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We used the CRISPR/Cas9 system to knock-in reporter transgenes at the kidney injury molecule-1 (KIM-1) locus and isolated human proximal tubule cell (HK-2) clones. PCR verified targeted knock-in of the luciferase and eGFP reporter at the KIM-1 locus. HK-2-KIM-1 reporter cells responded to various stimuli including hypoxia, cisplatin, and high glucose, indicative of upregulation of KIM-1 expression. We attempted using CRISPR/Cas9 to also engineer the KIM-1 reporter in telomerase-immortalized human RPTEC cells. However, these cells demonstrated an inability to undergo homologous recombination at the target locus. KIM-1-reporter human proximal tubular cells could be valuable tools in drug discovery for molecules inhibiting kidney injury. Additionally, our gene targeting strategy could be used in other cell lines to evaluate the biology of KIM-1 in vitro or in vivo.
OBJECTIVE - Hepatorenal Syndrome (HRS) is a devastating form of acute kidney injury (AKI) in advanced liver disease patients with high morbidity and mortality, but phenotyping algorithms have not yet been developed using large electronic health record (EHR) databases. We evaluated and compared multiple phenotyping methods to achieve an accurate algorithm for HRS identification.
MATERIALS AND METHODS - A national retrospective cohort of patients with cirrhosis and AKI admitted to 124 Veterans Affairs hospitals was assembled from electronic health record data collected from 2005 to 2013. AKI was defined by the Kidney Disease: Improving Global Outcomes criteria. Five hundred and four hospitalizations were selected for manual chart review and served as the gold standard. Electronic Health Record based predictors were identified using structured and free text clinical data, subjected through NLP from the clinical Text Analysis Knowledge Extraction System. We explored several dimension reduction techniques for the NLP data, including newer high-throughput phenotyping and word embedding methods, and ascertained their effectiveness in identifying the phenotype without structured predictor variables. With the combined structured and NLP variables, we analyzed five phenotyping algorithms: penalized logistic regression, naïve Bayes, support vector machines, random forest, and gradient boosting. Calibration and discrimination metrics were calculated using 100 bootstrap iterations. In the final model, we report odds ratios and 95% confidence intervals.
RESULTS - The area under the receiver operating characteristic curve (AUC) for the different models ranged from 0.73 to 0.93; with penalized logistic regression having the best discriminatory performance. Calibration for logistic regression was modest, but gradient boosting and support vector machines were superior. NLP identified 6985 variables; a priori variable selection performed similarly to dimensionality reduction using high-throughput phenotyping and semantic similarity informed clustering (AUC of 0.81 - 0.82).
CONCLUSION - This study demonstrated improved phenotyping of a challenging AKI etiology, HRS, over ICD-9 coding. We also compared performance among multiple approaches to EHR-derived phenotyping, and found similar results between methods. Lastly, we showed that automated NLP dimension reduction is viable for acute illness.
Copyright © 2018 Elsevier Inc. All rights reserved.
OBJECTIVES - Acute kidney injury frequently complicates critical illness and is associated with high morbidity and mortality. Frailty is common in critical illness survivors, but little is known about the impact of acute kidney injury. We examined the association of acute kidney injury and frailty within a year of hospital discharge in survivors of critical illness.
DESIGN - Secondary analysis of a prospective cohort study.
SETTING - Medical/surgical ICU of a U.S. tertiary care medical center.
PATIENTS - Three hundred seventeen participants with respiratory failure and/or shock.
INTERVENTIONS - None.
