Cell Markers, Cytokines, and Immune Parameters in Cement Mason Apprentices
Arthritis & Rheumatism (Arthritis Care & Research) Vol. 57, No. 1,
February 15, 2007, pp 147–153 DOI 10.1002/art.22486 © 2007,
American College of Rheumatology ORIGINAL ARTICLE
C. CARLSTEN, A. J. DE ROOS, J. D. KAUFMAN, H. CHECKOWAY, M. WENER, AND N. SEIXAS
Objective.
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-1 (IL-1 ; 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- (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.
KEY WORDS. Autoimmunity; Cytokines; Quartz. INT
INTRODUCTION
Increased risks of autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, and scleroderma, have also been observed among occupational groups highly exposed to silica (5–7). Although inflammatory effects in the lung tissue associated with silica exposure are well documented, there is sparse and inconsistent information about early systemic changes that may contribute to development of autoimmune disease. Patients with silicosis and other individuals highly exposed to silica have been shown to have increased autoantibodies (8,9), immunoglobulins, and immune complexes (10). However, a recent study of lupusprone mice demonstrated a decrease in serum immunoglobulin levels associated with the development of autoimmunity (11), and decreased levels of immunoglobulins were observed in foundry and pottery workers working in their jobs for an average of 15 years (12).
To investigate potential early biologic effects of silica exposure that could be used in a prospective study of silica exposure and associated immune effects, we studied mason and electrician apprentices. Using a cross-sectional design, we compared lung function, immune markers, and inflammatory markers between these apprentice groups using cell surface markers and cytokines generally invoked in proinflammatory models of inhaled particle–related disease (or those well established or strongly hypothesized to be involved in autoimmunity). The study was intended to be hypothesis generating, with a goal to characterize differences for further study.
C. Carlsten, MD, A. J. De Roos, PhD, J. D. Kaufman, MD, MPH, H. Checkoway, PhD, M.
Wener, MD, N. Seixas, PhD: University of Washington, Seattle.
Address correspondence to C. Carlsten, MD, University of Washington,
Department of Medicine, 4225 Roosevelt Way NE, Suite 100, Seattle, WA 98105.
E-mail: carlsten@u. washington.edu.
Submitted for publication December 16, 2005; accepted in revised form May 2, 2006
MATERIALS AND METHODS
Division. Data collection and processing.
A questionnaire and spirometry were administered by trained study personnel. The questionnaire was a 42-item form assessing demographics, industrial occupational history, dust exposure history, smoking history, respiratory illness history, respiratory symptoms, immune/allergic illness history, and allergic symptoms. Exposure was assessed by a series of questions addressing the subject’s work history in construction and the number of years the subject worked in other specific industries with known silica exposures. For each job, the number of hours worked per day in dustproducing activities was requested. The full text of the questionnaire is available as an online supplement(available at http://www.interscience.wiley.com/jpages/0004- 3591:1/suppmat/index.html).
Self-reported dust exposure history was limited to stone, brick, block, and concrete dust (i.e., masonry dust). Directly measured personal exposure data were not available.
Fractional exhaled nitric oxide (eNO) was collected according to American Thoracic Society recommendations for offline measurement (13).
Exhaled breath was collected before lung function measurements because deep inspiration may affect nitric oxide concentration (14). The subjects were instructed to inhale to nearly total lung capacity and exhale through an offline collection device (Vital Capacity Kit for collection of exhaled breath; Sievers Ionics, Boulder, CO). This cycle was repeated twice and the third breath was collected into a nonreactive, self-sealing Mylar balloon. Nitric oxide was measured within 24 hours of collection using a chemiluminescent nitrogen oxide monitor (model 280i; Sievers Ionics).
The average of 3 replicates of the above procedure was reported. Spirometry data (forced expiratory volume in 1 second [FEV1] and forced vital capacity [FVC]) were collected in compliance with American Thoracic Society criteria (15), and FEV1 and FVC were converted to percents predicted using published reference equations (16).
Peripheral blood was sent within 1 hour to the University of Washington Department of Laboratory Medicine for analysis. Immunonephelometric assays were performed for C-reactive protein levels; rheumatoid factor; antinuclear antibodies; and IgA, IgE, IgG, and IgM (Dade Behring, Newark, DE).
Total white blood cells, white blood cell subsets (neutrophils, lymphocytes, monocytes, eosinophils, and basophils), and platelets were calculated by automated cell count. Cell surface markers (CD3, CD4, CD8, CD19, CD25, CD26, and CD69), gated to the lymphocyte population only, were analyzed by flow cytometry and reported both in absolute terms and as percentages of total lymphocytes. Interferon- (IFN ) and interleukin-1 (IL-1), IL-2, IL-4, IL-6, and IL-10 were quantified by Luminex 100 liquid array bioassay (Miraibio, Alameda, CA) with analysis by MasterPlex QT software (Miraibio).
Laboratory personnel responsible for analysis of blood samples were blinded to subjects’ apprenticeship program and demographics.
Statistical analysis.
