Characterization of arsenic metabolites in urine using chromatography and mass spectrometry
Creators: Davydiuk, Tetiana
Publisher: name: University of Alberta Library
Year: 2024

<p>Inorganic arsenic (iAs) continues to be the contaminant of the highest priority. Millions of people around the world are exposed to high concentrations of arsenic. Chronic exposure to iAs increases the risk of cancers of bladder, lungs and skin, cardiovascular diseases, and skin lesions. Severity of the adverse health outcomes caused by iAs is highly variable between individuals. However, factors that determine susceptibility to iAs toxicity are not well established, which makes it challenging to better protect vulnerable populations. Because iAs is metabolized in humans, primarily through methylation, measurements of iAs and its methylated metabolites can be used to evaluate the efficiency of arsenic methylation. Information on arsenic species in human urine can serve as potential biomarkers of susceptibility to arsenic toxicity.<br>
My thesis focused on detailed characterization of arsenic metabolic profiles in human urine with the goal to improve studies of methylation efficiency of iAs and assist in determining biomarkers of susceptibility to iAs toxicity. A method of high-performance liquid chromatography (HPLC) separation with inductively coupled plasma mass spectrometry (ICPMS) detection was established for the determination of arsenic species in urine. The HPLC-ICPMS method was applied to the speciation analysis of arsenic in 994 urine samples collected from the Health Effects of Arsenic Longitudinal Study (HEALS) population located in Araihazar, Bangladesh. Results of these 994 urine samples were combined with those of previous arsenic speciation analysis of 879 urine samples from the same population. Results of arsenic speciation analysis of the 1873 urine samples showed that dimethylarsinic acid (DMA) was detectable in all samples, and its concentration ranged from 0.3 μg/L to 1599 μg/L, with a mean concentration of 79.2 μg/L and median of 44.1 μg/L. Monomethylarsonic acid (MMA) was detectable in 99.9% of the urine samples, and MMA concentration ranged from 0.05 μg/L (detection limit) to 279 μg/L, with a mean of 12.1 μg/L and median of 5.9 μg/L. The sum of arsenite (iAsIII) and arsenate (iAsV) ranged from 0.1 μg/L (detection limit) to 611 μg/L, with a mean of 16.4 μg/L and median of 8.0 μg/L. The concentration of arsenobetaine (AsB) ranged from 0.05 μg/L (detection limit) to 103 μg/L, with a mean of 2.1 μg/L and median of 0.9 μg/L. The summed concentrations of arsenic species measured using HPLC-ICPMS (mean 110.5 μg/L, range 0.5 ̶ 2387 μg/L) were in good agreement with the total concentration of arsenic measured using ICPMS (mean 114.3 μg/L, range 0.9 ̶ 2633 μg/L).<br><br>
The HPLC-ICPMS method enabled the separation and detection of AsB, iAsIII, DMA, MMA, iAsV, and up to seven other (unknown) arsenic species in urine samples within 10 min of analysis. Chromatographic peaks of unknown arsenic species were matched based on their chromatographic behaviour with the consideration of retention time shifts. At least one unknown arsenic species was detected in 579 of 994 urine samples (58.2%). The sum of all unknown arsenic species was approximately 1.8 µg/L (mean). The highest concentration of a single unknown arsenic species was 33 µg/L. The commonly detected unknowns and urinary DMA concentrations had strong positive association with correlation coefficients ranging from 0.58 to 0.79 (p-value &lt; 0.001). The median DMA% were significantly higher in urine samples with detectable unknowns (p-value &lt; 0.001) suggesting that the unknown arsenic metabolites may serve as a surrogate to indicate potential exposure to complex arsenic species.<br>
A method combining HPLC with ICPMS and electrospray ionization mass spectrometry (ESIMS) was developed and used to measure eleven organic arsenic species at low concentrations in complex matrices of urine and kelp (seaweed) extract. The HPLC-ICPMS/ESIMS method enabled the identification of Unknown 1 as tetramethylarsonium ion (TMI) in a representative urine sample.<br>
My thesis contributed to the development of methods for quantitative measurement of arsenic species in urine, detailed characterization of arsenic metabolic profiles, as well as approaches for further data analysis and interpretation. The urinary arsenic speciation dataset described in this thesis will be further used for establishing relationships between arsenic methylation efficiency and health effects, understanding factors influencing individual differences in metabolic profiles, and studying susceptibility to arsenic toxicity.</p>