Epidemiology of Putative Causal Variants in the Multiethnic Cohort

描述（由申请人提供）：为了响应RFA-HG-07-014，我们建议使用多民族队列（MEC）研究来表征在大规模基因组关联研究中发现的各种复杂特征（慢性疾病、中间表型和行为风险因素）的假定因果变异的“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= 67000）和冷冻保存淋巴细胞（N= 15000），与广泛的前瞻性收集的风险因素（如饮食、吸烟、体育活动）、生物标志物和临床数据相关，涉及MEC的五个种族/民族群体。这项针对夏威夷和加利福尼亚超过215,000名男性和女性的队列研究的独特之处在于它是以人口为基础的，并且包括了美国五个种族/民族群体（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原住民）的大量老年人（基线45-75岁），他们患慢性病的风险各不相同。我们建议研究：1)我们有大量病例和对照DNA的疾病（乳腺癌、前列腺癌、结直肠癌、糖尿病和肥胖症）；2)不太常见的重要癌症（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)作为这些疾病危险因素的共同特征（例如，身体质量指数/体重、腰臀比、身高）和4)与疾病相关的生物标志物（例如，空腹胰岛素和脂质、类固醇激素）。我们的具体目标是：1)确定MEC地区五个种族/民族中假定的因果变异的基于人群的流行病学概况（等位基因频率、主要影响、疾病特征的异质性）；2)对于在民族/种族群体中表现出影响异质性的变异，我们将利用LD的差异来确定这些位点上更完整的相关变异谱；3)研究基因x与基因x环境的相互作用，确定修饰因子；4)检查假定的因果变异与已经测量的中间表型（例如，血浆胰岛素、脂质、类固醇激素）的关联；4)对于不属于已知基因的变异，开始在小型基因组研究中调查它们与基因表达和表观遗传模式的关系。我们将与通过该RFA资助的其他队列/临床试验协调这些变异和终点的选择、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.