Author:
Kujat Jacob,Langhans Valerie,Brand Hannah,Freund Paul,Görlich Nina,Wagner Leonie,Metzke Diana,Timm Sara,Ochs Matthias,Grützkau Andreas,Baumgart Sabine,Skopnik Christopher M.,Hiepe Falk,Riemekasten Gabriela,Klocke Jan,Enghard Philipp
Abstract
IntroductionAcute kidney injury (AKI) is associated with significant morbidity and mortality. The diagnosis is currently based on urine output and serum creatinine and there is a lack of biomarkers that directly reflect tubular damage. Here, we establish flow cytometric quantification of renal epithelial cells as a potential biomarker for quantifying the severity of tubular kidney damage and for predicting AKI outcome.MethodsA total of 84 patients with AKI were included in this study, divided into an exploratory cohort (n=21) and confirmatory cohort (n=63), as well as 25 controls. Urine of patients was collected and processed within 72 hours after AKI onset. Different urinary tubular epithelial cell (TEC) populations were identified and quantified by flow cytometry (FACS). Urinary cell counts were analyzed regarding AKI severity defined by KDIGO stage as well as renal recovery, length of hospital stay and occurrence of MAKE-30 events.ResultsUrinary TEC counts correlated with stages of AKI based on KDIGO classification and were significantly enriched in patients with AKI compared to healthy donors and inpatient controls in both cohorts. Furthermore, both proximal and distal TEC (pTEC, dTEC) counts performed well in identification of patients with AKI regardless of stage. Urinary amounts of pTEC and dTEC showed a strong correlation, with predominance of dTEC. Higher numbers of TEC were associated with extended length of hospital stay, while elevated pTEC counts were associated with the occurrence of MAKE-30 events. Follow-up measurements showed decreasing amounts of urinary TEC after AKI recovery over several days.ConclusionThe amount of urinary TEC directly reflects severity of tissue damage in human AKI. Our protocol furthermore provides a basis for a deeper phenotypic analysis of urinary TEC populations.
Publisher
Cold Spring Harbor Laboratory
Reference33 articles.
1. Acute kidney injury;Annual Review of Medicine,2016
2. Levey AS , James MT . In the Clinic: Acute Kidney Injury. Annals of Internal Medicine 2017; 167.
3. Chronic kidney disease after acute kidney injury: a systematic review and meta-analysis
4. Acute kidney injury network: Report of an initiative to improve outcomes in acute kidney injury;Critical Care,2007
5. Kidney disease: Improving global outcomes (KDIGO) acute kidney injury work group. KDIGO clinical practice guideline for acute kidney injury;Kidney International Supplements,2012
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