Structural and Functional Characteristics of XYY - Relationship to ASD

XYY 的结构和功能特征 - 与 ASD 的关系

• 批准号: 9254609
• 负责人: Timothy P Roberts
• 金额: $ 20.6万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-11 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9254609
• 关键词: 16 year old; Acoustics; Address; Affect; Age; Anisotropy; Auditory; Auditory area; Autacoids; Autistic Disorder; Behavior; Behavior Disorders; Behavioral; Behavioral Symptoms; Biological; Biological Markers; Brain; Characteristics; Child; Child health care; Clinical; Cognitive; Coupled; Data; Data Collection; Data Set; Development; Developmental Delay Disorders; Diagnosis; Diagnostic; Diffuse; Diffusion Magnetic Resonance Imaging; Disease; Dissociation; Etiology; Fragile X Syndrome; Future; Gene Dosage; Genes; Genetic; Genetic Determinism; Genetic Heterogeneity; Genetic Models; Genetic Predisposition to Disease; Glutamates; Goals; Hereditary Disease; Heritability; Heterogeneity; Image; Intercept; Intervention; Link; Magnetic Resonance Spectroscopy; Magnetoencephalography; Matched Group; Measures; Methods; Modality; Modeling; Multivariate Analysis; Neurobiology; Neurodevelopmental Disorder; Neurotransmitters; Pathogenesis; Pathway interactions; Phase; Phenotype; Population; Radiation; Rett Syndrome; Risk; Role; Sex Chromosome Disorders; Sex Chromosomes; Social Interaction; Specificity; Subgroup; Superior temporal gyrus; Synapses; Syndrome; XYY Karyotype; Y Chromosome; autism spectrum disorder; boys; clinical biomarkers; clinical phenotype; cohort; communication behavior; design; disorder risk; efficacy study; falls; gamma-Aminobutyric Acid; genetic risk factor; improved; innovation; male; meetings; multidisciplinary; neural correlate; neurochemistry; neuroimaging; neurophysiology; overexpression; phenotypic biomarker; postnatal; public health relevance; repetitive behavior; sex; synaptic function; synergism; white matter

 DESCRIPTION (provided by applicant): This proposal addresses two challenges of great importance to child health: defining genetic etiologies of autism spectrum disorders (ASD) and establishing clinical-pathophysiological mechanisms in ASD. Autism is common in the US, affecting ~1% of the population, and is heterogeneous with regard to etiology, pathogenesis, and clinical presentation. A known, genetic risk factor for ASD is the male sex chromosome disorder, 47,XYY syndrome (XYY). Approximately one third of males with XYY satisfy diagnostic criteria for ASD, and XYY is significantly overrepresented in autism cohorts; yet this significant association is understudied. Coupled with the 4:1 male predominance for ASD, the increased risk for ASD in XYY suggests the involvement of sex-linked genes (i.e. increased Y chromosome gene copy number in XYY leads to over- expression of Y-linked genes related to brain development and function, thereby increasing ASD risk). The overarching goals of this proposal are to 1) better understand the particular role of the Y-chromosome in ASD, given the male preponderance and likely involvement of sex-linked genes, 2) to improve understanding of the neuroanatomic and neurophysiologic correlates of ASD in this relatively genetically homogeneous model of autism 3) to enlighten our understanding of convergent pathophysiological mechanisms that may generalize to the broader autism spectrum, and 4) to characterize the neural correlates of behavioral symptoms in boys with XYY, leading towards future targeted treatments and interventions. To accomplish these goals, we will contrast the clinical, behavioral and neurophysiological markers of ASD in four groups (20 per group) of age-matched (6-16 yrs) boys: XYY with ASD (XYY+ASD), XYY without ASD (XYY-ASD), ASD-Idiopathic (ASD-I) and typically developing (TD) controls. An existing well-characterized dataset will be used for ASD-I and TD cohorts. Cognitive and behavioral phenotypes will be obtained from 80 boys with XYY to yield 40 (20 XYY+ASD / 20 XYY-ASD) subjects suitable for imaging. Aims 1 and 2 seek to establish commonalities between the XYY+ASD and ASD-I populations as well as specificities of the ASD phenotype within the XYY population (XYY+ASD vs XYY-ASD) by comparing clinical/behavioral markers of ASD (in Aim 1) and local cortical neurophysiologic (magnetoencephalography) markers (in Aim 2) in the four groups. The mechanisms underlying the neurophysiologic measures will be probed in Aim 3, via the neuro- chemical magnetic resonance spectroscopy of key neurotransmitters GABA and glutamate and quantitative diffusion MRI. Aim 4 examines interactions between clinical/behavioral phenotypic markers and neurophys- iological, neurochemical and neuroimaging measures and will demonstrate that ASD in XYY+ASD shares a neurobiological basis with ASD-I. This innovative study takes advantage of the methodical ASD characteriza- tion of the unique XYY cohort (Dr. Ross), extensive ASD-I neuroimaging expertise (Dr. Roberts), compelling synergies of the multidisciplinary team, multi-modal data collection, and sophisticated multivariate analysis.

