Metabolomic based approach to identify biomarkers of broccoli intake.

It is well-established that consumption of cruciferous and brassica vegetables has a correlation with reduced rates of many negative health outcomes. There is an increased interest in identifying food intake biomarkers to address limitations related to self-reported dietary assessment. The study aims to identify biomarkers of broccoli intake using metabolomic approaches, examine the dose-response relationship, and predict the intake by multimarker panel. Eighteen volunteers consumed cooked broccoli in A-Diet Discovery study and fasting and postprandial urine samples were collected at 2, 4 and 24 hours. Subsequently the A-Diet Dose-response study was performed where volunteers consumed different portions of broccoli (49, 101 or 153 g) and urine samples were collected at the end of each intervention week. Urine samples were analysed by H-NMR and LC-MS. Multivariate data analysis and one-way ANOVA were performed to identify discriminating biomarkers. A panel of putative biomarkers was examined for its ability to predict intake through a multiMarker model. Multivariate analysis revealed discriminatory spectral regions between fasting and fed metabolic profiles. Subsequent time-series plots revealed multiple features increased in concentration following the consumption. Urinary -methyl cysteine sulfoxide (SMCSO) increased as broccoli intake increased (0.17-0.24 μM per mOSM per kg, < 0.001). Similarly from LC-MS data genipin, dihydro-β-tubaic acid and sinapic acid increased with increasing portions of intake. A panel of 8 features displayed good ability to predict intake from biomarker data only. In conclusion, urinary SMCSO and several LC-MS features appeared as potentially promising biomarkers of broccoli consumption and demonstrated dose-response relationship. Future work should focus on validating these compounds as food intake biomarkers.