MEASUREMENTS AND MAIN RESULTS - Acute kidney injury was determined using Kidney Disease Improving Global Outcomes stages. Clinical frailty status was determined using the Clinical Frailty Scale at 3 and 12 months following discharge. Covariates included mean ICU Sequential Organ Failure Assessment score and Acute Physiology and Chronic Health Evaluation II score as well as baseline comorbidity (i.e., Charlson Comorbidity Index), kidney function, and Clinical Frailty Scale score. Of 317 patients, 243 (77%) had acute kidney injury and one in four patients with acute kidney injury was frail at baseline. In adjusted models, acute kidney injury stages 1, 2, and 3 were associated with higher frailty scores at 3 months (odds ratio, 1.92; 95% CI, 1.14-3.24; odds ratio, 2.40; 95% CI, 1.31-4.42; and odds ratio, 4.41; 95% CI, 2.20-8.82, respectively). At 12 months, a similar association of acute kidney injury stages 1, 2, and 3 and higher Clinical Frailty Scale score was noted (odds ratio, 1.87; 95% CI, 1.11-3.14; odds ratio, 1.81; 95% CI, 0.94-3.48; and odds ratio, 2.76; 95% CI, 1.34-5.66, respectively). In supplemental and sensitivity analyses, analogous patterns of association were observed.
CONCLUSIONS - Acute kidney injury in survivors of critical illness predicted worse frailty status 3 and 12 months postdischarge. These findings have important implications on clinical decision making among acute kidney injury survivors and underscore the need to understand the drivers of frailty to improve patient-centered outcomes.
OBJECTIVE - Hypoglycemia is common in patients with diabetes. The risk of hypoglycemia after acute kidney injury (AKI) is not well defined. The purpose of this study was to compare the risk for postdischarge hypoglycemia among hospitalized patients with diabetes who do and do not experience AKI.
RESEARCH DESIGN AND METHODS - We performed a propensity-matched analysis of patients with diabetes, with and without AKI, using a retrospective national cohort of veterans hospitalized between 2004 and 2012. AKI was defined as a 0.3 mg/dL or 50% increase in serum creatinine from baseline to peak serum creatinine during hospitalization. Hypoglycemia was defined as hospital admission or an emergency department visit for hypoglycemia or as an outpatient blood glucose <60 mg/dL. Time to incident hypoglycemia within 90 days postdischarge was examined using Cox proportional hazards models. Prespecified subgroup analyses by renal recovery, baseline chronic kidney disease, preadmission drug regimen, and HbA were performed.
RESULTS - We identified 65,151 propensity score-matched pairs with and without AKI. The incidence of hypoglycemia was 29.6 (95% CI 28.9-30.4) and 23.5 (95% CI 22.9-24.2) per 100 person-years for patients with and without AKI, respectively. After adjustment, AKI was associated with a 27% increased risk of hypoglycemia (hazard ratio [HR] 1.27 [95% CI 1.22-1.33]). For patients with full recovery, the HR was 1.18 (95% CI 1.12-1.25); for partial recovery, the HR was 1.30 (95% CI 1.23-1.37); and for no recovery, the HR was 1.48 (95% CI 1.36-1.60) compared with patients without AKI. Across all antidiabetes drug regimens, patients with AKI experienced hypoglycemia more frequently than patients without AKI, though the incidence of hypoglycemia was highest among insulin users, followed by glyburide and glipizide users, respectively.
CONCLUSIONS - AKI is a risk factor for hypoglycemia in the postdischarge period. Studies to identify risk-reduction strategies in this population are warranted.
© 2018 by the American Diabetes Association.
No therapies have been shown to improve outcomes in patients with acute kidney injury (AKI). Given the high morbidity and mortality associated with AKI this represents an important unmet medical need. A common feature of all of the therapeutic development efforts for AKI is that none were driven by target selection or preclinical modeling that was based primarily on human data. This is important when considering a heterogeneous and dynamic condition such as AKI, in which in the absence of more accurate molecular classifications, clinical cohorts are likely to include patients with different types of injury at different stages in the injury and repair continuum. The National Institutes of Health precision medicine initiative offers an opportunity to address this. By creating a molecular tissue atlas of AKI, defining patient subgroups, and identifying critical cells and pathways involved in human AKI, this initiative has the potential to transform our current approach to therapeutic discovery. In this review, we discuss the opportunities and challenges that this initiative presents, with a specific focus on AKI, what additional efforts will be needed to apply these discoveries to therapeutic development, and how we believe this effort might lead to the development of new therapeutics for subsets of patients with AKI.
