Literature DB >> 20224435

Identification of diagnostic urinary biomarkers for acute kidney injury.

Sanju A Varghese1, Thomas B Powell, Michael G Janech, Milos N Budisavljevic, Romesh C Stanislaus, Jonas S Almeida, John M Arthur.   

Abstract

Acute kidney injury (AKI) is an important cause of death among hospitalized patients. The 2 most common causes of AKI are acute tubular necrosis (ATN) and prerenal azotemia (PRA). Appropriate diagnosis of the disease is important but often difficult. We analyzed urine proteins by 2-dimensional gel electrophoresis from 38 patients with AKI. Patients were randomly assigned to a training set, an internal test set, or an external validation set. Spot abundances were analyzed by artificial neural networks to identify biomarkers that differentiate between ATN and PRA. When the trained neural network algorithm was tested against the training data, it identified the diagnosis for 16 of 18 patients in the training set and all 10 patients in the internal test set. The accuracy was validated in the novel external set of patients where conditions of 9 of 10 patients were correctly diagnosed including 5 of 5 with ATN and 4 of 5 with PRA. Plasma retinol-binding protein was identified in 1 spot and a fragment of albumin and plasma retinol-binding protein in the other. These proteins are candidate markers for diagnostic assays of AKI.

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Year:  2010        PMID: 20224435      PMCID: PMC2864920          DOI: 10.231/JIM.0b013e3181d473e7

Source DB:  PubMed          Journal:  J Investig Med        ISSN: 1081-5589            Impact factor:   2.895


  35 in total

1.  Epidemiology of de novo acute renal failure in hospitalized African Americans: comparing community-acquired vs hospital-acquired disease.

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Review 2.  Predictive non-linear modeling of complex data by artificial neural networks.

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Journal:  Curr Opin Biotechnol       Date:  2002-02       Impact factor: 9.740

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Journal:  Kidney Int       Date:  1996-09       Impact factor: 10.612

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Journal:  J Clin Pathol       Date:  1993-05       Impact factor: 3.411

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Journal:  J Am Soc Nephrol       Date:  1994-01       Impact factor: 10.121

8.  Urinary excretion of beta 2-glycoprotein-1 (apolipoprotein H) and other markers of tubular malfunction in "non-tubular" renal disease.

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Journal:  J Clin Pathol       Date:  1992-07       Impact factor: 3.411

9.  Kidney Injury Molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury.

Authors:  Won K Han; Veronique Bailly; Rekha Abichandani; Ravi Thadhani; Joseph V Bonventre
Journal:  Kidney Int       Date:  2002-07       Impact factor: 10.612

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Authors:  F G Brivet; D J Kleinknecht; P Loirat; P J Landais
Journal:  Crit Care Med       Date:  1996-02       Impact factor: 7.598

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  6 in total

Review 1.  Emergence of biomarkers in nephropharmacology.

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2.  Quantitative mass spectrometry of urinary biomarkers.

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3.  A comprehensive analysis and annotation of human normal urinary proteome.

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4.  Correlation Between Tenofovir Drug Levels and the Renal Biomarkers RBP-4 and ß2M in the ION-4 Study Cohort.

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Journal:  Open Forum Infect Dis       Date:  2019-01-24       Impact factor: 3.835

Review 5.  The Clinical Significance of Urinary Retinol-Binding Protein 4: A Review.

Authors:  Krzysztof Ratajczyk; Andrzej Konieczny; Adrian Czekaj; Paweł Piotrów; Marek Fiutowski; Kornelia Krakowska; Paweł Kowal; Wojciech Witkiewicz; Karolina Marek-Bukowiec
Journal:  Int J Environ Res Public Health       Date:  2022-08-11       Impact factor: 4.614

6.  Urinary Kininogen-1 and Retinol binding protein-4 respond to Acute Kidney Injury: predictors of patient prognosis?

Authors:  Laura Gonzalez-Calero; Marta Martin-Lorenzo; Angeles Ramos-Barron; Jorge Ruiz-Criado; Aroa S Maroto; Alberto Ortiz; Carlos Gomez-Alamillo; Manuel Arias; Fernando Vivanco; Gloria Alvarez-Llamas
Journal:  Sci Rep       Date:  2016-01-21       Impact factor: 4.379

  6 in total

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