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Nanoparticle Detection of Urinary Markers for Point-of-Care Diagnosis of Kidney Injury.

ABSTRACT: The high incidence of acute and chronic kidney injury due to various environmental factors such as heavy metals or chemicals has been a major problem in developing countries. However, the diagnosis of kidney injury in these areas can be more challenging due to the lack of highly sensitive and specific techniques that can be applied in point-of-care settings. To address this, we have developed a technique called 'micro-urine nanoparticle detection (?UNPD)', that allows the detection of trace amounts of molecular markers in urine. Specifically, this technique utilizes an automated on-chip assay followed by detection with a hand-held device for the read-out. Using the ?UNPD technology, the kidney injury markers KIM-1 and Cystatin C were detected down to concentrations of 0.1 ng/ml and 20 ng/ml respectively, which meets the cut-off range required to identify patients with acute or chronic kidney injury. Thus, we show that the ?UNPD technology enables point of care and non-invasive detection of kidney injury, and has potential for applications in diagnosing kidney injury with high sensitivity in resource-limited settings.

SUBMITTER: Chung HJ

PROVIDER: S-EPMC4506142 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Nanoparticle Detection of Urinary Markers for Point-of-Care Diagnosis of Kidney Injury.

Chung Hyun Jung HJ Pellegrini Kathryn L KL Chung Jaehoon J Wanigasuriya Kamani K Jayawardene Innocent I Lee Kyungheon K Lee Hakho H Vaidya Vishal S VS Weissleder Ralph R

PloS one 20150717 7

The high incidence of acute and chronic kidney injury due to various environmental factors such as heavy metals or chemicals has been a major problem in developing countries. However, the diagnosis of kidney injury in these areas can be more challenging due to the lack of highly sensitive and specific techniques that can be applied in point-of-care settings. To address this, we have developed a technique called 'micro-urine nanoparticle detection (μUNPD)', that allows the detection of trace amou ...[more]

PMID: 26186708

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Project description:Objectives: Secretion of extracellular vesicles (EV) and associated micro-RNAs (miR) is altered during cellular stress and may serve as biomarkers of organ injury. We hypothesized that measuring changes in urinary levels of EV and miR will predict the onset of acute kidney injury in cardiac surgery patients. Design: Predictive accuracy biomarker study performed in the cohort of the REVAKI-2 trial Setting: Single center ICU between September 2015 and September 2018 Interventions: Intravenous sildenafil citrate 12.5 mg kg-1 over 150 min or dextrose 5% at the commencement of surgery. Measurements and main results: Urine samples were collected before and 24 hours after the procedure from 93 cardiac surgery patients. Urine EV concentrations and size distribution were assessed using NanoSight. EV derivation and levels were measured using flow cytometry. Samples from 10 selected patients were sequenced to detect differentially expressed miR. Verification was performed with advanced TaqMan assays in samples from all patients. Urine EV concentrations significantly increased in patients with AKI after surgery, with the percentage of EV positive for aquaporin-2 and β1-integrin also increasing. Pre surgery podocalyxin-positive EV were significantly lower, and β1-integrin EV werehigher in patients with AKI. The levels of the former correlated with the severity of theinjury. miR-125a-5p was expressed at higher levels in urine from patients with AKI stage 2/3. Levels of miR-10a-5p decreased after surgery in AKI patients; its levels correlated with the severity of the injury. Preoperative levels of podocalyxin EVs and miR-125a-5p had moderate AKI predictive value and, in a logistic model together with ICU lactate levels, offered good (AUC = 80.9%) AKI prediction. Conclusions: Lower levels of podocalyxin-positive EV at baseline predict the severity of post-surgery AKI. Urine EV concentrations and miR expression offer excellent predictive accuracy when combined with commonly measured biomarkers.

Project description:BackgroundAdverse outcome of chronic kidney disease, such as end stage renal disease, is a significant burden on personal health and healthcare costs. Urinary tubular injury markers, such as NGAL, KIM-1 and NAG, could provide useful prognostic value for the early identification of high-risk patients. However, discrepancies between recent large prospective studies have resulted in controversy regarding the potential clinical value of these markers. Therefore, we conducted the first meta-analysis to provide a more persuasive argument to this debate.MethodsIn the current meta-analysis, based on ten prospective studies involving 29366 participants, we evaluated the role of urinary tubular injury markers (NGAL, KIM-1 and NAG) in predicting clinical outcomes including CKD stage 3, end stage renal disease and mortality. The prognostic values of these biomarkers were estimated using relative risks and 95% confidence interval in adjusted models. All risk estimates were normalized to those of 1 standard deviation increase in log-scale concentrations to minimize heterogeneity. Fixed-effects models were adopted to combine risk estimates. The quality of the research and between-study heterogeneity were evaluated. The level of research evidence was identified according to the GRADE profiler.ResultsuNGAL was identified as an independent risk predictor of ESRD (pooled adjusted relative risk: 1.40[1.21 to 1.61], p<0.001) and of overall mortality (pooled adjusted relative risk: 1.10[1.03 to 1.18], p = 0.001) in patients with chronic kidney disease. A borderline significance of uKIM-1 in predicting CKD stage 3 independently in the community-based population was observed (pooled adjusted relative risk: 1.13[1.00 to 1.27], p = 0.057). Only the prognostic value of uNGAL for ESRD was supported by a grade B level of evidence.ConclusionThe concentration of uNGAL can be used in practice as an independent predictor of end stage renal disease among patients with chronic kidney disease, but it may be not useful in predicting disease progression to CKD stage 3 among community-based population.

Dataset Information

Nanoparticle Detection of Urinary Markers for Point-of-Care Diagnosis of Kidney Injury.

Publications

Nanoparticle Detection of Urinary Markers for Point-of-Care Diagnosis of Kidney Injury.

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