Development and validation of a metabolite score for red meat intake: an observational cohort study and randomized controlled dietary intervention

Abstract

Background: Self-reported meat consumption is associated with disease risk but objective assessment of different dimensions of this heterogeneous dietary exposure in observational and interventional studies remains challenging.

Objectives: We aimed to derive and validate scores based on plasma metabolites for types of meat consumption. For the most predictive score, we aimed to test whether the included metabolites varied with change in meat consumption, and whether the score was associated with incidence of type 2 diabetes (T2D) and other noncommunicable diseases.

Methods: We derived scores based on 781 plasma metabolites for red meat, processed meat, and poultry consumption assessed with 7-d food records among 11,432 participants in the EPIC-Norfolk (European Prospective Investigation into Cancer and Nutrition-Norfolk) cohort. The scores were then tested for internal validity in an independent subset (n = 853) of the same cohort. In focused analysis on the red meat metabolite score, we examined whether the metabolites constituting the score were also associated with meat intake in a randomized crossover dietary intervention trial of meat (n = 12, Lyon, France). In the EPIC-Norfolk study, we assessed the association of the red meat metabolite score with T2D incidence (n = 1478) and other health endpoints.

Results: The best-performing score was for red meat, comprising 139 metabolites which accounted for 17% of the explained variance of red meat consumption in the validation set. In the intervention, 11 top-ranked metabolites in the red meat metabolite score increased significantly after red meat consumption. In the EPIC-Norfolk study, the red meat metabolite score was associated with T2D incidence (adjusted HR per SD: 1.17; 95% CI: 1.10, 1.24).

Conclusions: The red meat metabolite score derived and validated in this study contains metabolites directly derived from meat consumption and is associated with T2D risk. These findings suggest the potential for objective assessment of dietary components and their application for understanding diet-disease associations.The trial in Lyon, France, was registered at clinicaltrials.gov as NCT03354130.

Keywords: biomarker; diabetes; meat; metabolomics; prediction.

© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.

Figures

FIGURE 1

Flowchart for the overall analytic approach for development and validation of the meat metabolomics score. *The visualization simplifies the design of the RCT because only 2 out of 5 arms are shown. EPIC-Norfolk, European Prospective Investigation into Cancer and Nutrition-Norfolk; IARC, International Agency for Research on Cancer; RCT, randomized controlled trial; T2D, type 2 diabetes.

FIGURE 2

Coefficients of metabolites with self-reported red and processed meat and poultry intake: the European Prospective Investigation into Cancer and Nutrition-Norfolk study (n = 11,432). Metabolites were classifed by metabolic pathway (16). The colors represent the coefficients (weights) of each metabolite in each metabolite score; red means positive association and blue means negative association. *The metabolite was annotated based on in silico predictions, which indicates the compound has not been confirmed based on a standard but its identity is confident. GPA, glycerol-3-phosphate; GPC, glycerophosphocholine; GPE, glycerophosphoethanolamine; GPI, glycosylphosphatidylinositol; HODE, hydroxyoctadecadienoic acid.

FIGURE 3

Volcano plot of candidate metabolites for red meat intake (n = 139) against self-reported red meat intake and comparison of the red meat metabolite score across different categories of meat consumer groups: the European Prospective Investigation into Cancer and Nutrition-Norfolk study (n = 11,432). (A) The top 5 metabolites with the strongest association with self-reported red meat intake after adjustment for age and sex are annotated in the volcano plot. *The metabolite was annotated based on in silico predictions, which indicates the compound has not been confirmed based on a standard but its identity is confident. (B) A red meat nonconsumer was defined as a participant with red meat consumption equal to 0 (n = 1569) and a red meat consumer was a participant with red meat consumption > 0 (n = 9863). Participants who reported consuming a vegetarian diet, other diet, or no special diet were identified from self-reported questionnaires. GPC, glycerophosphocholine; GPE, glycerophosphoethanolamine.

FIGURE 4

The associations of the red meat metabolite score and self-reported red meat intake with incident T2D in a nested case-cohort study and exploratory analyses of multiple other health outcomes in the EPIC-Norfolk study. Regression model 1 adjusted for age and sex; regression model 2 adjusted for the following potential confounders: age, sex, education, smoking status, alcohol drinking, alcohol drinking squared, BMI, BMI squared, and dietary factors (consumption of fruits, vegetables, fatty fish and white fish, sugar-sweetened beverages, dairy, legumes, nuts, eggs, and total energy intake). Supplemental Table 1 reports the definition of incident cases and exclusion of prevalent cases. *The association with incident T2D was conducted in a nested case-cohort study in the EPIC-Norfolk study; associations with other exploratory health outcomes were conducted in the EPIC-Norfolk study after exclusion of participants involved in the case-cohort study. EPIC-Norfolk, European Prospective Investigation into Cancer and Nutrition-Norfolk; Mscore, red meat metabolite score; T2D, type 2 diabetes; 7dDD, 7-d diet diary.