Alignment of cortical development trajectories with emergent dimensional psychopathology and related risk factors among early adolescents in the ABCD Study

破译精神疾病的生物学特征的努力现在越来越多地集中在青春期，这一时期 在许多疾病的发病高峰期之前的大脑快速发育的特征。成熟度 长期以来，大脑皮层一直被认为是早期症状出现的媒介。 然而，虽然特定的皮质变化与少数特定的综合征有关，但对于 大多数情况下，作为精神病理学分化基础的皮质发育模式仍然存在。 不确定。正在进行的青少年大脑认知发展(ABCD)研究提供了一项前所未有的 将特定的精神病理学模式的出现与大脑皮层的特定变化相结合的机会 成熟。在接下来的5年里，ABCD将获得年度、标准化的测量维度 对21个美国网站的11875名年轻人进行了精神病理学和每两年一次的核磁共振扫描，年龄从9岁到16岁不等。 拟议的研究将利用这种纵向设计来发现区域和时间上的特定 与次元精神病理学的出现有关的皮质发育特征，然后 将这些模式与潜在的基因组和环境风险的特定特征联系起来。基线分析 从9岁到10岁的数据，包括在这份申请中，表明精神病理学处于早期阶段 分化，虽然已经与儿童发病障碍的多基因风险密切相关，但与 确立了产前和产后的环境侮辱。拟议研究的目标1将并列临床和 通过三个后续时间点对基线数据进行成像，主要关注是否偏离 神经年龄相关的皮质变薄轨迹(通过截距、斜率和二次指数进行评估) 与疾病的特定方面的出现有关。临床和临床的精确时间对齐 皮质变薄轨迹将向推断因果关系迈出第一步，这将进一步 通过与基因组(目标2)和环境(目标3)风险概况进行三角测量而得到证实。多基因 由精神病学基因组学联盟开发的评分方法将用于确定 Aim 1中的皮质成熟轨迹在基因组风险和紧急情况之间的关系中起中介作用 次元精神病态学。然后，使用数百项环境措施的数据进行游说 参与者的日常活动、营养、生活压力源、社会经济地位、家庭动态、邻居 安全性和许多其他因素，我们将使用新的机器学习方法来开发配置文件 暴露的危险因素，预测紧急维度精神病理，并确定皮质 成熟模式在环境风险特征与临床病程之间的关系中起中介作用。由 总结建议的研究，我们希望建立特定的皮质信号，连接原因因素 青春期的紧急精神病理学，这可以被用来开发新的预防措施 干预措施。

Efforts to decipher biological signatures for mental illness now focus increasingly on adolescence, a period of rapid brain development that immediately precedes the peak age of onset for many disorders. Maturation of the cerebral cortex during this time has long been thought to mediate emergence of early symptoms. However, while specific cortical changes have been implicated in a small number of specific syndromes, for the most part, patterns in cortical development that underlie the differentiation of psychopathology remain uncertain. The ongoing Adolescent Brain Cognitive Development (ABCD) study provides an unprecedented opportunity to align emergence of specific patterns of psychopathology with specific changes in cortical maturation. Over the next 5 years, ABCD will obtain annual, standardized measures dimensional psychopathology, and biennial MRI scans, of 11,875 youths across 21 US-based sites, covering age 9 to 16. The proposed studies will leverage this longitudinal design to discover regionally- and temporally-specific features of cortical development that associate with emergence of dimensional psychopathology, and then to relate these patterns to specific profiles of underlying genomic and environmental risk. Analysis of baseline data from age 9-10, included in this application, indicates that psychopathology is in early stages of differentiation, although already strongly related to polygenic risk for child-onset disorders, and to well- established pre- and post-natal environmental insults. Aim 1 of the proposed studies will juxtapose clinical and imaging data from baseline through three follow-up time points, focusing primarily on whether departures from neurotypical age-related cortical thinning trajectories (assessed via intercept, slope, and quadratic indices) associate with emergence of specific dimensions of illness. The precise temporal alignment of clinical and cortical thinning trajectories will take an initial step towards inferring causal relationships, which will be further substantiated through triangulation with genomic (Aim 2) and environmental (Aim 3) risk profiles. Polygenic scoring methods developed by the Psychiatric Genomics Consortium will be used to determine whether cortical maturation trajectories developed in Aim 1 mediate relationships between genomic risk and emergent dimensional psychopathology. Then, using data from hundreds of environmental measures that canvass participants’ daily activities, nutrition, life stressors, socioeconomic status, family dynamics, neighborhood safety, and numerous other factors, we will use novel machine learning methods to develop profiles of exposomic risk factors that predict emergent dimensional psychopathology, and determine whether cortical maturation patterns mediate the relationship between environmental risk profiles and clinical course. By the conclusion of the proposed studies we hope to establish specific cortical signatures that bridge causal factors with emergent psychopathology in adolescence, and that can be leveraged to develop new preventative interventions.