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Discriminating poststroke depression from stroke by nuclear magnetic resonance spectroscopy-based metabonomic analysis

Authors Xiao J, Zhang J, Sun D, Wang L, Yu L, Wu H, Wang D, Qiu X

Received 15 April 2016

Accepted for publication 9 May 2016

Published 2 August 2016 Volume 2016:12 Pages 1919—1925

DOI https://doi.org/10.2147/NDT.S110613

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Prof. Dr. Roumen Kirov

Peer reviewer comments 3

Editor who approved publication: Professor Wai Kwong Tang


Jianqi Xiao,1,* Jie Zhang,2,* Dan Sun,3,* Lin Wang,4,* Lijun Yu,5 Hongjing Wu,5 Dan Wang,5 Xuerong Qiu5

1Department of Neurosurgery, The First Hospital of Qiqihar City, Qiqihar, 2Department of Internal Medicine, Central Hospital of Jiamusi City, Jiamusi, 3Department of Geriatrics, General Hospital of Daqing Oil Field, Daqing, 4Department of Nursing, 5Department of Neurology, The First Hospital of Qiqihar City, Qiqihar, Heilongjiang, People’s Republic of China

*These authors contributed equally to this work

Abstract: Poststroke depression (PSD), the most common psychiatric disease that stroke survivors face, is estimated to affect ~30% of poststroke patients. However, there are still no objective methods to diagnose PSD. In this study, to explore the differential metabolites in the urine of PSD subjects and to identify a potential biomarker panel for PSD diagnosis, the nuclear magnetic resonance-based metabonomic method was applied. Ten differential metabolites responsible for discriminating PSD subjects from healthy control (HC) and stroke subjects were found, and five of these metabolites were identified as potential biomarkers (lactate, α-hydroxybutyrate, phenylalanine, formate, and arabinitol). The panel consisting of these five metabolites provided excellent performance in discriminating PSD subjects from HC and stroke subjects, achieving an area under the receiver operating characteristic curve of 0.946 in the training set (43 HC, 45 stroke, and 62 PSD subjects). Moreover, this panel could classify the blinded samples from the test set (31 HC, 33 stroke, and 32 PSD subjects) with an area under the curve of 0.946. These results laid a foundation for the future development of urine-based objective methods for PSD diagnosis and investigation of PSD pathogenesis.

Keywords: poststroke depression, PSD, stroke, nuclear magnetic resonance, NMR, metabonomic

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