Genetic Risk for Serious Mental Illness and Development

项目总结/摘要 临床分期作为一个潜在的强有力的框架正在获得牵引力，以了解发病机制， 严重精神疾病（SMI）的出现，如精神分裂症（SCZ），双相情感障碍（BP）和严重 抑郁症（严重DEP），跨发展，并指导旨在改变疾病的早期干预措施 弹道然而，要充分发挥这一方法的潜力，需要克服一些挑战。 这些挑战包括精神疾病之间的不精确界限;不明确的有效性， 早期临床和神经行为标志物预测后期疾病发作的特异性; 认识到目前的精神病疾病分类学可能无法以最佳的方式映射到潜在病因学的差异， 路上了事实上，随着大规模的遗传学研究继续揭开精神疾病的遗传结构， 疾病，已经很清楚，每种疾病的遗传风险是复杂的和高度多基因的;涉及 跨越等位基因频率范围的变异;并且个体遗传变异经常会带来以下风险 多种疾病利用遗传风险特征来确定风险人群，并绘制 因此，在整个发育过程中，临床表型的进展可能提供一种生物学上更有效的方法， 用于定义精神疾病的疾病分类学，识别具有最大预测有效性的生物标志物 和针对不同临床结果的特异性，并优化早期干预。为此，目前 该项目将调查遗传风险特征与精神病理学早期标志物之间的关系， “派萨”是一个基因和文化上同质的人口，主要居住在安第斯山脉， 哥伦比亚.具体来说，我们会在现有基础设施的基础上，在区内进行大规模的SMI研究 建立一个新的3,000名儿童和青少年高风险（n = 2,700）或低风险（n = 300）队列 对于SMI。我们将获得DNA样本和全面的临床和神经行为表型， 生成基于常见变异的多基因风险评分（PRS）的主要精神疾病，以及罕见的 变体评分总结了罕见破坏性变体和拷贝数缺失的负担。我们将描述 儿童期临床症状与神经行为特征的关系（目的1）。我们将绘制 常见的基于变异的SMI遗传风险、罕见的破坏性变异负担和 儿童期精神病诊断（目标2），以及认知，运动，感觉和心理标志物， 功能（目标3）。最后，利用现有的最先进的精神病电子病历（EMR） 数据库获得纵向结果，我们将探讨遗传和临床和神经行为 与2年内不良临床结局相关的特征。研究结果将阐明跨诊断 vs.儿童期特定神经行为障碍特征，识别临床综合征和神经行为障碍。 与SMI遗传易感性相关的儿童期特征，并量化遗传与 临床和神经行为特征预测近端精神病结局。

PROJECT SUMMARY/ABSTRACT Clinical staging is gaining traction as a potentially powerful framework for understanding the pathogenesis and emergence of serious mental illnesses (SMI), such as schizophrenia (SCZ), bipolar disorder (BP), and severe depression (severe-DEP), across development, and for guiding early interventions that aim to alter disease trajectory. However, realizing the full potential of this approach requires overcoming a number of challenges. These challenges include the imprecise boundaries between psychiatric disorders; unclear validity and specificity of early clinical and neurobehavioral markers for predicting later illness onset; and growing recognition that current psychiatric nosology may not map onto differences in underlying etiology in an optimal way. Indeed, as large-scale genetic studies continue to unravel the genetic architecture of psychiatric disorders, it has become clear that genetic risk for each disorder is complex and highly polygenic; involves variants that span the allelic frequency range; and that individual genetic variants frequently confer risk for multiple disorders. Leveraging genetic risk profiles to define groups of at-risk individuals and map the progression of clinical phenotypes across development may therefore offer a more biologically valid approach for defining the nosology of psychiatric disorders, identifying biomarkers with the greatest predictive validity and specificity for different clinical outcomes, and optimizing early intervention. Towards this end, the current project will investigate the relationships between genetic risk profiles and early markers of psychopathology in the “Paisa,” a genetically and culturally homogenous population that predominates in the Andean Mountains of Colombia. Specifically, we will build upon our existing infrastructure for large-scale studies of SMI in the region to establish a new cohort of 3,000 children and early adolescents at elevated (n = 2,700) or low risk (n = 300) for SMI. We will obtain DNA samples and comprehensive clinical and neurobehavioral phenotyping and will generate common-variant based polygenic risk scores (PRS) for major psychiatric disorders, as well as rare variant scores summarizing burden of rare damaging variants and copy number deletions. We will characterize relationships between clinical syndromes and neurobehavioral traits in childhood (Aim 1). We will then map relationships between common variant-based genetic risk for SMI, rare damaging variant burden, and psychiatric diagnoses in childhood (Aim 2), as well as cognitive, motor, sensory, and psychological markers of functioning (Aim 3). Finally, using existing state-of-the-art psychiatric electronic medical record (EMR) databases to obtain longitudinal outcomes, we will explore genetic and clinical and neurobehavioral characteristics associated with poor clinical outcome within 2 years. Study findings will clarify trans-diagnostic vs. disorder-specific neurobehavioral profiles in childhood, identify clinical syndromes and neurobehavioral traits in childhood associated with genetic liability for SMI, and quantify the relative power of genetic versus clinical and neurobehavioral characteristics for predicting proximal psychiatric outcomes.