ArticleAmino acids2023
Serum metabolomics study of narcolepsy type 1 based on ultra-performance liquid chromatography-tandem mass spectrometry.
Article in Amino acids, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Causality of blood metabolites and narcolepsy type 1: A Mendelian randomization study.Medicine · 2025Article
- Alteration of Metabolic Profile in Patients with Narcolepsy Type 1.Metabolites · 2025Article
- REM Density, Leg Movements, and REM Sleep without Atonia: Differentiating Type 1 from Type 2 Narcolepsy Through Polysomnographic Analysis, a Preliminary Study.Nature and science of sleep · 2025Article
- Serum Metabolomic Signatures of Dyslipidemia in Narcolepsy Type 1: A Multi-Center Cross-Sectional Study.Nature and science of sleep · 2025Article
- Metabolomic analysis of swainsonine poisoning in renal tubular epithelial cells.Frontiers in veterinary science · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Narcolepsy is a chronic and underrecognized sleep disorder characterized by excessive daytime sleepiness and cataplexy. Furthermore, narcolepsy type 1 (NT1) has serious negative impacts on an individual's health, society, and the economy. Currently, many sleep centers lack the means to measure orexin levels in the cerebrospinal fluid. We aimed to analyze the characteristics of metabolite changes in patients with NT1, measured by ultra-performance liquid chromatography-tandem mass spectrometry. A principal component analysis (PCA), an orthogonal partial least square discriminant analysis (OPLS-DA), t tests, and volcano plots were used to construct a model of abnormal metabolic pathways in narcolepsy. We identified molecular changes in serum specimens from narcolepsy patients and compared them with control groups, including dehydroepiandrosterone, epinephrine, N-methyl-D-aspartic acid, and other metabolites, based on an OPLS-loading plot analysis. Nine metabolites yielded an area under the receiver operating curve > 0.75. Meanwhile, seven abnormal metabolic pathways were correlated with differential metabolites, such as metabolic pathways; neuroactive ligand‒receptor interaction; and glycine, serine, and threonine metabolism. To our knowledge, this is the first study to reveal the characteristic metabolite changes in sera from NT1 patients for the selection of potential blood biomarkers and the elucidation of NT1 pathogenesis.
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