Genetic Risk for Serious Mental Illness and Development

项目摘要/摘要 临床分期作为一种潜在的强有力的框架，用于理解肿瘤的发病机制和预后。 出现严重精神疾病(SMI)，如精神分裂症(SCZ)、双相情感障碍(BP)和严重精神疾病 抑郁症(严重-DEP)，跨越发育阶段，并指导旨在改变疾病的早期干预 弹道。然而，实现这一方法的全部潜力需要克服一些挑战。 这些挑战包括精神障碍之间不精确的界限；不清楚的有效性和 早期临床和神经行为标记物预测较晚发病和生长的特异性 认识到目前的精神病学病因学可能不会以最佳的方式映射到潜在病因的差异 道路。事实上，随着大规模的基因研究继续揭开精神病患者的基因结构 在疾病方面，很明显，每种疾病的遗传风险都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；以及个别遗传变异经常会导致 多发性疾病。利用遗传风险简档来定义高危人群，并绘制 因此，临床表型在发育过程中的进展可能会提供一种更有效的生物学方法 用于定义精神疾病的病因学，识别具有最大预测有效性的生物标记物 和不同临床结果的特异性，并优化早期干预。为此，当前 该项目将调查遗传风险特征与精神病理学早期标记之间的关系 “Paisa”，一个基因和文化上均一的种群，在安第斯山脉占主导地位 哥伦比亚。具体地说，我们将在现有基础设施的基础上，在该地区进行大规模的SMI研究 建立3,000名高风险(n=2,700)或低风险(n=300)儿童和早期青少年的新队列 对SMI来说。我们将获得DNA样本和全面的临床和神经行为表型分析，并将 为主要精神疾病以及罕见的精神疾病生成基于共同变量的多基因风险评分(PR) 变异分数总结了罕见破坏性变异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(目标1)。然后我们将绘制地图 SMI常见的基于变异的遗传风险、罕见的破坏性变异负担与 儿童精神病学诊断(目标2)，以及认知、运动、感觉和心理标记物 运作(目标3)。最后，使用现有最先进的精神科电子病历(EMR) 为了获得纵向结果，我们将探索遗传、临床和神经行为 2年内临床结果不佳的特征。研究结果将澄清跨诊断 对照儿童时期特定障碍的神经行为特征，确定临床症状和神经行为 儿童时期的特征与SMI的遗传易感性相关，并量化遗传与 临床和神经行为特征对近期精神疾病预后的预测。

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.