Genome Wide Association Study: Variants Influencing Steroid Hormone Levels

全基因组关联研究：影响类固醇激素水平的变异

• 批准号: 7501343
• 负责人: Immaculata De Vivo
• 金额: $ 8.75万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-27 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7501343
• 关键词: Age; Biological Assay; Blood; Carcinoma in Situ; Caucasians; Caucasoid Race; Collection; DNA; Data; Development; Diagnosis; Disease; Disease Outcome; Estradiol; Genetic; Genetic Markers; Genetic Polymorphism; Genotype; Gonadal Steroid Hormones; Hormone replacement therapy; Hormones; Individual; Invasive; Joints; Measures; Menopause; Numbers; Nurses' Health Study; Plasma; Population; Postmenopause; Predisposition; Sampling; Sex Hormone-Binding Globulin; Single Nucleotide Polymorphism; Staging; Testosterone; Time; Variant; Woman; Work; base; cancer genetics; case control; cost; cost effective; design; genome wide association study; genotyping technology; malignant breast neoplasm; steroid hormone

DESCRIPTION (provided by applicant): There is substantial evidence that circulating sex steroid hormone levels are influenced by genetic factors. Sex steroid hormones, such as estradiol and testosterone, are implicated in the development of many diseases, including breast cancer. Recent advances in genotyping technology have reduced genotyping costs, allowing for the development of genotyping platforms capable of performing genome wide association scans. The Cancer Genetic Markers of Susceptibility (CGEMS) project has been initiated to perform a genome wide association study to detect single nucleotide polymorphisms (SNPs) which predispose for breast cancer, using the Illumina HumanHap500 bead chip. The Nurses' Health Study (NHS) is part of this collaborative effort, providing DNA from 2300 women (1150 women diagnosed with invasive breast cancer after menopause, and 1150 age-matched women not diagnosed with breast cancer). Levels of estradiol, testosterone, and SHBG have been assayed in plasma collected prospectively from women who were postmenopausal at blood collection, not having recently taken hormone replacement therapy. Approximately 430 cases and 415 controls within the samples genotyped in the CGEMS project fit these criteria, and have estradiol, testosterone, and SHBG levels available. These same plasma hormone levels have been assayed on a second control sample for each case, as well as the control subjects for women diagnosed with in situ carcinoma, however these control subjects (n~1100) have not been genotyped as part of the CGEMS project. The objective of this work is to describe polymorphisms that are associated with plasma sex steroid hormone levels. This will be accomplished in an initial screen of the 550,000 SNPs genotyped in the CGEMS project for associations with hormone levels using analysis of covariance. A subset of these SNPs will then be genotyped in the additional control samples, and joint analyses of the initial and second stages will provide strong evidence for association between SNP loci and plasma hormone levels. As hypothesis generating secondary analysis, we will also examine copy number variants (CNVs) for association with steroid hormone levels. By using genotype data collected in the CGEMS project, and sex steroid hormone levels assayed previously in the NHS, this work will provide a unique, cost effective, and powerful genome wide association study to describe polymorphisms which predict sex steroid hormone levels. The genotyping data collected in the current study will be combined with already available sex steroid hormone data to provide well powered joint analyses of the SNPs most strongly associated with sex steroid hormone levels from this two stage genome wide association scan. Therefore, polymorphisms found to be associated with sex steroid hormone levels in this joint analysis will provide very likely candidates for further study with respect to their influence on sex steroid hormone levels, which are well recognized predictors of many diseases, including breast cancer.

描述（由申请人提供）： 有大量证据表明，循环性类固醇激素水平受遗传因素的影响。性类固醇激素，如雌二醇和睾酮，与许多疾病的发展有关，包括乳腺癌。基因分型技术的最新进展降低了基因分型成本，从而允许开发能够进行全基因组关联扫描的基因分型平台。癌症易感性遗传标记（CGEMS）项目已启动，以进行全基因组关联研究，以检测单核苷酸多态性（SNP），易患乳腺癌，使用Illumina HumanHap 500微珠芯片。护士健康研究（NHS）是这项合作努力的一部分，提供了2300名妇女的DNA（1150名绝经后诊断为浸润性乳腺癌的妇女，1150名年龄匹配的妇女未诊断为乳腺癌）。雌二醇、睾酮和SHBG的水平已经在血浆中进行了测定，这些血浆是从血液采集时绝经后、最近没有接受激素替代治疗的女性中前瞻性采集的。CGEMS项目中基因分型样本中约有430例病例和415例对照符合这些标准，并具有雌二醇、睾酮和SHBG水平。这些相同的血浆激素水平已经在每个病例的第二个对照样本中进行了测定，以及诊断为原位癌的女性的对照受试者，但是这些对照受试者（n~1100）尚未作为CGEMS项目的一部分进行基因分型。这项工作的目的是描述与血浆性类固醇激素水平相关的多态性。这将在CGEMS项目中基因分型的550，000个SNP的初始筛选中使用协方差分析与激素水平的关联中完成。然后将在额外的对照样品中对这些SNP的子集进行基因分型，并且初始和第二阶段的联合分析将为SNP位点与血浆激素水平之间的关联提供强有力的证据。作为假设产生的二次分析，我们还将检查拷贝数变异（CNVs）与类固醇激素水平的关联。通过使用CGEMS项目中收集的基因型数据，以及NHS中以前测定的性类固醇激素水平，这项工作将提供一个独特的，具有成本效益的，强大的全基因组关联研究，以描述预测性类固醇激素水平的多态性。本研究中收集的基因分型数据将与现有的性类固醇激素数据相结合，以提供来自该两阶段全基因组关联扫描的与性类固醇激素水平最强相关的SNP的充分联合分析。因此，在这项联合分析中发现的与性类固醇激素水平相关的多态性将为进一步研究它们对性类固醇激素水平的影响提供非常可能的候选者，性类固醇激素水平是公认的许多疾病的预测因子，包括乳腺癌。