RESULTS: In the AKI and non-AKI groups, we found similar prehospitalization median levels of TNFR1 (1373 pg/ml versus 1371 pg/ml, for AKI and non-AKI, respectively), TNFR2 (47,141 pg/ml versus 46,135 pg/ml, respectively), and KIM-1 (857 pg/ml versus 719 pg/ml, respectively). Compared with matched study participants who did not experience AKI, study participants who did experience AKI had greater increases in TNFR1 (23% versus 10%, P<0.01), TNFR2 (10% versus 3%, P<0.01), and KIM-1 (13% versus -2%, P<0.01). CONCLUSIONS: Among patients with CKD, AKI during hospitalization was associated with increases in plasma TNFR1, TNFR2, and KIM-1 several months after their hospitalization. These results highlight a potential mechanism by which AKI may contribute to more rapid loss of kidney function months to years after the acute insult.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury.

BACKGROUND: The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure. METHODS: To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later. RESULTS: Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression. CONCLUSIONS: A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

Biomarkers of Acute and Chronic Kidney Disease.

The current unidimensional paradigm of kidney disease detection is incompatible with the complexity and heterogeneity of renal pathology. The diagnosis of kidney disease has largely focused on glomerular filtration, while assessment of kidney tubular health has notably been absent. Following insult, the kidney tubular cells undergo a cascade of cellular responses that result in the production and accumulation of low-molecular-weight proteins in the urine and systemic circulation. Modern advancements in molecular analysis and proteomics have allowed the identification and quantification of these proteins as biomarkers for assessing and characterizing kidney diseases. In this review, we highlight promising biomarkers of kidney tubular health that have strong underpinnings in the pathophysiology of kidney disease. These biomarkers have been applied to various specific clinical settings from the spectrum of acute to chronic kidney diseases, demonstrating the potential to improve patient care.