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A multifaceted approach for analyzing complex phenotypic data in rodent models of autism
Molecular Autism ( IF 6.2 ) Pub Date : 2019-03-12 , DOI: 10.1186/s13229-019-0263-7
Ishita Das , Marcel A. Estevez , Anjali A. Sarkar , Sharmila Banerjee-Basu

Autism (MIM 209850) is a multifactorial disorder with a broad clinical presentation. A number of high-confidence ASD risk genes are known; however, the contribution of non-genetic environmental factors towards ASD remains largely uncertain. Here, we present a bioinformatics resource of genetic and induced models of ASD developed using a shared annotation platform. Using this data, we depict the intricate trends in the research approaches to analyze rodent models of ASD. We identify the top 30 most frequently studied phenotypes extracted from rodent models of ASD based on 787 publications. As expected, many of these include animal model equivalents of the “core” phenotypes associated with ASD, such as impairments in social behavior and repetitive behavior, as well as several comorbid features of ASD including anxiety, seizures, and motor-control deficits. These phenotypes have also been studied in models based on a broad range of environmental inducers present in the database, of which gestational exposure to valproic acid (VPA) and maternal immune activation models comprising lipopolysaccharide (LPS) and poly I:C are the most studied. In our unique dataset of rescue models, we identify 24 pharmaceutical agents tested on established models derived from various ASD genes and CNV loci for their efficacy in mitigating symptoms relevant for ASD. As a case study, we analyze a large collection of Shank3 mouse models providing a high-resolution view of the in vivo role of this high-confidence ASD gene, which is the gateway towards understanding and dissecting the heterogeneous phenotypes seen in single-gene models of ASD. The trends described in this study could be useful for researchers to compare ASD models and to establish a complete profile for all relevant animal models in ASD research.

中文翻译:

在自闭症啮齿动物模型中分析复杂表型数据的多方面方法

自闭症(MIM 209850)是一种具有广泛临床表现的多因素疾病。许多高可信度的ASD风险基因是已知的。然而,非遗传环境因素对自闭症的贡献仍然不确定。在这里,我们介绍了使用共享注释平台开发的ASD遗传模型和诱导模型的生物信息学资源。利用这些数据,我们描述了分析ASD啮齿动物模型的研究方法中的复杂趋势。我们确定了基于787出版物从ASD啮齿动物模型中提取的前30个最常研究的表型。正如预期的那样,其中许多包括与ASD相关的“核心”表型的动物模型等效物,例如社交行为和重复行为的损伤,以及ASD的多种合并症,包括焦虑,癫痫发作,和运动控制缺陷。这些表型也已经在基于数据库中广泛环境诱导剂的模型中进行了研究,其中对丙戊酸(VPA)的妊娠暴露以及包含脂多糖(LPS)和poly I:C的母体免疫激活模型的研究最多。 。在我们独特的抢救模型数据集中,我们确定了从各种ASD基因和CNV基因座衍生的模型上测试的24种药剂在缓解与ASD相关症状方面的功效。作为案例研究,我们分析了Shank3小鼠模型的大量集合,从而提供了该高可信度ASD基因在体内作用的高分辨率视图,这是通向了解和解剖单基因模型中异质表型的途径ASD。
更新日期:2019-03-12
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