Copyright © 2017. Published by Elsevier Inc.
BACKGROUND - Acute kidney injury (AKI) after cardiac surgery is associated with increased short- and long-term mortality. Inflammation, oxidative stress, and endothelial dysfunction and damage play important roles in the development of AKI. High-density lipoproteins (HDLs) have anti-inflammatory and antioxidant properties and improve endothelial function and repair. Statins enhance HDL's anti-inflammatory and antioxidant capacities. We hypothesized that a higher preoperative HDL cholesterol concentration is associated with decreased AKI after cardiac surgery and that perioperative statin exposure potentiates this association.
METHODS AND RESULTS - We tested our hypothesis in 391 subjects from a randomized clinical trial of perioperative atorvastatin to reduce AKI after cardiac surgery. A 2-component latent variable mixture model was used to assess the association between preoperative HDL cholesterol concentration and postoperative change in serum creatinine, adjusted for known AKI risk factors and suspected confounders. Interaction terms were used to examine the effects of preoperative statin use, preoperative statin dose, and perioperative atorvastatin treatment on the association between preoperative HDL and AKI. A higher preoperative HDL cholesterol concentration was independently associated with a decreased postoperative serum creatinine change (=0.02). The association between a high HDL concentration and an attenuated increase in serum creatinine was strongest in long-term statin-using patients (=0.008) and was further enhanced with perioperative atorvastatin treatment (=0.004) and increasing long-term statin dose (=0.003).
CONCLUSIONS - A higher preoperative HDL cholesterol concentration was associated with decreased AKI after cardiac surgery. Preoperative and perioperative statin treatment enhanced this association, demonstrating that pharmacological potentiation is possible during the perioperative period.
CLINICAL TRIAL REGISTRATION - URL: http://www.clinicaltrials.gov. Unique Identifier: NCT00791648.
© 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
BACKGROUND - Acute kidney injury (AKI) is common and associated with poor outcomes. Heart failure is a leading cause of cardiovascular disease among patients with chronic kidney disease. The relationship between AKI and heart failure remains unknown and may identify a novel mechanistic link between kidney and cardiovascular disease.
STUDY DESIGN - Observational study.
SETTING & PARTICIPANTS - We studied a national cohort of 300,868 hospitalized US veterans (2004-2011) without a history of heart failure.
PREDICTOR - AKI was the predictor and was defined as a 0.3-mg/dL or 50% increase in serum creatinine concentration from baseline to the peak hospital value. Patients with and without AKI were matched (1:1) on 28 in- and outpatient covariates using optimal Mahalanobis distance matching.
OUTCOMES - Incident heart failure was defined as 1 or more hospitalization or 2 or more outpatient visits with a diagnosis of heart failure within 2 years through 2013.
RESULTS - There were 150,434 matched pairs in the study. Patients with and without AKI during the index hospitalization were well matched, with a median preadmission estimated glomerular filtration rate of 69mL/min/1.73m. The overall incidence rate of heart failure was 27.8 (95% CI, 19.3-39.9) per 1,000 person-years. The incidence rate was higher in those with compared with those without AKI: 30.8 (95% CI, 21.8-43.5) and 24.9 (95% CI, 16.9-36.5) per 1,000 person-years, respectively. In multivariable models, AKI was associated with 23% increased risk for incident heart failure (HR, 1.23; 95% CI, 1.19-1.27).
LIMITATIONS - Study population was primarily men, reflecting patients seen at Veterans Affairs hospitals.
CONCLUSIONS - AKI is an independent risk factor for incident heart failure. Future studies to identify underlying mechanisms and modifiable risk factors are needed.
Copyright © 2017 National Kidney Foundation, Inc. All rights reserved.
