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© 2020. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Background: Post-stroke depression (PSD) is one of the most common complications in stroke survivors. But, there are still no objective methods to diagnose PSD. This study aims to identify potential biomarkers for diagnosing PSD in middle-aged stroke survivors.

Methods: Middle-aged subjects aged 30 to 59 years (92 PSD patients and 89 stroke survivors without depression) were included in this study. Urinary metabolites were detected by gas chromatography-mass spectrometry (GC-MS). Differential urinary metabolites and potential biomarkers were screened by applying statistical analysis.

Results: The different urinary metabolic phenotypes between PSD patients and stroke survivors without depression were identified. A total of 12 differential urinary metabolites were accurately identified by using orthogonal partial least-squares-discriminant analysis. After analyzing those 12 differential urinary metabolites by step-wise logistic regression analysis, only seven metabolites (palmitic acid, hydroxylamine, myristic acid, glyceric acid, lactic acid, tyrosine and azelaic acid) were finally selected as potential biomarkers for diagnosing PSD in middle-aged stroke survivors. A panel consisting of these potential biomarkers could effectively diagnose middle-aged PSD patients.

Conclusion: Urinary metabolic profiles were different between middle-aged PSD patients and stroke survivors without depression. Our results would be helpful in future for developing an objective method to diagnose PSD in middle-aged stroke survivors.

Details

Title
Identification of Potential Metabolite Markers for Middle-Aged Patients with Post-Stroke Depression Using Urine Metabolomics
Author
Xie, Jing; Han, Yu; Hong, Yueling; Wen-wen, Li; Pei, Qilin; Zhou, Xueyi; Zhang, Bingbing; Wang, Ying
Pages
2017-2024
Section
Original Research
Publication year
2020
Publication date
2020
Publisher
Taylor & Francis Ltd.
ISSN
1176-6328
e-ISSN
1178-2021
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2443713467
Copyright
© 2020. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.