Identification of 102 Correlations between Serum Metabolites and Habitual Diet in a Metabolomics Study of the Prostate, Lung, Colorectal, and Ovarian Cancer Trial

Abstract

Background: Metabolomics has proven useful for detecting objective biomarkers of diet that may help to improve dietary measurement. Studies to date, however, have focused on a relatively narrow set of lipid classes.

Objective: The aim of this study was to uncover candidate dietary biomarkers by identifying serum metabolites correlated with self-reported diet, particularly metabolites in underinvestigated lipid classes, e.g. triglycerides and plasmalogens.

Methods: We assessed dietary questionnaire data and serum metabolite correlations from 491 male and female participants aged 55-75 y in an exploratory cross-sectional study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Self-reported intake was categorized into 50 foods, food groups, beverages, and supplements. We examined 522 identified metabolites using 2 metabolomics platforms (Broad Institute and Massachusetts General Hospital). Correlations were identified using partial Pearson's correlations adjusted for age, sex, BMI, smoking status, study site, and total energy intake [Bonferroni-corrected level of 0.05/(50 × 522) = 1.9 × 10-6]. We assessed prediction of dietary intake by multiple-metabolite linear models with the use of 10-fold crossvalidation least absolute shrinkage and selection operator (LASSO) regression.

Results: Eighteen foods, beverages, and supplements were correlated with ≥1 serum metabolite at the Bonferroni-corrected significance threshold, for a total of 102 correlations. Of these, only 5 have been reported previously, to our knowledge. Our strongest correlations were between citrus and proline betaine (r = 0.55), supplements and pantothenic acid (r = 0.46), and fish and C40:9 phosphatidylcholine (PC) (r = 0.35). The multivariate analysis similarly found reasonably large correlations between metabolite profiles and citrus (r = 0.59), supplements (r = 0.57), and fish (r = 0.44).

Conclusions: Our study of PLCO participants identified many novel food-metabolite associations and replicated 5 previous associations. These candidate biomarkers of diet may help to complement measures of self-reported diet in nutritional epidemiology studies, though further validation work is still needed.

Keywords: biomarkers; dietary questionnaire; food; metabolites; metabolomics.

FIGURE 1

A–B. Gaussian graphical models of 2 clusters of diet-related metabolites measured in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Metabolites are depicted as hexagons, and pairs with an absolute value of conditional correlation >0.4 are connected by a line. Black lines represent positive conditional correlations. Gray lines represent inverse conditional correlations. Clusters with <8 metabolites not shown.

FIGURE 2

Correlations and 95% CIs between self-reported dietary intake and predicted intake based on metabolites and 10-fold crossvalidated LASSO regression in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Cruc. vegetables, cruciferous vegetables; LASSO, least absolute shrinkage and selection operator; o/y vegetables, orange/yellow vegetables; SSB, sugar sweetened beverage.