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Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis
Background. The aim of this study is to evaluate the usefulness of serum N-glycan profiling for prognosis in hemodialysis patients. Methods. Serum N-glycan analysis was performed in 100 hemodialysis patients in June 2008 using the glycoblotting method, which allows high-throughput, comprehensive, an...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3884780/ https://www.ncbi.nlm.nih.gov/pubmed/24453820 http://dx.doi.org/10.1155/2013/268407 |
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author | Hatakeyama, Shingo Amano, Maho Tobisawa, Yuki Yoneyama, Tohru Tsushima, Megumi Hirose, Kazuko Yoneyama, Takahiro Hashimoto, Yasuhiro Koie, Takuya Saitoh, Hisao Yamaya, Kanemitsu Funyu, Tomihisa Nishimura, Shin-Ichiro Ohyama, Chikara |
author_facet | Hatakeyama, Shingo Amano, Maho Tobisawa, Yuki Yoneyama, Tohru Tsushima, Megumi Hirose, Kazuko Yoneyama, Takahiro Hashimoto, Yasuhiro Koie, Takuya Saitoh, Hisao Yamaya, Kanemitsu Funyu, Tomihisa Nishimura, Shin-Ichiro Ohyama, Chikara |
author_sort | Hatakeyama, Shingo |
collection | PubMed |
description | Background. The aim of this study is to evaluate the usefulness of serum N-glycan profiling for prognosis in hemodialysis patients. Methods. Serum N-glycan analysis was performed in 100 hemodialysis patients in June 2008 using the glycoblotting method, which allows high-throughput, comprehensive, and quantitative N-glycan analysis. All patients were longitudinally followed up for 5 years. To evaluate the independent predictors for prognosis, patients' background, blood biochemistry, and N-glycans intensity were analyzed using Cox regression multivariate analysis. Selected N-glycans and independent factors were evaluated using the log-rank test with the Kaplan-Meier method to identify the predictive indicators for prognosis. Each patient was categorized according to the number of risk factors to evaluate the predictive potential of the risk criteria for prognosis. Results. In total, 56 N-glycan types were identified in the hemodialysis patients. Cox regression multivariate analysis showed cardiovascular events, body mass index, maximum intima media thickness, and the serum N-glycan intensity of peak number 49 were predictive indicators for overall survival. Risk classification according to the number of independent risk factors revealed significantly poor survival by increasing the number of risk factors. Conclusions. Serum N-glycan profiling may have a potential to predict prognosis in patients undergoing hemodialysis. |
format | Online Article Text |
id | pubmed-3884780 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-38847802014-01-21 Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis Hatakeyama, Shingo Amano, Maho Tobisawa, Yuki Yoneyama, Tohru Tsushima, Megumi Hirose, Kazuko Yoneyama, Takahiro Hashimoto, Yasuhiro Koie, Takuya Saitoh, Hisao Yamaya, Kanemitsu Funyu, Tomihisa Nishimura, Shin-Ichiro Ohyama, Chikara ScientificWorldJournal Research Article Background. The aim of this study is to evaluate the usefulness of serum N-glycan profiling for prognosis in hemodialysis patients. Methods. Serum N-glycan analysis was performed in 100 hemodialysis patients in June 2008 using the glycoblotting method, which allows high-throughput, comprehensive, and quantitative N-glycan analysis. All patients were longitudinally followed up for 5 years. To evaluate the independent predictors for prognosis, patients' background, blood biochemistry, and N-glycans intensity were analyzed using Cox regression multivariate analysis. Selected N-glycans and independent factors were evaluated using the log-rank test with the Kaplan-Meier method to identify the predictive indicators for prognosis. Each patient was categorized according to the number of risk factors to evaluate the predictive potential of the risk criteria for prognosis. Results. In total, 56 N-glycan types were identified in the hemodialysis patients. Cox regression multivariate analysis showed cardiovascular events, body mass index, maximum intima media thickness, and the serum N-glycan intensity of peak number 49 were predictive indicators for overall survival. Risk classification according to the number of independent risk factors revealed significantly poor survival by increasing the number of risk factors. Conclusions. Serum N-glycan profiling may have a potential to predict prognosis in patients undergoing hemodialysis. Hindawi Publishing Corporation 2013-12-23 /pmc/articles/PMC3884780/ /pubmed/24453820 http://dx.doi.org/10.1155/2013/268407 Text en Copyright © 2013 Shingo Hatakeyama et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hatakeyama, Shingo Amano, Maho Tobisawa, Yuki Yoneyama, Tohru Tsushima, Megumi Hirose, Kazuko Yoneyama, Takahiro Hashimoto, Yasuhiro Koie, Takuya Saitoh, Hisao Yamaya, Kanemitsu Funyu, Tomihisa Nishimura, Shin-Ichiro Ohyama, Chikara Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title | Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title_full | Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title_fullStr | Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title_full_unstemmed | Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title_short | Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis |
title_sort | serum n-glycan profiling predicts prognosis in patients undergoing hemodialysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3884780/ https://www.ncbi.nlm.nih.gov/pubmed/24453820 http://dx.doi.org/10.1155/2013/268407 |
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