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

项目摘要 尽管全基因组关联研究（GWAS）在识别许多 与精神分裂症和双相情感障碍风险相关的种系变异，在这些基因座的绝大多数， 遗传变异和疾病风险之间的因果机制仍然未知。这限制了 开发新的药物靶点和/或个性化治疗。精神分裂症和双相情感障碍 许多遗传风险位点，从而激励方法来深入了解这两个共享的分子基础， 疾病后GWAS研究正在经历一场“大数据”革命， 高通量基因组分析的成本，包括转录组水平，表观遗传修饰， 组织特异性调控位点的定位，这些位点正在越来越大的队列中收集， 个体在这里，我们提出了一个严格的框架，旨在基因座的共享或疾病特异性风险， 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， 表观遗传控制为了提高发现的能力，同时也促进新发现的验证，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。

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.