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Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system
BACKGROUND: Additional urinary biomarkers for diabetic nephropathy (DN) are needed, providing early and reliable diagnosis and new insights into its mechanisms. Rigorous selection criteria and homogeneous study population may improve reproducibility of the proteomic approach. METHODS: Long-term type...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372325/ https://www.ncbi.nlm.nih.gov/pubmed/28359252 http://dx.doi.org/10.1186/s12882-017-0519-4 |
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author | Vitova, Lenka Tuma, Zdenek Moravec, Jiri Kvapil, Milan Matejovic, Martin Mares, Jan |
author_facet | Vitova, Lenka Tuma, Zdenek Moravec, Jiri Kvapil, Milan Matejovic, Martin Mares, Jan |
author_sort | Vitova, Lenka |
collection | PubMed |
description | BACKGROUND: Additional urinary biomarkers for diabetic nephropathy (DN) are needed, providing early and reliable diagnosis and new insights into its mechanisms. Rigorous selection criteria and homogeneous study population may improve reproducibility of the proteomic approach. METHODS: Long-term type 1 diabetes patients without metabolic comorbidities were included, 11 with sustained microalbuminuria (MA) and 14 without MA (nMA). Morning urine proteins were precipitated and resolved by 2D electrophoresis. Principal component analysis (PCA) and Projection to latent structures discriminatory analysis (PLS-DA) were adopted to assess general data validity, to pick protein fractions for identification with mass spectrometry (MS), and to test predictive value of the resulting model. RESULTS: Proteins (n = 113) detected in more than 90% patients were considered representative. Unsupervised PCA showed excellent natural data clustering without outliers. Protein spots reaching Variable Importance in Projection score above 1 in PLS (n = 42) were subjected to MS, yielding 33 positive identifications. The PLS model rebuilt with these proteins achieved accurate classification of all patients (R2X = 0.553, R2Y = 0.953, Q2 = 0.947). Thus, multiple earlier recognized biomarkers of DN were confirmed and several putative new biomarkers suggested. Among them, the highest significance was met in kininogen-1. Its activation products detected in nMA patients exceeded by an order of magnitude the amount found in MA patients. CONCLUSIONS: Reducing metabolic complexity of the diseased and control groups by meticulous patients’ selection allows to focus the biomarker search in DN. Suggested new biomarkers, particularly kininogen fragments, exhibit the highest degree of correlation with MA and substantiate validation in larger and more varied cohorts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12882-017-0519-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5372325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53723252017-03-31 Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system Vitova, Lenka Tuma, Zdenek Moravec, Jiri Kvapil, Milan Matejovic, Martin Mares, Jan BMC Nephrol Research Article BACKGROUND: Additional urinary biomarkers for diabetic nephropathy (DN) are needed, providing early and reliable diagnosis and new insights into its mechanisms. Rigorous selection criteria and homogeneous study population may improve reproducibility of the proteomic approach. METHODS: Long-term type 1 diabetes patients without metabolic comorbidities were included, 11 with sustained microalbuminuria (MA) and 14 without MA (nMA). Morning urine proteins were precipitated and resolved by 2D electrophoresis. Principal component analysis (PCA) and Projection to latent structures discriminatory analysis (PLS-DA) were adopted to assess general data validity, to pick protein fractions for identification with mass spectrometry (MS), and to test predictive value of the resulting model. RESULTS: Proteins (n = 113) detected in more than 90% patients were considered representative. Unsupervised PCA showed excellent natural data clustering without outliers. Protein spots reaching Variable Importance in Projection score above 1 in PLS (n = 42) were subjected to MS, yielding 33 positive identifications. The PLS model rebuilt with these proteins achieved accurate classification of all patients (R2X = 0.553, R2Y = 0.953, Q2 = 0.947). Thus, multiple earlier recognized biomarkers of DN were confirmed and several putative new biomarkers suggested. Among them, the highest significance was met in kininogen-1. Its activation products detected in nMA patients exceeded by an order of magnitude the amount found in MA patients. CONCLUSIONS: Reducing metabolic complexity of the diseased and control groups by meticulous patients’ selection allows to focus the biomarker search in DN. Suggested new biomarkers, particularly kininogen fragments, exhibit the highest degree of correlation with MA and substantiate validation in larger and more varied cohorts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12882-017-0519-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-30 /pmc/articles/PMC5372325/ /pubmed/28359252 http://dx.doi.org/10.1186/s12882-017-0519-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Vitova, Lenka Tuma, Zdenek Moravec, Jiri Kvapil, Milan Matejovic, Martin Mares, Jan Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title | Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title_full | Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title_fullStr | Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title_full_unstemmed | Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title_short | Early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
title_sort | early urinary biomarkers of diabetic nephropathy in type 1 diabetes mellitus show involvement of kallikrein-kinin system |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372325/ https://www.ncbi.nlm.nih.gov/pubmed/28359252 http://dx.doi.org/10.1186/s12882-017-0519-4 |
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