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Identification of likely associations between cerebral folate deficiency and complex genetic- and metabolic pathogenesis of autism spectrum disorders by utilization of a pilot interaction modeling approach

机译:利用先导相互作用建模方法,鉴定脑叶酸缺乏症缺乏和复杂遗传学和代谢发病机制的识别

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Recently, cerebral folate deficiency (CFD) was suggested to be involved in the pathogenesis of autism spectrum disorders (ASD). However, the exact role of folate metabolism in the pathogenesis of ASD, identification of underlying pathogenic mechanisms and impaired metabolic pathways remain unexplained. The aim of our study was to develop and test a novel, unbiased, bioinformatics approach in order to identify links between ASD and disturbed cerebral metabolism by focusing on abnormal folate metabolism, which could foster patient stratification and novel therapeutic interventions. An unbiased, automatable, computational workflow interaction model was developed using available data from public databases. The interaction network model of ASD-associated genes with known cerebral expression and function (SFARI) and metabolic networks (MetScape), including connections to known metabolic substrates, metabolites and cofactors involving folates, was established. Intersection of bioinformatically created networks resulted in a limited amount of interaction modules pointing to common disturbed metabolic pathways, linking ASD to CFD. Two independent interaction modules (comprising three pathways) covering enzymes encoded by ASD-related genes and folate cofactors utilizing enzymes were generated. Module 1 suggested possible interference of CFD with serine and lysine metabolism, while module 2 identified correlations with purine metabolism and inosine monophosphate production. Since our approach was primarily conceived as a proof of principle, further amendments of the presented initial model are necessary to obtain additional actionable outcomes. Our modelling strategy identified not only previously known interactions supported by evidence-based analyses, but also novel plausible interactions, which could be validated in subsequent functional and/or clinical studies. Autism Res2017, 10: 1424-1435. (c) 2017 International Society for Autism Research, Wiley Periodicals, Inc.
机译:最近,建议脑叶酸缺乏(CFD)参与自闭症谱系障碍(ASD)的发病机制。然而,叶酸代谢在ASD发病机制中的确切作用,鉴定潜在的致病机制和损伤的代谢途径仍未解释。我们研究的目的是通过专注于异常的叶酸代谢来制定和测试一种新颖的,无偏的生物信息学方法,以识别ASD和干扰的脑代谢之间的联系,这可能促进患者分层和新的治疗干预措施。使用公共数据库的可用数据开发了一个无偏偏见的自动计算工作流交互模型。建立了具有已知脑表达和功能(SFARI)和代谢网络(METSCAPE)的ASD相关基因的相互作用网络模型,包括与已知代谢底物,代谢物和涉及叶子的代谢物和辅助actor的连接。生物信息创建的网络的交叉点导致有限的相互作用模块指向常见的扰动代谢途径,将ASD连接到CFD。产生了使用诸如相关基因和利用酶的叶酸胶囊编码的覆盖酶的两个独立的相互作用模块(包含三种途径)。模块1表明CFD与丝氨酸和赖氨酸代谢的可能干扰,而模块2鉴定了与嘌呤代谢和InoSine单磷酸盐产生的相关性。由于我们的方法主要被认为是原则证明,因此对所提出的初始模型的进一步修改是获得额外的可操作结果。我们的建模策略不仅鉴定了以前通过循证分析支持的相互作用,而且还具有新的合理相互作用,可以在随后的功能和/或临床研究中验证。自闭症Res2017,10:1424-1435。 (c)2017国际自闭症研究协会,Wiley Hearyicals,Inc。

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