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到遗传因素的影响。性类固醇激素，例如雌二醇和睾酮，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，使得能够开发能够执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，旨在使用 Illumina HumanHap500 微珠芯片进行全基因组关联研究，检测易患乳腺癌的单核苷酸多态性 (SNP)。护士健康研究 (NHS) 是这项合作的一部分，提供了 2300 名女性的 DNA（1150 名绝经后诊断出患有浸润性乳腺癌的女性，以及 1150 名年龄匹配的未诊断出患有乳腺癌的女性）。已对采血时绝经后且近期未接受激素替代疗法的女性前瞻性采集的血浆中的雌二醇、睾酮和性激素结合球蛋白 (SHBG) 水平进行了测定。 CGEMS 项目基因分型样本中大约有 430 个病例和 415 个对照符合这些标准，并且具有可用的雌二醇、睾酮和 SHBG 水平。这些相同的血浆激素水平已在每个病例的第二个对照样本以及诊断为原位癌的女性对照受试者中进行了测定，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。这将通过使用协方差分析对 CGEMS 项目中基因分型的 550,000 个 SNP 进行初步筛选来完成，以了解与激素水平的关联。然后，将在额外的对照样本中对这些 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。作为生成二次分析的假设，我们还将检查拷贝数变异 (CNV) 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之前在 NHS 中测定的性类固醇激素水平，这项工作将提供一种独特的、具有成本效益的、强大的全基因组关联研究来描述预测性类固醇激素水平的多态性。当前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，为两阶段全基因组关联扫描中与性类固醇激素水平最密切相关的 SNP 提供强有力的联合分析。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其对性类固醇激素水平的影响提供非常有可能的候选者，性类固醇激素水平是许多疾病（包括乳腺癌）公认的预测因子。