Literature DB >> 25578432

Changes in urine proteome accompanying diabetic nephropathy progression.

Andrzej Lewandowicz, Magdalena Bakun, Rafał Kohutnicki, Agnieszka Fabijańska, Michał Kistowski, Jacek Imiela, Michał Dadlez.   

Abstract

INTRODUCTION: Owing to the prevalence of type 2 diabetes, diabetic kidney disease (DKD) becomes the major cause of end-stage renal disease. The current markers of diabetic nephropathy are based on albuminuria and clinical signs of retinopathy. Sensitive and specific noninvasive diagnostic tools, unbiased by the presence of comorbidities, are needed, especially to detect the early stages of diabetic complications.
OBJECTIVES: The aim of the study was to analyze changes in urinary protein excretion based on the stage of DKD using quantitative proteomics. PATIENTS AND METHODS: A total of 27 healthy controls were age- and sex-matched to 72 diabetes patients classified into 3 groups: no signs of retinopathy or nephropathy (n = 33), retinopathy but no microalbuminuria (n = 15), and diabetic nephropathy (DN) based on overt albuminuria or microalbuminuria with retinopathy (n = 24). To assess the intergroup differences, samples were partially pooled, tagged using 8-plex iTRAQ reagents, and the resulting peptide mixture was resolved by isoelectrofocusing. The obtained fractions were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Data were analyzed using the MASCOT software and dedicated in-house proteomic data analysis programs.
RESULTS: The changes in the urine proteome following DKD progression involved some known protein markers of DN and several other proteins. Decreased levels of some proteins are presumably related to impaired secretory function of other organs affected by diabetes. In particular, a diminished excretion of pancreatic amylase and deoxyribonuclease I suggested exocrine pancreatic insufficiency (EPI), coexisting with type 2 diabetes.
CONCLUSIONS: A decrease in the urinary excretion of some pancreatic enzymes suggests EPI associated with diabetes. This hypothesis is yet to be verified; nevertheless, renal and extrarenal confounders must be considered when interpreting the results of quantitative urinary proteomics.

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Year:  2015        PMID: 25578432     DOI: 10.20452/pamw.2640

Source DB:  PubMed          Journal:  Pol Arch Med Wewn


  8 in total

Review 1.  Insights into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics.

Authors:  Julie A D Van; James W Scholey; Ana Konvalinka
Journal:  J Am Soc Nephrol       Date:  2017-02-03       Impact factor: 10.121

2.  Diabetic Nephropathy Assessment: Microtubule-Associated Protein 1 Light-Chain 3B a New Promising Biomarker.

Authors:  Magdy M Mohamed; Sanaa Eissa; Mona Mostafa; Marwa G A Hegazy
Journal:  Indian J Clin Biochem       Date:  2018-06-22

3.  Urine Proteomics Reveals Sex-Specific Response to Total Pancreatectomy With Islet Autotransplantation.

Authors:  Tue Bjerg Bennike; Kate Templeton; Kimino Fujimura; Melena D Bellin; Saima Ahmed; Christoph N Schlaffner; Rohit Arora; Zobeida Cruz-Monserrate; Ramy Arnaout; Gregory J Beilman; Amit S Grover; Darwin L Conwell; Hanno Steen
Journal:  Pancreas       Date:  2022-07-27       Impact factor: 3.243

Review 4.  Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy.

Authors:  G Currie; C Delles
Journal:  Curr Diab Rep       Date:  2016-11       Impact factor: 4.810

Review 5.  Human Urine Proteomics: Analytical Techniques and Clinical Applications in Renal Diseases.

Authors:  Shiva Kalantari; Ameneh Jafari; Raheleh Moradpoor; Elmira Ghasemi; Ensieh Khalkhal
Journal:  Int J Proteomics       Date:  2015-11-29

6.  Is Urinary NGAL Determination Useful for Monitoring Kidney Function and Assessment of Cardiovascular Disease? A 12-Month Observation of Patients with Type 2 Diabetes.

Authors:  Agnieszka Żyłka; Agnieszka Gala-Błądzińska; Paulina Dumnicka; Piotr Ceranowicz; Marek Kuźniewski; Krzysztof Gil; Rafał Olszanecki; Beata Kuśnierz-Cabala
Journal:  Dis Markers       Date:  2016-12-05       Impact factor: 3.434

7.  Urinary peptidomics and bioinformatics for the detection of diabetic kidney disease.

Authors:  Letícia de Almeida Brondani; Ariana Aguiar Soares; Mariana Recamonde-Mendoza; Angélica Dall'Agnol; Joíza Lins Camargo; Karina Mariante Monteiro; Sandra Pinho Silveiro
Journal:  Sci Rep       Date:  2020-01-27       Impact factor: 4.379

8.  Urine proteomics of primary membranous nephropathy using nanoscale liquid chromatography tandem mass spectrometry analysis.

Authors:  Lu Pang; Qianqian Li; Yan Li; Yi Liu; Nan Duan; Haixia Li
Journal:  Clin Proteomics       Date:  2018-02-07       Impact factor: 3.988

  8 in total

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