Genetic identification

在美国，冠状动脉疾病(CAD)是导致死亡的唯一主要原因。冠心病是一种复杂的疾病，具有明确的遗传和环境风险因素。早发(早发)冠状动脉疾病(EOCAD)，定义为发病年龄小于50岁，已知具有特别强的遗传成分。然而，导致这种风险增加和对CAD的基本理解的实际基因仍然不清楚。我们建议使用微卫星标记在438个有多个成员的冠心病家系中进行基因定位研究。我们假设，受影响的个体，特别是发病年龄较早的个体，具有潜在的冠心病发生的遗传易感性。我们将使用一种全面的策略，包括精细定位、候选基因分析和基于家庭的关联研究，使用CEGS的微卫星目标。首先，它提供了一种独立的方法来确定基于人群的关联研究的候选基因，这种方法基于高危家庭中易感等位基因的基因组位置，而不是关于潜在生理的生物学假设。其次，它提供了一种新的方法来选择用于表达分析的“定制”打印阵列的基因，这种方法同样是基于易感等位基因的基因组位置，而不是基于生物偏见。

Coronary artery disease (CAD) is the single leading cause of death in the US. CAD is a complex disease with clear genetic and environmental risk factors. Early onset (premature) coronary artery disease (EOCAD), defined as age of onset less than 50 years of age, is known to have a particularly strong genetic component. However, the actual genes leading to this increased risk and to a basic understanding of CAD remain obscure. We propose to perform a gene mapping study using microsatellite markers in 438 families with multiple members with CAD. We hypothesize that affected individuals, particularly individuals with an early age of onset, have an underlying genetic susceptibility to development of CAD. We will use a comprehensive strategy comprising fine mapping, candidate gene analysis, and family-based association studies using microsatellite goals of the CEGS. First, it provides an independent approach to identify candidate genes for population-based association studies, one based on the genome location of susceptibility alleles in high-risk families, and not on biological assumptions about underlying physiology. Second, it provides a novel approach for the selection of genes for "custom" printed arrays for expression analyses, again, one that is based on the genome location of susceptibility alleles, and not on biological biases.