Computational identification of variables in neonatal vocalizations predictive for postpubertal social behaviors in a mouse model of 16p11.2 deletion.
Computational identification of variables in neonatal vocalizations predictive for postpubertal social behaviors in a mouse model of 16p11.2 deletion.
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DOI：
10.1038/s41380-021-01089-y
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发表时间：
2021-11
影响因子：
11
通讯作者：
Hiroi N
中科院分区：
文献类型：
--
作者：
Nakamura M;Ye K;E Silva MB;Yamauchi T;Hoeppner DJ;Fayyazuddin A;Kang G;Yuda EA;Nagashima M;Enomoto S;Hiramoto T;Sharp R;Kaneko I;Tajinda K;Adachi M;Mihara T;Tokuno S;Geyer MA;Broin PÓ;Matsumoto M;Hiroi N
自闭症谱系障碍（ASD）通常由婴儿期的非典型哭声发出信号。拷贝数变异（CNV）提供了遗传上可识别的ASD病例，但早期非典型哭声如何预测CNV携带者中ASD的后期发作尚不清楚。CNVs的遗传小鼠模型提供了一种可靠的工具，可以通过实验分离CNVs的影响，并确定ASD相关行为后期异常的早期预测因子。然而，许多技术问题混淆了这种小鼠模型的表型表征，包括系统性偏倚的遗传背景和弱或不存在的行为表型。为了解决这些问题，我们开发了人类近端16p11.2半合子缺失的共基因小鼠模型，并应用计算方法来识别新生儿发声中的隐藏变量，这些变量对与ASD相关的青春期后尺寸具有预测能力。通过最小绝对收缩和选择算子（Lasso）、随机森林和马尔可夫模型选择新生儿发声变量后，构建回归模型预测青春期后ASD相关维度。虽然许多标准的行为分析设计的模型尺寸的平均分数没有区分模型的16p11.2半合子缺失和野生型同窝出生，特定的呼叫类型和呼叫序列的新生儿发声预测个体变异性的青春期后互惠社会互动和嗅觉反应的社会线索在基因型特异性的方式。深层表型分析和计算分析确定了新生儿社交中的隐藏变量，这些变量可预测青春期后的行为。
Autism spectrum disorder (ASD) is often signaled by atypical cries during infancy. Copy number variants (CNVs) provide genetically identifiable cases of ASD, but how early atypical cries predict a later onset of ASD among CNV carriers is not understood in humans. Genetic mouse models of CNVs have provided a reliable tool to experimentally isolate the impact of CNVs and identify early predictors for later abnormalities in behaviors relevant to ASD. However, many technical issues have confounded the phenotypic characterization of such mouse models, including systematically biased genetic backgrounds and weak or absent behavioral phenotypes. To address these issues, we developed a coisogenic mouse model of human proximal 16p11.2 hemizygous deletion and applied computational approaches to identify hidden variables within neonatal vocalizations that have predictive power for postpubertal dimensions relevant to ASD. After variables of neonatal vocalizations were selected by least absolute shrinkage and selection operator (Lasso), random forest, and Markov model, regression models were constructed to predict postpubertal dimensions relevant to ASD. While the average scores of many standard behavioral assays designed to model dimensions did not differentiate a model of 16p11.2 hemizygous deletion and wild-type littermates, specific call types and call sequences of neonatal vocalizations predicted individual variability of postpubertal reciprocal social interaction and olfactory responses to a social cue in a genotype-specific manner. Deep-phenotyping and computational analyses identified hidden variables within neonatal social communication that are predictive of postpubertal behaviors.
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影响因子：
11.9
作者：
Hiroi N
通讯作者：
Hiroi N
DOI：
10.1016/j.jaac.2013.08.008
发表时间：
2013-11-01
影响因子：
13.3
作者：
Gothelf, Doron;Schneider, Maude;Eliez, Stephan
通讯作者：
Eliez, Stephan
影响因子：
2.2
作者：
Kato R;Machida A;Nomoto K;Kang G;Hiramoto T;Tanigaki K;Mogi K;Hiroi N;Kikusui T
通讯作者：
Kikusui T
影响因子：
4.5
作者：
Kates, Wendy R.;Olszewski, Amy K.;Gnirke, MatthewH.;Kikinis, Zora;Nelson, Joshua;Antshel, Kevin M.;Fremont, Wanda;Radoeva, Petya D.;Middleton, Frank A.;Shenton, Martha E.;Coman, Ioana L.
通讯作者：
Coman, Ioana L.
影响因子：
10.6
作者：
Hippolyte, Loyse;Maillard, Anne M.;Jacquemont, Sebastien
通讯作者：
Jacquemont, Sebastien