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

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，与非洲男性一样 血统的前列腺癌发病率和死亡率最高。虽然造成这种显著健康差距的原因 都是未知的，有证据表明遗传因素有贡献，而且环境因素很可能像 井。然而，大多数PCA研究都集中在欧洲血统的男性身上，特别是全基因组 关联研究(GWAS)，这导致多基因模型在非 欧洲人。这项研究的首要目标是确定影响基因组和代谢的因素 多种族男性患前列腺癌的风险。促进构建全基因组多种族多基因风险评分 在这项研究的K99阶段，Darst博士将开发一种新的变体选择算法来识别 全基因组数据中的信息性变异(目标1)。然后，她将构建一个多种族的全基因组PR 使用大的多族裔PCA样本(实际，N=237,380)(目标2)。这项计划将在总体上得到发展 PCA(目标1A)、攻击性PCA(目标2B)和PCA发病年龄(目标2C)，预计将导致改善 与大约150个已知变种的PRS和仅使用欧洲人开发的PRS相比，具有预测价值。Dr。 达斯特在遗传流行病学方面的专业知识将与癌症流行病学的额外培训相辅相成， 先进的统计基因组学，以及通过课程作业、研讨会、 会议，以及由她的专家指导团队提供的指导。在R00阶段，Darst博士将启动一项 新的研究路线应用整合技术来研究基因组和代谢组合 影响PCA风险的因素。这将直接建立在K99期间所接受的研究和培训的基础上。 她将确定基因调控的代谢物，这些代谢物可能与多种族的前列腺癌有关 人口(目标3)。这将需要开发一个大型多民族代谢组学分配小组，并使用 随后的荟萃分析汇总统计，为每个被调查的人开发全基因组范围的多种族PR 代谢物。这些PR将被用于将代谢组学归因于实际的联合体。一种代谢体- 然后将进行广泛的关联研究，以确定被归因于或受基因调控的代谢物水平 是整体PCA或侵略性PCA的预测指标。使用来自美国的1186名非洲裔美国人 多种族队列(MEC)和前列腺癌、肺癌、结直肠癌和卵巢癌(PLCO)筛查试验，Dr。 达斯特将研究可能调节遗传因素影响的代谢物，包括来自AIM的prs 2、关于全面和积极的主成分分析(目标4a)。她还将使用综合技术来识别基因组和 区分前列腺癌高危人群的代谢因素(目标4b)。结果在意料之中 为了显著提高我们发现将从更早或更密集的治疗中受益的高危人群的能力 在多种族人群中进行前列腺癌筛查并提供新的生物学机制以预防为目标 这些措施可能会降低PCA的死亡率和不必要地治疗懒惰的PCA病例的数量。

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.