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

项目总结 尽管全基因组关联研究(GWAS)已经非常成功地识别了 生殖系变异与精神分裂症和双相情感障碍的风险相关，在这些基因座中的绝大多数， 基因变异和疾病风险之间的因果机制尚不清楚。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是相同的 因此，许多遗传风险基因座促使人们深入了解这两个基因的共同分子基础 疾病。后Gwas时代的研究正在经历一场由指数级下降驱动的“大数据”革命 高通量基因组分析的成本，包括转录组水平、表观遗传修饰和 组织特异性调控位点的本地化，正在收集越来越大的 个人。在这里，我们提出了一个严格的框架，旨在针对共享风险或疾病特定风险的基因座 精神分裂症和双相情感障碍是通过基因表达水平的改变来调节的，通过 表观遗传控制。为了增加发现的能力，同时也促进对新发现的验证，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化数据。 我们建议检查精神分裂症和双相情感障碍的风险基因，以确定因果变异和基因的优先顺序。 并在功能检测中进行验证。

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.