Identifying shared and distinct alterations in brain structure across childhood psychiatric disorders using the ENIGMA consortium

流行病学研究估计，大约16%的儿童有可诊断的心理健康问题。儿童期精神障碍与不良后果有关，如生活质量和功能较差、犯罪和持续的精神健康问题。因此，它们造成了巨大的个人和社会成本。研究儿童时期的心理健康问题是促进早期预防和干预策略的关键。虽然现代精神病学主要关注分类诊断，但越来越多的证据表明，合并症超越了这些不同的诊断，以及跨疾病的共同遗传影响。尽管如此，迄今为止，大多数神经影像学研究集中在单一的，特定的疾病，而不是比较多个诊断彼此和对照组。那些尝试跨疾病比较往往只集中在成人样本，并产生不一致的结果，防止跨诊断神经生物学基板的强大的理解。小样本量和异质性参与者群体（例如，在年龄和性别方面）降低了我们在研究之间进行比较的能力，并对统计能力产生了负面影响。此外，方法上的差异（例如，因此，使用统一的数据采集、处理和分析协议，Meta分析和大规模分析的应用对于研究各种疾病之间共享的和不同的神经生物学改变至关重要。这项大规模研究的可行性已经在Goodkind et al.（2015）和Opel et al.（2020）的大脑结构研究中以及Koshiyama et al.（2020）的白质连接研究中得到了证实，他们都发现了疾病特异性和交叉疾病改变的证据。然而，缺乏来自儿童和青少年样本的证据。因此，本项目将填补文献中的空白，旨在调查不同儿童精神疾病之间大脑结构或连接的共同与独特改变。此外，我们将探索不同疾病的大脑成熟模式，并研究合并症和性别等因素的影响。本研究将利用来自Enhancing Neuro-Imaging Genetics through Meta-Analysis（ENIGMA）联盟的数据，ENIGMA联盟是一个旨在汇集数据和资源的国际团队科学合作，并通过避免方法异质性和出版偏倚来克服常见局限性（Thompson et al. 2020）。ENIGMA由50多个工作组组成，该项目将利用这些工作组的数据，重点关注情绪和行为障碍。这些障碍的最终样本量估计为6，000 - 10，000，与一个更大的数字典型的发展controls.This项目将是最大的和最全面的神经影像学研究的transdiagnosis精神病理学在儿童和青少年的日期，而大分析的白质连接数据是一个特别新颖的方法在该领域。无论是一般性还是特定性疾病，这些发现都将为关于精神病理学性质的关键辩论提供信息，可能建立在行为遗传学研究的基础上，为儿童心理健康提供一个组织模型，对我们的诊断系统具有重要意义（例如，DSM、ICD）。按年龄组对样本进行分层将允许调查不同疾病的大脑成熟模式，这一现象可能在以前的研究中混淆。该项目的研究结果有助于儿童疾病的早期诊断和治疗，对整个社会有重大的好处。我希望能去南加州大学进行一次机构访问，恩尼格玛中心就在那里。

Epidemiological studies estimate that around 16% of children have a diagnosable mental health problem. Childhood psychiatric disorders are associated with adverse outcomes such as poorer quality of life and functioning, criminality, and continued mental health difficulties. Consequently, they incur significant individual and societal costs. Studying mental health difficulties in childhood is key to promoting early prevention and intervention strategies.While modern psychiatry has largely focused on categorical diagnoses, there is increasing evidence of comorbidity transcending these distinct diagnoses, as well as shared genetic influences across disorders. Still, to date most neuroimaging studies focus on single, specific disorders, rather than comparing multiple diagnoses with each other and control groups. Those that do attempt cross-disorder comparisons often focus exclusively on adult samples, and yield inconsistent findings that prevent a robust understanding of transdiagnostic neurobiological substrates. Small sample sizes and heterogenous participant groups (e.g., in terms of age and sex) reduce our ability to compare across studies and negatively impact statistical power. Additionally, methodological differences (e.g., data acquisition and analysis methods) further limit the comparability of findings.The application of meta- and mega-analyses are therefore vital to study shared and distinct neurobiological alterations across disorders, using harmonised protocols for data acquisition, processing and analysis. The feasibility of this large-scale research has been established in studies of brain structure by Goodkind et al. (2015) and Opel et al. (2020), and in white-matter connectivity by Koshiyama et al. (2020), all of whom found evidence of both disorder-specific and cross-disorder alterations. However, there is a dearth of evidence from child and adolescent samples.This project will therefore address a gap in the literature, with the aim of investigating shared versus distinct alterations in brain structure or connectivity across different childhood psychiatric disorders. Furthermore, we will explore different patterns of brain maturation across disorders, and study the impact of factors such as comorbidity and sex. This study will utilise data from the Enhancing Neuro-Imaging Genetics through Meta-Analysis (ENIGMA) consortium, an international team-science collaboration aiming to pool data and resources, and overcome common limitations by avoiding methodological heterogeneity and publication bias (Thompson et al. 2020). While ENIGMA is comprised of over 50 working groups, this project will draw on data from the working groups focusing on emotional and behavioural disorders. The final sample size of those with disorders is estimated to be 6,000-10,000, with an even larger number of typically-developing controls.This project will be the largest and most comprehensive neuroimaging study of transdiagnostic psychopathology in children and adolescents to date, while mega-analysis of white-matter connectivity data is a particularly novel methodology in the field. Whether disorder-general or specific, the findings will inform key debates regarding the nature of psychopathology, potentially building on behavioural genetic research to provide an organising model of childhood mental health, with important implications for our diagnostic systems (e.g., DSM, ICD). Stratifying the samples by age group will allow the investigation of different patterns of brain maturation across disorders, a phenomenon which may have been a confound in previous research. The findings of this project could contribute to early diagnosis and treatment of childhood disorders, with significant benefits to society at large.I hope to go on an institutional visit to the University of Southern California, where ENIGMA Central is based.