Acute Kidney Injury, Systemic Inflammation and Long-term Cognitive Function: ASSESS-AKI.

BACKGROUND: Cognitive dysfunction is a well-known complication of chronic kidney disease, but it is less known whether cognitive decline occurs in survivors after acute kidney injury (AKI). We hypothesized that an episode of AKI is associated with poorer cognitive function, mediated, at least in part, by persistent systemic inflammation. METHODS: ASSESS-AKI enrolled patients surviving three months after hospitalization with and without AKI matched based on demographics, comorbidities, and baseline kidney function. A subset underwent cognitive testing using the modified mini-mental status examination (3MS) at 3, 12, and 36 months. We examined the association of AKI with 3MS scores using mixed linear models and assessed the proportion of risk mediated by systemic inflammatory biomarkers. RESULTS: Among 1538 participants in ASSESS-AKI, 1420 (92%) completed the 3MS assessment at 3 months and had a corresponding matched participant. Participants with AKI had lower 3MS scores at three years (difference -1.1 (95% CI: -2.0, -0.3) P=0.009) compared to participants without AKI. A higher proportion of AKI participants had a clinically meaningful (≥ 5 point) reduction in 3MS scores at three years compared to participants without AKI (14% vs. 10%, P=0.04). In mediation analyses, plasma soluble tumor necrosis factor receptor-1 (sTNFR-1) at three months after AKI mediated 35% (P=0.02) of the AKI related risk for 3MS scores at three years. CONCLUSIONS: AKI was associated with lower 3MS scores and sTNFR-1 concentrations appeared to mediate a significant proportion of the risk of long-term cognitive impairment. Further work is needed to determine if AKI is causal or a marker for cognitive impairment.

Integrated multiomics implicates dysregulation of ECM and cell adhesion pathways as drivers of severe COVID-associated kidney injury.

COVID-19 has been a significant public health concern for the last four years; however, little is known about the mechanisms that lead to severe COVID-associated kidney injury. In this multicenter study, we combined quantitative deep urinary proteomics and machine learning to predict severe acute outcomes in hospitalized COVID-19 patients. Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrated predictive power for both discovery and validation set with 87% and 79% accuracy, respectively. These predictive urinary biomarkers were recapitulated in non-COVID acute kidney injury revealing overlapping injury mechanisms. We further combined orthogonal multiomics datasets to understand the mechanisms that drive severe COVID-associated kidney injury. Functional overlap and network analysis of urinary proteomics, plasma proteomics and urine sediment single-cell RNA sequencing showed that extracellular matrix and autophagy-associated pathways were uniquely impacted in severe COVID-19. Differentially abundant proteins associated with these pathways exhibited high expression in cells in the juxtamedullary nephron, endothelial cells, and podocytes, indicating that these kidney cell types could be potential targets. Further, single-cell transcriptomic analysis of kidney organoids infected with SARS-CoV-2 revealed dysregulation of extracellular matrix organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters showed significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Collectively, these data suggest that extracellular matrix degradation and adhesion-associated mechanisms could be a main driver of COVID-associated kidney injury and severe 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.

Assessment of Plasma Oxalate Concentration in Patients With CKD.

INTRODUCTION: Alterations in oxalate homeostasis are associated with kidney stone disease and progression of chronic kidney disease (CKD). However, accurate measurement of plasma oxalate (POx) concentrations in large patient cohorts is challenging as prompt acidification of samples has been deemed necessary. In the present study, we investigated the effects of variations in sample handling on POx results and examined an alternative strategy to the established preanalytical procedures. METHODS: The effect of storage time at room temperature (RT) and maintenance of samples at -80°C was tested. POx was measured in 1826 patients enrolled in the German Chronic Kidney Disease (GCKD) study, an ongoing multicenter, prospective, observational cohort study. RESULTS: We demonstrate that POx concentrations increased rapidly when samples were maintained at RT. This was most relevant for POx <10 µM, as concentrations more than doubled within a few hours. Immediate freezing on dry ice and storage at -80°C provided stable results and allowed postponement of acidification for >1 year. In the patients of the lowest estimated glomerular filtration rate (eGFR) quartile, median POx was 2.7 µM (interquartile range [IQR] <2.0-4.2) with a median eGFR of 25.1 ml/min per 1.73 m2 (IQR 20.3-28.1). CONCLUSION: We conclude that immediate freezing and maintenance of plasma samples at -80°C facilitates the sample collection process and allows accurate POx assessment in large cohorts. The present study may serve as a reference for sample handling to assess POx in clinical trials and to determine its role in CKD progression.

Association Between Early Recovery of Kidney Function After Acute Kidney Injury and Long-term Clinical Outcomes.

Importance: The severity of acute kidney injury (AKI) is usually determined based on the maximum serum creatinine concentration. However, the trajectory of kidney function recovery could be an additional important dimension of AKI severity. Objective: To assess whether the trajectory of kidney function recovery within 72 hours after AKI is associated with long-term risk of clinical outcomes. Design, Setting, and Participants: This prospective, multicenter cohort study enrolled 1538 adults with or without AKI 3 months after hospital discharge between December 1, 2009, and February 28, 2015. Statistical analyses were completed November 1, 2018. Participants with or without AKI were matched based on demographic characteristics, site, comorbidities, and prehospitalization estimated glomerular filtration rate. Participants with AKI were classified as having resolving or nonresolving AKI based on previously published definitions. Resolving AKI was defined as a decrease in serum creatinine concentration of 0.3 mg/dL or more or 25% or more from maximum in the first 72 hours after AKI diagnosis. Nonresolving AKI was defined as AKI not meeting the definition for resolving AKI. Main Outcomes and Measures: The primary outcome was a composite of major adverse kidney events (MAKE), defined as incident or progressive chronic kidney disease, long-term dialysis, or all-cause death during study follow-up. Results: Among 1538 participants (964 men; mean [SD] age, 64.6 [12.7] years), 769 (50%) had no AKI, 475 (31%) had a resolving AKI pattern, and 294 (19%) had a nonresolving AKI pattern. After a median follow-up of 4.7 years, the outcome of MAKE occurred in 550 (36%) of all participants. The adjusted hazard ratio for MAKE was higher for patients with resolving AKI (adjusted hazard ratio, 1.52; 95% CI, 1.01-2.29; P = .04) and those with nonresolving AKI (adjusted hazard ratio 2.30; 95% CI, 1.52-3.48; P < .001) compared with participants without AKI. Within the population of patients with AKI, nonresolving AKI was associated with a 51% greater risk of MAKE (95% CI, 22%-88%; P < .001) compared with resolving AKI. The higher risk of MAKE among patients with nonresolving AKI was explained by a higher risk of incident and progressive chronic kidney disease. Conclusions and Relevance: This study suggests that the 72-hour period immediately after AKI distinguishes the risk of clinically important kidney-specific long-term outcomes. The identification of different AKI recovery patterns may improve patient risk stratification, facilitate prognostic enrichment in clinical trials, and enable recognition of patients who may benefit from nephrology consultation.