INTEGRATIVE GENOMICS & RISK OF CORONARY HEART DISEASE & RELATED PHENOTYPES IN THE WOMEN'S HEALTH INITIATIVE3/29/2014 - 3/28/2015CAN: 14-8470187

综合基因组学

• 批准号: 9042180
• 负责人: N/A N/A
• 金额: $ 54.91万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-29 至 2016-03-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9042180
• 关键词: Age; Biological; Biological Markers; Biology; Blood Banks; Contractor; Coronary heart disease; DNA Methylation; Data; Diagnostic; Event; Genes; Genetic Fingerprintings; Genetic Markers; Genomics; Mediating; Medical Genetics; Methodology; Pathway interactions; Phenotype; Plasma; Postmenopause; Resolution; Resources; Risk; Risk Factors; Technology; Testing; Woman; Women' s Health; age related; circulating microRNA; follow-up; genome wide association study; genome-wide; member; novel; prognostic

The contactor will take advantage of the existing large and unique Women’s Health Initiative (WHI) biological resource, which includes bio-banked blood from a large number of postmenopausal women who have been extensively phenotyped over a follow-up period of up to nineteen years. The contractor will carefully profile the DNA and plasma of Coronary Heart Disease (CHD) cases, as well as an appropriate set of controls, using two complementary, but well-validated, genomic technologies at baseline. These high throughput genomic technologies are expected to generate high quality and high-resolution genome wide DNA methylation profiles, as well as a comprehensive assessment of circulating microRNA levels in plasma. We will then comprehensively analyze and integrate this genomic data with existing clinical, genetic, and biomarker data using state of the art statistical methodologies developed by members of the investigative team to identify genomic signatures and pathways relevant to CHD and its risk factors.

该接触器将利用现有的大型且独特的妇女健康倡议 (WHI) 生物资源，其中包括来自大量绝经后妇女的生物库血液，这些妇女在长达十九年的随访期内已进行了广泛的表型分析。承包商将在基线上使用两种互补但经过充分验证的基因组技术，仔细分析冠心病 (CHD) 病例的 DNA 和血浆，以及一组适当的对照。这些高通量基因组技术预计将产生结果。高的然后，我们将使用最先进的统计方法，全面分析该基因组数据并将其与现有的临床、遗传和生物标志物数据整合。由调查团队成员开发，用于识别与 CHD 及其风险因素相关的基因组特征和途径。