Characterizing mechanistic heterogeneity across ADHD and Autism

说明(申请人提供)：由于缺乏能够检测和区分疾病的客观生物学措施，在确定精神疾病病因学方面的进展受到限制。这个问题在发育障碍中尤其重要，在发育障碍中，早期识别最终可能有助于预防终身损伤。儿童精神病学中最常见和代价最高的两种早期发育障碍是注意力缺陷多动障碍(ADHD)和自闭症谱系障碍(ASD)。最近2011年的一项研究对1997-2008年间的情况进行了调查，现在证实，每6名儿童中就有1名患有发育障碍，在过去十年中增加了17%，主要是由于自闭症和ADHD的增加。这些事态发展突出表明，需要采取创新办法来解决这些疾病的根本原因。临床的异质性和其病因学区别的不精确性质很可能是从根本上限制了对其病因、预防和治疗的更好理解的混杂因素。有趣的是，关于ASD和ADHD的脑成像，一个新的观察结果是，它们通常具有相同的非典型功能脑信号。然而，由于这两种综合征几乎都是单独研究的，所以很难确定与每种疾病的不同之处相比，常见的非典型脑功能。如果我们要提高我们对这些疾病的潜在病因的理解，就有必要同时研究这些人群。话虽如此，简单地根据DSM诊断对儿童进行分组比较不太可能满足需要。每个综合征中的行为和生物异质性进一步复杂化了在脑成像中发现的任何给定的组差异的意义。因此，我们在理解上的进步不仅需要在相同的研究中检查这些障碍，还需要确定大脑特征如何与跨越症状的不同行为成分(即，内表型)相关。在此背景下，根据NIMH的新战略计划，战略1.4(也参见RDoC)，当前的提议旨在使用静息状态功能连通性磁共振(Rs-fcMRI)和结构连通性(DTI)来识别与ADHD和/或ASD中发现的基本行为成分(执行、面部识别和情感识别)相对应的大脑特征。我们的目标还包括利用包括图论和支持向量机(SVM)的模式分类在内的计算工具来开发这些疾病的集成的、多模式子分类(即神经类型)或“生物特征”。拟议的机械性分类对ADHD和ASD未来的功能、遗传、治疗和其他翻译研究的潜在影响是巨大的。

DESCRIPTION (provided by applicant): Progress in establishing the etiology of psychiatric illness is limited by the absence of objective biological measures able to detect and discriminate between disorders. This problem is particularly important in developmental disorders, where early identification could eventually assist in prevention of lifelong impairments. The two earlies onsets, most common and costly developmental disorders in child psychiatry are attention deficit hyperactivity disorder (ADHD) and Autism spectrum disorders (ASD). A recent 2011 study, surveying the years 1997-2008, has now verified that 1 in 6 children have a developmental disability, a 17% increase over the past decade driven largely by increases in ASD and ADHD. These developments highlight the need for innovative approaches to address the underlying cause of these disorders. It is likely that the clinical heterogeneity and the imprecise nature of their nosological distinctions represent fundamentally confounding factors limiting a better understanding of their etiology, prevention, and treatment. Interestingly, an emerging observation regarding brain imaging in ASD and ADHD is that they often have the same atypical functional brain signatures. However, because these two syndromes are almost exclusively studied separately, it is difficult to determine atypical brain function that is common compared to what is distinct for each disorder. If we are to improve our understanding regarding the underlying etiology of these disorders, it will be necessary to study these populations simultaneously. With that said, simply comparing groups of children based on their DSM diagnosis is unlikely to suffice. The behavioral and biological heterogeneity within each syndrome further complicates the meaning of any given group difference found in brain imaging. Thus, progress in our understanding requires not only examining these disorders in the same studies, but also identifying how brain signatures relate to distinct behavioral components (i.e., endophenotypes) that span the syndromes. Under this context, and consistent with NIMH's new strategic plan, Strategy 1.4 (also see RDoC), the current proposal aims to use resting state functional connectivity MRI (rs-fcMRI) and structural connectivity (DTI) to identify brain signatures that correspond to fundamental behavioral components (executive, facial recognition, and affect recognition) found in ADHD and/or ASD. We also aim to develop integrated, multimodal sub-classifications (i.e. neurotypes) or "biosignatures" of these disorders with computational tools that include Graph Theory and support vector machine (SVM) based pattern classification. The potential impact of the proposed mechanistic categorization on future functional, genetic, treatment, and other translational studies of ADHD and ASD are substantial.