Abstract PO-142: Development of Empirical Dietary Inflammatory Pattern (EDIP) scores with different food groups and biomarkers

Abstract

Abstract Background: The empirical dietary inflammatory pattern (EDIP) is a hypothesis- driven dietary pattern used to assess the inflammatory potential of diet in the US population. It is usually composed of food groups obtained from a food-frequency questionnaire. Methods: EDIP scores were calculated for 4 models from 24hr recalls reported by 67 women noncancer controls that had signed an informed consent prior to participation. The Luminex Human Chemokine Multiplex Assay was used to measure 11 chemokines and cytokines. As seen in previous studies, we first derived a model, EDIP-Limited (EDIP-L), by entering 18 food groups in reduced rank regression models followed by a multivariable regression analysis to identify a dietary pattern that predicts concentrations of two inflammatory biomarkers: IL-6 and TNF-a. We derived another EDIP score using a new model, EDIP-All Inclusive (EDIP-AI), which included the same 18 food groups to predict all 11 biomarkers. Lastly, we developed two other EDIP models. EDIP-Limited New (EDIP-LN) used 14 new food groups derived from the same 24hr recalls, only predicting IL-6 and TNF-a. EDIP-All New (EDIP-AN) used those 14 food groups with all 11 biomarkers. Results: In this study, we optimize models for EDIP and report the differences in EDIP scores based on the inflammatory biomarkers and food groups used in analysis. Briefly, the components of EDIP-L were not significant. After including all the biomarkers, the components of EDIP-AI were: “fruit juice” (p = 0.0009), “snacks” (p = 0.0008), “leafy green vegetables” (p = 0.0074), “low-energy beverages” (p = 0.0098), “red meat” (p = 0.0038), “fruit” (p = 0.0002) and “whole wheat grains” (p = 0.0138). Similarly, after reorganizing our food items into 14 food groups, the components of EDIP-LN were not significant. However, components of EDIP-AN were: “fruit juice” (p = 0.0107), “snacks” (p = 0.0116) and “fruit” (p = 0.0026). Conclusions: Findings demonstrate the EDIP scores differ based on the inflammatory biomarkers and food groups used in the analysis on the same noncancer controls. Depending on the methods used, an individual’s diet may be considered more pro- or anti-inflammatory. This study provides insight into the inflammatory potential of an individual’s diet and the factors that may affect how we calculate this potential. Citation Format: Emma Guyonnet, Millicent Amankwah, Yalei Chen, Rachel Martini, Melissa Davis, Lisa Newman. Development of Empirical Dietary Inflammatory Pattern (EDIP) scores with different food groups and biomarkers [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-142.