Identifying genes underlying linkage peaks for clusters of CVD risk factors

识别 CVD 危险因素簇连锁峰的基因

• 批准号: 8451833
• 负责人: KAREN L EDWARDS
• 金额: $ 79.66万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8451833
• 关键词: Accounting; Affect; African American; American; Architecture; Bioinformatics; Blood Pressure; Body Weight; Candidate Disease Gene; Central obesity; Clinical; Complex; DNA; Data; Disease; Drug Targeting; Ethnic group; European; Family; Family Study; Family member; Generations; Genes; Genetic; Genetic Heterogeneity; Genetic Variation; Genotype; Glucose Intolerance; Goals; Health; Heterogeneity; High Density Lipoprotein Cholesterol; Hypertension; Individual; Insulin; Insulin Resistance; Japanese American; Japanese Population; Laboratories; Lead; Link; Lipids; Metabolic syndrome; Mexican; Mexican Americans; Microsatellite Repeats; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Open Reading Frames; Pattern; Plasma; Population; Prevention; Public Health; Race; Risk; Risk Factors; Running; Sampling; Scanning; Signal Transduction; Stroke; Technology; Testing; Time; Translations; Triglycerides; Variant; Work; base; cardiovascular disorder risk; clinical practice; diabetes risk; economic implication; exome; exome sequencing; genetic linkage analysis; genetic variant; heart disease risk; innovation; interest; novel; pleiotropism; racial and ethnic; trait

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.

描述（由申请人提供）：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，这些特征是相互关联的，而且，这些模式通常在家族中遗传。这些相关性可能反映了潜在的共同遗传效应。专注于识别影响性状簇的基因的研究为研究常见、复杂疾病的遗传基础提供了重要和创新的方法。代谢综合征（MetS）以一系列特征为特征，包括全局性和中枢性肥胖、脂质异常、高血压、葡萄糖耐受不良和胰岛素抵抗。此外，MetS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，个体的MetS性状受到遗传的影响，但基因是否影响表征MetS的性状的聚类却知之甚少。例如，聚类是由于：1)单个基因同时影响多个MetS性状（多效性），还是2)几个密切相关的基因每个影响不同的个体性状（共发生连锁），还是3)两种机制的结合？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。利用一项多种族研究的家庭数据，我们先前确定了三个染色体区域，有力证据表明它们与MetS特征的特定组合有关，并且还发现了多效性和重合连锁的证据。这个项目的目标是确定特定的变异，这些变异是met性状集群连锁信号的基础。这将通过四个具体目标来实现，并侧重于先前有关联证据的家庭子集。我们将与Nickerson实验室和Bruce Weir博士合作，将第二代蛋白质编码区（外显子组）测序和靶向基因分型纳入我们现有的研究中。我们还将使用作为我们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。我们期望确定负责连锁信号的特定基因和变异。确定影响几种已确定的心血管疾病危险因素的基因将提供一个重要的新药物靶点，可能对转化为临床实践具有重大意义。公共卫生影响和意义：确定几个民族/种族群体中增加多种MetS特征风险的基因和特定变异，扩大了该项目的潜在公共卫生影响。潜在的临床影响和意义：识别同时影响几种已知危险因素的基因将提供重要的新药物靶点。