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In populations exposed to heavy metals, there are few biomarkers that capture intermediate exposure windows. We sought to determine the correlation between toenail metal concentrations and prior 12-month work activity in welders with variable, metal-rich, welding fume exposures. Forty-eight participants, recruited through a local union, provided 69 sets of toenail clippings. Union-supplied and worker-verified personal work histories were used to quantify hours welded and respirator use. Toenail samples were digested and analyzed for lead (Pb), manganese (Mn), cadmium (Cd), nickel (Ni), and arsenic (As) using ICP-MS. Spearman correlation coefficients were used to examine the correlation between toenail metal concentrations. Using mixed models to account for multiple participation times, we divided hours welded into three-month intervals and examined how weld hours correlated with log-transformed toenail Pb, Mn, Cd, Ni, and As concentrations. Highest concentrations were found for Ni, followed by Mn, Pb and As, and Cd. All the metals were significantly correlated with one another (rho range = 0.28–0.51), with the exception of Ni and As (rho = 0.20, p = 0.17). Using mixed models adjusted for age, respirator use, smoking status, and BMI, we found that Mn was associated with weld hours 7–9 months prior to clipping (p = 0.003), Pb was associated with weld hours 10–12 months prior to clipping (p = 0.03) and over the entire year (p = 0.04). Cd was associated with weld hours 10–12 months prior to clipping (p = 0.05), and also with the previous year's total hours welded (p = 0.02). The association between Ni and weld hours 7–9 months prior to clipping approached significance (p = 0.06). Toenail metal concentrations were not associated with the long-term exposure metric, years as a welder. Results suggest Mn, Pb, and Cd may have particular windows of relevant exposure that reflect work activity. In a population with variable exposure, toenails may serve as useful biomarkers for occupational metal fume exposures to Mn, Pb, and Cd during distinct periods over the year prior to sample collection. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence suggests that welding fume exposure is associated with systemic inflammation. Although celluar metabolites may be associated with inflammation, there is limited information on metabolomic changes during welding fume exposure. Such changes may play an important role in the occurrence, development, and prevention of metal-associated diseases. We aim to investigate human metabolomics changes pre- and post-welding fume exposure., Methods: This study included 52 boilermakers totally. We collected plasma samples pre- and post-shift welding fume exposure and prepared samples using the automated MicroLab STAR® system. Metabolite concentrations were measured using ultra performance liquid chromatography - tandem mass spectrometer (UPLC-MS/MS) methods. Two-way analysis of variance was used to test the significance of metabolite changes with false discovery rate correction., Results: Analysis detected several metabolic changes after welding fume exposure, mainly involved in the lipid pathway [glucocorticoid class (cortisol, corticosterone, and cortisone), acylcarnitine class, and DiHOME species (9,10-DiHOME and 12,13-DiHOME)], amino acid utilization (isoleucine, proline and phenylalanine), and S-(3-hydroxypropyl) mercapturic acid (3-HPMA). These compounds are all associated with inflammation according to previous studies. Further, additive interaction effects linked smoking and 3-HPMA levels. In the metabolite set enrichment analysis for diseases, the top two disease-associated metabolite pathways were systemic inflammation-related diseases including rheumatoid arthritis and systemic lupus erythematosus., Conclusions: This global metabolomics study shows evidence that metabolite changes during welding fume exposure are closely associated with systemic inflammation. The altered metabolites detected may be potential health monitoring biomarkers for boilermakers, especially for inflammation-related disease prevention.

Background: Although it has been well recognized that exposure to secondhand tobacco smoke (SHS) is associated with cardiovascular mortality, the mechanisms and time course by which SHS exposure may lead to cardiovascular effects are still being explored., Methods: Non-smoking workers were recruited from a local union and monitored inside a union hall while exposed to SHS over approximately 6 hours. Participants were fitted with a continuous electrocardiographic monitor upon enrollment which was removed at the end of a 24-hr monitoring period. A repeated measures study design was used where resting ECGs and blood samples were taken from individuals before SHS exposure (baseline), immediately following SHS exposure (post) and the morning following SHS exposure (next-morning).Inflammatory markers, including high sensitivity C-reactive protein (CRP) and white blood cell count (WBC) were analyzed. Heart rate variability (HRV) was analyzed from the ECG recordings in time (SDNN, rMSSD) and frequency (LF, HF) domain parameters over 5-minute periods. SHS exposure was quantified using a personal fine particulate matter (PM2.5) monitor.Linear mixed effects regression models were used to examine within-person changes in inflammatory and HRV parameters across the 3 time periods. Exposure-response relationships with PM2.5 were examined using mixed effects models. All models were adjusted for age, BMI and circadian variation., Results: A total of 32 male non-smokers were monitored between June 2010 and June 2012. The mean PM2.5 from SHS exposure was 132 μg/m3. Immediately following SHS exposure, a 100 μg/m3 increase in PM2.5 was associated with declines in HRV (7.8% [standard error (SE) =3%] SDNN, 8.0% (SE = 3.9%) rMSSD, 17.2% (SE = 6.3%) LF, 29.0% (SE = 10.1%) HF) and increases in WBC count 0.42 (SE = 0.14) k/μl. Eighteen hours following SHS exposure, a 100 μg/m3 increase in PM2.5 was associated with 24.2% higher CRP levels., Conclusions: Our study suggest that short-term SHS exposure is associated with significantly lower HRV and higher levels of inflammatory markers. Exposure-associated declines in HRV were observed immediately following exposure while higher levels of CRP were not observed until 18 hours following exposure. Cardiovascular autonomic and inflammation responses may contribute to the pathophysiologic pathways that link SHS exposure with adverse cardiovascular outcomes.