Developmental Functional Genomics in ASD Toddlers

自闭症谱系障碍 (ASD) 幼儿的发育功能基因组学

• 批准号: 9159490
• 负责人: ERIC COURCHESNE
• 金额: $ 63.63万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9159490
• 关键词: 2 year old; Address; Age; Animal Model; Autistic Disorder; Behavior; Biological; Biological Assay; Biological Markers; Blood; Brain; CRISPR/Cas technology; Categories; Cell model; Child; Clinical; Data; Data Analyses; Data Set; Defect; Development; Developmental Delay Disorders; Diagnostic; Disease; Early Diagnosis; Early Intervention; Early identification; Figs - dietary; Friendships; Future; Gene Expression; Gene Expression Profile; Genes; Genomics; Goals; Grant; Growth; Hematopoietic; Hematopoietic stem cells; Heterogeneity; Immune; Intervention; Language; Leukocytes; Life; Link; Microglia; Molecular; Mother-Child Relations; Network-based; Outcome; Parents; Pathway interactions; Pattern; Phenotype; Process; Protein Translation Pathway; RNA; Regression Analysis; Research; Sample Size; Sampling; Sensitivity and Specificity; Signal Transduction; Specificity; Staging; Subgroup; Symptoms; Testing; Toddler; Uncertainty; Validation; Variant; base; candidate marker; cellular pathology; cohort; developmental disease; diagnostic biomarker; disability; disorder subtype; early detection biomarkers; functional genomics; genetic variant; human stem cells; impression; improved; individualized medicine; knowledge base; loss of function mutation; molecular pathology; nerve stem cell; neurodevelopment; non-genetic; novel; outcome forecast; preference; prognostic; protein protein interaction; relating to nervous system; risk variant; skills; social; success; transcription factor; transcriptome sequencing; transcriptomics; treatment trial; trend

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.

在自闭症中，早期的生物标志物是稀缺的。迫切需要进行研究，以确定 症状发作、传达预后信息或指示疾病亚型。我们提出的功能基因组学 ASD早期发展研究解决了许多这些生物标志物目标， 这个发现过程。稳健的生物标志物可能是难以捉摸的，因为ASD是异质性的。 发育障碍与成千上万的推测风险基因和潜在的非遗传免疫因素。我们 假设基于通路的转录组学生物标志物可能提供信息，如我们最近的证据所示- 概念研究，其中基于白细胞的基因表达提供了早期诊断ASD分类器。我们 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， 等等）。并且网络在白细胞中的表达与在大脑中一样强烈。此外，假设免疫 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白细胞， 被确定为ASD的脑分子和细胞病理学。在我们提议的研究中，我们将使用1500个 来自1，000名ASD和典型发育中的幼儿的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途径生物标志物。我们将进一步 研究ASD基因缺陷和早期神经发育中表达模式的生物标志物关系。要求1 将使用数据驱动和基于知识的网络分析1,000名1-2奥尔兹的RNA-Seq数据 鉴定早期ASD诊断生物标志物的方法，其将1-2岁的ASD（n=390）与 非ASD组（n=610）。诊断生物标志物将包括途径和共表达网络，以解决 ASD受试者之间的异质性。目的2将在390例受试者中鉴定预后性RNA-Seq表达模式。 ASD 1-2奥尔兹通过分析基因表达水平来揭示预测良好/不良社交和 3-4岁时的语言结果。目标2还将纵向观察ASD（n=300）， （n=200）表达数据，以鉴定作为从1-2年到10年的临床进展的基础的转录组学轨迹。 3-4在这些不同的临床结果亚组中，目标3将研究发展中的变化 功能性基因组模式涉及诊断类别中的社会和语言能力的变化 （n= 1，000）和ASD内（n=390）使用降维和特征选择回归。多重共线的 回归将用于联合收割机降维的多变量趋势观察与 回归的预测能力。目标4将把目标1至3中的关键转录组学效应与目标2中的遗传变异联系起来。 高置信度和可能的ASD基因，这些基因与我们ASD受试者中被破坏的细胞通路有关。 这些基因中的有害变体将使用CRISPR-Cas9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将用于测定对ASD相关基因的影响。 细胞通路