Fred Tabung

PhD, MSPH

The Ohio State University

Assistant Professor

IDATA (Learn more about this study)

IDATA-77

Aug 15, 2024

Metabolomics profile of an insulinemic dietary pattern and colorectal cancer risk in phenotypically and geographically diverse global populations

Overview: We are submitting this analysis proposal to use dietary, and metabolomics data from IDATA. The proposal is part of a COMETS consortium project with multiple cohorts including PLCO and NIH-AARP. Cohorts contribute data to different aims. The proposed metabolomics work in IDATA will support a larger effort looking at both EDIH (diet-only based on FFQ data with cancer incidence in cohort studies and with metabolomics (EDIH metabolomics profile score) in IDATA and other nested studies. EDIH=Empirical Dietary Inex for Hyperinsulinemia dietary pattern.

Background: Despite improvements in early screening and management of pre-cancerous lesions, there has been a concerning increase in sporadic colorectal cancer (CRC) incidence among young adults (<50 years), especially men, and CRC remains a huge public health burden among all population groups. The etiology is unknown, but strong birth cohort effects suggest that recent changes in exposures like diet may play a role. Diet likely drives etiology of CRC through several biological processes, including insulin signaling.1,2 We developed the hypothesis-oriented empirical dietary index for hyperinsulinemia (EDIH)3 that represents the pattern of foods consumed as part of a whole diet that influences circulating c-peptide, a marker of β-cell secretory activity4 associated with CRC risk.5-7 A low EDIH score, associated with lower c-peptide, is more predictive of disease risk and prognosis (including CRC)1,2,8 than conventional dietary patterns.9-11 The EDIH nutrient profile adheres to a healthy diet (e.g. high in carbohydrates from wholegrains, fiber and phytochemicals, low in total/saturated fat). Our preliminary data reveal that combining and balancing foods in the diet to lower insulin hypersecretion provides an opportunity for CRC prevention. EDIH concurs with current dietary recommendations for CRC prevention from key organizations like the American Cancer Society12 but refines the emphasis on specific food combinations for optimization of relevant biomarkers.

Summary: CRC remains a significant cause of morbidity and mortality globally, with diet being an important driver. With the contribution of the AARP cohort and IDATA subcohort, COMETS will enable us to conduct a study of dietary pattern biomarkers and CRC with unprecedented power. We expect to identify metabolite profiles influenced by the interaction of diet with insulin metabolism and other related biological pathways that drive CRC etiology, and to identify population subgroups for whom an anti-insulinemic diet may be most effective for CRC prevention.

Our aims are to
(1) replicate EDIH-CRC associations in heterogeneous populations;
(2) identify how EDIH influences whole-body metabolism;
(3) determine if gene polymorphisms related to insulinemia modify observed associations.

Aim 2: for this aim, we will include 718 IDATA participants with metabolomics data and dietary data measured via food frequency questionnaire (FFQ) at baseline and at 6 months. We will calculate EDIH scores using FFQ data.

Aim 2 analysis: We will leverage the metabolomics data measured at two timepoints (baseline and 6 months) and calculate an average measure to account for within-person variance. We will then use elastic net regression to identify the metabolomics profile of the EDIH dietary pattern in IDATA and construct an integrated EDIH metabolite index score representing the metabolic insulinemic potential of the diet. We will evaluate associations of individual metabolites and the EDIH metabolite profile score with CRC risk using multivariable-adjusted logistic regression analysis in cohorts with both metabolomics and CRC data.