Genetic Networks Influencing Gray Matter Changes in Persistent ADHD

 描述(申请人提供)：注意缺陷多动障碍(ADHD)指的是一种早发性神经行为障碍。在15%到65%的病例中，这一大群患者的失业率、婚姻问题(Relationship⁄)、冒险行为、事故和违法行为都较高。这项建议的目的是提高我们对持续性ADHD的神经病理学的理解。有三种遗传途径与ADHD症状负荷、疾病严重程度和神经心理表现相关：多巴胺/去甲肾上腺素途径、5-羟色胺途径和神经突起生长网络。ADHD患者大脑中的灰质减少已被反复报道，它可能涉及额纹状体回路以外的许多复杂网络。然而，确切的遗传变异，以及它们对大脑结构缺陷和成年后持久性的综合影响，仍然未知。我们将系统地整合与儿童和成人ADHD相关的大脑结构、常见基因变异和症状，以揭示持续到成年的ADHD症状对神经基质的遗传影响。我们将首先提取成人大脑结构图像中的灰质(GM)网络，并评估它们与ADHD的两个症状域(注意力不集中和多动/冲动)的相关性。然后，我们将分析儿童和青少年的数据集，以确定与儿童的这两个症状领域相关的GM网络。通过比较成人和儿童的ADHD症状相关网络，我们将能够识别ADHD儿童和成人共同的GM减少模式，这些模式对ADHD的持久性具有指示和预测能力。其次，我们将结合与ADHD症状相关的GM网络，分析来自三条遗传途径的单核苷酸多态(SNPs)，并确定未受影响的兄弟姐妹是否携带中等遗传图谱风险和GM网络缺陷。最后，我们将利用两个独立的数据集，(1)被诊断为ADHD的儿童和成年后的随访信息，以及2)ADHD成人和年龄匹配的健康对照组)来重复最初的结果，并基于GM异常和已确定的遗传因素评估ADHD的分类和预测能力。在这个项目结束时，我们已经确定了灰质的模式，显示出与儿童和成人的ADHD症状显著相关。这将使我们能够理清导致持续性ADHD的(部分)神经变化。更重要的是，我们将确定这三条途径的遗传变异与这些神经生物学异常之间的联系，并提高我们对持续性ADHD神经病理的理解。由此得到的GM特征和遗传因素为持续性ADHD提供了生物学指标，这将有助于预测ADHD儿童在成年后是否会继续出现症状，从而有助于早期预防、诊断和治疗。

 DESCRIPTION (provided by applicant): Attention Deficit Hyperactivity Disorder (ADHD) refers to an early-onset neurobehavioral disorder. Its persistence into adulthood has just been recognized in 15% to 65% of cases, and this large group of patients suffers from higher rates of unemployment, relationship ⁄marital difficulties, risk taking behavior, accidents and legal violations. The goal of this proposal is to improve our understanding of the neuropathology of persistent ADHD. Three genetic pathways have shown genetic associations with ADHD symptom load, disease severity and neuropsychological performance: the dopamine/noradrenaline pathway, the serotonin pathway and the neurite outgrowth network. Gray matter reduction in the brain of patients with ADHD has been repeatedly reported, and it likely involves many complex networks beyond the fronto-striatal circuit. Yet the exact genetic variants, and their integrated effect on the brain structural deficits and persistence into adulthood, are still unknown. We will systemically integrate brain structure, common genetic variants and symptoms associated with children and adults with ADHD, to reveal genetic effects on the neural substrate of ADHD symptoms which persist into adulthood. We will first extract gray matter (GM) networks in adults' structural brain images, and evaluate their associations with the two symptom domains (inattentive and hyperactive/impulsive) of ADHD. We will then analyze datasets of children and adolescents to identify GM networks related to the two symptom domains in children. Through comparing ADHD symptom related networks in adults and children, we will be able to identify the GM reduction patterns common to children and adults with ADHD, which carry indicative and predictive power for the persistence of ADHD. Second, we will analyze Single Nucleotide Polymorphisms (SNPs) from the three genetic pathways in conjunction with GM networks associated with ADHD symptoms, and we will determine whether unaffected siblings carry intermediate genetic profile risks and GM network deficits. Finally, we will leverage two independent datasets, (1) children diagnosed with ADHD and with follow-up information in adulthood, and 2) adults with ADHD and age-matched healthy controls) to replicate the initial results and to evaluate the classification and prediction power n persistence of ADHD based on GM abnormalities and genetic factors identified. At the end of this project, we have identified the patterns of gray matter showing significant association with ADHD symptoms in both childhood and adulthood. This will allow us to disentangle the neural changes (partially) responsible for the persistent form of ADHD. More importantly, we will identify the connections between genetic variations from the three pathways and such neurobiological anomalies, and improve our understanding of neuropathology of persistent ADHD. The derived GM features and genetic factors provide biological metrics for persistent ADHD, which will help to predict whether a child with ADHD will continue to have symptoms in adulthood, thus aid early prevention, diagnosis, and treatment.