Urinary
Metabolomics Revealed Arsenic Internal Dose-Related
Metabolic Alterations: A Proof-of-Concept Study in a Chinese Male
Cohort
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Abstract
Urinary
biomonitoring provides the most accurate arsenic exposure
assessment; however, to improve the risk assessment, arsenic-related
metabolic biomarkers are required to understand the internal processes
that may be perturbed, which may, in turn, link the exposure to a
specific health outcome. This study aimed to investigate arsenic-related
urinary metabolome changes and identify dose-dependent metabolic biomarkers
as a proof-of-concept of the information that could be obtained by
combining metabolomics and targeted analyses. Urinary arsenic species
such as inorganic arsenic, methylarsonic acid, dimethylarsinic acid
and arsenobetaine were quantified using high performance liquid chromatography
(HPLC)-inductively coupled plasma-mass spectrometry in a Chinese adult
male cohort. Urinary metabolomics was conducted using HPLC-quadrupole
time-of-flight mass spectrometry. Arsenic-related metabolic biomarkers
were investigated by comparing the samples of the first and fifth
quintiles of arsenic exposure classifications using a partial least-squares
discriminant model. After the adjustments for age, body mass index,
smoking, and alcohol consumption, five potential biomarkers related
to arsenic exposure (i.e., testosterone, guanine, hippurate, acetyl-<i>N</i>-formyl-5-methoxykynurenamine, and serine) were identified
from 61 candidate metabolites; these biomarkers suggested that endocrine
disruption and oxidative stress were associated with urinary arsenic
levels. Testosterone, guanine, and hippurate showed a high or moderate
ability to discriminate the first and fifth quintiles of arsenic exposure
with area-under-curve (AUC) values of 0.89, 0.87, and 0.83, respectively; their combination
pattern showed an AUC value of 0.91 with a sensitivity of 88% and
a specificity of 80%. Arsenic dose-dependent AUC value changes were
also observed. This study demonstrated that metabolomics can be used
to investigate arsenic-related biomarkers of metabolic changes; the
dose-dependent trends of arsenic exposure to these biomarkers may
translate into the potential use of metabolic biomarkers in arsenic
risk assessment. Since this was a proof-of-concept study, more research
is needed to confirm the relationships we observed between arsenic
exposure and biochemical changes