Acute kidney injury (AKI) is associated with subsequent chronic kidney disease (CKD), but the mechanism is unclear. To clarify this, we examined the association of AKI and new-onset or worsening proteinuria during the 12 months following hospitalization in a national retrospective cohort of United States Veterans hospitalized between 2004-2012. Patients with and without AKI were matched using baseline demographics, comorbidities, proteinuria, estimated glomerular filtration rate, blood pressure, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker (ACEI/ARB) use, and inpatient exposures linked to AKI. The distribution of proteinuria over one year post-discharge in the matched cohort was compared using inverse probability sampling weights. Subgroup analyses were based on diabetes, pre-admission ACEI/ARB use, and AKI severity. Among the 90,614 matched AKI and non-AKI pairs, the median estimated glomerular filtration rate was 62 mL/min/1.73m. The prevalence of diabetes and hypertension were 48% and 78%, respectively. The odds of having one plus or greater dipstick proteinuria was significantly higher during each month of follow-up in patients with AKI than in patients without AKI (odds ratio range 1.20-1.39). Odds were higher in patients with Stage II or III AKI (odds ratios 1.32-1.81) than in Stage I AKI (odds ratios 1.18-1.32), using non-AKI as the reference group. Results were consistent regardless of diabetes status or baseline ACEI/ARB use. Thus, AKI is a risk factor for incident or worsening proteinuria, suggesting a possible mechanism linking AKI and future CKD. The type of proteinuria, physiology, and clinical significance warrant further study as a potentially modifiable risk factor in the pathway from AKI to CKD.
Published by Elsevier Inc.
BACKGROUND - Critically ill patients with acute kidney injury (AKI) can be divided into two subphenotypes, resolving or nonresolving, on the basis of the trajectory of serum creatinine. It is unknown if the biology underlying these two AKI recovery patterns is different.
METHODS - We measured eight circulating biomarkers in plasma obtained from a cohort of patients admitted to an intensive care unit (ICU) (n = 1241) with systemic inflammatory response syndrome. The biomarkers were representative of several biologic processes: apoptosis (soluble Fas), inflammation (soluble tumor necrosis factor receptor 1, interleukin 6, interleukin 8) and endothelial dysfunction, (angiopoietin 1, angiopoietin 2, and soluble vascular cell adhesion molecule 1). We tested for associations between biomarker levels and AKI subphenotypes using relative risk regression accounting for multiple hypotheses with the Bonferroni correction.
RESULTS - During the first 3 days of ICU admission, 868 (70%) subjects developed AKI; 502 (40%) had a resolving subphenotype, and 366 (29%) had a nonresolving subphenotype. Hospital mortality was 12% in the resolving subphenotype and 21% in the nonresolving subphenotype. Soluble Fas was the only biomarker associated with a nonresolving subphenotype after adjustment for age, body mass index, diabetes, and Acute Physiology and Chronic Health Evaluation III score (p = 0.005).
CONCLUSIONS - Identifying modifiable targets in the Fas-mediated pathway may lead to strategies for prevention and treatment of a clinically important form of AKI.
The cellular responses that occur following acute kidney injury (AKI) are complex and dynamic, involving multiple cells types and molecular pathways. For this reason, early selection of defined molecular targets for therapeutic intervention is unlikely to be effective in complex in vivo models of AKI, let alone Phase 3 clinical trials in patients with even more complex AKI pathobiology. Phenotypic screening using zebrafish provides an attractive alternative that does not require prior knowledge of molecular targets and may identify compounds that modify multiple targets that might be missed in more traditional target-based screens. In this review, we discuss results of an academic drug discovery campaign that used zebrafish as a primary screening tool to discover compounds with favorable absorption, metabolism, and toxicity that enhance repair when given late after injury in multiple models of AKI. We discuss how this screening campaign is being integrated into a more comprehensive, phenotypic, and target-based screen for lead compound optimization.
© 2017 S. Karger AG, Basel.