Identifying genes underlying linkage peaks for clusters of CVD risk factors

描述(申请人提供)：大多数基因研究寻找影响个体特征的基因，如体重或血压。然而，在许多情况下，特征之间是相互关联的，而且，这些模式通常在家庭中发生。这些相关性可能反映了潜在的共同遗传效应。专注于识别影响特征簇的基因的研究为研究常见、复杂疾病的遗传基础提供了一种重要的创新方法。代谢综合征(METS)以一系列特征为特征，包括全身性和中心性肥胖、血脂异常、高血压、糖耐量减低和胰岛素抵抗。此外，甲型肝炎是一个重要且日益严重的公共卫生问题，目前影响着34%的美国人口，并与心血管疾病、中风和2型糖尿病的风险增加有关。虽然很明显，个体METS的特征受到基因的影响，但关于基因是否影响METS特征的特征聚集，人们知之甚少。例如，聚集性是由于：1)单个基因(S)同时影响一个以上的Met性状(多效性)，还是2)几个紧密连锁的基因，每个基因影响不同的个体性状(共生连锁)，或者3)两种机制的组合？METS特别适合于评估这些影响和了解这种复杂疾病的潜在遗传结构。利用来自多种族研究的家系数据，我们以前发现了三个染色体区域，这些区域有强有力的证据表明与特定的蛋氨酸性状组合存在连锁，还发现了多效性和重合连锁的证据。该项目的目标是确定构成蛋氨酸性状簇的连锁信号的特定变种。这将通过四个具体目标来实现，并将重点放在先前有联系证据的家庭子集上。我们将与尼克森实验室和Bruce Weir博士合作，将第二代蛋白质编码区(外显子)测序和定向基因分型纳入我们现有的研究。我们还将使用作为现有研究的一部分收集的四个不同种族/民族群体来评估异质性。我们希望确定负责连锁信号的特定基因和变种。识别影响几个已确立的心血管疾病风险因素的基因将提供一个重要的新药靶点，可能对转化为临床实践具有重要意义。公共卫生影响和意义：确定在几个民族/种族群体中增加多发性甲型肝炎风险的基因和特定变种，扩大了该项目对公共卫生的潜在影响。潜在的临床影响和意义：识别同时影响几个已建立的危险因素的基因将提供重要的新药靶点。

DESCRIPTION (provided by applicant): Most genetic studies look for genes that influence individual traits, such as body weight or blood pressure. However, there are many situations in which traits are correlated with each other and, further, these patterns often run in families. These correlations may reflect underlying shared genetic effects. Studies that focus on identifying genes that influence clusters of traits provide an important and innovative approach to studying the genetic basis of common, complex diseases. The Metabolic Syndrome (MetS) is characterized by a cluster of traits, including overall and central obesity, lipid abnormalities, hypertension, glucose intolerance, and insulin resistance. Further, MetS is an important and growing public health problem, currently affecting 34% of the U.S. population and associated with increased risk for cardiovascular disease, stroke, and type 2 diabetes. Although it is clear that the individual MetS traits are genetically influenced, less is known about whether genes affect the clustering of traits that characterize MetS. For example, is the clustering due to: 1) individual gene(s) that affect more than one MetS trait at a time (pleiotropy), or 2) several closely linked genes that each affect the different individual traits (co-incident linkage), or 3) combination of both mechanisms? MetS is particularly well suited for evaluating these effects and understanding the underlying genetic architecture of this complex disease. Using family data from a multi-ethnic study, we previously identified three chromosomal regions with strong evidence for linkage to specific combinations of MetS traits, and also found evidence of both pleiotropy and coincident linkage. The goal of this project is to identify the specific variants tat underlie the linkage signals for clusters of MetS traits. This will be accomplished through four specific aims and focusing on the subset of families with prior evidence for linkage. We will work with the Nickerson laboratory and Dr. Bruce Weir to incorporate second generation sequencing of protein coding regions (exomes) and targeted genotyping into our existing study. We will also evaluate heterogeneity using the four different racial/ethnic groups collected as part of our existing study. We expect to identify the specific genes and variants that are responsible for the linkage signals. Identifying genes that influence several established cardiovascular disease risk factors would provide an important new drug target that could have significant implications for translation to clinical practice. Public Health Impact and Significance: Identifying genes and specific variants that increase risk of multiple MetS features in several ethnic/racial groups broadens the potential public health impact of this project. Potential Clinical Impact and Significance: Identifying genes that influence several established risk factors simultaneously would provide important new drug targets.