Integrating case-control transcriptomic and genetic data in admixed individuals to identify disease genes for schizophrenia and bipolar disorder

项目总结 全基因组关联研究已经确定了数百个增加疾病的基因组基因座 精神分裂症(SCZ)和躁郁症(BP)的易感性。我们和其他人已经证明了 功能分子数据，包括转录本丰度水平，可以用来破译 Gwas鉴定了等位基因变异对疾病易感性的影响。遗传危险因素的识别和 因果解释为个性化基因组医学的未来提供了最大的潜力。这些 然而，研究和进展大多是在欧洲血统的个人身上进行的，因此 加剧了具有不同和混合基因祖先的最脆弱人群的健康差距。对此 时间，NIMH正在领导通过资助大型- SCZ和BP的Gwas项目规模较大，但有必要同时增加黄瓜的遗传多样性 用于数据集成和破译SCZ和BP涉及的因果生物效应的功能分子数据。 我们将解决在解释遗传易感性的综合转录研究中缺乏多样性的问题。 通过刻意整合新的统计方法，在拉丁裔混合人群中发现SCZ和BP 开发新的转录切分数据生成。我们将生成1500个拉丁语的转录组数据 个人(500个SCZ病例，500个BP病例，500个对照)作为公共资源，以产生关于以下方面的新见解 SCZ和BP发病风险的分子机制。同时，我们将开发新的统计方法 利用混合过程来提高绘制基因效应对基因表达影响的能力的方法 拉丁裔个体。我们将把本地和全球的遗传祖先整合到混合的个体中，以 提高转录组广泛关联和表达数量性状评分(EQTS)研究的能力 鉴定新的易感基因。我们将把拉丁裔个人的新转录数据与正在进行的 SCZ和BP的拉丁裔GWA涉及数万名拉丁裔个人，两者都产生了新的生物 并验证我们新的统计方法。最有希望的因果变异和易感性 基因将接受功能验证。我们的努力将导致一个大型的公共基因表达资源，新奇 统计工具，以及在功能分析中得到验证的新的生物学发现。我们的发现可能会在临床上产生 SCZ和BP的诊断和治疗的相关应用，特别是在已被 在大规模基因组研究中，传统上没有得到足够的服务。

PROJECT SUMMARY Genome-wide association studies (GWAS) have identified hundreds of genomic loci that increase disease susceptibility for schizophrenia (SCZ) and bipolar disorder (BP). We and others have shown that integration of functional molecular data, including transcript abundance levels, can be used to decipher causal insights from GWAS-identified allelic variant to gene to disease susceptibility. The identification of genetic risk factors and causal interpretations provide the greatest potential for the future of personalized genomic medicine. These studies and advances, however, have mostly been performed in individuals of European ancestry, thereby exacerbating health disparities of most vulnerable populations of diverse and admixed genetic ancestries. At this time, NIMH is leading the effort for genetic discoveries in underrepresented populations through funding of large- scale GWAS projects of SCZ and BP, but it is necessary to simultaneously increase the genetic diversity of functional molecular data for data integration and deciphering causal biological effects involved in SCZ and BP. We will tackle the lack of diversity in integrative transcriptomic studies for the deciphering of genetic susceptibility of SCZ and BP in Latino admixed populations, through deliberate integration of novel statistical method development with new transcriptomic data generation. We will generate transcriptome data in 1,500 Latino individuals (500 SCZ cases, 500 BP cases, 500 controls) as a public resource to generate new insights about the molecular mechanisms that contribute to risk of SCZ and BP. At the same time, we will develop new statistical methods that leverage the admixture process to improve the power of mapping genetic effects on expression in Latino individuals. We will incorporate the local and global genetic ancestries within admixed individuals to increase power of transcriptome-wide association (TWAS) and expression quantitative trait score (eQTS) studies to identify novel susceptibility genes. We will integrate new transcriptomic data in Latino individuals with ongoing Latino GWAS of SCZ and BP involving tens of thousands of Latino individuals both to generate new biological hypotheses and to validate our new statistical methods. The most promising causal variants and susceptibility genes will undergo functional validation. Our efforts will result in a large public gene expression resource, novel statistical tools, and new biological findings validated in functional assays. Our findings may yield clinically relevant applications for diagnosis and treatment for SCZ and BP particularly in Latino individuals that have been traditionally underserved in large-scale genomic studies.