In addition, each continuous outcome variable was regressed on dusthour-years (divided into tertiles). For dichotomous outcome variables (i.e., yes/no questionnaire symptom items), odds ratios were generated to estimate the relative risk associated with mason apprenticeship versus electrician apprenticeship. All analyses were performed using Stata software (StataCorp, College Station, TX). Only those outcomes listed above were analyzed. Because this was an exploratory analysis, explicitly hypothesis generating rather than oriented toward definitive association, adjustment for multiple comparisons was not performed.
RESULTS
Table 1
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The electrician apprentices in their third year had a significantly higher mean dust-houryears index compared with electrician apprentices in the first year (14.7 versus 1.06, respectively; P 0.005), but for mason apprentices, whose indexes were higher overall, there was no significant difference between those in their third and first years (25.70 versus 55.37, respectively; P 0.35). Regarding estimated daily hours of masonry dust exposure, the average for masons was significantly higher than that of electricians (5.82 versus 2.26, respectively; P 0.005), but there was no significant difference in estimated daily hours between first- and third-year masons (6.25 versus 5.40, respectively; P 0.44). Total years in construction work did not differ significantly between the groups. Notably, subjects were relatively young and ages were closely matched between groups.
Comparing mason and electrician apprentices, there were no significant differences in eNO, spirometry data, C-reactive protein level, rheumatoid factor, antinuclear antibodies, immunoglobulin levels, platelets, or white blood cells (including subsets) (Table 2). Of these, particularly notable was the lack of significant difference in FEV1 percent predicted (93.60 versus 95.35 in masons and electricians; P 0.65) and in IgG (977.09 versus 1,092.45 mg/dl in masons and electricians; P 0.10). Neither history of lung disease nor self-reported pulmonary or immunologic symptoms or disorders were different between the groups (data not shown). Of the cell surface markers we examined (Table 3), percentages of lymphocytes positive for CD25 (Figure 1) and CD69 were significantly lower in mason than in electrician apprentices, whereas the percentage of lymphocytes positive for CD19 was significantly higher. Among cytokines, IL-1, IL-2, IL-4, IL-10, and IFN were all significantly higher in mason than in electrician apprentices (Table 4). However, by linear regression, dust-hour-years tertiles were not significantly associated with any of the outcome variables. Notably, analysis stratified by year of apprenticeship (Table 5) demonstrated that several of the differences in Tables 3 and 4 might be accounted for primarily by third-year masons.
Table 2
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Table 3
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DISCUSSION
This study, although exploratory, provides support for
early inflammatory and immune effects occurring among
workers exposed to masonry dust known to contain silica;
these effects, if validated, may have implications for the
subsequent development of autoimmune diseases.
First, in
demonstrating a correlation between masonry status and
several proinflammatory cytokines, the data suggest a significant
inflammatory milieu even within early-career mason
apprentices.
To our knowledge, this has never been
demonstrated before in such a population.
Second, the
decrease in CD25 lymphocytes in this population is consistent
with a decrease in regulatory T cells that may lead
to increased susceptibility to autoimmune phenomena,
although this is speculative.
CD25 is generally known as a marker of the IL-2 receptor
on T lymphocytes and functions as a marker of regulatory
or suppressor T cells (17,18).
However, CD25 is not only amarker for regulatory T cells, but is also transiently upregulated
on activated nonregulatory T cells independently
stimulated by CD69 (19). Regardless, when CD4
cell suspensions from BALB/c nu/ mice were depleted of
CD25 cells and then injected into athymic BALB/c mice,
all recipients developed autoimmune disease (20). Reconstitution
of CD4 /CD25 cells back into the mice within
a limited period after CD4 /CD25 inoculation prevented
such autoimmune disease.
Increases in IL-1 and other key cytokines are thought to
activate and perpetuate an inflammatory cascade that ultimately
leads to fibrosis in persons sufficiently exposed to
silica (21).
However, the work by Kumar et al (22) and
Garn et al (23,24) has demonstrated the importance of
lymphocytes in silicotic rats, particularly in association
with cytokine signals, such as IFN gene transcription. In
these studies, CD25 (i.e., IL-2 receptor positive) T cells
were increased significantly. The studies by Kumar et al
and Garn et al therefore raise the possibility of migration of
such cells from the blood into the lung, leaving a relative
paucity of immune-regulatory cells circulating; our data
are consistent with this model. Clearly, this is highly speculative
because we did not assess cell populations outside
of the systemic circulation or test chronological changes in
blood levels to confirm this possibility.
Regarding premorbid exposure to silica, only in mice
(11,25) has there been a close examination of the relevant
changes in systemic cytokine and lymphocyte marker pro-
files in this context.
Recognizing that both immune activation
and loss of peripheral tolerance to self are necessary
for autoimmune phenomena, Pfau et al (25) have hypothesized
that apoptosis exposes antigenic epitopes, otherwise
nonexposed, that lead to reaction by the innate immune
system.
Although our preliminary data appear to
better support the earlier-described mechanism, i.e., an
effect of altered autoimmunity due to changes in T regulatory
cells, diverse mechanistic possibilities will need to
be explored in more focused future studies.
