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基于 UHPLC-QTOF/MS 的非靶向代谢组学分析揭示自闭症相关的代谢改变。

Untargeted Metabolomic Profiling Using UHPLC-QTOF/MS Reveals Metabolic Alterations Associated with Autism.

机构信息

Department of Child and Adolescent Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Key Laboratory for Psychological Healthcare & Shenzhen Institute of Mental Health, Shenzhen, China.

Department of Chemistry, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.

出版信息

Biomed Res Int. 2020 Sep 11;2020:6105608. doi: 10.1155/2020/6105608. eCollection 2020.

Abstract

Autism spectrum disorder (ASD) is a clinical spectrum of neurodevelopment disorder characterized by deficits in social communication and social interaction along with repetitive/stereotyped behaviors. The current diagnosis for autism relies entirely on clinical evaluation and has many limitations. In this study, we aim to elucidate the potential mechanism behind autism and establish a series of potential biomarkers for diagnosis. Here, we established an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry- (UHPLC-QTOF/MS-) based metabonomic approach to discriminate the metabolic modifications between the cohort of autism patients and the healthy subjects. UHPLC-QTOF/MS analysis revealed that 24 of the identified potential biomarkers were primarily involved in amino acid or lipid metabolism and the tryptophan kynurenine pathway. The combination of nicotinamide, anthranilic acid, D-neopterin, and 7,8-dihydroneopterin allows for discrimination between ASD patients and controls, which were validated in an independent autism case-control cohort. The results indicated that UHPLC-QTOF/MS-based metabolomics is capable of rapidly profiling autism metabolites and is a promising technique for the discovery of potential biomarkers related to autism.

摘要

自闭症谱系障碍(ASD)是一种神经发育障碍的临床谱系,其特征是社交沟通和社交互动能力缺陷,以及重复/刻板行为。目前的自闭症诊断完全依赖于临床评估,存在许多局限性。在这项研究中,我们旨在阐明自闭症背后的潜在机制,并建立一系列潜在的诊断生物标志物。在这里,我们建立了一种基于超高效液相色谱-四极杆飞行时间质谱(UHPLC-QTOF/MS)的代谢组学方法,以区分自闭症患者队列和健康受试者之间的代谢变化。UHPLC-QTOF/MS 分析显示,在鉴定出的 24 种潜在生物标志物中,主要涉及氨基酸或脂质代谢和色氨酸犬尿氨酸途径。烟酰胺、邻氨基苯甲酸、D-新蝶呤和 7,8-二氢新蝶呤的组合可用于区分 ASD 患者和对照组,在一个独立的自闭症病例对照队列中得到了验证。结果表明,基于 UHPLC-QTOF/MS 的代谢组学能够快速分析自闭症代谢物,是发现与自闭症相关的潜在生物标志物的有前途的技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e274/7502129/a901760f595e/BMRI2020-6105608.001.jpg

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