 描述(由申请人提供)：这项建议解决了两个对儿童健康非常重要的挑战：定义自闭症谱系障碍(ASD)的遗传病因和建立自闭症谱系障碍的临床病理生理机制。自闭症在美国很常见，影响大约1%的人口，并且在病因、发病机制和临床表现方面是不同的。已知的ASD的遗传风险因素是男性性染色体紊乱，47，XYY综合征(XYY)。大约三分之一患有XYY的男性符合ASD的诊断标准，而XYY在自闭症队列中的比例明显过高；然而，这种显著的联系还没有得到充分的研究。再加上ASD的男性比例为4：1，XYY患ASD的风险增加表明与性别相关的基因参与其中(即XYY中Y染色体基因拷贝数增加导致与大脑发育和功能相关的Y连锁基因过度表达，从而增加ASD风险)。这项建议的总体目标是：1)更好地理解Y染色体在自闭症中的特殊作用，考虑到男性的优势和性相关基因的可能参与；2)提高对自闭症这种相对遗传同质的自闭症模型中自闭症的神经解剖学和神经生理学相关性的理解；3)启发我们对可能概括到更广泛的自闭症谱系的趋同的病理生理机制的理解；以及4)表征患有XYY的男孩行为症状的神经相关性，从而引导未来的有针对性的治疗和干预。为了实现这些目标，我们将对比四组(每组20名)6-16岁男孩的ASD的临床、行为和神经生理学标志物：XYY伴ASD(XYY+ASD)、XYY无ASD(XYY-ASD)、ASD-特发性(ASD-I)和典型发育(TD)对照组。现有的特征良好的数据集将用于ASD-I和TD队列。将从80名患有XYY的男孩中获得认知和行为表型，以产生40名适合成像的受试者(20名XYY+ASD/20名XYY-ASD)。目标1和目标2通过比较四组ASD的临床/行为标记物(目标1)和局部皮质神经生理学(脑磁图)标记物(目标2)，试图建立XYY+ASD和ASD-I群体之间的共性以及XYY群体内ASD表型的特异性(XYY+ASD与XYY-ASD)。目标3将通过关键神经递质GABA和谷氨酸的神经化学磁共振波谱和定量扩散磁共振成像来探索神经生理学措施背后的机制。目的4研究临床/行为表型标记物与神经生理、神经化学和神经影像指标之间的相互作用，并将证明XYY+ASD的ASD与ASD-I具有共同的神经生物学基础。这项创新的研究利用了独特的XYY队列(Ross博士)的有条不紊的ASD特征、广泛的ASD-I神经成像专业知识(Roberts博士)、多学科团队的令人信服的协同效应、多模式数据收集和复杂的多变量分析。