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Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling
A critical issue in the management of chronic kidney disease (CKD) is to prevent patients from the progression to end-stage kidney disease (ESKD), however, there is only limited number of biomarkers for the discrimination of the high-risk CKD patients. We aimed to identify the metabolites which poss...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870629/ https://www.ncbi.nlm.nih.gov/pubmed/27188985 http://dx.doi.org/10.1038/srep26138 |
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author | Kimura, Tomonori Yasuda, Keiko Yamamoto, Ryohei Soga, Tomoyoshi Rakugi, Hiromi Hayashi, Terumasa Isaka, Yoshitaka |
author_facet | Kimura, Tomonori Yasuda, Keiko Yamamoto, Ryohei Soga, Tomoyoshi Rakugi, Hiromi Hayashi, Terumasa Isaka, Yoshitaka |
author_sort | Kimura, Tomonori |
collection | PubMed |
description | A critical issue in the management of chronic kidney disease (CKD) is to prevent patients from the progression to end-stage kidney disease (ESKD), however, there is only limited number of biomarkers for the discrimination of the high-risk CKD patients. We aimed to identify the metabolites which possess the ability to predict the earlier kidney deterioration. We performed capillary electrophoresis and liquid chromatography mass spectrometry (CE-MS)-based metabolic profiling in a prospective cohort, which consisted of referred 112 CKD patients with median follow-up period of 4.4 years. The association between the levels of candidate metabolites and the outcomes (progression to ESKD alone or in combination with death before ESKD) were assessed by multivariate Cox proportional hazard models after adjusting for the baseline covariates. A total of 218 metabolites were detected in the plasma of CKD patients. We identified 16 metabolites which have predictive values for the composite outcome: The risk for composite outcome was elevated from 2.0- to 8.0-fold in those with higher levels of 16 plasma metabolites. Our results suggest that the measurement of these metabolites may facilitate CKD management by predicting the risk of progression to ESKD. |
format | Online Article Text |
id | pubmed-4870629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48706292016-06-01 Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling Kimura, Tomonori Yasuda, Keiko Yamamoto, Ryohei Soga, Tomoyoshi Rakugi, Hiromi Hayashi, Terumasa Isaka, Yoshitaka Sci Rep Article A critical issue in the management of chronic kidney disease (CKD) is to prevent patients from the progression to end-stage kidney disease (ESKD), however, there is only limited number of biomarkers for the discrimination of the high-risk CKD patients. We aimed to identify the metabolites which possess the ability to predict the earlier kidney deterioration. We performed capillary electrophoresis and liquid chromatography mass spectrometry (CE-MS)-based metabolic profiling in a prospective cohort, which consisted of referred 112 CKD patients with median follow-up period of 4.4 years. The association between the levels of candidate metabolites and the outcomes (progression to ESKD alone or in combination with death before ESKD) were assessed by multivariate Cox proportional hazard models after adjusting for the baseline covariates. A total of 218 metabolites were detected in the plasma of CKD patients. We identified 16 metabolites which have predictive values for the composite outcome: The risk for composite outcome was elevated from 2.0- to 8.0-fold in those with higher levels of 16 plasma metabolites. Our results suggest that the measurement of these metabolites may facilitate CKD management by predicting the risk of progression to ESKD. Nature Publishing Group 2016-05-18 /pmc/articles/PMC4870629/ /pubmed/27188985 http://dx.doi.org/10.1038/srep26138 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Kimura, Tomonori Yasuda, Keiko Yamamoto, Ryohei Soga, Tomoyoshi Rakugi, Hiromi Hayashi, Terumasa Isaka, Yoshitaka Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title | Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title_full | Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title_fullStr | Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title_full_unstemmed | Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title_short | Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
title_sort | identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870629/ https://www.ncbi.nlm.nih.gov/pubmed/27188985 http://dx.doi.org/10.1038/srep26138 |
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