Integrating Genomics and Metabolomics to Develop Predictive Models of Prostate Cancer in Multiethnic Men

整合基因组学和代谢组学来开发多种族男性前列腺癌的预测模型

• 批准号: 10768434
• 负责人: Burcu Frances Darst
• 金额: $ 8.8万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10768434
• 关键词: African American; African ancestry; American; Award; Biological; Cancer Etiology; Cessation of life; European; Funding; Genetic; Genetic Risk; Genomics; Goals; Incidence; Individual; Indolent; Investigation; Malignant neoplasm of prostate; Measures; Mediating; Mendelian randomization; Metabolic; Modeling; Parents; Phase; Population; Predictive Value; Preventive measure; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; Research; Sampling; Screening for Prostate Cancer; Subgroup; Techniques; Training; anticancer research; cohort; genome wide association study; health disparity; high risk population; improved; men; metabolomics; mortality; multi-ethnic; novel; polygenic risk score; predictive modeling; prostate cancer model; prostate cancer risk; risk variant; screening; statistics

PROJECT SUMMARY/ABSTRACT OF THE FUNDED PARENT AWARD Prostate cancer (PCa) is the second leading cause of cancer death among American men, with men of African ancestry have the highest PCa incidence and mortality rates. While the causes of this notable health disparity are not fully understood, growing evidence suggests that genetics is a contributing factor. However, most PCa research has focused on men of European descent, particularly genome-wide association studies (GWAS), which has resulted in polygenic models having poorer predictive value in non-Europeans. The overarching goal of this research is to identify genomic and metabolomic factors that contribute to PCa risk in men across multi- ancestry populations. In the R00 phase of this award, Dr. Darst will initiate a new line of research that applies integrative techniques to investigate combined genomic and metabolomic factors influencing PCa risk. This will build directly upon the research and training received in the K99 period. She will identify genetically regulated metabolites that could be causally associated with PCa risk in multi-ancestry populations and/or indicate potentially novel genetic risk loci (Aim 1). This will require developing a large multi-ancestry metabolomic imputation panel and performing two-sample Mendelian randomization for each metabolite and GWAS summary statistics from the large and diverse PRACTICAL Consortium. Using a subset of 872 African American men from the Multiethnic Cohort (MEC) and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, Dr. Darst will investigate the biological mechanisms implicated by genetic risk of PCa, as measured by a multi- ancestry polygenic risk score, metabolites that could mediate the effects of genetic factors on overall and aggressive PCa, and whether integrative techniques could be used to identify genomic and metabolomic factors that distinguish subgroups of individuals with high PCa risk (Aim 2). Results are expected to substantially improve our ability to detect high risk individuals who would benefit from earlier or more intensive PCa screening across multi-ancestry populations and provide novel biological mechanisms to target for preventative measures, likely reducing PCa mortality and the number of indolent PCa cases treated unnecessarily.

受资助家长奖的项目摘要/摘要 前列腺癌 (PCa) 是美国男性癌症死亡的第二大原因，其中非洲男性 血统的 PCa 发病率和死亡率最高。虽然造成这种显着健康差异的原因 虽然尚未完全了解，但越来越多的证据表明遗传是一个促成因素。然而，大多数前列腺癌 研究重点是欧洲血统的男性，特别是全基因组关联研究（GWAS）， 这导致多基因模型对非欧洲人的预测价值较差。总体目标 这项研究的目的是确定导致多种男性前列腺癌风险的基因组和代谢组因素。 祖先群体。在该奖项的 R00 阶段，Darst 博士将启动一项新的研究，适用于 综合技术研究影响 PCa 风险的基因组和代谢组学因素。这将 直接建立在 K99 时期接受的研究和培训的基础上。她将识别基因调控 可能与多祖先人群中 PCa 风险存在因果关系和/或表明的代谢物 潜在的新遗传风险位点（目标 1）。这将需要开发一个大型的多祖先代谢组学 插补小组并对每个代谢物和 GWAS 总结执行两个样本孟德尔随机化 来自大型且多样化的实用联盟的统计数据。使用来自 872 名非洲裔美国男性的子集 多种族队列 (MEC) 和前列腺癌、肺癌、结直肠癌和卵巢癌 (PLCO) 癌症筛查试验， Darst 博士将研究 PCa 遗传风险所涉及的生物学机制，通过多种方法测量 祖先多基因风险评分，代谢物可以介导遗传因素对整体和 侵袭性前列腺癌，以及是否可以使用综合技术来识别基因组和代谢组学因素 区分具有高 PCa 风险的个体亚组（目标 2）。预计业绩将大幅改善 我们有能力发现高风险个体，这些个体将受益于早期或更深入的前列腺癌筛查 多祖先群体并提供新的生物机制作为预防措施的目标，可能 降低 PCa 死亡率和不必要治疗的惰性 PCa 病例数量。