Whole Genome Association Study of Mammographic Density

乳腺X线密度的全基因组关联研究

• 批准号: 7656493
• 负责人: Rulla M Tamimi
• 金额: $ 45.92万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-03-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7656493
• 关键词: Affect; Biological; Biological Markers; Biology; Blood specimen; Body mass index; Breast; Breast Cancer Prevention; Breast Cancer Risk Factor; Chronic Disease; Complement; Complex; Coronary Arteriosclerosis; Data; Diet; Disease; Environmental Risk Factor; Etiology; Genes; Genetic; Genetic Markers; Genetic Variation; Genome Scan; Genotype; Health; Heritability; Heritable Quantitative Trait; Hormones; Inherited; Intervention; Lead; Life; Lipids; Malignant neoplasm of prostate; Mammographic Density; Mammography; Measures; Nurses' Health Study; Outcome; Participant; Pathway interactions; Phenotype; Population; Positioning Attribute; Postmenopause; Predisposition; Prevention; Risk; Risk Factors; Staging; Surrogate Markers; Variant; Woman; breast density; cancer genetics; cancer genome; cancer risk; carcinogenesis; case control; cohort; cost; density; gene environment interaction; gene interaction; genetic variant; genome wide association study; lifestyle factors; malignant breast neoplasm; non-genetic; novel; public health relevance; reproductive; trait

DESCRIPTION (provided by applicant): Mammographic density is one of the strongest risk factors for breast cancer. Women with the highest mammographic density are at a four- to six-fold greater risk of breast cancer than women with the lowest density. Recently for other chronic diseases (e.g., coronary artery disease), we have seen proof-of-principle that utilizing a reliably measured, heritable quantitative trait (e.g., circulating lipids) that is a strong risk factor for the outcome can identify novel loci for the disease that were not identified through genome-wide association studies (GWASs) of the outcome. Thus, studies of heritable phenotypes can uncover biological pathways that will lead to a better understanding of basic mechanisms of disease and may identify targets for intervention. In a similar paradigm, mammographic density is a highly heritable, reliably measured, quantitative trait and a well-established strong predictor of breast cancer independent of known breast cancer risk factors. Identifying genes associated with mammographic density will identify mechanisms related to not only breast density, but has immense potential to detect genes involved with breast cancer. We propose to conduct a multi-stage GWAS of mammographic density among postmenopausal women (Aim 1). As part of the Cancer Genetic Markers of Susceptibility (CGEMS) project, postmenopausal breast cancer cases and controls in the Nurses' Health Study (NHS) have whole genome scans completed. We estimate that we will have mammographic density data on 1,800 of these women. Our initial analysis will examine the association between 2.5 million SNPs (includes 550,000 genotyped and the remainder imputed) and mammographic density among women included in the CGEMS project (Stage 1). To minimize false positive and negative associations, we will pursue the highest-ranking 7,600 SNPs from Stage 1 in an additional 1,200 postmenopausal women from the NHS (Stage 2). The 1,536 most promising SNPs will be genotyped in 3,000 postmenopausal participants in the Mayo Mammography Health Study (MMHS) (Stage 3).Validated SNPs that emerge from the multi-stage study will be evaluated for biologically plausible gene-environment interactions (Aim 2). The NHS and MMHS are both well established cohorts of demographically similar populations with blood samples, mammographic density data and extensive exposure information on breast cancer risk factors. We will also evaluate if validated SNPs from Aim 1 are associated with breast cancer risk in the NHS and in the Breast and Prostate Cancer Cohort Consortium (with over 6,000 breast cancer cases and controls). The results of the proposed study will complement those from breast cancer GWASs by increasing our understanding of breast biology and etiology of breast cancer. This is a unique, cost-efficient, and timely proposal to identify novel genetic pathways underlying breast density and breast cancer. Identification of genes associated with mammographic density will allow for study of their function as it relates to density and breast cancer and opens up the possibility for novel targets of breast cancer prevention and treatment. PUBLIC HEALTH RELEVANCE: Elucidating the genetic components of complex diseases with multifactorial causes such as breast cancer can be enhanced through concentration on heritable risk factors for the disease. Mammographic density is a highly heritable, reliably measured, quantitative trait and a well- established strong predictor of breast cancer independent of known breast cancer risk factors. This multi-stage genome-wide association study of mammographic density will not only identify novel loci associated with breast density, but will complement the studies of breast cancer by increasing our understanding of breast biology and etiology of breast cancer.