Our preliminary study has several important limitations.
The small sample size limits the degree to which
significant differences between the mason groups may be
detected, and the possibility of false positive associations
can only be partially accounted for by statistical testing.
Repeating the study with a larger sample size would allow
for confirmation of these preliminary results.
Furthermore, the cross-sectional design does not allowfor assessment of temporal changes in any of the inflammatory
or immune parameters. Rather, we could only compare
mason and electrician apprentices at one point in
time and hypothesize that the noted differences in masonry
dust exposure and inflammatory cytokines and
CD25 lymphocytes may be causally related. Furthermore,
because most of the inflammatory and cell surface
markers highlighted are thought to fluctuate relatively
acutely (i.e., within hours to days) in response to stimulation,
these data may best reflect only short-term responses
to masonry dust. Therefore, an association with recent but
not cumulative exposure may be why no association with
the dust-hour-years index was noted.
However, the available
background data on relevant surface marker kinetics
are limited. Stimulus-related changes in CD25, for example,
appear to persist for at least 1 week, according to an in
vitro model (26), and a cross-sectional analysis of silicotics
found a decreased percentage of CD25 lymphocytes in
silicotics, long removed from the exposure environment,
compared with healthy controls (8).
Unfortunately, our
study design and available data are not able to clarify the
effects of acute versus chronic exposure, although this is of
great interest.
A long-term prospective study of apprentice
groups, ideally with less heterogeneity of exposure within
each group, may better infer a chronic, causal relationship.
Presumably, such chronic stimulus could lead to persistent
patterns in cytokines and surface markers, but this is
a hypothesis that remains to be proven.
Table 4
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Another limitation is the lack of individual exposure
data. Our assessment relied on a work history questionnaire
specifically targeting silica-containing dusts. Based
on the questionnaire, we derived a semiquantitative exposure
metric based on duration of work in dust-producing
activities. Both electricians and masons, not surprisingly,
reported exposure to masonry dusts; however, as expected,
masons reported a greater degree of such exposure,
providing a degree of validation to the exposure metric.
Future studies using personal monitoring and evaluating
the extent and effectiveness of the use of respiratory protection,
although historically minimally and ineffectively
used in this setting (27), would allow for development of
an individually based quantitative exposure metric.
Similarly, the questionnaire did not assess other occupational
history and exposures (i.e., work involving asbestos
or beryllium) that could affect inflammatory and immune
markers.
However, based on our knowledge of
construction work, it is unlikely that such exposures
would significantly confound the association between
dust exposure and our outcomes.
A further limitation is that flow cytometry for CD25 was
not gated by CD4 positivity. However, given that CD25 is
normally expressed on 10% of peripheral CD4 T cells
and 1% of CD8 T cells, it is expected that the large
majority of CD25 lymphocytes are also CD4 . Also, as
noted, changes in CD25 positivity may parallel activity of
However, because CD25 and CD69 had opposite correlations
with masonry status, it is unlikely that nonregulatory
T cells are the source of the changes in CD25 positivity.
Moreover, the discordance of IL-2 differences with CD25
differences may further reflect the limitation of the crosssectional
design (28). In a future study, the regulatory
nature of T cells may be characterized by more specific
testing (29).
Finally, exclusion of current smoking, current allergic or
respiratory symptoms, or recent food intake should have
reduced known confounding of exhaled nitric oxide
and/or spirometry interpretation. However, inflammatory
markers may be altered by a broad range of stimuli and it
is not unreasonable to consider unrecognized confounding
factors that could explain the differences noted between
the apprentice groups.
In conclusion, mason apprentices in our study had
higher levels of plasma proinflammatory cytokines and a
lower percentage of CD25 lymphocytes than did electrician
apprentices.
These observations, although limited by
a small sample size, cross-sectional design, and lack of
direct personal exposure measures, suggest a proinflammatory
state that may be associated with immune dysregulation.
The possibility that this may be due to reduced
regulatory (suppressor) T cells may be explored in a future
study that includes improvements in study design.nonregulatory T cells, as assessed by CD69 positivity.
Table 5
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ACKNOWLEDGMENTS
The authors would like to thank the following individuals
for their generous support: Duwamish and Renton apprentices
and associated staff, Susan Brower, Sara Jarvis, Karen
Jansen, Mary Ellen Flanagan, Dr. Austin Sumner, and Sebrina
Somers.
AUTHOR CONTRIBUTIONS
Dr. Carlsten had full access to all of the data in the study and
takes responsibility for the integrity of the data and the accuracy
of the data analysis.
Study design. Drs. De Roos, Kaufman, Checkoway, and Seixas.
Acquisition of data. Drs. Carlsten, De Roos, and Seixas.
Analysis and interpretation of data. Drs. Carlsten, De Roos, Kaufman,
Checkoway, Wener, and Seixas.
Manuscript preparation. Drs. Carlsten, De Roos, Kaufman,
Checkoway, Wener, and Seixas.
Statistical analysis. Drs. Carlsten, De Roos, and Seixas.
Lab assays. Dr. De Roos.
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