Abstract
Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet–metabolite associations were examined by Pearson’s partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet–metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46–0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies.
Highlights
Self-reported diet assessment tools such as food frequency questionnaires (FFQs) have long been used to assess habitual diet in population studies
With repeated FFQs, 24-h diet recall (24HR) and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study
We observed a greater number of associations in the current study than in our previous study in the Cancer Prevention Study II (CPS-II) Nutrition Cohort [8], probably because in the Cancer Prevention Study-3 (CPS-3), the FFQ was collected in closer proximity to blood draw, and using an average of two blood samples likely better captured usual metabolite levels during the year
Summary
Self-reported diet assessment tools such as food frequency questionnaires (FFQs) have long been used to assess habitual diet in population studies. Such methods are subject to random and systematic measurement errors that could lead to underestimated diet–disease risk estimates and inconsistent findings in nutritional epidemiological studies [1]. Recovery dietary biomarkers can be used to estimate absolute intake (e.g., 24-h urinary nitrogen for protein intake) [2,3,4], and concentration biomarkers and predictive biomarkers can be used as stand-alone risk factors for disease outcomes, and to correct for measurement errors of a FFQ [5,6]. Promising tools for diet assessment, the few established dietary biomarkers are primarily nutrient-based, and there is great potential and need for robust food-based biomarkers.
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