From Genotypes to Phenotypes in Schizophrenia: A Developmental Functional Genomics Approach

从精神分裂症的基因型到表型：发育功能基因组学方法

基本信息

批准号：
10490530
负责人：
Jennifer Katherine Forsyth
金额：
$ 18.33万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-12 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10490530
关键词：
Bioinformatics Biological Biological Process Brain Characteristics Clinical Cognitive Data Development Disease Etiology Genes Genetic Heterogeneity Genetic Risk Genomic approach Genomics Genotype Human Individual Infrastructure Intervention Knowledge Link Magnetic Resonance Imaging Maps Mentors National Institute of Mental Health Neurodevelopmental Disorder Pathogenesis Pathway Analysis Pathway interactions Patients Phenotype Population Process Psychoses Research Research Personnel Research Training Schizophrenia Scientist Structure Subgroup Testing Time Training Variant Work base burden of illness clinical heterogeneity cognitive function cohort exome sequencing functional genomics genetic architecture genetic variant genome wide association study insight neuroimaging rare variant schizophrenia risk transcriptomics whole genome

项目摘要

PROJECT SUMMARY Efforts to understand the core biological processes underlying schizophrenia (SCZ) have been hampered by the clinical and genetic heterogeneity of the disorder. However, large-scale genomic studies have begun to yield major insights into the genetic architecture of SCZ. Applying a developmental functional genomics approach to characterize findings from large-scale genomic studies of SCZ and related disorders, and examine relationships between genotypes and phenotypes in well-characterized cohorts may therefore help determine which neurotypical processes are most impacted by genetic risk for SCZ, and facilitate the discovery of links between specific genotypes and phenotypes in SCZ. In line with NIMH Strategic Objective 1, the PI therefore aims to: 1) integrate large-scale genomic findings for schizophrenia and related neurodevelopmental disorders with gene co-expression networks derived from the developing human brain to understand the impact of polygenic risk for schizophrenia on brain development at the clinical population level; and 2) using a unique cohort of 650 predominantly recent-onset SCZ patients with rich clinical, cognitive, and structural magnetic resonance imaging phenotyping, determine whether specific genetic risk profiles predict distinct phenotypes among SCZ patients. In particular, the PI will evaluate the extent to which common and rare variants associated with SCZ and related neurodevelopmental disorders converge on developmentally regulated biological pathways (Aim 1), derived from applying weighted gene co-expression network analyses (WGCNA) to BrainSpan transcriptomic data. Then, using common and rare variant data derived from genome-wide association study (GWAS) chips and whole exome sequencing in a cohort of 650 SCZ patients, the PI will test whether common variants, rare variants, and/or their combination in biologically-partitioned genetic risk profiles (partitioned based on BrainSpan modules developed in Aim 1) predict current and premorbid clinical and cognitive phenotypes (Aim 2); and/or specific neuroanatomic characteristics (Aim 3). Through structured coursework, mentoring from a team of distinguished scientists (Drs. Bearden, Ophoff, Nuechterlein, and Eichler), and UCLA and UW’s outstanding infrastructure for genomics, neuroimaging, and psychosis research, the proposed research and training plan will allow the PI to extend her training to work with whole-genome genotyping and exome sequencing data; deepen her knowledge of bioinformatics, neurodevelopmental disorders, and neuroimaging; and ultimately, transition to an independent investigator able to integrate genomic, clinical, and neuroimaging data to help map the pathogenesis of SCZ through development. Successful completion of this project will provide mechanistic insights into the neurotypical processes impacted by genetic risk for SCZ and has the potential to inform biologically valid subtypes of SCZ with distinct developmental trajectories, in line with NIMH Strategic Objective 2.

项目概要了解精神分裂症 (SCZ) 核心生物过程的努力受到以下因素的阻碍：然而，大规模的基因组研究已经开始研究该疾病的临床和遗传异质性。应用发育功能基因组学对 SCZ 的遗传结构产生重要见解。方法来表征 SCZ 和相关疾病的大规模基因组研究的结果，并检查因此，在特征明确的队列中基因型和表型之间的关系可能有助于确定哪些神经典型过程受 SCZ 遗传风险影响最大，并有助于发现联系 SCZ 中特定基因型和表型之间的差异根据 NIMH 战略目标 1，PI 因此。旨在：1）整合精神分裂症和相关神经发育障碍的大规模基因组发现利用来自发育中的人类大脑的基因共表达衍生网络来了解精神分裂症对临床人群大脑发育的多基因风险；2) 使用独特的方法；由 650 名主要是近期发病的 SCZ 患者组成的队列，具有丰富的临床、认知和结构磁力共振成像表型，确定特定的遗传风险状况是否可以预测不同的表型特别是在 SCZ 患者中，PI 将评估常见和罕见变异的程度。与 SCZ 和相关神经发育障碍相关的集中于发育调节生物途径（目标 1），源自应用加权基因共表达网络分析 (WGCNA) 然后，使用来自全基因组的常见和罕见变异数据。 PI 将在 650 名 SCZ 患者队列中进行关联研究 (GWAS) 芯片和全外显子组测序测试生物分区遗传风险概况中是否存在常见变异、罕见变异和/或它们的组合（根据目标 1 中开发的 BrainSpan 模块进行分区）预测当前和发病前的临床和认知表型（目标 2）；和/或特定的神经解剖学特征（目标 3）。课程作业，由杰出科学家团队（Bearden、Ophoff、Nuechterlein 博士和 Eichler），以及加州大学洛杉矶分校和华盛顿大学在基因组学、神经影像学和精神病研究方面的出色基础设施，拟议的研究和培训计划将使 PI 能够将其培训扩展到全基因组工作基因分型和外显子组测序数据；加深她对生物信息学、神经发育学的了解疾病和神经影像学；并最终转变为能够整合的独立研究者基因组、临床和神经影像数据有助于绘制 SCZ 整个发育过程的发病机制。该项目的成功完成将为受影响的神经典型过程提供机械见解 SCZ 的遗传风险，并有可能告知具有不同特征的 SCZ 的生物学有效亚型发展轨迹，符合 NIMH 战略目标 2。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Developmental trajectories of premorbid functioning predict cognitive remediation treatment response in first-episode schizophrenia.

病前功能的发展轨迹预测首发精神分裂症的认知矫正治疗反应。

DOI：
发表时间：
2023-10
期刊：
影响因子：
6.9
作者：
Kuo, Susan S;Ventura, Joseph;Forsyth, Jennifer K;Subotnik, Kenneth L;Turner, Luana R;Nuechterlein, Keith H
通讯作者：
Nuechterlein, Keith H

Genetics of Childhood-onset Schizophrenia 2019 Update.

2019 年儿童期发病精神分裂症的遗传学更新。