Multiparametric Assays Capture Sex- and Environment-Dependent Modifiers of Behavioral Phenotypes in Autism Mouse Models

IF 4 Q2 NEUROSCIENCES
Lucas Wahl, Arun Karim, Amy R. Hassett, Max van der Doe, Stephanie Dijkhuizen, Aleksandra Badura
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引用次数: 0

Abstract

Background

Current phenotyping approaches for murine autism models often focus on one selected behavioral feature, making the translation onto a spectrum of autistic characteristics in humans challenging. Furthermore, sex and environmental factors are rarely considered. Here, we aimed to capture the full spectrum of behavioral manifestations in 3 autism mouse models to develop a “behavioral fingerprint” that takes environmental and sex influences under consideration.

Methods

To this end, we employed a wide range of classical standardized behavioral tests and 2 multiparametric behavioral assays—the Live Mouse Tracker and Motion Sequencing—on male and female Shank2, Tsc1, and Purkinje cell–specific Tsc1 mutant mice raised in standard or enriched environments. Our aim was to integrate our high dimensional data into one single platform to classify differences in all experimental groups along dimensions with maximum discriminative power.

Results

Multiparametric behavioral assays enabled a more accurate classification of experimental groups than classical tests, and dimensionality reduction analysis demonstrated significant additional gains in classification accuracy, highlighting the presence of sex, environmental, and genotype differences in our experimental groups.

Conclusions

Together, our results provide a complete phenotypic description of all tested groups, suggesting that multiparametric assays can capture the entire spectrum of the heterogeneous phenotype in autism mouse models.

多参数测定捕捉自闭症小鼠模型行为表型的性别和环境依赖性修饰因子
背景目前对小鼠自闭症模型进行表型的方法通常只关注一种选定的行为特征,这使得将其转化为人类自闭症特征谱系具有挑战性。此外,性别和环境因素也很少被考虑在内。为此,我们采用了一系列经典的标准化行为测试和两种多参数行为测定--活体小鼠追踪器和运动序列测定--在标准或富集环境中饲养的雌雄Shank2、Tsc1和浦肯野细胞特异性Tsc1突变小鼠。我们的目的是将高维数据整合到一个单一的平台上,以最大的鉴别力对所有实验组的差异进行分类。结果与传统测试相比,多参数行为测定能对实验组进行更准确的分类,降维分析表明分类准确性有了显著提高,突出了实验组中存在的性别、环境和基因型差异。结论我们的研究结果为所有测试组提供了完整的表型描述,表明多参数测定可以捕捉自闭症小鼠模型异质性表型的整个谱系。
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来源期刊
Biological psychiatry global open science
Biological psychiatry global open science Psychiatry and Mental Health
CiteScore
4.00
自引率
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审稿时长
91 days
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