Integrative Genomics in Asthmatics of African Descent

描述（由申请人提供）：哮喘是一种复杂的疾病，其牢固的遗传基础已被确立。哮喘患病率与长期暴露于某些环境因素（尤其是与室内灰尘相关的环境因素）引发的免疫反应密切相关。哮喘的表现取决于 T 细胞的活性，特别是 T 细胞的 CD4 Th2 子集。与欧洲血统的个体相比，非洲血统的哮喘患者往往患有更严重的哮喘和更严重的临床症状，但相对较少的研究关注这一代表性不足的少数群体。全基因组关联研究 (GWAS) 已成功识别与哮喘风险增加相关的基因，但 GWAS 发现的单核苷酸多态性 (SNP) 关联与了解这些位点如何控制疾病之间存在很大差距。由于大多数 GWAS 关联涉及基因间或内含子区域的 SNP，因此调节元件的多态性似乎可以解释哮喘遗传性缺失的很大一部分。为了检验这一假设，我们提出了一系列研究，将非洲血统人群最全面的 GWAS 数据库之一与下一代测序技术 (RNA-Seq) 和 eQTL 作图相结合，以阐明从生活在同质、特征明确的环境中的非洲加勒比特应性哮喘患者和非特应性非哮喘对照中分离的 CD4 T 细胞基因表达定量水平差异的遗传变异。来自巴巴多斯的这个种群已被广泛地进行表型分析并跟踪了 20 年以上。该应用程序的具体目标建立在国际研究人员小组的基础设施之上，该小组具有多元化但高度综合的专业领域，包括以下内容：（i）识别顺式和反式效应 通过执行 RNA 测序和 eQTL 分析，从 250 名特应性哮喘患者分离的 CD4 T 细胞的转录组中鉴定出变异； (ii) 通过比较特应性哮喘患者的转录组与 250 名非特应性、非哮喘对照者的转录组，鉴定特应性哮喘特异性 CD4 T 细胞的 eQTL 模式，并探索与哮喘中 CD4 T 细胞失调相关的调控网络； (iii) 将哮喘患者 (SA1) 与非哮喘患者 (SA2) 相比的新 eQTL 与预先存在的哮喘 GWAS 数据相整合。将通过使用 NanoString nCounter 技术测量 150 名独立特应性哮喘患者和 150 名非特应性非哮喘对照者的转录变化来验证最强的 eQTL。我们将把这项研究产生的结果与通过微阵列测定产生的哮喘患者和非哮喘患者的 CD4 T 细胞的公开 eQTL 数据进行比较，以评估泛化性并探索基因网络。通过挖掘公开可用的 GWAS 数据库，我们将确定 CD4 T 细胞中发现的新 eQTL 和转录本表达是否会导致哮喘易感性，并可能解释之前发现的 GWAS 关联。这些研究将大大增进我们对哮喘分子基础的理解。

DESCRIPTION (provided by applicant): Asthma is a complex disease for which a strong genetic basis has been firmly established. Asthma prevalence is closely related to an immune response initiated by chronic exposure to certain environmental factors, especially those associated with house dust. Manifestations of asthma depend on T cell activities, particularly the CD4+ Th2 subset of T cells. Asthmatics of African ancestry tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry, but relatively few studies have focused on this underrepresented minority group. Genome-wide association studies (GWAS) have been successful in identifying genes associated with increased risk of asthma, but there is a substantial gap between single nucleotide polymorphism (SNP) associations discovered by GWAS and understanding how these loci control disease. Because most GWAS associations involve SNPs in intergenic or intronic regions, it seems likely polymorphisms in regulatory elements may account for a large portion of the missing heritability of asthma. To test this hypothesis, we propose a series of studies to integrate one of the most comprehensive GWAS databases on an African ancestry population with next-generation sequencing technology (RNA-Seq) and eQTL mapping, to elucidate the genetic variation underpinning differences in quantitative levels of gene expression of CD4+ T cells isolated from African Caribbean atopic asthmatics and non-atopic, non-asthmatic controls living in a homogeneous, well-characterized environment. This population from Barbados has been extensively phenotyped and followed for >20 years. The specific aims of this application build upon the infrastructure of an international group of investigators with diverse but highly integrated areas of expertise, and include the following: (i) to identify cis- and trans-effects of variants identified in the transcriptome from isolated CD4+ T cells from 250 atopic asthmatics by performing RNA-Seq followed by eQTL analyses; (ii) to identify eQTL patterns from CD4+ T cells specific to atopic asthma by comparing the transcriptomes of atopic asthmatics to that of 250 non-atopic, non-asthmatic controls, and explore regulatory networks associated with dysregulation of CD4+ T cells in asthma; and (iii) to integrate novel eQTLs among asthmatics (SA1) compared to non-asthmatics (SA2) with pre-existing asthma GWAS data. The strongest eQTLs will be validated by measuring the change in transcription in 150 independent atopic asthmatics and 150 non-atopic, non- asthmatic controls using NanoString nCounter technology. We will compare results generated from this study to publicly available eQTL data on CD4+ T cells from asthmatics and non-asthmatics generated from microarray assays to assess generalization, and explore networks of genes. By mining publicly available GWAS databases we will determine whether the novel eQTLs and transcript expression identified in CD4+ T cells contribute to asthma susceptibility and perhaps explain previously identified GWAS associations. These studies should substantially advance our understanding of the molecular basis for asthma.