Risk Burden of Lipoprotein Metabolic Gene Haplotypes

描述(申请人提供)：近年来，一些候选遗传变异(例如，单核苷酸多态，SNPs)被报道与冠心病(CHD)有关。然而，这些关联研究受到了可变性和复制失败的影响。这可能部分是由于选择了与真正的疾病相关的SNPs或与其他调节效应的遗传变异处于连锁不平衡(LD)的标记SNPs。其他问题包括在有限大小的样本中发挥偶然性，人口分层人工制品，以及单个SNP的小效应大小。最近的一项发现是，基因组在种群水平上被组织成基本不变的DNA片段，其特征是罕见的重组事件穿插着重组的“热点”，并被指定为“单倍型块”。这些单倍型区块可以通过在目标基因上创建SNPs的密集图谱并分析群体水平Ld来确定。然后，可以选择几个SNP来指定(标记)每个单倍型块，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通路中的多个基因，并评估基因组合，可能会增加发现与冠心病风险的遗传关联的能力。这个雄心勃勃的项目建议建立高密度的SNP图谱，覆盖6个基因的外显子、剪接区和5‘和3’调控区，这些基因在脂蛋白的运输和代谢中发挥关键作用(ABCA1、CETP、LCAT、HL、LPL、SRB1)；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)SNPs的组合，“遗传负担”可以在4个水平上被评分并与冠心病风险相关：1)生物标记物(脂/脂蛋白水平)，2)解剖(血管造影)冠心病，3)临床结果(死亡/心肌梗死)，4)对降脂的探索性反应。检测将在犹他州3个大型、不同但互补的人群中进行，这些人群存在早期冠心病的主要或次要风险。检测将分两个阶段进行，以确定重复性：在较大的独立样本中进行初步筛选阶段，然后是确认阶段(对于有希望的遗传标记和组合)。这项研究将采用新的方法，将高通量SNP发现和基因分型能力与遗传流行病学方法相结合，以确定感兴趣基因内部和周围的单倍型块，识别htSNP，并评估与单独的htSNP及其组合(“遗传负担”)的疾病关联。为此，该项目带来了大型、特点良好的数据库，这些数据库经过长达9年的组装和跟踪，将在目前的项目下进一步扩大。我们相信，这种彻底的、新颖的方法将导致遗传性冠心病风险评估的重大进步，使基于基因的CHD医学愿景得以实现。

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.