Fine-mapping psychiatricdisease variants that affect post-transcriptional gene regulation

精细绘制影响转录后基因调控的精神疾病变异

基本信息

批准号：
10445082
负责人：
William G Fairbrother
金额：
$ 72.94万
依托单位：
NEW YORK GENOME CENTER
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-05 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10445082
关键词：
Affect Alleles Alternative Splicing Alzheimer&apos s Disease American Autopsy Biological Assay Bipolar Disorder Brain Candidate Disease Gene Cell physiology Clustered Regularly Interspaced Short Palindromic Repeats Complex Development Diagnostic Disease Electrophysiology (science)Engineering Etiology Evaluation Exhibits Exons FURIN gene Functional disorder Gene Expression Genes Genetic Genetic Diseases Genetic Engineering Genomics Genotype Glutamates Goals Heritability Human Impairment In Vitro Individual Induced pluripotent stem cell derived neurons Introns Libraries Machine Learning Maps Mediating Mental disorders Modeling Modification Molecular Mutation Neurons Pathogenesis Pathogenicity Pathway interactions Patients Phenotype Post-Transcriptional Regulation Protein Isoforms Proteins Quantitative Trait Loci RNA RNA Processing RNA Splicing Reporter Research Risk Risk Factors Role Schizophrenia Single Nucleotide Polymorphism Spliced Genes Structure Susceptibility Gene Synapses Testing Transcriptional Regulation Untranslated RNA Untranslated Regions Variant Work autism spectrum disorder base causal variant cell type clinical predictors cohort disorder risk falls follow-up genetic variant genome wide association study genome-wide improved in silico induced pluripotent stem cell insight machine learning method mutant neuropsychiatric disorder neuropsychiatry novel novel therapeutic intervention outcome prediction overexpression personalized approach predictive modeling risk variant standard care stem cell biology stem cell model synaptic function therapeutic target tool transcriptomics

项目摘要

PROJECT SUMMARY Neuropsychiatric disorders (NPD) such as schizophrenia (SZ), autism spectrum disorders (ASD) and bipolar disorders (BD) are remarkably common, with SZ alone affecting nearly three million Americans. Despite more than fifty years of research, no cures exist for these conditions and the standard of treatment remains unsatisfactory. Genome-wide association studies (GWAS) indicate that, in addition to highly penetrant rare mutations, NPD risk also reflects the impact of hundreds of common single nucleotide polymorphisms with small effect sizes. A major challenge in the field has been illuminating the pathways connecting these genetic variants (the vast majority of which fall in non-coding sequences) to target genes and causal cellular phenotypes. To understand how these myriad risk loci causally contribute to disease risk, it is essential to screen for putatively causal variant(s) and determine how they influence gene expression, which has been shown to be cell-type specific, as well as cellular function. Recent evidence has emerged indicating a substantial contribution of RNA splicing variation to heritability across many complex genetic diseases, including SZ. Based on our preliminary analyses and the work of others, we hypothesize that a substantial proportion of NPD GWAS loci exert their pathogenic effects on neuronal function by impacting RNA: its structure, modifications, protein interactions and splicing. To test this, we will apply novel tools and machine learning methods to predict and quantify RNA splicing in the largest SZ, ASD and BD GWAS, in order to predict splicing quantitative trait loci (sQTLs, Aim 1). To confirm true effects on exon inclusion independently in glutamatergic and GABAergic neurons (i.e., the major cell-types impacted in NPD), up to several thousand of the predicted splice variants will be tested by a massively parallel reporter assay, MaPSy (Aim 2). Finally, in order to evaluate the cell-type-specific impact of putative causal sQTLs identified in Aims 1 and 2 on neuronal maturation and synaptic function, we will use CRISPR gene editing to engineer these mutations within human induced pluripotent stem cell (hiPSC)-based models of both neural cell types (Aim 3). Our overarching goal is to map and functionally evaluate the NPD-GWAS loci that impact alternative splicing and neuronal function. Our work may impact the field by delivering new insights into the role of common variants in NPD pathophysiology, which could inform ways of improving diagnostics, predicting clinical trajectories, and developing novel therapeutic interventions.

项目概要神经精神疾病 (NPD)，例如精神分裂症 (SZ)、自闭症谱系障碍 (ASD) 和双向情感障碍精神障碍 (BD) 非常常见，仅精神分裂症就影响了近 300 万美国人。尽管更多经过五十多年的研究，这些病症还没有治愈方法，治疗标准仍然存在不满意。全基因组关联研究（GWAS）表明，除了高度渗透性的罕见 NPD 风险还反映了数百种常见单核苷酸多态性的影响，这些多态性具有较小的突变效应大小。该领域的一个主要挑战是阐明连接这些遗传变异的途径（其中绝大多数属于非编码序列）针对目标基因和因果细胞表型。到为了了解这些无数的风险位点如何导致疾病风险，有必要筛查推定的因果变异并确定它们如何影响基因表达，这已被证明是细胞类型的具体的以及细胞功能。最近出现的证据表明 RNA 的重大贡献许多复杂遗传疾病（包括 SZ）的剪接变异与遗传力相关。根据我们的初步分析和其他人的工作，我们假设很大一部分 NPD GWAS 位点发挥其作用通过影响 RNA 对神经元功能产生致病作用：其结构、修饰、蛋白质相互作用和拼接。为了测试这一点，我们将应用新的工具和机器学习方法来预测和量化 RNA 剪接在最大的 SZ、ASD 和 BD GWAS 中，以预测剪接数量性状位点（sQTL，目标 1）。确认对谷氨酸能和 GABA 能神经元（即主要细胞类型）中外显子包含的真实影响独立受到 NPD 的影响），多达数千个预测的剪接变体将通过大规模并行测试进行测试报告基因检测，MaPSy（目标 2）。最后，为了评估假定因果 sQTL 的细胞类型特异性影响目标 1 和 2 中确定了神经元成熟和突触功能，我们将使用 CRISPR 基因编辑来在基于人类诱导多能干细胞 (hiPSC) 的神经细胞模型中设计这些突变类型（目标 3）。我们的首要目标是绘制和功能评估影响的 NPD-GWAS 位点选择性剪接和神经元功能。我们的工作可能会通过提供对该角色的新见解来影响该领域 NPD 病理生理学中的常见变异，可以为改进诊断、预测的方法提供信息临床轨迹，并开发新的治疗干预措施。