An understanding of causal relations between diet and health is hindered by the lack of robust biological markers of food exposure (1)
.
The rapid development of metabolomics technology offers opportunity for the identification of urine biomarkers for the intake of a
range of foods of high public health importance (2), (3)
. Using high mass resolution mass spectrometry and machine learning data analysis,
we have discovered potential urinary biomarkers in controlled clinical studies with a range of analytical techniques (2)
. To have
utility for population monitoring, we aim to validate biomarker performance in free-living individuals using urine samples collected in
the home with a minimal impact on normal daily activities.
Two complementary multiple reaction monitoring (MRM) routines using triple quadrupole mass spectrometry (QQQ-MS) have
been developed to quantify concurrently dietary exposure biomarkers of more than 20 foods of high public health importance in
the UK. MRM quantification of metabolite levels in spot urines collected either before bed time or a first morning void identified
a sub-set of potential biomarkers that demonstrated robust linkage with reported dietary intake (examples in Table 1). Figure 1
demonstrates the ability of selected biomarkers to report exposure in relation to muscle meat intake from lunch time to bedtime
(Beefburger; 106gm, Chicken breast; 130gm; Processed Ham; 40·5 gm) in 6 free-living individuals. Anserine was strongly, and specifically,
associated with poultry intake, whilst the urinary outputs of 3-methyl histidine and carnosine reflect striated muscle intake,
with levels substantially reduced when meals contain lower quality, and processed, meats with reduced levels of striated muscle
content.