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

基本信息

批准号：
10547987
负责人：
Burcu Frances Darst
金额：
$ 24.9万
依托单位：
FRED HUTCHINSON CANCER CENTER
依托单位国家：
美国
项目类别：
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/10547987
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 Environmental Risk Factor Ethnic group European Genetic Genetic Risk Genetic Variation Genomics Goals Health Heritability Incidence Individual Indolent Investigation Latino Lead 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 Research Training Risk Risk Assessment Sampling Screening for Prostate Cancer Study of serum Subgroup Systems Biology Techniques Training Variant anticancer research base cancer epidemiology cancer health disparity case control cohort flexibility genetic epidemiology genetic variant genome wide association study genome-wide health disparity high risk 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

项目摘要

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.

项目概要/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未知，有证据表明遗传因素的作用，并且环境因素很可能起到作用出色地。然而，大多数前列腺癌研究都集中在欧洲血统的男性身上，特别是全基因组研究关联研究（GWAS），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。这项研究的总体目标是确定有助于多种族男性的 PCa 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 博士将开发一种新颖的变体选择算法来识别全基因组数据中的信息变异（目标 1）。然后她将构建一个多种族全基因组 PRS 使用大型多种族 PCa 样本（实用，N=237,380）（目标 2）。该 PRS 将在总体上制定 PCa（目标 1A）、侵袭性 PCa（目标 2B）和 PCa 发病年龄（目标 2C），预计将导致改善与约 150 个已知变体的 PRS 以及仅使用欧洲人开发的 PRS 相比，预测价值。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，通过课程、研讨会、会议以及她的专家指导团队提供的指导。在 R00 阶段，Darst 博士将启动新的研究领域应用综合技术来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 时期接受的研究和培训的基础上。她将鉴定可能与多种族 PCa 存在因果关系的基因调控代谢物人口（目标 3）。这将需要开发一个大型的多种族代谢组学插补小组并使用随后的荟萃分析汇总统计数据，为每个研究开发全基因组多种族 PRS 代谢物。这些 PRS 将用于将代谢组学归入 PACTICAL 联盟。代谢组—— 然后将进行广泛关联研究，以确定估算的或基因调控的代谢水平，可以预测总体 PCa 或侵袭性 PCa。使用来自 1,186 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，Dr. Darst 将研究可能介导遗传因素影响的代谢物，包括 Aim 的 PRS 2，关于整体和积极的 PCa（目标 4a）。她还将使用综合技术来识别基因组和区分 PCa 高风险个体亚组的代谢组学因素（目标 4b）。结果是预期的大幅提高我们发现高风险个体的能力，这些人将从早期或更密集的治疗中受益对多种族人群进行 PCa 筛查，并提供新的生物学机制来进行预防措施，可能会降低 PCa 死亡率和不必要治疗的惰性 PCa 病例数量。