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

利用罕见的遗传病因来推进神经精神疾病的知识和治疗

• 批准号: 10597665
• 负责人: David H. Ledbetter
• 金额: $ 182.67万
• 依托单位: GEISINGER CLINIC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-10 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10597665
• 关键词: 1q21; Acceleration; Adult; Age; Behavior assessment; Behavioral; Biological; Biological Models; Bipolar Disorder; Brain; Cardiovascular Diseases; Child; Clinical; Cognitive; Collaborations; Community Health; Consensus; Data; Data Analyses; Data Set; Development; DiGeorge Syndrome; Diagnostic; Dimensions; Disease; Electronic Health Record; Electronics; Eligibility Determination; Etiology; Family; Family member; Future; Genes; Genetic; Genetic Counseling; Genetic Diseases; Genetic Predisposition to Disease; Genetic study; Genome; Genomics; Genotype; Health system; Healthcare; Healthcare Systems; Individual; Infrastructure; Investigation; Knowledge; Lead; Learning; Malignant Neoplasms; Microarray Analysis; Modeling; Mood Disorders; Neurobiology; Nucleotides; Other Genetics; Outcome; Parents; Participant; Pathogenicity; Pathway interactions; Patients; Persons; Phenotype; Population; Predisposition; Prognosis; Psychoses; Rare Diseases; Recontacts; Research; Resources; Risk; Risk Factors; Role; Schizophrenia; Scientific Advances and Accomplishments; Secure; Severities; Siblings; Site; Standardization; Statistical Data Interpretation; Symptoms; Technology; United States; Universities; Variant; Washington; algorithm development; autism spectrum disorder; behavioral health; cancer therapy; clinical care; clinical diagnosis; clinical heterogeneity; cohort; cost; cost effective; data sharing; design; disorder risk; exome sequencing; family genetics; gene discovery; genetic resource; genetic selection; genetic testing; genetic variant; genome-wide; loss of function; neuropsychiatric disorder; neuropsychiatric symptom; neuropsychiatry; phenotypic data; polygenic risk score; precision medicine; proband; protective factors; rare genetic disorder; rare variant; recruit; resilience; sharing platform; trait; young adult

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.

项目摘要 精神分裂症，躁郁症和自闭症等神经精神疾病（NPD）是行为定义的 和病因的疾病，具有广泛的严重性和结果。用于癌症和其他 常见疾病，对罕见遗传疾病的研究具有关键的病理生理机制， 导致重大治疗进展。我们假设该策略可以成功应用于 NPD。新的基因组技术导致由于拷贝数发现了数百种稀有遗传NPD （CNV）和单基因核苷酸变体（SNV）的大小。但是，详细的神经精神病学 在大多数情况下，尚未建立配置文件，部分原因是难以招募足够的队列 大小到功率统计分析。我们将利用Geisinger的大量NPD临床人群 华盛顿大学和圣路易斯华盛顿大学，招募患有罕见遗传疾病的人 对于这项研究。我们还将研究整个基因组中其他贡献者对变量的影响 这些疾病中神经精神症状的表达。这项研究将系统地检查这些 稀有遗传NPD的各个方面通过以下目的：1）采用高成本效益的遗传学优先 与遗传NPD病因的大型队列实现基线表征的策略。每年， 作为精神病，发展和行为医疗保健的一部分，有价值的基因型和表型数据是 由稀有遗传NPD的个体产生。我们将协调临床中使用的核心评估电池 谨慎利用这些高质量数据进行大量数据共享和分析> 1,000个概率，加速 发现并大大降低了多维表型的研究成本。 2）描述详细信息 选定稀有遗传NPD中的表型特征，包括家庭背景对 可变表达性。我们将表征针对选定稀有遗传NPD的定量神经精神特征 （最初是1q21.1和15q13.3 CNV和CHD8 SNV）。这三种疾病均显示出全基因组的意义 为了增加神经精神型表型的风险，包括精神病，情绪障碍和自闭症。我们将 在250个概率中评估行为，精神病和认知性状，并具有这些稀有遗传NPD及其第一 学位家庭成员探索家庭背景对神经精神病的可变表达性的影响 症状。 3）评估常见和次要稀有基因组变体对变量的贡献 稀有遗传NPD的表现性。通过两个子aims，我们将探索常见的影响（多基因风险 分数）和罕见的（“第二击”）基因组贡献者对神经精神症状的风险或韧性。 除了对基因组和电子的更广泛的探索外，分析通过目标1和2收集的数据 健康记录来自盖辛格（Geisinger）的Mycode队列中25万个人的数据，我们将演示 基因组背景因素导致稀有遗传NPD患者的临床异质性。这些 研究最终可能会为神经精神上的结果提供个人水平预后。

项目成果

Attributing social meaning to animated shapes: A new experimental study of apparent behavior.

• DOI: 10.5406/amerjpsyc.133.3.0295
• 发表时间: 2020
• 期刊: The American journal of psychology
• 作者: Ratajska A;Brown MI;Chabris CF
• 通讯作者: Chabris CF

Phenotypic shift in copy number variants: Evidence in 16p11.2 duplication syndrome.

• DOI: 10.1016/j.gim.2022.09.011
• 发表时间: 2023-01
• 期刊: GENETICS IN MEDICINE
• 影响因子: 8.8
• 作者: Taylor, Cora M.;Finucane, Brenda M.;Moreno-De-Luca, Andres;Walsh, Lauren K.;Martin, Christa Lese;Ledbetter, David H.
• 通讯作者: Ledbetter, David H.

The Social Shapes Test as a Self-Administered, Online Measure of Social Intelligence: Two Studies with Typically Developing Adults and Adults with Autism Spectrum Disorder.

• DOI: 10.1007/s10803-023-05901-2
• 发表时间: 2024-05
• 期刊: JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS
• 影响因子: 3.9
• 作者: Brown, Matt I. I.;Heck, Patrick R. R.;Chabris, Christopher F. F.
• 通讯作者: Chabris, Christopher F. F.

Using game-like animations of geometric shapes to simulate social interactions: An evaluation of group score differences.

• DOI: 10.1111/ijsa.12375
• 发表时间: 2022-03
• 期刊: INTERNATIONAL JOURNAL OF SELECTION AND ASSESSMENT
• 影响因子: 2.2
• 作者: Brown, Matt, I;Speer, Andrew B.;Tenbrink, Andrew P.;Chabris, Christopher F.
• 通讯作者: Chabris, Christopher F.

Rare variants and the oligogenic architecture of autism.

• DOI: 10.1016/j.tig.2022.03.009
• 发表时间: 2022-09
• 期刊: TRENDS IN GENETICS
• 影响因子: 11.4
• 作者: Wang, Tianyun;Zhao, Peiyao A.;Eichler, Evan E.
• 通讯作者: Eichler, Evan E.