Global metabolomics profiling, dietary factors, and colorectal cancer risk in the NIH-Consortium of Metabolomics Studies (COMETS)

摘要 结直肠癌(CRC)的患病率在全球范围内持续上升，目前仍居世界第三位。 在美国被普遍诊断为癌症。加强对结直肠癌病因学的理解对于 制定量身定制的风险预测方法。代谢组学是对小分子代谢物的综合研究，是一种 寻找结直肠癌病因学生物标志物的有效途径。代谢组学分析联合应用 有关膳食摄入量的信息可用于确定结直肠癌的客观膳食生物标志物。 然而，预测结直肠癌的精确代谢生物标记物还没有找到。到目前为止，还没有客观的饮食习惯 结直肠癌风险的生物标志物和饮食与结直肠癌之间关系的生物学基础仍然很差 明白了。 拟议工作的目标是调查代谢物与结直肠癌风险的关联，并增强 我们对饮食与结直肠癌之间潜在生物学关系的理解。为了实现这一目标，我们将使用 三个最先进的实验室使用预诊断生成的现有全球代谢组学数据 来自美国、欧洲和亚洲的8个独立的、预期的队列中的生物标本。这些井- 带注释和唯一的数据集包括来自n=3,085个匹配病例对照对的数据 从而确保已确定的生物标记物的广泛普适性和临床适用性。数据是 整合在NIH资助的代谢组学研究联盟(COMET)中，与标准化和 经过验证的食物频率问卷(FFQ)以及流行病学和临床数据。我们会发现和 在n=1900人的发现集中验证新的血液代谢生物标记物对结直肠癌风险的影响(目标1) 配对病例对照。调查结果将在包括n=1,185的独立验证集中进行确认 配对病例对照。此外，我们将按性别、肿瘤位置和年龄进行分层分析。 诊断以提高我们对不同亚型结直肠癌病因的理解。使用所描述的 数据集，我们将发现并验证食物组与代谢物之间的相关性。我们将表演 对表现最好的饮食-代谢物相关性进行中介分析，以考察间接影响 通过代谢产物研究饮食对结直肠癌风险的影响(目标2)。拟议的研究具有很高的创新性，因为它使用了 严格的多步骤设计，首次采用了广泛的代谢生物标志物(n~381)和饮食 信息，来自具有高度特征化的生物样本队列和癌症前收集的问卷 因此，诊断可以防止反向因果关系。我们的跨学科团队在以下领域拥有丰富的经验 在癌症研究中使用代谢组学，并利用大量的初步数据。我们希望我们的 调查将发现和验证新的结直肠癌生物标志物，并加深我们对 饮食生物学在结直肠癌病因学中的潜在作用，从而解决明确界定的临床和公共卫生需求。

Summary The prevalence of colorectal cancer (CRC) continues to increase worldwide and it remains the third most commonly diagnosed cancer in the United States. An enhanced understanding of CRC etiology is essential to develop tailored risk prediction methods. Metabolomics, the comprehensive study of small metabolites, is a promising approach to discover etiological biomarkers for CRC. Metabolomics analysis in combination with information on dietary intake could be used for the identification of objective dietary biomarkers for CRC. However, precise metabolic biomarkers to predict CRC are missing. To date, there are no objective dietary biomarkers for CRC risk and the biology underlying the relationship between diet and CRC remains poorly understood. The goal of the proposed work is to investigate associations of metabolites with CRC risk and to enhance our understanding of the underlying biology of the diet-CRC relationship. To achieve this goal, we will use existing global metabolomics data generated in three state-of-the art laboratories using pre-diagnosis biospecimens from eight independent, prospective cohorts from the US, Europe, and Asia. These well- annotated and unique datasets include data from n=3,085 matched case-control pairs from diverse populations, and thus ensure broad generalizability and clinical applicability of identified biomarkers. Data are integrated in the NIH-funded Consortium of Metabolomics Studies (COMETS) together with standardized and validated food frequency questionnaires (FFQ), and epidemiologic and clinical data. We will discover and validate novel blood-based metabolic biomarkers for CRC risk (Aim 1) in a discovery set of n=1,900 matched case-control pairs. Findings will be confirmed in an independent validation set including n=1,185 matched case-control pairs. Additionally, we will perform stratified analyses by sex, tumor location, and age at diagnosis to advance our understanding of CRC etiology across distinct subtypes. Using the described datasets, we will discover and validate correlations of food groups with metabolites. We will perform mediation analysis for the top performing diet-metabolite correlations to investigate the indirect effect of diet on CRC risk through metabolites (Aim 2). The proposed research is highly innovative in that it uses a rigorous multi-step design, employs for the first time a broad set of metabolic biomarkers (n~381) and dietary information, from highly characterized cohorts with biospecimens and questionnaires collected before cancer diagnosis, thus, protecting against reverse causation. Our interdisciplinary team has extensive experience in using metabolomics in cancer research and leverages substantial preliminary data. We expect that our investigation will discover and validate novel CRC biomarkers and enhance our understanding of the underlying biology of diet in CRC etiology, thus addressing a clearly defined clinical and public health need.