Molecular Basis of High Density Lipoprotein Deficiency

描述(由申请人提供)：低水平的高密度脂蛋白胆固醇(高密度脂蛋白胆固醇)是冠心病(CHD)的独立危险因素。据估计，人类高密度脂蛋白水平变化的50%以上是由基因决定的。人们非常感兴趣的概念是，常见的基因变异导致了常见疾病易感性的遗传差异。解决这一问题的一个有希望的方法是在基于人群的关联研究中将DNA序列的变异与患者特征联系起来。我们建议使用退伍军人事务部高密度脂蛋白干预试验(VA-HIT，CASES)的样本来识别与低高密度脂蛋白特征相关的等位基因变异，这项研究旨在探索在低高密度脂蛋白(40 mg/dL)、正常低密度脂蛋白(140 mg/dL)和已知冠心病的男性中使用吉非罗齐提高高密度脂蛋白的益处，以及弗雷明翰后代研究(FOS，对照)。我们的主要目的是确定：1)低高密度脂蛋白性状的易感基因座，2)与载脂蛋白A-L所含高密度脂蛋白亚种水平相关的等位基因变异，3)与吉非罗齐治疗VA-HIT相关的等位基因变异。对于目标1，我们将审查生物(n=38)和位置(n=3)候选人。前者将包括与高密度脂蛋白代谢、胰岛素抵抗和炎症有关的基因，而后者将根据全基因组连锁扫描与FOS中高密度脂蛋白-C水平相关的数量性状基因座的结果进行选择。对于每个候选人，我们将使用HapMap数据来选择信息量最大的一组SNP(Tag SNP)，这将使我们能够解析所有单倍型的80%。在此算法的基础上，我们将在每个候选基因/区域中每2500个碱基对1个SNP进行分型。为了解决人口分层的问题，我们将使用一种结构化的关联方法，使用一组250个能够检测到适度分层的标记。这项工作的结果将为了解高密度脂蛋白代谢、炎症和胰岛素抵抗途径中的等位基因变异对低高密度脂蛋白胆固醇复杂表型的贡献提供重要的见解。

DESCRIPTION (provided by applicant): A low level of high density lipoprotein cholesterol (HDL-C) is an independent risk factor for coronary heart disease (CHD). It is estimated that more than 50% of the variation in HDL-C levels in humans is genetically determined. There is great interest in the concept that common genetic variants contribute to inherited differences in the susceptibility to common diseases. One promising approach to address this issue is to relate variation in DNA sequence with patient characteristics in population-based association studies. We are proposing to identify allelic variants associated with the low HDL trait, using samples from the Veterans Affairs HDL Intervention Trial (VA-HIT, cases), a study designed to explore the benefits of HDL-raising with gemfibrozil in men having low HDL-C (<40 mg/dL), normal LDL-C (<140 mg/dL) and known CHD, and the Framingham Offspring Study (FOS, controls). Our primary aims are to identify: 1) susceptibility loci for the low HDL trait, 2) allelic variants associated with levels of apolipoproteinA-l-containing HDL subspecies, and 3) allelic variants associated with response to gemfibrozil in VA-HIT. For Aim 1, we will examine biological (n=38) and positional (n=3) candidates. The former will include genes involved in HDL metabolism, insulin resistance and inflammation, while the latter will be selected on the basis of results from genome-wide linkage scans for quantitative trait loci associated with HDL-C levels in FOS. For each candidate, we will use HapMap data in order to select a maximally informative set of SNPs (tagSNPs), which will allow us to resolve >80% of all haplotypes. Based on this algorithm, we will genotype 1 SNP per 2500 bp across each candidate gene/region. To address the issue of population stratification, we will employ a structured association approach, using a set of 250 markers that has the ability to detect modest amounts of stratification. The results of this work will provide important insight into the contribution of allelic variation in the pathways of HDL metabolism, inflammation, and insulin resistance to the complex phenotype of low HDL-C.