Discovering Molecular and Neural Biomarkers of Social and Language Development in ASD Toddlers

发现 ASD 幼儿社交和语言发展的分子和神经生物标志物

• 批准号: 10862025
• 负责人: ERIC COURCHESNE
• 金额: $ 66.01万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10862025
• 关键词: Address; Adult; Affect; Affective; Affective Symptoms; Age; Autopsy; Behavioral; Biological; Biological Markers; Biological Process; Brain; Brain imaging; Cell model; Child; Clinical; Communication; Data; Data Set; Development; Diagnosis; Disease; Ethnic Origin; Functional Magnetic Resonance Imaging; Functional disorder; Gene Expression; General Population; Genes; Gestational Age; Glean; Grant; Heterogeneity; Image; Impairment; Intake; Knowledge; Language; Language Development; Learning; Leukocytes; Licensing; Life; Linear Regressions; Link; Magnetic Resonance Imaging; Maps; Measures; Methods; Modality; Molecular; Molecular Medicine; Molecular Profiling; National Institute on Deafness and Other Communication Disorders; Neuronal Dysfunction; Neurons; Outcome; Parents; Pathway interactions; Patients; Pattern; Process; Prognosis; Prognostic Marker; Psychologist; Psychometrics; Publications; Race; Reproducibility; Role; Sampling; Severities; Signal Pathway; Signal Transduction; Social Development; Social Interaction; Social outcome; Speech; Standardization; Structure; Subgroup; Symptoms; Testing; Time; Toddler; Treatment outcome; Validation; Work; autism spectrum disorder; brain overgrowth; cell type; checkup examination; clinical predictors; clinical prognosis; clinically actionable; cohort; computer studies; design; differential expression; disability; disorder subtype; early screening; fetus cell; in vivo; indexing; individual patient; innovation; insight; language outcome; molecular subtypes; morphometry; multimodality; nerve stem cell; neural; neuroimaging; novel; outcome prediction; patient prognosis; patient subsets; pediatrician; postnatal; precision medicine; predict clinical outcome; prenatal; prenatal disorder; prevent; prognostic; response; risk variant; social; social communication; social deficits; transcriptomics; visual tracking

Social affect, social processing, and social communication symptoms differing in degrees of severity appear in the first years of life in autism spectrum disorder (ASD), giving rise to pervasive, lifelong challenges to patients, parents, and therapists. Lack of verified early-age biological and clinical ASD subtypes prevents accurate prediction of clinical progression and treatment outcome. ASD social affective symptoms are ASD specific signs and can be indexed by motherese eye tracking (ET); social differences are undoubtedly caused by neural dysfunction such as those found by our grant, but the molecular pathobiology underlying neural and ET social heterogeneity are not well understood. Subtypes of fMRI neural responses to social affective language are known from our grant work, as are atypical cortical patterning for a subgroup of ASD toddlers with poor language and social outcomes. Our recent work identifies gene expression features associated with such subgroups, and dysregulated signaling pathways are related to social symptom severity. Missing is how these various imaging, social and gene findings are connected in ASD subtypes, and what molecular drivers underlie social neural activity. AIM 1 - discover underlying molecular drivers of ASD social neural and social ET subtypes. Using an unsupervised data-driven precision medicine method (Similarity Network Fusion (SNF)) for patient subtyping, we will integrate multimodality social clinical, social eye tracking, social speech activation fMRI, MRI-based cortical parcellation, and transcriptomic data from a large new cohort of toddlers to discover molecular dysregulations underlying subtypes of ASD social neural dysfunction. Replication analyses will use our existent NIDCD cohort as an independent sample. Subtypes will be tested for robustness and reproducibility. Features in each modality that differentiate ASD subtypes will be identified via tests of each pair of subtypes over each data modality. AIM 2 - prenatal molecular processes and cell types associated with ASD neural-social subtypes. Using normative BrainSpan expression data to map prenatal temporal-spatial activity of pathways disrupted in ASD subtypes, we will learn when and where disrupted pathways in ASD subtypes are normally upregulated during prenatal development. Top differentially expressing (DE) genes in each disrupted pathway will be analyzed for enrichment in GO biological processes. Using normative cell type- specific gene markers, we will test whether DE genes in ASD neural-social subtypes enrich prenatal and postnatal cell type-specific markers, and determine which neural-social subtypes strongly express a recently identified multi-pathway DE-ASD network that is over-active in ASD neural progenitors and neurons. AIM 3 – prognosis prediction from ASD subtypes. For toddlers in each ASD subtype, we use Bayesian multimodality sparse linear regression learning to determine which transcriptomic, brain imaging, eye tracking and treatment features in each subtype predict each child's outcome social and language 1.5 years after clinical intake. This opens avenues for clinical actionable prognostic outcome subtype markers for individual patients.

社会影响、社会处理和社会沟通症状的严重程度不同， 自闭症谱系障碍（ASD）的最初几年，给患者带来了普遍的终身挑战， 父母和治疗师缺乏经过验证的早期ASD生物学和临床亚型， 预测临床进展和治疗结果。ASD社交情感症状是ASD的特异性体征 并且可以通过母亲的眼动追踪（ET）进行索引;社会差异无疑是由神经系统引起的。 功能障碍，如我们的资助发现，但神经和ET社会基础的分子病理学， 异质性还没有得到很好理解。对社会情感语言的功能磁共振成像神经反应的亚型是已知的 从我们的资助工作中，一个语言能力差的ASD幼儿亚组的非典型皮层模式也是如此， 社会成果。我们最近的工作确定了与这些亚群相关的基因表达特征， 失调的信号通路与社会症状的严重程度有关。缺少的是这些不同的成像， 社会和基因发现在ASD亚型中是相互联系的，什么样的分子驱动因素是社会神经的基础？ 活动目的1 -发现ASD社交神经和社交ET亚型的潜在分子驱动因素。使用 一种无监督的数据驱动的患者精准医疗方法（相似网络融合（SNF）） 分型，我们将整合多模态社会临床，社会眼动跟踪，社会言语激活功能磁共振成像， 基于MRI的皮质包裹，以及来自一个新的大型幼儿队列的转录组数据， ASD社交神经功能障碍亚型的分子失调。复制分析将使用 我们现有的NIDCD队列作为独立样本。将检测亚型的稳健性， 再现性将通过每种模态的测试来识别区分ASD亚型的每种模态的特征。 每个数据模态上的子类型对。目的2 -产前分子过程和细胞类型与 ASD神经社会亚型使用规范的BrainSpan表达数据绘制产前时空图 活动的途径中断ASD亚型，我们将了解何时何地中断途径在ASD 亚型通常在产前发育期间上调。差异表达（DE）基因 将分析每种被破坏的途径在GO生物过程中的富集。使用标准细胞类型- 特异性基因标记，我们将测试ASD神经社会亚型中的DE基因是否丰富了产前和 出生后的细胞类型特异性标记，并确定哪些神经社会亚型强烈表达最近 鉴定了在ASD神经祖细胞和神经元中过度活跃的多途径DE-ASD网络。目标3 - ASD亚型的预后预测对于每种ASD亚型的幼儿，我们使用贝叶斯多模态 稀疏线性回归学习，以确定哪些转录组，脑成像，眼动跟踪和治疗 每个亚型的特征预测每个儿童在临床摄入后1.5年的社交和语言结果。这 为个体患者的临床可操作预后结果亚型标记物开辟了途径。