Identification of Regulatory Variants in Novel Candidate Genes for Diabetes

描述（由申请人提供）：2型糖尿病现在被认为是世纪人类健康的主要威胁之一。在这个项目中，我们建议使用整合基因组学的方法，以确定潜在的功能调节变异的新的候选基因的糖尿病风险，在一个大的家庭为基础的研究。这些客观选择的候选基因是通过对来自1,240名圣安东尼奥家庭心脏研究参与者的淋巴细胞样本进行大规模转录谱分析获得的。基于定量基因表达水平与空腹血糖水平（主要糖尿病风险因素）以及一个或多个糖尿病风险因素（包括空腹胰岛素和复合糖尿病风险指数）之间存在显著相关性，提名目标候选基因座。利用我们独特的基于家族的全基因组定量转录谱资源，我们将研究100个新的候选基因，这些基因表现出表达水平顺式调节的强有力证据，以及表达水平与糖尿病风险表型之间的显著相关性。我们以前的链接为基础的顺式作用序列变异的证据，可以利用作为一个概率因果锚，应该最大限度地提高我们的机会，发现近端启动子内的功能变异。对于这些客观选择的基因中的每一个，我们将：1）在182个创始者个体中对推定的启动子区域的大约两个DNA酶进行重测序以鉴定启动子变体; 2）对我们具有转录谱的1，240个SAFHS样品中的100个候选基因中的每一个中的所有检测到的启动子变异进行基因分型; 3）测试启动子序列变体是否与适当候选基因的基因表达水平相关; 4）测试启动子序列变体与糖尿病风险表型之间的关联;和5）确认在两个独立的样本群体中观察到的关联。仅在美国，糖尿病的估计经济负担就约为每年1000亿美元，这使得这种疾病具有重大的公共卫生重要性。该项目所获得的知识将有助于通过识别新的和潜在功能的候选基因来理解2型糖尿病的遗传学，并有助于开发新的预防措施和/或治疗方法。

DESCRIPTION (provided by applicant): Type 2 diabetes is now considered one of the main threats to human health in the 21st century. In this project, we propose to use an integrative genomics approach to identify potentially functional regulatory variants in novel candidate genes for diabetes risk, in a large family based study. These objectively chosen candidate genes were obtained using large-scale transcriptional profiling of lymphocyte samples from 1,240 San Antonio Family Heart Study participants. Target candidate loci were nominated based on the existence of significant correlations of quantitative gene expression levels with fasting glucose levels, a major diabetes risk factor, plus one or more diabetes risk factors including fasting insulin and composite diabetes risk index. Using our unique family-based resource of quantitative genome-wide transcriptional profiles, we will examine 100 novel candidate genes that exhibit both strong evidence for cis-regulation of expression levels and significant correlations between expression levels and diabetes risk phenotypes. Our prior linkage-based evidence for cis-acting sequence variation can be exploited as a probabilistic causal anchor that should maximize our chance for finding functional variation within proximal promoters. For each of these objectively chosen genes, we will: 1) resequence approximately two kilobases of putative promoter region in 182 founder individuals to identify promoter variants; 2) genotype all detected promoter variation in each of the 100 candidate genes in the 1,240 SAFHS samples for whom we have transcriptional profiles; 3) test whether promoter sequence variants are associated with gene expression levels of the appropriate candidate gene; 4) test for associations between promoter sequence variants and diabetes risk phenotypes; and 5) confirm observed associations in two independent sample populations. The estimated economic burden of diabetes in the United States alone is approximately $100 billion per year, making this disease of major public health importance. The knowledge gained by this project will help contribute to the understanding of the genetics of type 2 diabetes through the identification of novel and potentially functional candidate genes, assisting in the development of new preventative measures and/or therapies.