Epidemiology of Putative Causal Variants in the Multiethnic Cohort

描述（由申请人提供）： 作为对RFA-HG-07-014的回应，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确定的假定因果变异体的“流行病学结构”，这些研究涉及跨种族/种族人群的各种复杂性状（慢性疾病、中间表型和行为风险因素）。我们已经建立了一个大型的血液和尿液（N= 67，000）和冷冻保存的淋巴细胞（N= 15，000）的生物储存库，与广泛的、前瞻性收集的风险因素（例如，饮食、吸烟、体力活动）、生物标志物和临床数据，用于MEC中的五个种族/民族组。这项在夏威夷和加州超过215，000名男性和女性中进行的队列研究的独特之处在于，它是基于人群的，包括5个美国种族/族裔群体（日裔美国人、非洲裔美国人、欧洲裔美国人、拉丁美洲人和夏威夷土著人）中老年人（基线时45-75岁）的大量代表性，这些人群具有不同的慢性疾病风险。我们建议研究：1）我们有大量病例和对照组DNA可用的疾病（乳腺癌、前列腺癌和结肠直肠癌、糖尿病和肥胖症）; 2）不太常见的重要癌症（例如，肺癌、胰腺癌、子宫内膜癌、NHL），但我们建议将我们的数据与其他资助组合并; 3）作为这些疾病风险因素的共同特征（例如，体重指数/体重、腰臀比、身高）和4）相关的疾病相关生物标志物（例如，空腹胰岛素和脂质、类固醇激素）。我们的具体目标是：1）确定基于人口的流行病学概况（等位基因频率、主要效应、疾病特征的异质性）; 2）对于在人种/人种组中显示效应异质性的变体，我们将利用LD的差异来鉴定这些基因座处的相关变体的更完整谱; 3）研究基因X基因和基因X环境相互作用以鉴定修饰物; 4）检查推定的因果变体与已经测量的中间表型（例如，血浆胰岛素、脂质、类固醇激素）;以及4）对于不属于已知基因的变体，开始在小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。我们将与通过本RFA资助的其他队列/临床试验协调这些变体和终点的选择、分析方法、数据分析和结果的快速报告。

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.