Arsenic speciation analysis in human urine for long term epidemiological studies: The Multi-Ethnic Study of Atherosclerosis (MESA)

Abstract

Arsenic is a ubiquitous toxic metalloid causing serious health problems. Speciation analysis of arsenic in human urine provides valuable insights for large-scale epidemiological studies and informs on sources of exposure as well as human metabolism. The Multi-Ethnic Study of Atherosclerosis (MESA) is a valuable cohort for assessing chronic low-moderate arsenic exposure and health effects in an ethnically diverse US population. We present a state-of-the-art arsenic speciation analysis methodology and its application to 7677 MESA spot urine samples based on high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. This method is fast, robust and detects a total of 11 individual As species at method detection limits of 0.02-0.03 μg arsenic/L urine for each individual species. Our analytical approach features excellent mean method accuracy (98%) and precision (5%) for the main arsenic species in urine (arsenobetaine, methylarsonic acid, dimethylarsinic acid, and total inorganic As); intra- (3-6%) and inter-day coefficients of variability (5-6%); column recovery (96 ± 7%); and spike recovery (97 ± 6%). The main arsenic species were detectable in ≥95% of urine samples due to the implementation of an oxidation step. Each individual minor arsenic species was detectable in ≤25% of all urines, although at least one of them was detected in almost half the participants. We identified two minor urinary arsenic species as dimethylarsinoylacetic acid and dimethylarsinoylpropionic acid, potential metabolites of seafood-related arsenicals. We observed differences in individual As species excretion by race/ethnicity, with Asian-American participants featuring 3-4 times higher concentrations compared to other participants. We also found differences by site, body mass index, smoking status, rice intake, and water arsenic levels, potentially indicating different exposures or related to individual bio-metabolism. The proposed approach is suitable for epidemiological studies and the collected data will constitute the base for future research on potential health effects of chronic low-level arsenic exposure.

Keywords: Anion-exchange HPLC-ICPMS/MS; Descriptive statistics; High-throughput urine arsenic speciation analysis; Large-scale epidemiologic studies; Method development; Quality control; Urine arsenic metabolites.