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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
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.
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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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