描述（由申请人提供）：乳腺X线摄影密度是乳腺癌最强的危险因素之一。乳房X线学密度最高的女性比密度最低的女性患乳腺癌的风险高四至六倍。最近，对于其他慢性疾病（例如冠状动脉疾病），我们看到了利用可靠测量的，可遗传的定量性状（例如，循环脂质）的原则证明，这是结果的强大风险因素，可以通过基因组研究（GWASS）（GWASS）（GWASS）的疾病来鉴定出新的基因座的疾病。因此，对可遗传表型的研究可以揭示生物学途径，从而可以更好地理解疾病的基本机制，并可能确定干预措施的目标。在类似的范式中，乳腺X线摄影密度是一种高度可靠的，可靠的测量，定量性状，并且是乳腺癌的良好强大预测指标，独立于已知的乳腺癌危险因素。鉴定与乳房X线照相密度相关的基因将不仅鉴定与乳房密度相关的机制，而且具有检测与乳腺癌有关的基因的巨大潜力。我们建议在绝经后妇女中进行乳房X线摄影密度的多阶段GWA（AIM 1）。作为易感性（CGEM）项目的癌症遗传标记的一部分，护士健康研究（NHS）中绝经后乳腺癌病例和对照组完成了整个基因组扫描。我们估计我们将拥有1,800名这些女性的乳房X线照相密度数据。我们的初步分析将研究250万SNP（包括550,000个基因分型和剩余的估算）和CGEM项目中包括的女性（第1阶段）之间的关联。为了最大程度地减少假积极和负面的关联，我们将在1,200名NHS（第2阶段）的1,200名绝经后妇女中追求最高的7,600个SNP。 1,536个最有前途的SNP将在Mayo乳腺摄影健康研究（MMHS）的3,000名绝经后参与者中进行基因分型（第3阶段）。从多阶段研究中出现的验证的SNP将在多阶段研究中进行评估，以评估生物学上可行的基因环境相互作用（AIM 2）。 NHS和MMHS都是具有血液样本，乳房X线密度数据以及有关乳腺癌危险因素的广泛暴露信息的人口相似的人群的良好人群。我们还将评估AIM 1的验证SNP是否与NHS以及乳腺癌和前列腺癌队列联盟（有6,000多个乳腺癌病例和对照组）中的乳腺癌风险有关。拟议的研究的结果将通过增加我们对乳腺癌的乳腺癌和病因的理解来补充乳腺癌GWASS的结果。这是一个独特的，成本效率且及时的建议，可以识别乳腺密度和乳腺癌的新遗传途径。鉴定与乳房X线照相密度相关的基因将允许研究其功能，因为它与密度和乳腺癌相关，并为预防乳腺癌预防和治疗的新型靶标提供了可能性。公共卫生相关性：通过专注于该疾病的可遗传危险因素，可以增强具有多因素原因（例如乳腺癌）的复杂疾病的遗传成分。乳腺X线摄影密度是一种高度可靠的，可靠的测量，定量性状，并且是乳腺癌的良好预测指标，独立于已知的乳腺癌危险因素。这项多阶段的全基因组乳房X线摄影密度研究将不仅鉴定与乳腺密度相关的新基因座，而且还可以通过增加对乳腺癌的乳腺癌和病因的理解来补充乳腺癌的研究。