ArticleBMC neurology2023
Phenylacetyl glutamine: a novel biomarker for stroke recurrence warning.
Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association of maternal gut microbial metabolites with gestational diabetes mellitus: evidence from an original case-control study, meta-analysis, and Mendelian randomization.European journal of clinical nutrition · 2025Pooled it
- Review
- Mixed sorbent in miniaturized stir bar sorptive dispersive microextraction for the determination of gut microbiome metabolites in plasma samples.Analytical and bioanalytical chemistry · 2026Article
- Dietary astragalus stems polysaccharides improve antioxidant capacity and lactation performance in dairy goats through integrated metabolomic and mechanistic analyses.Scientific reports · 2026Article
- Plasma Phenylacetylglutamine and Cognitive Impairment After Ischemic Stroke.Journal of the American Heart Association · 2025Article
- Multi-Omics Integration Reveals the Impact of Gastrointestinal Microbiota on Feed Efficiency in Tan Sheep.Microorganisms · 2025Article
- High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease.MedComm · 2024Article
- Role of the Gut Bacteria-Derived Metabolite Phenylacetylglutamine in Health and Diseases.ACS omega · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundStroke is the second leading cause of disease-related death and the third leading cause of disability worldwide. However, how to accurately warn of stroke onset remains extremely challenging. Recently, phenylacetyl glutamine (PAGln) has been implicated in the onset of stroke, but evidences from cohort studies of onset are lacking, especially in patients with first-onset or recurrent. It is necessary to deeply demonstrate the effectiveness of PAGln level on warning stroke onset.
methodsOne hundred fifteen first onset stroke patients, 33 recurrent stroke patients, and 135 non-stroke controls were included in the analysis. Risk factors associated with stroke attacking were evaluated, and plasma PAGln levels were detected via HPLC-MS based method. LASSO regression, Pearson correlation analysis, and univariate analysis were carried out to demonstrate the associations between PAGln levels and risk factors of stroke. Random forest machine learning algorithm was used to build classification models to achieve the distinction of first-onset stroke patients, recurrent stroke patients, and non-stroke controls, and further demonstrate the contribution of PAGln levels in the distinction of stroke onset.
resultsThe median level of PAGln in the first-onset stroke group, recurrent stroke group, and non-stroke group was 933 ng/mL, 1014 ng/mL, and 556 ng/mL, respectively. No statistical correlation was found between PAGln level and subject's living habits, eating preferences, and concomitant diseases (hypertension, hyperlipidemia, and diabetes). Stroke severity indicators, mainly age and NIHSS score, were found associate with the PAGln levels. Machine learning classification models confirmed that PAGln levels, as the main contributing variable, could be used to distinguish recurrent stroke patients (but not first-onset stroke patients) from non-stroke controls.
conclusionPAGln may be an effective indicator to monitor the recurrence in stroke patients.
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