Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus

Zi-Hong Liang,1 Yan-Bo Jia,2 Zi-Ru Li,1 Min Li,1 Mei-Ling Wang,1 Yong-Li Yun,1 Li-Jun Yu,1 Lei Shi,1 Run-Xiu Zhu11Department of Neurology, Inner Mongolia Autonomous Region People’s Hospital, Huhhot, Inner Mongolia, People’s Republic of China; 2Department of Orthopaedics, The Seco...

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Autores principales:	Liang ZH, Jia YB, Li ZR, Li M, Wang ML, Yun YL, Yu LJ, Shi L, Zhu RX
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2019
Materias:	type 2 diabetes mellitus post-stroke depression metabolite metabolomics Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/35b1a5f094a0482d9247b6bae4d58216
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spelling	oai:doaj.org-article:35b1a5f094a0482d9247b6bae4d582162021-12-02T07:25:14ZUrinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus1178-7007https://doaj.org/article/35b1a5f094a0482d9247b6bae4d582162019-08-01T00:00:00Zhttps://www.dovepress.com/urinary-biomarkers-for-diagnosing-poststroke-depression-in-patients-wi-peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Zi-Hong Liang,1 Yan-Bo Jia,2 Zi-Ru Li,1 Min Li,1 Mei-Ling Wang,1 Yong-Li Yun,1 Li-Jun Yu,1 Lei Shi,1 Run-Xiu Zhu11Department of Neurology, Inner Mongolia Autonomous Region People’s Hospital, Huhhot, Inner Mongolia, People’s Republic of China; 2Department of Orthopaedics, The Second Affiliated Hospital of Inner Mongolia Medical University, Huhhot, Inner Mongolia, People’s Republic of ChinaBackground: Depression can seriously affect the quality of life of type 2 diabetes mellitus (T2DM) patients after stroke. However, there were still no objective methods to diagnose T2DM patients with poststroke depression (PSD). Therefore, we conducted this study to deal with this problem.Methods: Gas chromatography-mass spectroscopy (GC-MS)-based metabolomics profiling method was used to profile the urinary metabolites from 83 nondepressed T2DM patients after stroke and 101 T2DM patients with PSD. The orthogonal partial least-squares discriminant analysis was conducted to explore the metabolic differences in T2DM patients with PSD. The logistic regression analysis was performed to identify the optimal and simplified biomarker panel for diagnosing T2DM patients with PSD. The receiver operating characteristic curve analysis was used to assess the diagnostic performance of this biomarker panel.Results: In total, 23 differential metabolites (7 decreased and 16 increased in T2DM patients with PSD) were found. A panel consisting of pseudouridine, malic acid, hypoxanthine, 3,4-dihydroxybutyric acid, fructose and inositol was identified. This panel could effectively separate T2DM patients with PSD from nondepressed T2DM patients after stroke. The area under the curve was 0.965 in the training set and 0.909 in the validation set. Meanwhile, we found that the galactose metabolism was significantly affected in T2DM patients with PSD.Conclusion: Our results could be helpful for future development of an objective method to diagnose T2DM patients with PSD and provide novel ideas to study the pathogenesis of depression.Keywords: type 2 diabetes mellitus, post-stroke depression, metabolite, metabolomicsLiang ZHJia YBLi ZRLi MWang MLYun YLYu LJShi LZhu RXDove Medical Pressarticletype 2 diabetes mellituspost-stroke depressionmetabolitemetabolomicsSpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 12, Pp 1379-1386 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	type 2 diabetes mellitus post-stroke depression metabolite metabolomics Specialties of internal medicine RC581-951
spellingShingle	type 2 diabetes mellitus post-stroke depression metabolite metabolomics Specialties of internal medicine RC581-951 Liang ZH Jia YB Li ZR Li M Wang ML Yun YL Yu LJ Shi L Zhu RX Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
description	Zi-Hong Liang,1 Yan-Bo Jia,2 Zi-Ru Li,1 Min Li,1 Mei-Ling Wang,1 Yong-Li Yun,1 Li-Jun Yu,1 Lei Shi,1 Run-Xiu Zhu11Department of Neurology, Inner Mongolia Autonomous Region People’s Hospital, Huhhot, Inner Mongolia, People’s Republic of China; 2Department of Orthopaedics, The Second Affiliated Hospital of Inner Mongolia Medical University, Huhhot, Inner Mongolia, People’s Republic of ChinaBackground: Depression can seriously affect the quality of life of type 2 diabetes mellitus (T2DM) patients after stroke. However, there were still no objective methods to diagnose T2DM patients with poststroke depression (PSD). Therefore, we conducted this study to deal with this problem.Methods: Gas chromatography-mass spectroscopy (GC-MS)-based metabolomics profiling method was used to profile the urinary metabolites from 83 nondepressed T2DM patients after stroke and 101 T2DM patients with PSD. The orthogonal partial least-squares discriminant analysis was conducted to explore the metabolic differences in T2DM patients with PSD. The logistic regression analysis was performed to identify the optimal and simplified biomarker panel for diagnosing T2DM patients with PSD. The receiver operating characteristic curve analysis was used to assess the diagnostic performance of this biomarker panel.Results: In total, 23 differential metabolites (7 decreased and 16 increased in T2DM patients with PSD) were found. A panel consisting of pseudouridine, malic acid, hypoxanthine, 3,4-dihydroxybutyric acid, fructose and inositol was identified. This panel could effectively separate T2DM patients with PSD from nondepressed T2DM patients after stroke. The area under the curve was 0.965 in the training set and 0.909 in the validation set. Meanwhile, we found that the galactose metabolism was significantly affected in T2DM patients with PSD.Conclusion: Our results could be helpful for future development of an objective method to diagnose T2DM patients with PSD and provide novel ideas to study the pathogenesis of depression.Keywords: type 2 diabetes mellitus, post-stroke depression, metabolite, metabolomics
format	article
author	Liang ZH Jia YB Li ZR Li M Wang ML Yun YL Yu LJ Shi L Zhu RX
author_facet	Liang ZH Jia YB Li ZR Li M Wang ML Yun YL Yu LJ Shi L Zhu RX
author_sort	Liang ZH
title	Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
title_short	Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
title_full	Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
title_fullStr	Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
title_full_unstemmed	Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
title_sort	urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus
publisher	Dove Medical Press
publishDate	2019
url	https://doaj.org/article/35b1a5f094a0482d9247b6bae4d58216
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Urinary biomarkers for diagnosing poststroke depression in patients with type 2 diabetes mellitus

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