title: Metabolomic characterization of laborers exposed to welding fumes.
abstract: The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders.
authors.affiliation: Graduate Institute of Biomedical Electronics and Bioinformatics, [corrected] National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan, [corrected] 106.
authors.forename: Kuo-Ching
authors.initials: KC
authors.lastname: Wang
authors.forename: Ching-Hua
authors.initials: CH
authors.lastname: Kuo
authors.forename: Tze-Feng
authors.initials: TF
authors.lastname: Tian
authors.forename: Mong-Hsun
authors.initials: MH
authors.lastname: Tsai
authors.forename: Yin-Mei
authors.initials: YM
authors.lastname: Chiung
authors.forename: Chun-Ming
authors.initials: CM
authors.lastname: Hsiech
authors.forename: Sung-Jeng
authors.initials: SJ
authors.lastname: Tsai
authors.forename: San-Yuan
authors.initials: SY
authors.lastname: Wang
authors.forename: Dong-Ming
authors.initials: DM
authors.lastname: Tsai
authors.forename: Chiang-Ching
authors.initials: CC
authors.lastname: Huang
authors.forename: Y Jane
authors.initials: YJ
authors.lastname: Tseng
mesh_terms: D000395:Air Pollutants, Occupational / Q000032:analysis; D000428:Alcohol Drinking / Q000378:metabolism; D015415:Biomarkers / Q000097:blood / Q000652:urine; D016207:Cytokines / Q000378:metabolism; D004784:Environmental Monitoring; D006801:Humans; D007958:Leukocyte Count; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D055432:Metabolomics; D019216:Metals, Heavy / Q000032:analysis; D015999:Multivariate Analysis; D017817:Nasal Lavage Fluid / Q000166:cytology; D016273:Occupational Exposure / Q000032:analysis*; D012907:Smoking / Q000378:metabolism; D013624:Taiwan; D014896:Welding
chemical_list: D000395:Air Pollutants, Occupational; D015415:Biomarkers; D016207:Cytokines; D019216:Metals, Heavy