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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| Format: | Article |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/268407 |
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| author | Shingo Hatakeyama Maho Amano Yuki Tobisawa Tohru Yoneyama Megumi Tsushima Kazuko Hirose Takahiro Yoneyama Yasuhiro Hashimoto Takuya Koie Hisao Saitoh Kanemitsu Yamaya Tomihisa Funyu Shin-Ichiro Nishimura Chikara Ohyama |
| author_facet | Shingo Hatakeyama Maho Amano Yuki Tobisawa Tohru Yoneyama Megumi Tsushima Kazuko Hirose Takahiro Yoneyama Yasuhiro Hashimoto Takuya Koie Hisao Saitoh Kanemitsu Yamaya Tomihisa Funyu Shin-Ichiro Nishimura Chikara Ohyama |
| author_sort | Shingo Hatakeyama |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-edfd40ed139f43a0ae554bcdd2f5f3dc |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-edfd40ed139f43a0ae554bcdd2f5f3dc2025-02-03T05:51:20ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/268407268407Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing HemodialysisShingo Hatakeyama0Maho Amano1Yuki Tobisawa2Tohru Yoneyama3Megumi Tsushima4Kazuko Hirose5Takahiro Yoneyama6Yasuhiro Hashimoto7Takuya Koie8Hisao Saitoh9Kanemitsu Yamaya10Tomihisa Funyu11Shin-Ichiro Nishimura12Chikara Ohyama13Department of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanFaculty of Advanced Life Science and Frontier Research Center for Post-Genome Science and Technology, Hokkaido University, Sapporo 001-0021, JapanDepartment of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Advanced Transplant and Regenerative Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Radiological Technology, Hirosaki University School of Health Sciences, Hirosaki 036-8562, JapanFaculty of Advanced Life Science and Frontier Research Center for Post-Genome Science and Technology, Hokkaido University, Sapporo 001-0021, JapanDepartment of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Advanced Transplant and Regenerative Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanDepartment of Urology, Oyokyo Kidney Research Institute, Hirosaki 036-8243, JapanDepartment of Urology, Oyokyo Kidney Research Institute, Hirosaki 036-8243, JapanDepartment of Urology, Oyokyo Kidney Research Institute, Hirosaki 036-8243, JapanFaculty of Advanced Life Science and Frontier Research Center for Post-Genome Science and Technology, Hokkaido University, Sapporo 001-0021, JapanDepartment of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, JapanBackground. 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.http://dx.doi.org/10.1155/2013/268407 |
| spellingShingle | Shingo Hatakeyama Maho Amano Yuki Tobisawa Tohru Yoneyama Megumi Tsushima Kazuko Hirose Takahiro Yoneyama Yasuhiro Hashimoto Takuya Koie Hisao Saitoh Kanemitsu Yamaya Tomihisa Funyu Shin-Ichiro Nishimura Chikara Ohyama Serum N-Glycan Profiling Predicts Prognosis in Patients Undergoing Hemodialysis The Scientific World Journal |
| 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 |
| url | http://dx.doi.org/10.1155/2013/268407 |
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