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CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis

National Kidney Foundation CKD staging has allowed uniformity in studies on CKD. However, early diagnosis and predicting progression to end stage renal disease are yet to be improved. Seventy six patients with different levels of CKD, including outpatients and dialysed patients were studied for tran...

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Autores principales: Argilés, Àngel, Siwy, Justyna, Duranton, Flore, Gayrard, Nathalie, Dakna, Mohammed, Lundin, Ulrika, Osaba, Lourdes, Delles, Christian, Mourad, Georges, Weinberger, Klaus M., Mischak, Harald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3653906/
https://www.ncbi.nlm.nih.gov/pubmed/23690958
http://dx.doi.org/10.1371/journal.pone.0062837
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author Argilés, Àngel
Siwy, Justyna
Duranton, Flore
Gayrard, Nathalie
Dakna, Mohammed
Lundin, Ulrika
Osaba, Lourdes
Delles, Christian
Mourad, Georges
Weinberger, Klaus M.
Mischak, Harald
author_facet Argilés, Àngel
Siwy, Justyna
Duranton, Flore
Gayrard, Nathalie
Dakna, Mohammed
Lundin, Ulrika
Osaba, Lourdes
Delles, Christian
Mourad, Georges
Weinberger, Klaus M.
Mischak, Harald
author_sort Argilés, Àngel
collection PubMed
description National Kidney Foundation CKD staging has allowed uniformity in studies on CKD. However, early diagnosis and predicting progression to end stage renal disease are yet to be improved. Seventy six patients with different levels of CKD, including outpatients and dialysed patients were studied for transcriptome, metabolome and proteome description. High resolution urinary proteome analysis was blindly performed in the 53 non-anuric out of the 76 CKD patients. In addition to routine clinical parameters, CKD273, a urinary proteomics-based classifier and its peptides were quantified. The baseline values were analyzed with regard to the clinical parameters and the occurrence of death or renal death during follow-up (3.6 years) as the main outcome measurements. None of the patients with CKD273<0.55 required dialysis or died while all fifteen patients that reached an endpoint had a CKD273 score >0.55. Unsupervised clustering analysis of the CKD273 peptides separated the patients into two main groups differing in CKD associated parameters. Among the 273 biomarkers, peptides derived from serum proteins were relatively increased in patients with lower glomerular filtration rate, while collagen-derived peptides were relatively decreased (p<0.05; Spearman). CKD273 was different in the groups with different renal function (p<0.003). The CKD273 classifier separated CKD patients according to their renal function and informed on the likelihood of experiencing adverse outcome. Recently defined in a large population, CKD273 is the first proteomic-based classifier successfully tested for prognosis of CKD progression in an independent cohort.
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spelling pubmed-36539062013-05-20 CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis Argilés, Àngel Siwy, Justyna Duranton, Flore Gayrard, Nathalie Dakna, Mohammed Lundin, Ulrika Osaba, Lourdes Delles, Christian Mourad, Georges Weinberger, Klaus M. Mischak, Harald PLoS One Research Article National Kidney Foundation CKD staging has allowed uniformity in studies on CKD. However, early diagnosis and predicting progression to end stage renal disease are yet to be improved. Seventy six patients with different levels of CKD, including outpatients and dialysed patients were studied for transcriptome, metabolome and proteome description. High resolution urinary proteome analysis was blindly performed in the 53 non-anuric out of the 76 CKD patients. In addition to routine clinical parameters, CKD273, a urinary proteomics-based classifier and its peptides were quantified. The baseline values were analyzed with regard to the clinical parameters and the occurrence of death or renal death during follow-up (3.6 years) as the main outcome measurements. None of the patients with CKD273<0.55 required dialysis or died while all fifteen patients that reached an endpoint had a CKD273 score >0.55. Unsupervised clustering analysis of the CKD273 peptides separated the patients into two main groups differing in CKD associated parameters. Among the 273 biomarkers, peptides derived from serum proteins were relatively increased in patients with lower glomerular filtration rate, while collagen-derived peptides were relatively decreased (p<0.05; Spearman). CKD273 was different in the groups with different renal function (p<0.003). The CKD273 classifier separated CKD patients according to their renal function and informed on the likelihood of experiencing adverse outcome. Recently defined in a large population, CKD273 is the first proteomic-based classifier successfully tested for prognosis of CKD progression in an independent cohort. Public Library of Science 2013-05-14 /pmc/articles/PMC3653906/ /pubmed/23690958 http://dx.doi.org/10.1371/journal.pone.0062837 Text en © 2013 Argilés et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Argilés, Àngel
Siwy, Justyna
Duranton, Flore
Gayrard, Nathalie
Dakna, Mohammed
Lundin, Ulrika
Osaba, Lourdes
Delles, Christian
Mourad, Georges
Weinberger, Klaus M.
Mischak, Harald
CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title_full CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title_fullStr CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title_full_unstemmed CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title_short CKD273, a New Proteomics Classifier Assessing CKD and Its Prognosis
title_sort ckd273, a new proteomics classifier assessing ckd and its prognosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3653906/
https://www.ncbi.nlm.nih.gov/pubmed/23690958
http://dx.doi.org/10.1371/journal.pone.0062837
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