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，早期生物标志物很少。迫切需要进行研究以识别先前的标记 症状发作，传达预后信息或表示障碍亚型。我们提出的功能基因组学 ASD早期发展的研究解决了许多此类生物标志物目标，并且是必不可少的早期一步 这个发现过程。自ASD是异质的，强大的生物标志物是难以捉摸的 具有数千种推测风险基因和潜在非遗传免疫因子的发育障碍。我们 假设基于途径的转录组生物标志物可能是有益的，如我们最近的证明所示 概念研究的研究基于白细胞的基因表达提供了早期诊断ASD分类剂。我们的 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）和网络在白细胞中与大脑一样强烈表达。此外，假设的免疫 ASD中的干扰也应反映在白细胞中，尤其是因为小胶质细胞是一种白细胞 在ASD中被确定为脑分子和细胞病理。在我们提出的研究中，我们将使用1,500 RNA-seq数据集来自1,000个ASD，通常和非典型开发幼儿，以识别生物分子 途径生物标志物，用于早期检测，预后，临床进展和临床亚型。我们将进一步 研究生物标志物与早期神经发育中ASD基因缺陷和表达模式的关系。目标1 将使用数据驱动和基于知识的网络分析1,000 1-2岁儿童的RNA-seq数据 确定早期ASD诊断生物标志物的方法 非ASD（n = 610）组。诊断生物标志物将包括途径和共表达网络以解决 ASD受试者的异质性。 AIM 2将在390中识别预后的RNA-seq表达模式 通过分析基因表达水平来揭示预测社会良好/差的途径，ASD 1-2岁的孩子 3-4岁的语言结果。 AIM 2还将纵向看ASD（n = 300），通常会发展 （n = 200）表达数据以识别从1 - 2年到临床进展的转录组轨迹 在这些不同的临床结果亚组中3 - 4年。 AIM 3将研究发展的变化 功能基因组模式与诊断类别的社会和语言能力的差异有关 （n = 1,000）和在ASD（n = 390）内使用尺寸降低和特征选择回归。多共线 回归将用于将降低维度降低的多元趋势观察与 回归的预测能力。 AIM 4将在AIM 1到3中的关键转录组效应与遗传变异 与我们ASD受试者中的细胞途径有关的高信心和可能的ASD基因。 这些基因中的有害变体将在造血和神经干细胞中使用CRISPR-CAS9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相关的影响 细胞途径。