Mary Playdon

Ph.D., M.P.H.

University of Utah

Assistant Professor

PLCO (Learn more about this study)

PLCO-1067

Oct 18, 2022

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

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 identify the association of metabolites with CRC risk and to enhance our understanding of the underlying biology of the role of diet in CRC etiology. 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 are comprised of 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.