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 /新研究者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的大脑功能连通性假设的改变。我们将对在高危婴儿中获得的功能连通性磁共振成像（FCMRI）的数据进行基于图理论的网络分析，这些数据目前正在NIH，NIH资助的自闭症卓越中心（ACE）研究R01 HD055741：HD055741：long Pittialinal MRI研究对Autism-Jose-Jose-Jose-Jose-jose-pipivive的风险。我们将前瞻性研究在自闭症脑部生长发生变化的时期，在症状表达之前，在脑部脑部生长改变时期，在自闭症谱系障碍（ASD）的婴儿中的功能网络有分歧的发育轨迹。所有四个ACE数据收集站点及其现有数据协调中心将参与。这些努力将在多达664个高风险和控制婴儿中提供纵向FCMRI数据（在6、12和24个月大的扫描）（544名高危婴儿中约15％）。所有四个ACE数据收集站点（截至2010年5月）已经在任何专用资金之前，以确保足够的FCMRI数据 - 获取有关其主题的FCMRI数据。与高风险的婴儿ACE结构成像研究及其补充剂的接口将使我们能够以现有的基础设施为基础，节省努力和成本，标准化收藏品并合并数据库。它还为未来的遗传功能成像关联提供了潜力。我们的FCMRI方法从大脑网络行为的改变以及严格定义的大脑区域的子网络之间的功能连通性的强度变化，考虑了自闭症的问题。我们认为，这种方法比考虑较少数量的大脑区域的方法更富有成果。我们还将使用一种新型的皮质功能性面部拟合程序（这是Co-I Steve Petersen等人开发的）来增强婴儿FCMRI数据分析的敏感性。独特的见解可能来自将我们的基于网络的FCMRI分析与现有ACE研究产生的广泛的表型数据进行比较（在同一婴儿中获得的FCMRI）。一旦在ACE研究中分配诊断后，我们将使用机器学习，多元模式分类方法（支持向量机：SVM）来探索为ASD开发诊断分类器的可能性。最终的目标是训练SVM，以预测哪些婴儿将基于其FCMRI数据的网络特性，然后在症状表达之前就会发展ASD。如果成功的话，我们提出的研究计划可能会为ASD的未来症状诊断测试的未来发展，增加我们对自闭症神经生物学的了解，并提供用于研究功能性大脑变化以应对干预措施的方法。这些方法可以适应其他神经发育和早期精神疾病的研究。

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