Uncovering Roles of Metabolites in Colorectal Cancer Etiology

项目总结 代谢紊乱或重新编程被认为是癌症的标志之一。几种常见的 代谢紊乱，如肥胖、2型糖尿病和血脂异常，都与结直肠癌有关。 (CRC)风险。随着代谢组学技术的进步，成百上千的代谢物可以 以一种不可知论的方式系统地衡量。一项精心设计的前瞻性代谢组学研究 癌症，新的风险相关生物标记物的识别将为癌症的病因学和 相关的生物途径。评估代谢物的传统研究费用高昂，而且可能存在偏差。 在观察性研究中经常遇到。人们越来越认识到，遗传因素 在确定许多代谢物的水平方面起着重要的作用。在此，我提出了一种经济高效的方法 系统评价血浆代谢物水平与结直肠癌风险之间的关系。我也是 结合分子/遗传流行病学、因果推断、癌症生物学和 新陈代谢和群体遗传学在这方面的应用实现了我的研究和职业目标所述 下面。提出的研究由四个目标组成。在目标1中，我将建立模型来预测代谢物 使用现有代谢组学和来自公共数据库的高密度基因分型数据和可能的数据的水平 在范德比尔特生成。在目标2中，具有令人满意的预测准确性和符合其他标准的代谢物 将在三个大型CRC财团中进行评估，总样本量约为80,900例 115,000名对照，评估基因预测的代谢物水平与结直肠癌风险的关系。在……里面 在这个奖项的R00阶段，我将与其他调查人员合作，然后进行嵌套案件- 一项对照研究，通过直接测量这些代谢物来确认从电子分析中鉴定的多达10种代谢物 使用在三个大型队列研究中收集的诊断前血浆的代谢物(目标3)。最后，我将评估 代谢产物对包括肥胖在内的生活方式因素之间关系的潜在中介作用 (体重指数和腰臀比)、体力活动、红肉摄入量、蔬菜摄入量、健康饮食 指数和CRC风险(目标4)。这项创新性的研究将首次系统地寻找小说 使用基因工具检测结直肠癌风险的代谢物生物标记物，并通过直接 测量。此外，这项研究将扩大对引起CRC的潜在机制的理解。 拟议的职业发展奖将帮助我建立遗传和分子方面的高级知识。 流行病学、癌症代谢、结直肠癌病因学和风险评估，以过渡到成功 独立调查员。

PROJECT SUMMARY Metabolic perturbation or reprogramming is considered one of the hallmarks of cancer. Several common metabolic disorders, such as obesity, type 2 diabetes, and dyslipidemia, have been linked to colorectal cancer (CRC) risk. With the advances in the techniques of metabolomics, hundreds to thousands of metabolites can be systematically measured in an agnostic manner. For a well-designed prospective metabolomic study of cancer, the identification of novel risk-associated biomarkers will shed new lights on the cancer etiology and related biological pathways. Conventional studies evaluating metabolites are costly and may suffer from biases commonly encountered in the observational studies. It has been increasingly recognized that genetic factors play a significant role in determining the levels of many metabolites. Herein, I propose a cost-efficient approach to systematically evaluate the associations between plasma levels of metabolites and CRC risk. I also incorporate didactic training on molecular/genetic epidemiology, causal inference, cancer biology and metabolism, and population genetics in this application to accomplish my research and career goals described below. The proposed research is composed of four aims. In aim 1, I will build models to predict metabolite levels using existing metabolomics and high-density genotyping data from a public database and possible data generated at Vanderbilt. In aim 2, metabolites with satisfactory prediction accuracy and meeting other criteria will be evaluated in three large-scale CRC consortia with a combined sample size of ~80,900 cases and 115,000 controls to assess the associations of genetically predicted metabolite levels with CRC risk. In collaboration with other investigators during the R00 phase of this award, I will then conduct a nested case- control study to confirm up to ten metabolites identified from in silico analysis by direct measurement of these metabolites using pre-diagnosis plasma collected in three large cohort studies (aim 3). Finally, I will evaluate the potential mediation effects of metabolites for the associations between lifestyle factors including obesity (body mass index and waist-hip-ratio), physical activity, red meat intakes, vegetable intakes, healthy eating index and CRC risk (aim 4). This innovative study will, for the first time, systematically search for novel metabolite biomarkers for CRC risk using genetic instruments and validate the identified associations by direct measurement. In addition, this study will expand the understanding of underlying mechanisms causing CRC. The proposed career development award will help me building advanced knowledge of genetic and molecular epidemiology, cancer metabolism, and CRC etiology and risk assessment to transition to a successful independent investigator.