fcMRI in Infants at High Risk for Autism

自闭症高危婴儿的 fcMRI

• 批准号: 9002864
• 负责人: John R Pruett
• 金额: $ 44.07万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-17 至 2018-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9002864
• 关键词: Adult; Affect; Age; Alzheimer' s Disease; Area; Atlases; Autistic Disorder; Behavior; Behavior assessment; Behavioral; Behavioral Symptoms; Brain; Brain Diseases; Brain region; Child; Childhood; Classification; Collection; Communication; Complement; Data; Data Analyses; Data Collection; Data Coordinating Center; Data Set; Databases; Development; Diagnosis; Diagnostic; Diagnostic tests; Diffusion Magnetic Resonance Imaging; Disease; Early identification; Ensure; Etiology; Euclidean Space; Fiber; Functional Imaging; Functional Magnetic Resonance Imaging; Funding; Future; Genetic; Genetic Risk; Genetic Screening; Goals; Group Meetings; Growth; Image; Image Analysis; Imagery; Individual; Infant; Intervention; Intervention Studies; Knowledge; Language; Length; Life; MRI Scans; Machine Learning; Magnetic Resonance Imaging; Measures; Mental disorders; Methods; Multimodal Imaging; Network-based; Neurobiology; Normal Range; Outcome; Parkinson Disease; Pathway Analysis; Pattern; Property; Public Health; Research; Research Infrastructure; Research Personnel; Rest; Risk; Scanning; Scientist; Seeds; Sensitivity and Specificity; Sensory; Site; Sleep; Structure; Symptoms; Testing; Thick; Training; United States National Institutes of Health; Work; autism spectrum disorder; autistic children; base; brain behavior; case control; cost; early onset; gaze; graph theory; high risk; high risk infant; improved; infancy; insight; interest; joint attention; novel; patient population; phenotypic data; programs; repetitive behavior; response; social; tool

DESCRIPTION (provided by applicant): This ESI / New Investigator clinician-scientist brings an expert team to test the altered brain functional connectivity hypothesis of autism during infancy. We will conduct graph-theory-based network analyses on functional connectivity magnetic resonance imaging (fcMRI) data acquired in high-risk infants who are currently being studied in the multi-site, NIH-funded Autism Center of Excellence (ACE) study R01 HD055741: A Longitudinal MRI Study of Infants at Risk for Autism - Joseph Piven: PI. We will prospectively study diverging developmental trajectories for functional networks of brain regions in infants who do and do not develop an Autistic Spectrum Disorder (ASD), during a suspected period of altered brain growth in autism, and prior to symptom expression. All four ACE data collection sites and their existing Data Coordination Center will participate. These efforts will provide longitudinal fcMRI data (scans at 6, 12, and 24 months old) in up to 664 high-risk and control infants (~15% of the 544 high-risk infants will develop an ASD). All four ACE data collection sites are already (as of May, 2010) - in advance of any dedicated funding, to ensure enough fcMRI data - acquiring fcMRI data on their subjects. Interfacing with the high-risk infant ACE structural imaging study and its supplements will allow us to build on existing infrastructure, save effort and cost, standardize collections, and merge databases. It also provides the potential for future genetic-functional imaging associations. Our fcMRI approach considers the problem of autism from the perspective of alterations in the behavior of brain-wide networks and changes in strengths of functional connectivity between and within rigorously defined sub-networks of brain regions. We believe this approach is more fruitful than those which consider smaller numbers of brain regions. We will additionally use a novel cortical functional areal parcellation routine (that Co-I Steve Petersen et al. have developed) to enhance the sensitivity of the infant fcMRI data analyses. Unique insights may come from comparing our network-based fcMRI analyses to the structural MRI, diffusion tensor imaging, and extensive phenotypic data generated by the existing ACE study (fcMRI acquired in the same infants). Once diagnoses are assigned in the ACE study, we will use a machine learning, multivariate pattern classification approach (Support Vector Machine: SVM) to explore the possibility of developing a diagnostic classifier for ASD. The eventual goal would be to train an SVM to predict which infants will and will not develop ASD, based on network properties of their fcMRI data, prior to the expression of symptoms. If successful, our proposed program of research could inform the future development of pre- symptomatic diagnostic tests for ASD, increase our knowledge about the neurobiology of autism, and provide methods for studying functional brain changes in response to interventions. These approaches could be adapted for the study of other neurodevelopmental and early-onset psychiatric disorders.

