ArticleNeuropsychiatric disease and treatment2016
Discriminating poststroke depression from stroke by nuclear magnetic resonance spectroscopy-based metabonomic analysis.
Article in Neuropsychiatric disease and treatment, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Metabolomics reveals key biomarkers for ischemic stroke: a systematic review of emerging evidence.Frontiers in neurology · 2025Pooled it
- Metabolomics facilitates the discovery of metabolic biomarkers and pathways for ischemic stroke: a systematic review.Metabolomics : Official journal of the Metabolomic Society · 2019Pooled it
- The role of metabolomics in stroke: biomarkers of diagnosis and therapy.Metabolic brain disease · 2025Review
- Metabolomics: A useful tool for ischemic stroke research.Journal of pharmaceutical analysis · 2023Review
- Peripheral blood and urine metabolites and biological functions in post-stroke depression.Metabolic brain disease · 2022Article
- Ischaemic background of brain fog in long-haul COVID-19 - a nuclear magnetic resonance spectroscopy-based metabonomic analysis. Preliminary results.Polish journal of radiology · 2021Article
- Amino acid metabolism, lipid metabolism, and oxidative stress are associated with post-stroke depression: a metabonomics study.BMC neurology · 2020Article
- Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior.Frontiers in psychiatry · 2020Article
- Hippocampal metabolic differences implicate distinctions between physical and psychological stress in four rat models of depression.Translational psychiatry · 2018Article
- Poststroke Depression Biomarkers: A Narrative Review.Frontiers in neurology · 2018Review
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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