Developmental Functional Genomics in ASD Toddlers

在自闭症患者中，早期生物标记物非常稀少。迫切需要研究以确定先于 症状出现，传达预后信息，或指示疾病亚型。我们提出的功能基因组学 对ASD早期发展的研究解决了许多这些生物标志物的目标，是ASD早期必不可少的步骤 这个发现过程。强大的生物标志物一直难以捉摸，可能是因为ASD是一种异质性 具有数千个推测的风险基因和潜在的非遗传免疫因素的发育障碍。我们 假设基于途径的转录生物标记物可能是信息性的，正如我们最近的证据所表明的- Of-Concept研究中，基于白细胞的基因表达提供了ASD的早期诊断分类。我们的 这些发现是合理的，因为许多高置信度ASD基因(例如，转录因子，信号基因， 等)而且，网络在白细胞和大脑中的表达强度一样高。此外，假设的免疫 ASD的破坏也应该反映在白细胞中，特别是因为小胶质细胞是一种 在ASD中被确立为脑分子和细胞病理。在我们提议的研究中，我们将使用1,500 来自1,000名ASD和典型和非典型发育幼儿的RNA-Seq数据集，以识别生物分子 用于早期检测、预后、临床进展和临床亚型的通路生物标志物。我们将进一步 研究生物标记物与ASD基因缺陷的关系以及在神经发育早期的表达模式。目标1 将使用数据驱动和基于知识的网络分析1,000名1-2岁儿童的RNA-Seq数据 识别早期ASD诊断生物标志物的方法区分1-2岁ASD(n=390) 非ASD组(n=610)。诊断生物标记物将包括要解决的途径和共表达网络 ASD受试者之间的异质性。AIM 2将在390个细胞中确定预后RNA-Seq表达模式 通过分析基因表达水平来揭示预测社交和社交能力好坏的途径，从而为1-2岁的儿童提供自闭症 3-4岁儿童的语言结果。AIM 2也将纵向观察ASD(n=300)并典型地发展 (n=200)表达数据以确定从1-2年到临床进展的转录轨迹 在这些不同的临床结果亚组中，3-4年。目标3将研究发育过程中的变异 功能基因组模式与不同诊断类别的社会和语言能力的差异有关 (n=1,000)和ASD内(n=390)，使用降维和特征选择回归。多重共线 回归将用于将降维的多变量趋势观测与 回归的预测力。目标4将把目标1至3中的关键转录效应与目标1至3中的遗传变异联系起来。 高信心和可能的ASD基因，与我们的ASD受试者细胞通路中断有关。 这些基因中的有害变异将使用CRISPR-Cas9 to在造血和神经干细胞中进行测试 在这些基因中引入功能丧失突变。RNA-Seq将被用来分析对ASD相关的影响 细胞通路。

In autism, early-age biomarkers are scarce. Research is urgently needed to identify markers that precede symptom onset, convey prognostic information, or indicate disorder subtypes. Our proposed functional genomics study of early development in ASD addresses many of these biomarker goals and is an essential early step in this discovery process. Robust biomarkers have been elusive presumably since ASD is a heterogeneous developmental disorder with thousands of speculated risk genes and potential non-genetic immune factors. We hypothesize that pathway-based transcriptomic biomarkers may be informative, as shown by our recent proof- of-concept study in which leukocyte-based gene expression provided an early diagnostic ASD classifier. Our findings are reasonable since many high confidence ASD genes (e.g., transcription factors, signaling genes, etc.) and networks are as strongly expressed in leukocytes as in brain. Furthermore, hypothesized immune disruptions in ASD should also be reflected in leukocytes, especially since microglia are a type of leukocyte that are established as a brain molecular and cellular pathology in ASD. In our proposed study, we will use 1,500 RNA-Seq datasets from 1,000 ASD and typically and atypically developing toddlers to identify biomolecular pathway biomarkers for early detection, prognosis, clinical progression and clinical subtyping. We will further study biomarker relationships to ASD gene defects and expression patterns in early neural development. Aim 1 will analyze RNA-Seq data from 1,000 1-2 year olds using data-driven and knowledge-based network approaches to identify early ASD diagnostic biomarkers that distinguish ASD (n=390) at ages 1-2 years from non-ASD (n=610) groups. Diagnostic biomarkers will include pathways and co-expression networks to address the heterogeneity across ASD subjects. Aim 2 will identify prognostic RNA-Seq expression patterns in the 390 ASD 1-2 year olds by analyzing gene expression levels to reveal pathways that predict good/poor social and language outcome at ages 3-4 years. Aim 2 will also look longitudinally at ASD (n=300) and typically developing (n=200) expression data to identify transcriptomic trajectories that underlie clinical progression from 1-2 years to 3-4 years in these different clinical outcome subgroups. Aim 3 will examine how variation in developmental functional genomic patterns relates to variation in social and language abilities across diagnostic categories (n=1,000) and within ASD (n=390) using dimensionality reduction and feature selecting regression. Multicollinear regressions will be used to combine multivariate trend observations of dimensionality reduction with the predictive power of regressions. Aim 4 will link key transcriptomic effects in Aims 1 to 3 to genetic variants in high-confidence and probable ASD genes that are linked to disrupted cellular pathways in our ASD subjects. Deleterious variants in those genes will be tested in hematopoietic and neural stem cells using CRISPR-Cas9 to introduce loss-of-function mutations in these genes. RNA-Seq will be used to assay the impact on ASD-relevant cellular pathways.