Joint genomic and statistical analyses of schizophrenia and bipolar to decipher genetic susceptibility

精神分裂症和躁郁症的联合基因组和统计分析以破译遗传易感性

基本信息

批准号：
10349574
负责人：
Roel A Ophoff
金额：
$ 74.88万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
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：
2018-04-01 至 2023-04-05
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10349574
关键词：
Big Data Biological Biological Assay Bipolar Disorder CRISPR/Cas technology Cells ChIP-seq Chromatin Clinical Complement Data Data Set Development Diagnosis Disease Disease susceptibility Epigenetic Process Etiology Gene Expression Genes Genetic Genetic Diseases Genetic Predisposition to Disease Genetic Risk Genetic Variation Genetic study Genome Genomics In Vitro Individual Joints Measurement Measures Mediating Methods Modification Molecular Neuroglia Neurons Open Reading Frames Outcome Pathway interactions Predisposition RNA Interference Regulatory Element Research Risk Scanning Schizophrenia Site Statistical Data Interpretation Statistical Methods Susceptibility Gene System Time Tissue-Specific Gene Expression Tissues Transcript Validation Variant case control causal variant cell type clinically relevant cohort cost disorder risk experience genetic architecture genome editing genome wide association study genome-wide genomic data genomic locus insight molecular phenotype neuropsychiatric disorder new therapeutic target novel personalized medicine prevent risk variant schizophrenia risk targeted treatment tool trait transcriptome transcriptome sequencing transcriptomics

项目摘要

PROJECT SUMMARY Although genome-wide association studies (GWAS) have been extremely successful in identifying numerous germline variants associated to risk for schizophrenia and bipolar disorder, at the vast majority of these loci, the causal mechanism between genetic variation and disease risk remains unknown. This limits the development of novel drug targets and/or personalized treatments. Schizophrenia and bipolar disorder share many genetic risk loci thus motivating approaches to gain insights into the shared molecular basis of these two diseases. Post-GWAS studies are experiencing a “big data” revolution driven by the exponentially decreasing costs of high-throughput genomic assays, including transcriptome levels, epigenetic modifications, and localization of tissue-specific regulatory sites, which are being collected in increasingly large cohorts of individuals. Here we propose a rigorous framework aimed at loci where shared or disease-specific risk for schizophrenia and bipolar disorder is mediated through alteration in gene expression levels, regulated via epigenetic control. To increase power for discovery while also facilitating validation of new findings, we will generate new disease-specific expression and chromatin variation data in subjects with known disease status. We propose to examine risk loci for schizophrenia and bipolar disorder to prioritize causal variants and genes and to validate them in functional assays.

项目概要尽管全基因组关联研究（GWAS）在识别大量在这些基因座的绝大多数中，与精神分裂症和双相情感障碍风险相关的种系变异，遗传变异与疾病风险之间的因果机制仍不清楚。精神分裂症和双相情感障碍共同开发新的药物靶点和/或个性化治疗。许多遗传风险位点因此激发了人们深入了解这两者的共同分子基础的方法后 GWAS 研究正在经历一场“大数据”革命，其驱动力是呈指数下降的疾病。高通量基因组检测的成本，包括转录组水平、表观遗传修饰和组织特异性调节位点的定位，这些位点正在越来越多的群体中收集在这里，我们提出了一个严格的框架，针对共同或特定疾病风险的位点。精神分裂症和双相情感障碍是通过基因表达水平的改变介导的，通过调节为了增加发现的力量，同时促进新发现的验证，我们将在已知疾病状态的受试者中生成新的疾病特异性表达和染色质变异数据。我们建议检查精神分裂症和双相情感障碍的风险位点，以优先考虑因果变异和基因并在功能测定中验证它们。