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Cell markers, cytokines, and immune parameters in cement mason apprentices
C Carlsten1, A J de Roos, J D Kaufman
1University of Washington, Department of Medicine, 4225 Roosevelt Way NE, Suite 100, Seattle, WA 98105, USA. carlsten@u.washington.edu
Objective:
Cement masons are known to have significant silica exposure, and silica exposure and silicosis are thought to increase risk of autoimmune disease. Because the mechanisms remain obscure, with inconclusive reports of systemic immune effects following silica exposure, our goal was to identify potential early markers of silica-related immunologic and respiratory effects.
Methods:
We conducted a cross-sectional study of cement mason apprentices and electrician (control) apprentices. Demographics, dust exposure history, symptoms, spirometry, exhaled nitric oxide, and blood (for immunoglobulins, cytokines, cell counts, and surface markers) were obtained from 11 cement mason apprentices and a comparison group of 21 electrician apprentices.
Results:
Masons had significantly higher (P < 0.05) masonry dust exposure (42 versus 9 dust-hour-years), serum interleukin-1beta (IL-1beta; 12 versus 9 pg/ml), IL-2 (20 versus 8 pg/ml), IL-4 (193 versus 67 pg/ml), IL-10 (44 versus 21 pg/ml), and interferon-gamma (139 versus 65 pg/ml) compared with electricians. In contrast, masons had significantly lower percentages of CD25+ (12% versus 20%) and CD69+ (4% versus 9%) lymphocytes.
Conclusion:
Mason apprentices had higher levels of serum proinflammatory cytokines and lower percentages of CD25+ and CD69+ lymphocytes than did electrician apprentices. These preliminary findings suggest that mason apprentices may be at greater risk of a systemic proinflammatory state that is potentially linked to immune dysregulation. Although distinct limitations of this preliminary data are recognized, this is consistent with early biologic effects leading to increased incidence of autoimmune disease among silica-exposed workers. Prospective studies are needed to validate these initial findings and clarify the temporal sequence of observed relationships.
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