A multifaceted approach for analyzing complex phenotypic data in rodent models of autism
A multifaceted approach for analyzing complex phenotypic data in rodent models of autism
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DOI：
10.1186/s13229-019-0263-7
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发表时间：
2019-03-12
期刊：
影响因子：
6.2
通讯作者：
Banerjee-Basu, Sharmila
中科院分区：
文献类型：
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作者：
Das, Ishita;Estevez, Marcel A.;Banerjee-Basu, Sharmila
自闭症（MIM 209850）是一种具有广泛临床表现的多因素障碍。许多高置信度的ASD风险基因是已知的;然而，非遗传环境因素对ASD的贡献在很大程度上仍然不确定。在这里，我们提出了使用共享注释平台开发的ASD遗传和诱导模型的生物信息学资源。使用这些数据，我们描绘了复杂的趋势，在研究方法来分析啮齿动物模型的ASD。我们根据787篇出版物确定了从ASD啮齿动物模型中提取的前30种最常研究的表型。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的几种共病特征，包括焦虑，癫痫发作和运动控制缺陷。还在基于数据库中存在的广泛环境诱导物的模型中研究了这些表型，其中研究最多的是妊娠期暴露于丙戊酸（VPA）和包含脂多糖（LPS）和聚I：C的母体免疫激活模型。在我们独特的救援模型数据集中，我们确定了24种药物，这些药物在来自各种ASD基因和CNV基因座的已建立模型上进行了测试，以评估其缓解ASD相关症状的功效。作为一个案例研究，我们分析了大量的Shank 3小鼠模型，提供了这种高置信度ASD基因的体内作用的高分辨率视图，这是理解和解剖ASD单基因模型中所见的异质性表型的门户。本研究中描述的趋势可能有助于研究人员比较ASD模型，并为ASD研究中的所有相关动物模型建立完整的档案。
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.