Epidemiology of Putative Causal Variants in the Multiethnic Cohort

描述(由申请人提供)：为响应RFA-HG-07-014，我们建议使用多种族队列(MEC)研究来表征在大规模基因组关联研究中针对广泛的复杂特征(慢性病、中间表型和行为风险因素)在种族/民族人群中确定的推定因果变异的“流行病学结构”。我们已经建立了一个大型的血液和尿液生物库(N=67,000)和冷冻保存的淋巴细胞(N=15,000)，与MEC中五个种族/民族的广泛、预期收集的危险因素(例如，饮食、吸烟、体力活动)、生物标记物和临床数据相关联。这项对夏威夷和加利福尼亚州超过215,000名男性和女性进行的队列研究是独一无二的，因为它是以人口为基础的，包括五个美国种族/民族(日裔美国人、非裔美国人、欧洲裔美国人、拉丁美洲人和夏威夷原住民)患有不同慢性病风险的大量老年人(基线年龄为45-75岁)。我们建议研究：1)我们拥有大量病例和对照(乳腺癌、前列腺癌、直肠癌、糖尿病和肥胖症)的DNA的疾病；2)不太常见的重要癌症(例如肺癌、胰腺癌、子宫内膜癌、非霍奇金淋巴瘤)，但我们建议与其他资助小组共享我们的数据；3)作为这些疾病的风险因素的共同特征(例如，体重指数/体重、腰臀比、身高)和4)与疾病相关的生物标志物(例如，空腹、胰岛素和血脂、类固醇激素)。我们的具体目标是：1)确定MEC中五个种族/民族推定的因果变异的基于人群的流行病学概况(等位基因频率、主效应、疾病特征的异质性)；2)对于显示跨种族/种族群体效应异质性的变异，我们将利用LD的差异来确定这些基因座上更完整的相关变异谱；3)调查基因x和基因x环境的相互作用以确定修饰因素；4)检查推定因果变异与已经测量的中间表型(例如，血浆胰岛素、血脂、类固醇激素)的关系；4)对于不属于已知基因的变异，开始在小型基因组研究中研究它们与基因表达和表观遗传模式的关系。我们将协调这些变种和终点的选择、分析方法、数据分析和结果的快速报告，并与通过该RFA资助的其他队列/临床试验进行协调。

DESCRIPTION (provided by applicant): In response to RFA-HG-07-014, we propose to use the Multiethnic Cohort (MEC) study to characterize the "epidemiologic architecture" of putative causal variants identified in large-scale genomic association studies for a wide range of complex traits (chronic diseases, intermediate phenotypes and behavioral risk factors) across racial/ethnic populations. We have established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factor (e.g., diet, smoking, physical activity), biomarker and clinical data, for five racial/ethnic groups in the MEC. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. We propose to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). Our specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 4) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. We will coordinate the selection of these variants and endpoints, analytical methods, data analyses, and rapid reporting of results with other cohorts/clinical trials funded through this RFA.