Genetics of Severe Mental Illness

项目总结/摘要 这个拟议的项目旨在利用遗传学来帮助开发一种对严重精神疾病进行分类的方法 (SMI)这比目前在研究和临床中使用的系统具有更强的科学基础， 实践世纪以来，这些分类系统将大部分SMI分为二分的 诊断类别：精神障碍（包括精神分裂症[SCZ]）和情绪障碍（包括 双相情感障碍[BP]和重度抑郁症[MDD]）。然而， 情绪和精神障碍，以及越来越多的证据表明这些类别之间的遗传相关性， 表明它们不准确地代表SMI的生物学基础。已经提出 基于层次和维度（定量）信息的框架，如NIMH研究 域标准（RDoC）将更好地反映遗传对SMI的贡献，因此将提供 更有用的分类框架。然而，支持这一假设的证据仍然存在。 稀疏，在很大程度上是因为我们缺乏正确的数据集来测试它。 在这个项目中，我们将生成一个独特的SMI数据集，使用电子健康记录来确定个人 他们在一家精神病医院接受住院治疗， 哥伦比亚卡尔达斯州的居民。我们将调查的所有个人都是 “派萨”是一个基因和文化上同质的人口，占该地区的大多数， 哥伦比亚.通过招募8，000名参与者，包括各种严重情绪和精神障碍（如 以及2，000个人口统计学匹配的对照）;对这10，000个个体进行统一的表型分析 使用诊断和定量评估;和全基因组基因分型，我们将建立维度 这些表型指示SMI的核心缺陷并且涉及多个RDoC结构域。然后我们将进行 基因水平和数量表型的遗传分析，评估它们与已知SMI基因座的关系 和多基因风险评分（PRS），代表共同遗传变异对这些风险的总体贡献。 精神病基因组学联盟（PGC）的SCZ、BP和MDD工作组将为我们提供 每个诊断都有最新的基因数据此外，我们将进行全基因组关联 数量性状分析，包括其他研究中评估的性状的荟萃分析 人口。我们还将贡献我们的数据（包括基因型提供给我们额外的6,000派萨 对照）的病例对照荟萃分析的PGC工作组，有助于他们的多样性， 通过从以前代表性不足的（西班牙裔）人口中添加大量样本来创建数据集。 .

PROJECT SUMMARY/ABSTRACT This proposed project aims to use genetics to help develop an approach for classifying severe mental illness (SMI) that has a stronger scientific foundation than the systems currently used in both research and clinical practice. These classification systems have, for more than a century, divided the bulk of SMI into dichotomous diagnostic categories: psychotic disorders (including schizophrenia [SCZ]) and mood disorders (including bipolar disorder [BP] and major depressive disorder [MDD]). However the overlap of symptomatology across mood and psychotic disorders, and growing evidence for the genetic correlation between these categories, demonstrate that they imprecisely represent the biological underpinning of SMI. It has been proposed that frameworks based on symptom-level and dimensional (quantitative) information, such as the NIMH Research Domain Criteria (RDoC), would better reflect the genetic contribution to SMI and would therefore provide a more useful framework for their classification. However the evidence supporting this hypothesis remains sparse, in large part because we lack the right datasets to test it. In this project we will generate a unique SMI dataset, using electronic health records to ascertain individuals who have received inpatient treatment at a single psychiatric hospital that serves the entire 1 million inhabitants of the state of Caldas, Colombia. All of the individuals whom we will investigate are members of the “Paisa”, a genetically and culturally homogeneous population that comprises the majority in this region of Colombia. By recruiting 8,000 participants across the full range of severe mood and psychotic disorders (as well as 2,000 demographically-matched controls); performing uniform phenotyping of these 10,000 individuals using diagnostic and quantitative assessments; and genome wide genotyping, we will establish dimensional phenotypes that index core deficits of SMI and that reference multiple RDoC domains. We will then conduct genetic analyses of symptom-level and quantitative phenotypes, evaluating their relationship to known SMI loci and to polygenic risk scores (PRS) that represent the overall contribution of common genetic variation to these disorders; the SCZ, BP, and MDD workgroups of the Psychiatric Genomics Consortium (PGC) will provide us with up-to-date genetic data for each diagnosis. Additionally, we will conduct genome wide association analyses of the quantitative traits, including meta-analyses for traits that have been assessed in other study populations. We will also contribute our data (including genotypes available to us for an additional 6,000 Paisa controls) to the case-control meta-analyses of the PGC workgroups, contributing to the diversity of their datasets by adding a substantial number of samples from a previously underrepresented (Hispanic) population. .