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Potential Plasma Metabolic Biomarkers of Tourette Syndrome Discovery Based on Integrated Non-Targeted and Targeted Metabolomics Screening

OBJECTIVE: Tourette syndrome (TS) is a chronic neuropsychiatric disorder characterized by abnormal movements, phonations, and tics, but an accurate TS diagnosis remains challenging and indeed depends on its description of clinical symptoms. Our study was conducted to discover and verify some metabol...

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Detalles Bibliográficos
Autores principales: Xi, Leying, Zhou, Fuqiong, Ji, Wenxiu, Zhu, Weina, Ruan, Jie, Zhang, Yajie, Hu, Xueling, Long, Hongyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894715/
https://www.ncbi.nlm.nih.gov/pubmed/36742270
http://dx.doi.org/10.1155/2022/5080282
Descripción
Sumario:OBJECTIVE: Tourette syndrome (TS) is a chronic neuropsychiatric disorder characterized by abnormal movements, phonations, and tics, but an accurate TS diagnosis remains challenging and indeed depends on its description of clinical symptoms. Our study was conducted to discover and verify some metabolite biomarkers based on nontargeted and targeted metabolomics. METHODS: We conducted untargeted ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) for preliminary screening of potential biomarkers on 30 TS patients and 10 healthy controls and then performed validation experiments based on targeted ultrahigh-performance liquid chromatography triple quadrupole-MS (UHPLC/MS/MS) on 35 TS patients and 14 healthy controls. RESULTS: 1775 differentially expressed metabolites were identified by partial least squares discriminant analysis (PLS-DA), fold-change analysis, T-test, and hierarchical clustering analysis (adjusted p value <0.05 and |logFC| > 1). TS plasma samples were found to be differentiated from healthy samples in our approach. Furthermore, aspartate and asparagine metabolism pathways were considered to be a significant enrichment pathway in TS progression based on metabolite pathway enrichment analysis. For the 8 metabolites involved in this pathway that we detected, we then performed validation experiments based on targeted UHPLC/MS/MS. The t-test, Mann–Whitney U test, and receiver operating characteristic (ROC) curve analysis were used to determine potential biomarkers. Ultimately, L-arginine and L-pipecolic acid were validated as significantly differentiated metabolites (p < 0.05), with an AUC of 70.0% and 80.3%, respectively. CONCLUSION: L-pipecolic acid was defined as a potential biomarker for TS diagnosis by the combined application of nontargeted and targeted metabolomic analysis.