Genetic Variants Associated with HDL and LDL Cholesterol, and Triglyceride Levels

高水平的低密度脂蛋白胆固醇（LDL-c）和低水平的高密度脂蛋白胆固醇（HDL-c）是独立的风险 冠状动脉疾病（CAD）的因素。在本奖项的指导阶段，我们已经确定了59个 与脂质水平相关的新区域（Teslovich等人，2010年）。我们正在继续研究， 通过几种策略与脂质水平相关的新基因和遗传区域，其中几种是 该奖项指导阶段成功目标的延伸。我们将继续测试 在GWAS框架中，通过在10万个额外的基因组中测试最有希望的5,000个遗传变异， 样品我们还参与了NHLBI的外显子组测序项目的分析， 完成了417个样本的全外显子组测序，全部来自LDL-c的上或下1%尾部 分布识别新的，高度破坏性的基因突变可能会提供有价值的线索， 该基因在一个潜在的大区域可能参与脂质代谢，这是一个典型的逆转， 范式，以确定基因中含有罕见的破坏性突变的常见变异， 紊乱对于这个奖项的独立阶段，旨在了解功能的实验 将在以前确定的遗传信号的基础上进行，包括比对发挥作用的遗传变异。 脂质水平中的作用与来自公开可获得的Chip-Seq的已知转录因子结合位点的位置 数据该奖项独立阶段的最终目标是使用来自1000个基因组的信息 估算和测试约1000万个SNP与血脂水平相关的项目， 相关区域，并完善远程监管要素的签名。

High levels of LDL cholesterol (LDL-c) and low levels of HDL cholesterol (HDL-c) are independent risk factors for coronary artery disease (CAD). During the mentored phase of this award, we have identified 59 novel regions associated with lipid levels (Teslovich et al., 2010). We are continuing our research to identify novel genes and genetic regions associated with lipid levels through several strategies, several of which are extensions to successful aims from the Mentored Phase of this award. We will continue to test for association in a GWAS framework by testing the most promising 5,000 genetic variants in 100,000 additional samples. We are also involved in the analysis ofthe Exome Sequencing Project of NHLBI which has completed whole exome sequencing of 417 samples, all from the upper or lower 1% tails ofthe LDL-c distribution. Identification of novel, highly disruptive genetic mutations may provide valuable clues about which gene in a potentially large region may be involved in lipid metabolism, a reversal of the typical paradigm to identify common variants in genes that contain rare disruptive mutations for related Mendelian disorders. For the independent phase of this award, experiments designed to understand the functional basis of previously identified genetic signals will be undertaken, including aligning genetic variants that play a role in lipid levels with position of known transcription factor binding sites from publicly-available Chip-Seq data. The final aim for the independent phase ofthe award is to use information from the 1000 Genomes Project to impute and test ~10 million SNPs for association with lipid levels, catalog associated variants in associated regions and refine signatures of long-range regulatory elements.