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Identification of Potential Metabolite Markers for Middle-Aged Patients with Post-Stroke Depression Using Urine Metabolomics

Authors :
Yu Han
Xueyi Zhou
Bingbing Zhang
Qilin Pei
Wen-wen Li
Jing Xie
Yueling Hong
Ying Wang
Source :
Neuropsychiatric Disease and Treatment. 16:2017-2024
Publication Year :
2020
Publisher :
Informa UK Limited, 2020.

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

ISSN :
11782021
Volume :
16
Database :
OpenAIRE
Journal :
Neuropsychiatric Disease and Treatment
Accession number :
edsair.doi...........85d29d246d50f07be89f7307294ed7b1
Full Text :
https://doi.org/10.2147/ndt.s271990