Assessing the utility of metabolite profiles of human serum, urine and saliva for determining dietary intake

Abstract

The work undertaken in this thesis aimed to use a combined NMR and MS-based metabolomics approach to discover and validate nutritional biomarkers in a cohort of Northern Irish older adults. Serum, urine and saliva samples from 96 participants of the NIDAS dietary validation sub-cohort of the NICOLA study were collected, together with detailed dietary information (food diaries) and biometric data. These samples were aliquoted and separately processed on both a Bruker 600MHz Ascent (1H NMR spectroscopy) and a Waters TQ-S (a triple quadrupole Mass Spectrometer) paired to an Acquity UPLC, the latter of which also employing 4 Biocrates p180 kits for targeted analysis. After adjusting for known confounders, twelve biomarkers of interest for single foods remained across the three biofluids, six of these in serum, four in urine and two in saliva. Of all these, a specific subset of circulating phosphatidylcholines associated with the intake of milk and dairy products, and a group of salivary amino acids and derivatives which strongly correlated with meat were the findings of highest interest. This same metabolomics data was then used to model two dietary scores measuring three key aspects of complex diets: dietary composition, grouped by k-means clustering; a modified FDSK-11 DDS score, which tracks dietary diversity; and the E-NRF score, which tracks the intake of seven key nutrients to encourage in an older population and three to limit. VIP (variable importance in projection) plots of these models showed consistently different features across groups, with higher levels of amino acids and choline-based compounds in lower scores and “unhealthier” clusters much higher in meat and sweet foods. However, these multivariate models also validated poorly, although the saliva-based OPLS-DA (Orthogonal Projections to Latent Structures Discriminant Analysis) models showed better visual separation and appeared to be less overfit. Together, these results show the benefits of a synergistic approach using multiple instruments towards biomarker discovery, the usefulness of metabolomics-based biomarkers as additional tools for the betterment of nutritional epidemiology studies, and the value of saliva as an under-utilized biofluid in metabolomics. Future work should focus on the validation of these biomarkers and models in larger and more heterogenous cohorts, with a specific focus on the creation of metabolomics-based multivariate approaches to modelling complex dietary patterns with better cross-validation.

Date of Award	Dec 2022
Original language	English
Awarding Institution	Queen's University Belfast
Sponsors	Marie Sklodowska Curie COFUND & Northern Ireland Department for the Economy
Supervisor	Jayne Woodside (Supervisor) & Brian Green (Supervisor)