Identification and Reproducibility of Plasma Metabolomic Biomarkers of Habitual Food Intake in a US Diet Validation Study

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.

Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study

“…Reproducibility of the 513 unique metabolites over six months was good for a large proportion, with 28% of metabolites with an ICC > 0.6. The comparisons of urinary dietary biomarkers identified in the present study with our previous findings in fasting plasma samples in the same study [13] revealed several overlapping food biomarkers identified in both blood and urine and many more putative biomarkers identified in urine for further evaluation. This study also provided important information on the reproducibility of the urinary biomarkers, which could facilitate their utilization in future clinical and epidemiological studies.…”

“…Several large metabolomics analyses conducted in cohort studies employing a cross-sectional study design have identified hundreds of potential biomarkers of habitual food intakes [6][7][8][9][10][11][12][13] or dietary patterns [14,15]. Our previous metabolomics analyses of blood samples from the Cancer Prevention Study-II (CPS-II) Nutrition Cohort [6] and CPS-3 [13] have identified more than 200 putative food-related metabolic markers, many of which replicated findings from other population and feeding studies. The most common metabolite class was xenobiotics, which were highly correlated with plant foods.…”

“…Playdon et al [11] identified more diet-metabolite correlations in urine than in blood and more than a third of the correlations found in blood were also found in urine with similar magnitude. We previously published findings of diet-related biomarkers identified in fasting plasma samples in the CPS-3 DAS [13]. Among 671 men and women with at least one fasting blood sample in the CPS-3 DAS, a total of 677 diet-metabolite associations were identified (238 metabolites were associated with 76 food groups/items).…”

“…We previously published results on biomarkers of food intake from fasting plasma samples and their reproducibility over six months from the CPS-3 Diet Assessment Substudy (DAS), a 12-month diet validation study [13]. In the present study, we extended our previous research to urine by utilizing the resources from the CPS-3 DAS including the post-study FFQ, repeated 24 h diet recalls (24HRs) and two 24 h urine samples collected six months apart.…”

“…Metabolomics has shown great promise for identifying novel dietary biomarkers from human blood and urine samples in both cross-sectional and feeding studies [5]. Several large metabolomics analyses conducted in cohort studies employing a cross-sectional study design have identified hundreds of potential biomarkers of habitual food intakes [6][7][8][9][10][11][12][13] or dietary patterns [14,15]. Our previous metabolomics analyses of blood samples from the Cancer Prevention Study-II (CPS-II) Nutrition Cohort [6] and CPS-3 [13] have identified more than 200 putative food-related metabolic markers, many of which replicated findings from other population and feeding studies.…”