Short Report: Using Targeted Urine Metabolomics to Distinguish Between Manganese Exposed and Unexposed Workers in a Small Occupational Cohort

Abstract

Objectives: Despite the widespread use of manganese (Mn) in industrial settings and its association with adverse neurological outcomes, a validated and reliable biomarker for Mn exposure is still elusive. Here, we utilize targeted metabolomics to investigate metabolic differences between Mn-exposed and -unexposed workers, which could inform a putative biomarker for Mn and lead to increased understanding of Mn toxicity.Methods: End of shift spot urine samples collected from Mn exposed (n = 17) and unexposed (n = 15) workers underwent a targeted assay of 362 metabolites using LC-MS/MS; 224 were quantified and retained for analysis. Differences in metabolite abundances between exposed and unexposed workers were tested with a Benjamini-Hochberg adjusted Wilcoxon Rank-Sum test. We explored perturbed pathways related to exposure using a pathway analysis.Results: Seven metabolites were significantly differentially abundant between exposed and unexposed workers (FDR ≤ 0.1), including n-isobutyrylglycine, cholic acid, anserine, beta-alanine, methionine, n-isovalerylglycine, and threonine. Three pathways were significantly perturbed in exposed workers and had an impact score >0.5: beta-alanine metabolism, histidine metabolism, and glycine, serine, and threonine metabolism.Conclusion: This is one of few studies utilizing targeted metabolomics to explore differences between Mn-exposed and -unexposed workers. Metabolite and pathway analysis showed amino acid metabolism was perturbed in these Mn-exposed workers. Amino acids have also been shown to be perturbed in other occupational cohorts exposed to Mn. Additional research is needed to characterize the biological importance of amino acids in the Mn exposure-disease continuum, and to determine how to appropriately utilize and interpret metabolomics data collected from occupational cohorts.

Diagnosis of manganism and manganese neurotoxicity: A workshop report

“…One of the workshop participants presented a study on 59 metabolites identified by NMR and 224 metabolites identified by MS in urine. The findings indicated differences in relative abundances of metabolites, and the pathways in which they operate, between Mn-exposed and unexposed workers ( 43 ). Although the results need to be interpreted with caution given the variability of metabolites due to internal and external cues, and the hypothesis-generation nature of the analysis, metabolomics and other emerging- omics technologies provide an opportunity for exploring the association between exposure and health outcomes and determining new biomarkers of exposure.…”

“…Metabolomics as an alternative to traditional biomonitoring for Mn exposure has begun to be explored in the literature and shows future promise for identifying biomarkers of Mn exposure and understanding pathways in the body through which Mn exerts toxicity (42)(43)(44). In particular, metabolomics holds promise for Mn, given the absence of strong support for useful traditional biomarkers of Mn exposures, such as Mn levels in blood, plasma or urine (31,45).…”

“…There are several limitations and challenges associated with the use of metabolomics for exposure assessment, given the inherent variability in small-molecule metabolites ( 42 ). In the most rigorous studies, care will be taken to ensure that samples are taken at the same time of day, and information on relevant covariates such as dietary habits, pre-existing health conditions and the use of pharmaceutical agents should also be collected ( 43 ). Given the large number of statistical comparisons made in metabolomics studies, a sufficient number of participants need to be enrolled to ensure that data can be spilt into separate training and testing sets to validate potential findings ( 42 ), and appropriate statistical methods for big data need to be utilized.…”

NMR Untargeted and HPLC-MS/MS Targeted Metabolomic Approaches for Evaluating Styrene Exposure in the Urine of Shipyard Workers

“…Walker et al used plasma metabolomics to link occupational exposure to trichloroethylene to modifications to the metabolism, identifying, among other things, changes in the purine, methionine and cysteine metabolism following exposure [ 24 ]. Carter et al found seven metabolites that differentiated exposed from unexposed workers, involving changes in beta-alanine metabolism, histidine metabolism, and glycine, serine, and threonine metabolism [ 25 ].…”