Genetic Analysis of Attention Deficit Hyperactivity Disorder

注意力缺陷/多动障碍(ADHD)是最常见的神经发育行为障碍，全球约10%的儿童和青少年受到影响，经常持续到成年，可能会造成严重的终生健康后果。受影响的个人受教育程度低、收入低、就业不足、法律困难和社会关系受损的风险增加。据保守估计，在美国，ADHD每年造成的社会负担高达425亿美元。此外，ADHD还增加了物质使用障碍(SUD)和破坏性(外化)障碍的风险，如对立违抗障碍(ODD)、品行障碍(CD)。SUD的特征是在面临严重不良后果的情况下强迫寻求药物的行为和药物的使用。世界卫生组织估计，全球至少有20亿酒精使用者、10亿烟草使用者和近1.85亿非法吸毒者。 遗传因素与ADHD密切相关。在过去的四年里，我们对ADHD的遗传学研究取得了重大进展，了解了：1)ADHD及其相关合并症的先天易感性，2)支持ADHD风险的遗传、人口和环境因素的相互作用，3)这些因素在多大程度上塑造了ADHD患者对药物干预的反应(ADHD的药物遗传学)，4)与确定突触结构有关的基于功能和本体的基因网络的过度表达，以及5)具有临床应用潜力的先进遗传-流行病学模型的使用(翻译基因组学)。 到目前为止，我们已经确定了易患ADHD86的LPHN3基因的变异，并表明LPHN3变异与染色体11q上的单倍型相互作用，使ADHD的易感性增加一倍。这种单倍型包括NCAM1、TTC12、ANKK1和DRD2基因。描述这种相互作用可以更好地预测ADHD的严重程度、长期结果和治疗反应，并告知这些基因的过度表达，特别是个体发育途径可能如何参与与突触形成相关的过程。此外，在四个独立的队列中使用基于分类树的递归划分模型，我们不仅建立并证明了受人口和环境因素影响的寡基因模型可以预测发展为ADHD和破坏性行为的风险。这些发现代表了有史以来关于ADHD的最有力的重复基因研究之一。 我们的成功依赖于我们的研究设计的几个方面：1)仔细、彻底的临床特征，以及在所有研究中使用高度一致的表型。这是在复杂和异质条件下评估遗传成分的基本方法；2)综合使用各种方法，包括对来自几个队列、数千名个体的大型、多代和核心家庭进行连锁和分离研究(总计n=6360,2627名患有多动症患者)；3)开发和应用复杂和/或新颖的统计遗传技术，以解决主观评估的局限性和缺乏生物标记的问题。例如，考虑到行为遗传学的复杂性，我们选择了一种多元分类方法，潜在类别分析(LCA)，以更好地服务于我们的遗传学研究。这项分析使我们能够包括共病的定量信息，识别较温和的表型，并解释共病和ADHD症状之间的相关性；4)对我们样本中强烈遗传信号的遗传区域进行系统审查。从我们以前的连锁研究中，我们发现了多个强遗传信号区，即4q13.2、5q33.3、8p23.1、11q22和17p11)。 我们期望，这些新的分子底物的发现将导致使用遗传变异作为ADHD临床严重性、功能障碍共病和个体治疗反应的预测因子。这个项目是基于九个小组的国际合作，这些小组来自ADHD和破坏性行为领域的顶尖研究人员。我们的研究结果可以为今后ADHD的遗传学和相关疾病的关键功能分析提供基础。

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental behavioral disorder, affecting about 10% of children and adolescents worldwide.It frequently persists into adulthood and can have serious life-long health consequences. Affected individuals are at increased risk for poor educational achievement, low income, underemployment, legal difficulties, and impaired social relationships. The annual societal burden of ADHD was conservatively estimated to reach $42.5 billion in the U.S. In addition, ADHD increases the risk of substance use disorder (SUD) and disruptive (externalizing) disorders such as oppositional defiant disorder (ODD), conduct disorder (CD). SUD is characterized by compulsive drug seeking behavior and drug use in the face of severe adverse consequences. The World Health Organization estimates that there are worldwide at least two billion alcohol users, one billion tobacco users and almost 185 million illicit drug users. Genetic factors are strongly implicated in ADHD. During the last four years, our research on the genetics of ADHD made seminal advances to understand: 1) the innate susceptibility to ADHD and associated comorbidities, 2) the interaction of genetic, demographic and environmental factors underpinning the risk of developing ADHD, 3) how much these factors shape the response of ADHD patients to pharmacological interventions (pharmacogenetics of ADHD), 4) the overrepresentation of functional and ontological gene-based networks implicated in determining synapse structure, and 5) the use of advanced genetic-epidemiological models with potential for use in clinical practice (translational genomics). Thus far, we have identified variants of the latrophilin 3 gene (LPHN3) predisposing to ADHD86 and showed that LPHN3 variants interact with a haplotype on chromosome 11q, doubling ADHD susceptibility. This haplotype encompasses the NCAM1, TTC12, ANKK1, and DRD2 genes. Characterizing this interaction better predicts ADHD severity, long-term outcome and response to treatment and informs how the over-representation of these genes in particular ontogenetic pathways might be involved in processes related to synapse formation. Further, using classification tree-based recursive partitioning models in four independent cohorts, we not only built but also demonstrated that an oligogenic model influenced by demographic and environmental factors could predict the risk of developing ADHD and disruptive behaviors. These findings represent one of the most robustly replicated genetic study on ADHD ever. Our success has depended on several aspects of our research design: 1) Careful, thorough clinical characterization and use of a highly consistent phenotype in all the studies. This has been fundamental for evaluating genetic components in complex and heterogeneous conditions; 2) The use of a combination of approaches including linkage and segregation studies of large, multigenerational and nuclear families from several cohorts with thousands of indviduals (total n=6360, 2627 with ADHD); 3) The development and application of complex and/or novel statistical genetic techniques that address the limitations of subjective evaluations and the lack of biological markers. For example, given the complexity of the genetics of behavior, we chose a multivariate classification method, latent class analysis (LCA) to better serve our genetic studies. This analysis allowed us to include quantitative information of co-morbidities, identify milder phenotypes, and account for correlations between co-morbid and ADHD symptoms; 4) The systematic review of genetic regions of strong genetic signal in our samples. From our previous linkage studies we identified multiple regions of strong genetic signal, namely 4q13.2, 5q33.3, 8p23.1, 11q22, and 17p11). We expect that the discovery of these new molecular substrates will lead to the use of genetic variation as a predictor of clinical severity, dysfunctional comorbidity and individual treatment response in ADHD. This project was based on an international collaboration of nine groups from among the top researchers in the field of ADHD and disruptive behaviors. Our results could provide the foundation for key functional analyses of the genetics of ADHD and related conditions in the future.