Leveraging rare genetic etiologies to advance knowledge and treatment of neuropsychiatric disorders

项目总结 神经精神障碍(NPD)，如精神分裂症、双相情感障碍和自闭症，都是由行为定义的 以及病原学异质性的疾病，具有广泛的严重性和结果。治疗癌症和其他疾病 常见疾病，对罕见遗传疾病的研究阐明了关键的病理生理机制， 从而带来了显著的治疗进步。我们假设这一策略可以成功地应用于 NPD。新的基因组技术导致了数百种罕见的基因NPD的发现，这是因为拷贝数 (CNV)和大效应大小的单基因核苷酸变异体(SNV)。然而，详细的神经精神病学 对于这些情况中的大多数，尚未建立概况，部分原因是难以招募足够的队列 用于支持统计分析的大小。我们将利用盖辛格的大量NPD临床人群， 华盛顿大学和圣路易斯华盛顿大学招收患有罕见遗传病的个人 为了这项研究。我们还将检查整个基因组中其他贡献者对变量的影响 神经精神症状在这些障碍中的表现。这项研究将系统地检查这些 稀有遗传NPD方面通过以下目标：1)采用高成本效益、遗传学优先 策略，以实现具有遗传性NPD病因的大型队列的基线特征。每年， 作为精神病学、发育和行为保健的一部分，有价值的基因型和表型数据包括 由患有罕见遗传性NPD的个体产生。我们将协调临床使用的核心评估电池 注意利用这些高质量数据对1,000名先证者进行广泛的数据共享和分析，从而加速 发现并大大降低了多维表型的研究成本。2)详细描述 所选稀有遗传性NPD的表型特征，包括家庭背景对 可变的表现力。我们将描述所选罕见遗传性NPD的数量神经精神病学特征 (最初为1q21.1和15q13.3 CNV和CHD8 SNV)。所有这三种疾病都显示出了全基因组的意义。 用于增加神经精神表型的风险，包括精神病、情绪障碍和自闭症。我们会 评估250名患有这些罕见遗传NPD的先证者的行为、精神和认知特征，以及他们的第一个 学位家庭成员探讨家庭背景对神经精神病学变量表达的影响 症状。3)评估常见和次要稀有基因组变异对变量的贡献 罕见遗传性NPD的表达能力。通过两个子目标，我们将探索共同(多基因风险)的影响 关于神经精神症状的风险或恢复力的基因组贡献者(得分)和罕见的(“二次命中”)。 分析通过目标1和目标2收集的数据，以及更广泛的基因组和电子探索 盖辛格MyCode队列中250,000人的健康记录数据，我们将演示如何不同 基因组背景因素导致罕见遗传性NPD患者的临床异质性。这些 研究可能最终为神经精神病学结果的个体水平的预后提供信息。

PROJECT SUMMARY Neuropsychiatric disorders (NPD), such as schizophrenia, bipolar disorder, and autism are behaviorally-defined and etiologically-heterogeneous conditions with a wide range of severity and outcomes. For cancer and other common diseases, the study of rare genetic disorders has illuminated key pathophysiological mechanisms, resulting in significant treatment advances. We hypothesize that this strategy can be successfully applied to NPD. New genomic technologies have led to the discovery of hundreds of rare genetic NPD due to copy number (CNVs) and single gene nucleotide variants (SNVs) of large effect size. However, detailed neuropsychiatric profiles have not been established for most of these conditions, due in part to difficulty recruiting adequate cohort sizes to power statistical analyses. We will capitalize on large NPD clinical populations at Geisinger, the University of Washington, and Washington University in St. Louis to recruit individuals with rare genetic disorders for this study. We will also examine the influence of additional contributors throughout the genome to the variable expressivity of neuropsychiatric symptoms in these disorders. This study will systematically examine these aspects of rare genetic NPD through the following aims: 1) Employ a highly cost-effective, genetics-first strategy to achieve baseline characterization of a large cohort with genetic NPD etiologies. Every year, as part of psychiatric, developmental, and behavioral healthcare, valuable genotype and phenotype data are generated from individuals with rare genetic NPD. We will harmonize core assessment batteries used in clinical care to leverage this high-quality data for broad data sharing and analyses on >1,000 probands, accelerating discovery and greatly reducing the research cost of multidimensional phenotyping. 2) Describe detailed phenotypic signatures in selected rare genetic NPD, including the impact of family background on variable expressivity. We will characterize quantitative neuropsychiatric traits for selected rare genetic NPD (initially 1q21.1 and 15q13.3 CNVs and CHD8 SNVs). All three disorders have shown genome-wide significance for increased risk of neuropsychiatric phenotypes, including psychosis, mood disorders, and autism. We will assess behavioral, psychiatric, and cognitive traits in 250 probands with these rare genetic NPD and their first- degree family members to explore the impact of family background on variable expressivity of neuropsychiatric symptoms. 3) Assess the contributions of common and secondary rare genomic variants to variable expressivity in rare genetic NPD. Through two sub-aims, we will explore the impact of common (polygenic risk scores) and rare (`second hits') genomic contributors on risk or resilience for neuropsychiatric symptoms. Analyzing data collected through Aims 1 and 2, in addition to a broader exploration of genomic and electronic health record data from 250,000 individuals in Geisinger's MyCode cohort, we will demonstrate how different genomic background contributors lead to clinical heterogeneity in individuals with rare genetic NPD. These studies may eventually inform individual-level prognoses for neuropsychiatric outcomes.