Risk Burden of Lipoprotein Metabolic Gene Haplotypes

描述（由申请人提供）：近年来，许多候选遗传变体（例如，单核苷酸多态性（SNP）与冠心病（CHD）相关。然而，这些协会的研究受到变异性和复制失败。这可能部分是由于选择了与真正疾病相关的SNP或其他效应调节遗传变异连锁不平衡（LD）的标记SNP。其他问题包括在有限大小的样本中的机会，群体分层假象和单个SNP的小效应大小。最近的发现是基因组在群体水平上被组织成基本不变的DNA片段，其特征在于不频繁的重组事件，其中散布有重组的“热点”和指定的“单倍型块”。这些单倍型块可以通过创建目标基因上的SNP的密集图谱并分析群体水平LD来确定。然后可以选择指定（“标记”）每个单倍型块的几个SNP，并用于全面评估整个基因的疾病关联。将这种方法应用于对血管健康至关重要的途径中的多个基因，并评估基因的组合，可能会增加发现与CHD风险的遗传关联的能力。这个雄心勃勃的项目提出建立高密度SNP图谱，包括外显子、剪接区以及在脂蛋白转运和代谢中起关键作用的6个基因（ABCA 1、CETP、LCAT、HL、LPL、SRB 1）的5'和3'调控区;将检查其中2个基因（CETP、LPL）的内含子。通过分析单倍型标记（ht）SNP的组合，可以在4个水平上对“遗传负担”进行评分并与CHD风险相关联：1）生物标志物（脂质/脂蛋白水平），2）解剖学（血管造影）CHD，3）临床结果（死亡/MI）和4）（探索性）对降脂的反应。将在3个具有早发CHD原发性或继发性风险的大型、不同但互补的犹他州人群中进行检测。测试将分两个阶段进行，以建立重现性：初始筛选阶段，然后是在更大的独立样本中的确认阶段（用于显示前景的遗传标记和组合）。这项研究将采用新的方法，结合联合收割机高通量SNP发现和基因分型能力与遗传流行病学方法，以确定单倍型块内和周围的感兴趣的基因，确定htSNPs，并评估疾病与个体和组合的htSNPs（“遗传负担”）。为此，该项目带来了大型的、特征良好的数据库，这些数据库经过了长达9年的组装和跟踪，并将在当前项目下进一步扩大。我们相信这种彻底的、新颖的方法将导致遗传性CHD风险评估的重大进展，使基于基因的CHD医学的愿景得以实现。

DESCRIPTION (provided by applicant): In recent years, a number of candidate genetic variants (e.g., single nucleotide polymorphisms, SNPs) have been reported to be associated with coronary heart disease (CHD). However, these association studies have suffered from variability and failures of replication. This may result in part from selection of marker SNPs in linkage disequilibrium (LD) with true disease-related SNPs or with other effect-modulating genetic variants. Other issues include the play of chance in samples of limited size, population stratification artifacts, and small effect size for single SNPs. A recent discovery is that the genome is organized into largely invariant DNA fragments at the population level characterized by infrequent recombination events interspersed with "hotspots" of recombination and designated "haplotype blocks". These haplotype blocks can be determined by creating a dense map of SNPs across the gene of interest and analyzing population level LD. A few SNPs then can be chosen that designate ("tag") each haplotype block and used to comprehensively assess disease associations across the entire gene. Applying this approach to multiple genes in pathways critical to vascular health and assessing combinations of genes is likely to increase the power to discover genetic associations with CHD risk. This ambitious project proposes to establish high density SNP maps across exons, splice regions, and 5' and 3' regulatory regions of 6 genes that play key roles in lipoprotein transport and metabolism (ABCA1, CETP, LCAT, HL, LPL, SRB1); introns will be examined for 2 of the genes (CETP, LPL). By analyzing combinations of haplotype-tagging (ht) SNPs, "genetic burden" can be scored and correlated with CHD risk at 4 levels: 1) biomarker (lipid/lipoprotein levels), 2) anatomic (angiographic) CHD, 3) clinical outcome (death/MI), and 4) (exploratory) response to lipid-lowering. Testing will be performed in 3 large, distinct, but complementary Utah populations at primary or secondary risk of premature CHD. Testing will occur in 2 stages to establish reproducibility: an initial screening phase followed by a confirmation phase (for genetic markers and combinations showing promise) in a larger, independent sample. The study will employ novel methods that combine high-throughput SNP discovery and genotyping capability with genetic epidemiological methods to identify the haplotype blocks within and surrounding the genes of interest, identify htSNPs, and assess disease associations with individual and combinations of htSNPs ("genetic burden"). To this, the project brings large, well characterized databases, assembled and followed for up to 9 years, which will be further expanded under the current project. We believe this thorough, novel approach will lead to a major advance in genetic CHD risk assessment, enabling the vision of gene-based medicine for CHD to be realized.