INTRODUCTION Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficiencies in social interactions and communication, combined with restricted and repetitive behavioral issues. OBJECTIVES As little is known about the etiopathophysiology of ASD and early diagnosis is relatively subjective, we aim to employ a targeted, fully quantitative metabolomics approach to biochemically profile post-mortem human brain with the overall goal of identifying metabolic pathways that may have been perturbed as a result of the disease while uncovering potential central diagnostic biomarkers. METHODS Using a combination of 1H NMR and DI/LC-MS/MS we quantitatively profiled the metabolome of the posterolateral cerebellum from post-mortem human brain harvested from people who suffered with ASD (n = 11) and compared them with age-matched controls (n = 10). RESULTS We accurately identified and quantified 203 metabolites in post-mortem brain extracts and performed a metabolite set enrichment analyses identifying 3 metabolic pathways as significantly perturbed (p < 0.05). These include Pyrimidine, Ubiquinone and Vitamin K metabolism. Further, using a variety of machine-based learning algorithms, we identified a panel of central biomarkers (9-hexadecenoylcarnitine (C16:1) and the phosphatidylcholine PC ae C36:1) capable of discriminating between ASD and controls with an AUC = 0.855 with a sensitivity and specificity equal to 0.80 and 0.818, respectively. CONCLUSION For the first time, we report the use of a multi-platform metabolomics approach to biochemically profile brain from people with ASD and report several metabolic pathways which are perturbed in the diseased brain of ASD sufferers. Further, we identified a panel of biomarkers capable of distinguishing ASD from control brains. We believe that these central biomarkers may be useful for diagnosing ASD in more accessible biomatrices.

中文翻译：

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靶向代谢组学突出了自闭症谱系障碍患者大脑中的代谢紊乱。

引言自闭症谱系障碍（ASD）是一组神经发育障碍，其特征在于社交互动和沟通不足，以及受限和重复的行为问题。目的由于对ASD的病因生理学了解很少，而且早期诊断相对主观，我们的目标是采用针对性的，完全定量的代谢组学方法对死后人脑进行生化分析，其总体目标是确定可能被干扰的代谢途径疾病的结果，同时发现潜在的中央诊断生物标志物。方法结合1H NMR和DI / LC-MS / MS，我们定量分析了从自ASD（n = 11）的人中采集的死后人脑的后外侧小脑的代谢组，并将其与年龄匹配的对照组进行了比较（n = 10）。结果我们准确地鉴定和定量了死后脑提取物中的203种代谢物，并进行了代谢物组富集分析，确定了3种代谢途径被显着扰动（p <0.05）。这些包括嘧啶，泛醌和维生素K代谢。此外，我们使用各种基于机器的学习算法，确定了一组能够区分ASD和AUC = 0.855的对照的中心生物标志物（9-十六碳酰肉碱（C16：1）和磷脂酰胆碱PC AE C36：1）。灵敏度和特异性等于0.80和0。分别为818。结论我们首次报道了使用多平台代谢组学方法对ASD患者的大脑进行生化分析，并报道了在ASD患者患病大脑中扰动的几种代谢途径。此外，我们鉴定了一组能够区分ASD和对照脑的生物标志物。我们相信这些中心生物标志物可能有助于诊断更易接近的生物基质中的ASD。