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: 10645105
• 负责人: Burcu Frances Darst
• 金额: $ 24.4万
• 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/10645105
• 关键词: African; African American; African ancestry; Age; Age of Onset; Aging; Algorithms; American; Asian; Biological; Cancer Etiology; Cessation of life; Complement; Complex; Data; Disease; Disparity; Environmental Risk Factor; Ethnic Origin; Ethnic Population; European; Exclusion; Genetic; Genetic Risk; Genetic Variation; Genomics; Goals; Health; Heritability; Incidence; Individual; Indolent; Investigation; Latino; Malignant neoplasm of prostate; Mediating; Mediation; Mentors; Meta-Analysis; Metabolic; Methods; Modeling; Outcome; Phase; Population; Predictive Value; Preventive measure; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; Research; Risk; Risk Assessment; Sampling; Screening for Prostate Cancer; Serum; Subgroup; Systems Biology; Techniques; Training; Variant; anticancer research; cancer epidemiology; cancer health disparity; cohort; flexibility; genetic epidemiology; genetic variant; genome wide association study; genome-wide; health disparity; high risk; high risk population; improved; insight; loss of function; men; metabolome; metabolomics; mortality; multi-ethnic; multiple omics; novel; polygenic risk score; predictive modeling; prostate cancer model; prostate cancer progression; prostate cancer risk; racial population; risk variant; screening; simulation; statistics; symposium

PROJECT SUMMARY/ABSTRACT 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 unknown, there is evidence of genetic contributions and it is likely that environmental factors contribute as well. 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 multiethnic men. To facilitate the construction of a genome-wide multiethnic polygenic risk score (PRS), in the K99 phase of this research, Dr. Darst will develop a novel variant selection algorithm to identify informative variants among genome-wide data (Aim 1). She will then construct a multiethnic genome-wide PRS using a large multiethnic PCa sample (PRACTICAL, N=237,380) (Aim 2). This PRS will be developed on overall PCa (Aim 1A), aggressive PCa (Aim 2B), and age of PCa onset (Aim 2C) and is expected to lead to improved predictive value compared to a PRS of ~150 known variants and to a PRS developed using Europeans only. Dr. Darst's expertise in genetic epidemiology will be complemented with additional training in cancer epidemiology, advanced statistical genomics, and cancer health disparities received through coursework, seminars, conferences, and guidance provided by her expert mentoring team. In the R00 phase, Dr. Darst will initiate a new line of research the 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 in multiethnic populations (Aim 3). This will require developing a large multiethnic metabolomics imputation panel and using subsequent meta-analysis summary statistics to develop genome-wide multiethnic PRS for each investigated metabolite. These PRS will be used to impute metabolomics into the PRACTICAL consortium. A metabolome- wide association study will then be performed to identify imputed, or genetically-regulated, metabolite levels that are predictive of overall PCa or aggressive PCa. Using a subset of 1,186 African American men from the Multiethnic Cohort (MEC) and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, Dr. Darst will investigate metabolites that could mediate the effects of genetic factors, including the PRS from Aim 2, on overall and aggressive PCa (Aim 4a). She will also use integrative techniques to identify genomic and metabolomic factors that distinguish subgroups of individuals with high PCa risk (Aim 4b). Results are expected to substantially improve our ability to detect high risk individuals who would benefit from earlier or more intensive PCa screening across multiethnic populations and provide novel biological mechanisms to target for preventative measures, likely reducing PCa mortality and the number of indolent PCa cases treated unnecessarily.

项目总结/摘要 前列腺癌（PCa）是美国男性癌症死亡的第二大原因，非洲男性是第二大原因。 有最高的PCa发病率和死亡率。虽然造成这种显著健康差距的原因 是未知的，有遗传贡献的证据，很可能是环境因素的贡献， 好.然而，大多数PCa研究都集中在欧洲血统的男性，特别是全基因组的男性。 关联研究（GWAS），这导致多基因模型在非遗传性疾病中的预测价值较差。 欧洲人这项研究的首要目标是确定基因组和代谢组学因素， 多种族男性中PCa的风险。促进全基因组多种族多基因风险评分的构建 (PRS)在这项研究的K99阶段，Darst博士将开发一种新的变异选择算法， 全基因组数据中的信息变异（Aim 1）。然后，她将构建一个多种族的全基因组PRS， 使用大型多种族PCa样本（实用，N= 237，380）（目标2）。本PRS将根据总体情况制定 PCa（Aim 1A）、侵袭性PCa（Aim 2B）和PCa发病年龄（Aim 2C），预计将导致改善 与约150种已知变体的PRS和仅使用欧洲人开发的PRS相比，预测值。博士 达斯特在遗传流行病学方面的专业知识将得到癌症流行病学方面的额外培训的补充， 先进的统计基因组学，以及通过课程，研讨会， 会议，并由她的专家指导团队提供指导。在R 00阶段，达斯特博士将启动一个 一条新的研究路线，应用综合技术研究基因组学和代谢组学的结合 影响PCa风险的因素。这将直接建立在K99期间接受的研究和培训的基础上。 她将确定遗传调节的代谢产物，这些代谢产物可能与多种族患者中的PCa有因果关系。 人口（目标3）。这将需要开发一个大型的多种族代谢组学估算小组，并使用 随后的荟萃分析汇总统计，为每个研究对象制定全基因组多种族PRS 代谢物。这些PRS将用于将代谢组学输入PRACTICAL联盟。代谢组- 然后将进行广泛关联研究，以确定插补的或遗传调节的代谢物水平， 是整体前列腺癌或侵袭性前列腺癌的预测指标。使用了一个由1,186名非洲裔美国人组成的子集， 多种族队列（MEC）和前列腺，肺，结直肠和卵巢（PLCO）癌症筛查试验，博士。 达斯特将研究可能介导遗传因素影响的代谢物，包括来自Aim的PRS 2、全面和积极的PCa（目标4a）。她还将使用综合技术来识别基因组和 代谢组学因素，区分个人亚组的高PCa风险（目的4 b）。结果预计 大大提高我们发现高危人群的能力，这些人将从早期或更密集的治疗中受益。 在多种族人群中进行PCa筛查，并提供新的生物学机制， 这些措施可能会降低PCa死亡率和不必要治疗的惰性PCa病例数量。