Protein network of high risk copy number variants for psychiatric disorders

精神疾病高风险拷贝数变异的蛋白质网络

基本信息

批准号：
8771945
负责人：
LILIA M IAKOUCHEVA
金额：
$ 22.71万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-07-01 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8771945
关键词：
16p11.2 Address Autistic Disorder Biological Biological Assay Bipolar Disorder Blood Brain Cells Collaborations Collection Databases Detection Disease Drug Targeting Etiology Fluorescence Functional disorder Gene Dosage Generations Genes Genetic Genomics Goals Human Individual Intellectual functioning disability Investigation Knowledge Lead Libraries Literature Manuals Mental disorders Methods Molecular Neurodevelopmental Disorder Open Reading Frames Pathology Pathway interactions Patients Phenotype Play Protein Fragment Proteins Publications Publishing RNA Reporting Reverse Transcriptase Polymerase Chain Reaction Risk Role Schizophrenia Societies System Testing Validation Variant Yeasts autism spectrum disorder base clinical phenotype follow-up genetic variant genome-wide high risk insight interest medical schools neuropsychiatry protein protein interaction public health relevance reconstitution relating to nervous system text searching transcriptomics yeast two hybrid system

项目摘要

DESCRIPTION (provided by applicant): Neuropsychiatric disorders such as autism, schizophrenia, bipolar disorder and intellectual disability are major burden to society. Our current knowledge of their underlying pathophysiology remains limited. However, a contribution of genetic factors has been clearly demonstrated. The goal of this study is to discover shared biological mechanisms between autism, schizophrenia and related disorders through investigation of the networks of interactions between proteins encoded by the high risk genetic factors implicated in these disorders. It is now firmly established that rare Copy Number Variants (CNVs): (1) play significant role in the risk of psychiatric disorders; (2) many high-risk CNVs cross disorder boundaries and are implicated in several psychiatric disorders. CNVs generally involve multiple genes, and how this large number of functionally heterogeneous genes contributes to the pathology is not completely understood. To advance our understanding of CNV contribution to psychiatric diseases, we propose to investigate how the genes from high risk rare CNVs interact on a protein level. The knowledge of the networks connecting CNV genes will help to better understand their pathological impact in different disorders. Using the constructed networks, we will test the hypotheses that: (1) cross-disorder CNVs share interacting protein partners that may explain shared etiology of different disorders; (2) cross-disorder CNVs have a unique set of interacting partners that may explain the differences between disorders. We have selected 11 high risk CNVs (containing 169 genes) that are firmly implicated in two or more psychiatric disorders for this study. Literature search fr binary protein-protein interactions (PPIs) for these 169 genes demonstrated that 33% of them have no PPIs annotated in the public databases, and only 3.5% of them interact with each other. However, it has been repeatedly demonstrated that literature PPIs are biased toward highly studied proteins, incomplete, and often are not as reliable as commonly assumed. Here, we are proposing to perform an unbiased protein interaction screen for 169 genes from high risk cross-disorder CNVs. Our Specific Aims are as follows: (1) Assemble a library of 169 open reading frame (ORF) clones corresponding to genes from 11 CNVs that confer high risk to psychiatric disorders; (2) Build and validate the cross-disorder CNV interactome; (3) Identify and perform follow-up functional studies of the interacting partners that are shared by or are unique to cross-disorder CNVs.

描述（由申请人提供）：神经精神疾病，如自闭症、精神分裂症、双相情感障碍和智力障碍是社会的主要负担。我们目前对其潜在病理生理学的了解仍然有限。然而，遗传因素的贡献已得到明确证明。本研究的目的是通过研究与这些疾病有关的高风险遗传因素编码的蛋白质之间的相互作用网络，发现自闭症、精神分裂症和相关疾病之间共有的生物学机制。现在已确定罕见的拷贝数变异 (CNV)：(1) 在精神疾病风险中发挥重要作用； (2)高风险较多 CNV 跨越疾病界限并与多种精神疾病有关。 CNV 通常涉及多个基因，而如此大量的功能异质基因如何影响病理学尚不完全清楚。为了加深我们对 CNV 对精神疾病的贡献的理解，我们建议研究来自高风险罕见 CNV 的基因如何在蛋白质水平上相互作用。了解连接 CNV 基因的网络将有助于更好地了解它们对不同疾病的病理影响。使用构建的网络，我们将测试以下假设：（1）跨疾病 CNV 共享相互作用的蛋白质伙伴，这可能解释不同疾病的共同病因； (2) 跨疾病 CNV 具有一组独特的相互作用伙伴，可以解释疾病之间的差异。我们为这项研究选择了 11 个与两种或多种精神疾病密切相关的高风险 CNV（包含 169 个基因）。对这 169 个基因的二元蛋白质-蛋白质相互作用 (PPI) 进行文献检索表明，其中 33% 在公共数据库中没有注释 PPI，并且只有 3.5% 的基因相互相互作用。然而，已经反复证明，文献中的 PPI 偏向于经过深入研究的蛋白质、不完整，并且往往不如通常假设的那么可靠。在这里，我们建议对来自高风险跨疾病 CNV 的 169 个基因进行无偏见的蛋白质相互作用筛选。我们的具体目标如下： (1) 构建一个由 169 个开放阅读框 (ORF) 克隆组成的文库，这些克隆对应于来自 11 个 CNV 的基因，这些 CNV 赋予精神疾病高风险； (2) 构建并验证跨疾病CNV相互作用组； (3) 识别跨疾病 CNV 共有或独特的相互作用伙伴，并对其进行后续功能研究。