Genomic dissection of a QTL affecting the lipid profile

描述(申请人提供)：代谢综合征是一种常见的疾病，对西半球的冠心病和早期死亡构成重大风险。其心血管并发症的核心是该综合征与特定的血脂和脂蛋白谱异常有关，包括血浆甘油三酯升高，高密度脂蛋白胆固醇降低，以及致密脂蛋白颗粒占优势。为了寻找这种血脂紊乱的遗传病因，我们在人类染色体7q36上发现了一个与血脂水平变化密切相关的数量性状基因座(QTL)。我们假设该QTL包含导致脂质紊乱发生的生物途径改变的遗传变异。为了验证这一假设，我们提出了一种综合的方法，利用已建立的资源和专业知识来识别该QTL中的功能序列变体。具体来说，我们将1。)识别整个QTL区域的单核苷酸多态(SNP)及其单倍型和连锁不平衡结构；利用方差成分连锁/不平衡分析，分析信息性SNPs与血浆甘油三酯水平、低密度脂蛋白水平和脂蛋白密度分数的关系；使用贝叶斯数量性状核苷酸分析识别相关基因或基因组区域中潜在的功能序列变异。新的基因组技术、新的统计方法、现有的DNA和表型信息以及该项目背后的专业技术的综合应用将确保成功地阐明这种脂质紊乱的遗传病因，从而开发有效的手段来预防和/或治疗代谢综合征的心血管并发症。

DESCRIPTION (provided by applicant): The metabolic syndrome is a common disorder posing a significant major risk for coronary heart disease and early mortality in the Western hemisphere. Central to its cardiovascular complications is the association of the syndrome with the specific abnormalities in plasma lipid and lipoprotein profiles including increased plasma triglycerides, decreased HDL cholesterol, and predominance of dense lipoprotein particles. In search for the genetic etiology of this lipid disorder, we identified a quantitative trait locus (QTL) on human chromosome 7q36 strongly linked to variation in plasma lipid levels. We hypothesize that this QTL contains genetic variants that contribute to alterations in biologic pathways underlying the genesis of the lipid disorder. To test for this hypothesis, we propose a comprehensive approach utilizing established resources and expertise to identify the functional sequence variants within this QTL. Specifically, we will 1.) identify single nucleotide polymorphisms (SNPs) and their haplotype and linkage disequilibrium structure across the entire QTL region; 2.) Analyze association of informative SNPs with plasma triglyceride levels, LDL levels, and lipoprotein density fractions using variance component linkage/disequilibrium analyses; and 3.) Identify potentially functional sequence variants in associated genes or genomic regions using Bayesian quantitative trait nucleotide analysis. This comprehensive application of newly available genomic technologies, novel statistical approaches, the DNA and phenotypic information available, and the consortium of expertise assembled behind this project will ensure the successful elucidation of the genetic etiology of this lipid disorder and consequently the development of effective means for prevention and/or treatment of cardiovascular complications of the metabolic syndrome.