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.

measured meat intake. A, the means and 95% confidence intervals (CI) of red meat consumption measured by (7dDD) in quintiles of the derived red meat metabolite score (139 metabolites) in the exploratory set in the EPIC-Norfolk study (n=11,432); B, the means and 95% CI of processed meat consumption measured by 7dDD in quintiles of the processed meat metabolite score (82 metabolites) in the exploratory set in the EPIC-Norfolk study (n=11,432); C, the means and 95% CI of poultry consumption measured by 7dDD in quintiles of the poultry metabolite score (139 metabolites) in the exploratory set in the EPIC-Norfolk study (n=11,432); D. the correlations matrix for consumption of types of meat (red meat, processed meat and poultry) measured by 7dDD and measured by derived metabolite scores in the validation set in the EPIC-Norfolk study (n=853). show the chromatogram of a compound after tofu intake and pork intake separately in the same participant. Isotope pattern was used as one indicator of the peak quality. The vertical lines represent the detected intensities of compounds. The boxes show the expected peaks. The plots indicate that high intensity compounds usually match very well with the expected isotope pattern. Column 5 shows the chromatogram of a compound in several samples of plasma after pork intake. It shows the variability of peak shapes and intensities (the variation of intensity of metabolites is reported in the boxplots in Supplementary Incident cases were defined either by hospital admissions data or death certificate.

Supplementary Table 1. The definition of non-communicable diseases outcomes in the exploratory analyses for the association
Incident stomach cancer ICD-9 codes: 151; ICD-10 codes: C16 Incident cases were defined either by hospital admissions data or death certificate.
All-cause mortality All-cause mortality Mortality from all causes was defined from death certificates.

prevalent cases for exclusion
Prevalent coronary heart disease was defined by a self-reported history of either angina or myocardial infarction.
Prevalent stroke was defined based on a self-reported history of stroke (any kind) by a doctor.
Prevalent stroke was defined based on a self-reported history of stroke (any kind) by a doctor.
We defined prevalent atrial fibrillation (AF) by self-reported intake of drugs that were used for treatment of AF in clinical practice at the time of the baseline survey (digitalis or vitamin K antagonists; PMID 25059930).
We defined prevalent heart failure by self-reported intake of drugs that were recommended for treatment of heart failure, namely loop diuretics in combination with digitalis or angiotensin-converting enzyme inhibitors (PMID 21835284).
Prevalent liver disease was defined based on self-reported diagnosis of any liver disease by a doctor.
Prevalent cases were defined based on a self-reported history of any cancer.
Prevalent cases were defined based on a self-reported history of any cancer.
outcomes in the exploratory analyses for the association between red meat metabolite score and health outcomes Prevalent cases were defined based on a self-reported history of any cancer.