描述（由申请人提供）：这位 ESI/New Investigator 临床医生科学家带来了一个专家团队来测试婴儿期自闭症改变的大脑功能连接假设。我们将对高危婴儿采集的功能连接性磁共振成像 (fcMRI) 数据进行基于图论的网络分析，这些婴儿目前正在 NIH 资助的多地点自闭症卓越中心 (ACE) 研究 R01 HD055741 中进行研究：对有自闭症风险的婴儿的纵向 MRI 研究 - Joseph Piven：PI。我们将前瞻性地研究患有和未患有自闭症谱系障碍（ASD）的婴儿在疑似自闭症大脑生长改变期间以及症状表现之前大脑区域功能网络的不同发育轨迹。所有四个 ACE 数据收集站点及其现有的数据协调中心都将参与。这些工作将为多达 664 名高危婴儿和对照婴儿提供纵向 fcMRI 数据（在 6、12 和 24 个月大时扫描）（544 名高危婴儿中约有 15% 会患上自闭症谱系障碍）。所有四个 ACE 数据收集站点都已经（截至 2010 年 5 月）——在任何专门资金之前——以确保足够的 fcMRI 数据——获取其受试者的 fcMRI 数据。与高风险婴儿 ACE 结构成像研究及其补充相结合将使我们能够在现有基础设施的基础上进行构建，节省精力和成本，标准化收集并合并数据库。它还为未来的遗传功能成像关联提供了潜力。我们的 fcMRI 方法从全脑网络行为的改变以及严格定义的大脑区域子网络之间和内部功能连接强度变化的角度来考虑自闭症问题。我们相信这种方法比那些考虑较少数量大脑区域的方法更有效。我们还将使用一种新颖的皮质功能区域分割例程（Co-I Steve Petersen 等人开发的）来增强婴儿 fcMRI 数据分析的灵敏度。独特的见解可能来自于将我们基于网络的 fcMRI 分析与结构 MRI、扩散张量成像以及现有 ACE 研究生成的广泛表型数据（在同一婴儿中获取的 fcMRI）进行比较。一旦在 ACE 研究中分配诊断，我们将使用机器学习、多元模式分类方法（支持向量机：SVM）来探索开发 ASD 诊断分类器的可能性。最终目标是训练 SVM，在症状出现之前，根据 fcMRI 数据的网络特性来预测哪些婴儿会患上 ASD，哪些不会患上 ASD。如果成功，我们提出的研究计划可以为自闭症谱系障碍症状前诊断测试的未来发展提供信息，增加我们对自闭症神经生物学的了解，并提供研究干预措施引起的功能性大脑变化的方法。这些方法可以适用于其他神经发育和早发精神疾病的研究。

项目成果

Commentary - Autism Spectrum Disorder: Spectrum or Cluster?

• DOI: 10.1002/aur.1650
• 发表时间: 2016-12
• 期刊: AUTISM RESEARCH
• 影响因子: 4.7
• 作者: Pruett, John R., Jr.;Povinelli, Daniel J.
• 通讯作者: Povinelli, Daniel J.

Joint Attention and Brain Functional Connectivity in Infants and Toddlers.

• DOI: 10.1093/cercor/bhw403
• 发表时间: 2017-03-01
• 期刊: Cerebral cortex (New York, N.Y. : 1991)
• 作者: Eggebrecht AT;Elison JT;Feczko E;Todorov A;Wolff JJ;Kandala S;Adams CM;Snyder AZ;Lewis JD;Estes AM;Zwaigenbaum L;Botteron KN;McKinstry RC;Constantino JN;Evans A;Hazlett HC;Dager S;Paterson SJ;Schultz RT;Styner MA;Gerig G;Das S;Kostopoulos P;IBIS Network†;Schlaggar BL;Petersen SE;Piven J;Pruett JR Jr
• 通讯作者: Pruett JR Jr