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Principal Investigator
Erikka Loftfield
Ph.D., M.P.H.
National Cancer Institute
Position Title
Research Fellow
About this CDAS Project
PLCO (Learn more about this study)
Project ID
Initial CDAS Request Approval
Mar 20, 2020
Biomarkers of Exposure and Response to Coffee Intake
The COnsortium of METabolomics Studies (COMETS) Steering Committee approved the project "Biomarkers of Exposure and Response to Coffee Intake" in 2019. The overall objective of this consortium project is to identify a panel of metabolites that can serve as robust biomarkers of coffee intake for measurement in population-based studies and to explore the metabolic impact of coffee drinking. In brief, coffee is a complex mixture of more than 1,000 bioactive compounds, many of which have anti-oxidant capacity including polyphenols, diterpenes, melanoidins and various minerals. Coffee has been shown to have anti-inflammatory and insulin-sensitizing properties and is associated with lower levels of inflammatory cytokines, and C-peptide. Due to these broad potential mechanisms and wide-ranging bioactive compounds, coffee drinking has been investigated in relation to a variety of health disorders, with beneficial effects consistently reported for metabolic syndrome and diabetes, liver and digestive disorders, cardiovascular disease, some cancers and overall mortality. Understanding the biological basis for the relationship between coffee and chronic disease is important because it could inform on underlying biological processes and provide clues on potential preventive pathways. Endogenous factors such as metabolic variability and the gut microbiome will affect how coffee is metabolized and potentially the bioactivity of its constituent compounds. Studies that can identify the components of coffee that are related to different disease endpoints and that evaluate the metabolic impact of coffee drinking will likely help elucidate potential underlying mechanisms. For this purpose, metabolomics has been utilized to identify biomarkers associated with coffee intake. For example, using an untargeted metabolomics approach in the European Prospective Investigation into Cancer (EPIC) cohort, coffee compounds and metabolites were identified with strong correlations observed between coffee drinking and the alkaloid trigonelline and caffeine metabolites paraxanthine and AAMU, as well as cyclo(prolyl-valyl) and cyclo(isoleucyl-prolyl)(Rothwell J, et al., Mol Nutr Food Res. 2019). These findings were consistent with an analysis of about 250 colorectal cancer cases and controls from the PLCO cohort (Guertin, Loftfield, et al., AJCN 2015) which also reported high correlations between coffee drinking and levels of trigonelline. Confirmation of these findings is now needed from large-scale analyses that capture variability in coffee drinking habits and in different populations. Further, to understand the potential biological pathways that underlie the link between coffee and various disease endpoints, robust analyses of the association of coffee drinking with endogenous metabolites and metabolic factors are needed.

Multiple studies nested in the PLCO cohort have now used Metabolon's Discovery metabolomics platform to generate metabolomics data. I am proposing to participate in the approved COMETS project described herein using available metabolomics, dietary (DQX), demographic, lifestyle, and mortality data from the PLCO study. All PLCO analyses would be run at NCI and summary data would be shared with Marc Gunter of IARC who is the PI of the COMETS coffee project.

Aim 1a: To identify serologic exogenous biomarkers of coffee intake (e.g., metabolites categorized in the super-pathways: 1) xenobiotic degradation and metabolism; 2) metabolism of cofactors and vitamins) suitable for measurement in epidemiological studies using a metabolomic approach.

Aim 1b: To investigate the "metabolic fingerprint" of coffee drinking through identification of endogenous metaboiltes that vary significantly between coffee drinkers and non-coffee drinkers.

Aim 2: To perform stratified analyses by sex, BMI, smoking status, caffeine-type, geographic region (e.g., North America, vs. Europe, vs. Asia), and fasting status to ascertain how these factors modify associations between coffee drinking and potential candidate biomarkers.

Aim 3: To explore associations of coffee drinking with metabolic markers (C-peptide, HbA1c, CRP, liver enzymes) that have been associated with chronic disease risk and overall mortality.

Aim 4: To investigate associations of coffee-associated metabolites and metabolic fingerprints with overall mortality.


Demetrius Albanes (Metabolic Epidemiology Branch, DCEG, NCI)
Rachael Stolzenberg-Solomon (Metabolic Epidemiology Branch, DCEG, NCI)
Steve Moore (Metabolic Epidemiology Branch, DCEG, NCI)
Linda Liao (Metabolic Epidemiology Branch, DCEG, NCI)
Neal D. Freedman (Metabolic Epidemiology Branch, DCEG, NCI)
Mary Playdon (University of Utah, Department of Nutrition and Integrative Physiology, Huntsman Cancer Institute, Cancer Control and Population Sciences Program)
Marc Gunter (IARC)