African
American (AA) smokers are at a higher risk of developing
lung cancer compared to whites. The variations in the metabolism of
nicotine and tobacco-derived carcinogens in these groups were reported
previously with the levels of nicotine metabolites and carcinogen-derived
metabolites measured using targeted approaches. While useful, these
targeted strategies are not able to detect global metabolic changes
for use in predicting the detrimental effects of tobacco use and ultimately
lung cancer susceptibility among smokers. To address this limitation,
we have performed global untargeted metabolomics profiling in urine
of AA and white smokers to characterize the pattern of metabolites,
identify differentially regulated pathways, and correlate these profiles
with the observed variations in lung cancer risk between these two
populations. Urine samples from AA (
n
= 30) and white
(
n
= 30) smokers were used for metabolomics analysis
acquired in both positive and negative electrospray ionization modes.
LC-MS data were uploaded onto the cloud-based XCMS online (
) platform for retention time correction, alignment, feature detection,
annotation, statistical analysis, data visualization, and automated
systems biology pathway analysis. The latter identified global differences
in the metabolic pathways in the two groups including the metabolism
of carbohydrates, amino acids, nucleotides, fatty acids, and nicotine.
Significant differences in the nicotine degradation pathway (cotinine
glucuronidation) in the two groups were observed and confirmed using
a targeted LC-MS/MS approach. These results are consistent with previous
studies demonstrating AA smokers with lower glucuronidation capacity
compared to whites. Furthermore, the
d
-glucuronate degradation
pathway was found to be significantly different between the two populations,
with lower amounts of the putative metabolites detected in AA compared
to whites. We hypothesize that the differential regulation of the
d
-glucuronate degradation pathway is a consequence of the variations
in the glucuronidation capacity observed in the two groups. Other
pathways including the metabolism of amino acids, nucleic acids, and
fatty acids were also identified, however, the biological relevance
and implications of these differences across ethnic groups need further
investigation. Overall, the applied metabolomics approach revealed
global differences in the metabolic networks and endogenous metabolites
in AA and whites, which could be used and validated as a new potential
panel of biomarkers that could be used to predict lung cancer susceptibility
among smokers in population-based studies.