Genetic determinants of early brain development in an animal model of autism spectrum disorder (ASD)

摘要 缩短的发育期和相似的大脑组织使非人灵长类动物成为理想的模型 研究自闭症谱系障碍（ASD）的夸大大脑生长假说。具体地说， 研究表明，大脑发育的轨迹是显着陡峭和不同的儿童， ASD与神经型对照相比，这种过度生长可能是由与ASD相关的几个基因驱动的。 神经发生和突触修剪。其中一个基因是DUF 1220，它已被证明会影响大脑发育， 但在非人类灵长类动物大脑中个体内变异的背景下， 发展在成年人中，DUF 1220中拷贝数增加的变体与以下因素正相关： 脑大小和脑大小病理学的个体差异。此外，在成年人中，DUF 1220的增加 拷贝数与（1）一般智力，（2）数学能力和（3） ASD症状严重程度。在这里，我们建议利用非人类灵长类动物模型（恒河猴）来测试 DUF 1220拷贝数的种内增加是否与整个和局部脑生长相关 以及ASD样行为表型的严重程度增加。在目标1中，我们将量化拷贝数， DUF 1220在1 q21区域的变异（来自血液），并在体内纵向采集MRI和DTI扫描。 42只6、12、18和24月龄猴的样本。我们将进行方差分析（ANOVA） 以每个进化枝中的DUF 1220拷贝数（低/高）和性别（雌性/雄性）作为自变量， 脑大小作为因变量（总体积、灰质和白色物质、表面积、皮质 厚度、旋转和连通性）。我们还将研究DUF 1220拷贝数对细胞凋亡的影响。 我们大脑测量的变化斜率（6、12、18、24个月）。此外，我们将使用一个区域- 一种感兴趣的方法来量化包括社会脑网络的脑区域内的灰质和白色物质 并测试它们与DUF 1220拷贝数变异体的关联。在目标2中，我们计划评估社会认知 每六个月使用三个与ASD相关的认知测试，包括相互凝视 目光跟随和社交动机测试我们将使用方差分析来确定社会差异， 动机，相互的眼睛凝视，以及那些具有低和高DUF 1220拷贝数的人之间的凝视。 在每个时间点（6、12、18和24个月）的六个进化枝中的任何一个。我们还将执行偏相关， 检查社会脑网络中灰质和白色物质体积与分数之间的关系 在社会认知测试中，以DUF 1220拷贝数作为协变量。这些发现将：（1） 为非人灵长类ASD模型的实用性提供了额外的证据，（2）有助于阐明 大脑大小和社会认知变化的发育时间框架，与DUF 1220有关，作为一种手段， 确定潜在有效干预措施的关键时间点。

Abstract The shortened developmental period and similar brain organization make nonhuman primates an ideal model for studying the exaggerated brain growth hypothesis of autism spectrum disorder (ASD). Specifically, research indicates that the brain development trajectory is significantly steeper and different in children with ASD compared to neurotypical controls, and this overgrowth is likely driven by several genes associated with neurogenesis and synaptic pruning. One such gene is DUF1220, which has been shown to affect brain growth, but remains largely understudied in the context of intra-individual variability in nonhuman primate brain development. In adult humans, increased copy number variants in DUF1220 are positively correlated with individual variation in brain size and brain size pathology. Further, in adult humans, increases in DUF1220 copy number is associated with higher scores on (1) general intelligence, (2) math ability, and (3) increases in ASD symptom severity. Here, we propose utilizing a nonhuman primate model (rhesus monkeys) to test whether intra-species increases in DUF1220 copy number is associated with whole and regional brain growth as well as increased severity of ASD-like behavioral phenotypes. In aim 1, we will quantify copy number variants in DUF1220 in the 1q21 region (from blood) and acquire in vivo MRI and DTI scans longitudinally in a sample of 42 monkeys at 6, 12, 18, and 24 months of age. we will perform analyses of variance (ANOVAs) with DUF1220 copy number in each clade (low/high) and sex (female/male) as the independent variables and the brain size measures as the dependent variables (total volume, gray and white matter, surface area, cortical thickness, gyrification, and connectivity). We will also examine the effect of DUF1220 copy number on the slope of change for our brain measures (across 6, 12, 18, 24 months). In addition, we will use a region-of- interest approach to quantify gray and white matter within brain regions comprising the social brain network and test for their association with DUF1220 copy number variants. In aim 2, we plan to assess social cognition every six months using three cognitive tests selected for their relevance to ASD, including mutual eye gaze and gaze following, and a social motivation test. We will use ANOVAs to determine the differences in social motivation, mutual eye gaze, and gaze following between those with low and high DUF1220 copy numbers in any of the six clades at each time point (6, 12, 18, and 24 months). We will also perform partial correlations to examine the relationship between gray matter and white matter volumes in the social brain network and scores on the social cognition tests, with DUF1220 copy number as a covariate. Together these findings will: (1) provide additional evidence of the utility of nonhuman primate models of ASD, and (2) help elucidate the developmental time frame for changes in brain size and social cognition, in relation to DUF1220, as a means of identifying key time points for potential effective interventions.