Identifying metabolomic profiles of inflammatory diets in postmenopausal women. Issue 5 (May 2020) - Tabung, Fred K.; Liang, Liming; Huang, Tianyi; Balasubramanian, Raji; Zhao, Yibai; Chandler, Paulette D.; Manson, JoAnn E.; Cespedes Feliciano, Elizabeth M.; Hayden, Kathleen M.; Van Horn, Linda; Clish, Clary B.; Giovannucci, Edward L.; et al.
Summary: Background: We previously showed that a food-based empirical dietary inflammatory pattern (EDIP) score is associated with circulating inflammatory biomarkers. Metabolomic profiling of inflammatory diets may therefore provide insights on mechanisms contributing to disease etiology and prognosis. We aimed to elucidate metabolites associated with inflammatory diets among postmenopausal women, utilizing a robust study design that incorporates independent discovery and validation datasets. Methods: This baseline cross-sectional investigation evaluated associations between continuous EDIP scores calculated from food frequency questionnaires and 448 log-transformed plasma metabolites as outcomes in multivariable-adjusted linear regression analyses. Metabolites were measured with liquid chromatography tandem mass spectroscopy. Metabolite discovery was conducted among 1109 Women's Health Initiative (WHI) Hormone Therapy trial participants and results were replicated in an independent dataset of 810 WHI Observational Study participants. Secondary analyses were stratified by standard body mass index (BMI, kg/m 2 ) categories. In discovery and replication datasets statistical significance was based on false-discovery rate adjusted P  < 0.05. Results: After adjusting for energy intake, BMI, physical activity, and other confounding variables, 23 metabolites were significantly associated with EDIP score in the discovery dataset. Of these, the following ten were replicated: trigonelline, caffeine, acethylamino-6-amino-3-methyluracil, 7-methylxanthine, 1, 7-dimethyluric acid, 3-methylxanthine, C18:3CE, glycine, associated with lower dietary inflammatory potential; whereas C52:3 triacylglycerol and linoleate associated with higher dietary inflammatory potential. Four of the ten were associated [glycine (inversely), caffeine, 1, 7-dimethyluric acid, C52:3 triacylglycerol, (positively)], with C-reactive protein levels. In secondary analyses, associations showed differences by BMI category. Four metabolites, related to coffee/caffeine metabolism were inversely associated among normal weight women, and 83 metabolites associated with EDIP among overweight/obese women, including 40 (48%) that were also associated with C-reactive protein. Conclusion: Metabolites associated with coffee/caffeine and lipid metabolism may reflect the inflammatory potential of diet. Potential differences by BMI and the linkage to disease outcomes, require further study. Highlights: Diet may influence disease risk and progression through inflammation. The specific mechanisms involved are not fully understood. Metabolomic profiling of inflammatory diets may therefore provide insights. We identified and replicated 10 metabolites associated with diet-related inflammation. Metabolites associated with lipid metabolism may reflect diet-related inflammation.