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Objective diagnosis of post-stroke depression using NMR-based plasma metabonomics

Authors Hu Z, Fan S, Liu M, Zhong J, Cao D, Zheng P, Wang Y, Wei Y, Fang L, Xie P

Received 26 October 2018

Accepted for publication 3 March 2019

Published 10 April 2019 Volume 2019:15 Pages 867—881

DOI https://doi.org/10.2147/NDT.S192307

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Andrew Yee

Peer reviewer comments 2

Editor who approved publication: Professor Jun Chen


Zicheng Hu,1–3 Songhua Fan,1–3 Meiling Liu,1–3 Jiaju Zhong,1–3 Du Cao,1–3 Peng Zheng,1–3 Ying Wang,1–3 Youdong Wei,1–3 Liang Fang,1–3 Peng Xie1–3

1Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing, People’s Republic of China; 3Chongqing Key Laboratory of Neurobiology, Chongqing, People’s Republic of China

Background: Post-stroke depression (PSD) is a frequent and serious complication of stroke. However, the underlying molecular basis of PSD remains largely unknown, and no empirical laboratory tests were available to diagnose this disorder.
Materials and methods: A proton nuclear magnetic resonance (1H NMR)-based metabonomic approach was employed to profile plasma samples from 32 PSD, 35 stroke patients and 35 healthy comparison subjects (the training set) in order to identify metabolite biomarkers for PSD. Then, 10 PSD, 11 stroke patients and 11 healthy comparison subjects (test set) were used to validate the diagnostic performance of these biomarkers.
Results: The multivariate statistical analysis demonstrated that PSD group was significantly distinguishable from non-PSD groups (non-depression stroke patients and healthy comparison group). Five plasma metabolites (phenylalanine, tyrosine, 1-methylhistidine, 3-methylhistidine and LDL CH3-(CH2)n-) were identified responsible for distinguishing PSD from non-PSD subjects. These metabolites were mainly involved in neurotransmitter metabolism and oxidative stress. The biomarker panel composing of these metabolites was capable of distinguishing test samples with a sensitivity of 100.0% and a specificity of 95.5%.
Conclusion: Our findings suggest that plasma disturbances of neurotransmitter levels and oxidative stress were implicated in the onset of PSD; these disturbed metabolites biomarkers facilitate to the development of diagnostic tool for PSD.

Keywords: post-stroke depression, stroke, metabonomics, diagnosis, NMR

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