Graduate Institute of Biomedical Electronics and Bioinformatics, [corrected] National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, Taiwan, [corrected] 106.
Chem Res Toxicol. 2012 Mar 19;25(3):676-86. doi: 10.1021/tx200465e. Epub 2012 Feb 10.
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.
焊接烟尘的复杂成分、多种分子靶标、多样化的细胞效应以及与劳动者相关的生活方式，使得焊接烟尘暴露的评估变得极为复杂。通过 1H NMR 光谱和模式识别方法，对台湾一家造船厂的 35 名男性焊工和 16 名男性办公室工作人员的尿液代谢组学图谱进行了描述。还采集了 51 名个体的血液样本，并检测了细胞因子和其他炎症标志物的表达水平。本研究将焊接暴露变量分为高（焊工）和低（办公室工作人员）暴露，以检查两组之间连续结果标志物代谢物和炎症标志物的差异。烟尘颗粒评估表明，焊工接触到不同浓度的铬、镍和锰颗粒。尿液代谢组学模式的多变量统计分析显示，焊工的甘氨酸、牛磺酸、甜菜碱/TMAO、丝氨酸、S-半胱氨酸、马尿酸、葡萄糖酸盐、肌酐和丙酮水平较高，而肌酸水平较低，而在所有测量的细胞因子和其他炎症标志物中，只有 TNF-α与焊接烟尘暴露显著相关。在所鉴定的代谢物中，焊工体内较高水平的甘氨酸、牛磺酸和甜菜碱可能在调节炎症和氧化组织损伤过程中发挥一定作用。在这项代谢组学实验中，我们还发现，所鉴定的代谢物与焊接暴露的关联受到吸烟的混杂，但不受饮酒的影响，这与已知的吸烟者炎症标志物的改变反应一致。我们的结果与先前使用非代谢组学分析技术的研究结果一致，表明代谢组学分析是一种有效的方法，可以描述焊接烟尘暴露及其他混杂因素的综合影响。
