Objectives: We investigated whether the metal components of PM determined activating histone modifications in 63 steel workers with well-characterized exposure to metal-rich PM.

Methods: We determined histone 3 lysine 4 dimethylation (H3K4me2) and histone 3 lysine 9 acetylation (H3K9ac) on histones from blood leukocytes. Exposure to inhalable metal components (aluminum, manganese, nickel, zinc, arsenic, lead, iron) and to total PM was estimated for each study subject.

Results: Both H3K4me2 and H3K9ac increased in association with years of employment in the plant (p-trend = 0.04 and 0.006, respectively). H3K4me2 increased in association with air levels of nickel [β = 0.16; 95% confidence interval (CI), 0.03–0.3], arsenic (β = 0.16; 95% CI, 0.02–0.3), and iron (β = 0.14; 95% CI, 0.01–0.26). H3K9ac showed nonsignificant positive associations with air levels of nickel (β = 0.24; 95% CI, –0.02 to 0.51), arsenic (β = 0.21; 95% CI, –0.06 to 0.48), and iron (β = 0.22; 95% CI, –0.03 to 0.47). Cumulative exposures to nickel and arsenic, defined as the product of years of employment by metal air levels, were positively correlated with both H3K4me2 (nickel: β = 0.16; 95% CI, 0.01–0.3; arsenic: β = 0.16; 95% CI, 0.03–0.29) and H3K9ac (nickel: β = 0.27; 95% CI, 0.01–0.54; arsenic: β = 0.28; 95% CI, 0.04–0.51).

Growing evidence indicates that epigenetic dysregulation of gene expression plays a primary role in cancer etiology (Feinberg and Tycko 2004; Ke et al. 2006). Several toxic metals have been shown to bind more avidly to histone proteins than to other biopolymers such as DNA or RNA (Conroy et al. 2008; Zoroddu et al. 2000, 2002). Recent in vitro studies have shown that carcinogenic metals cause posttranslational epigenetic modifications of histone proteins, thus derailing the normal programming of gene expression (Ke et al. 2006; Yan and Boyd 2006; Yan et al. 2003; Zhou X et al. 2009). In lung epithelial cell lines and malignant transformation models, arsenic (Jensen et al. 2009; Zhou X et al. 2009), nickel (Zhou QX et al. 2009), and chromium (Sun et al. 2009; Zhou X et al. 2009) have been linked with specific activating histone modifications, such as H3K4 (histone 3 lysine 4) dimethylation (H3K4me2), that contribute to the formation of a relaxed or “open” chromatin structure permissive for gene transcription (Surralles et al. 1998; Yan et al. 2003). Metal-related induction of activating histone modifications have been suggested to contribute to metal carcinogenesis by causing the expression of tumor suppressor or other cancer-promoting genes (Wang et al. 2005; Zhou X et al. 2008). Inhaled PM pollutants have been previously shown to produce systemic changes in gene expression, which can be detected in peripheral blood of exposed individuals (Salnikow and Zhitkovich 2008). However, whether metals in inhalable PM induce alterations of histone modifications in human subjects has never been evaluated.

Although wide strata of the general population are exposed to low, background levels of toxic and carcinogenic inhalable compounds, industrial workers have been often exposed to significantly higher concentrations of potentially carcinogenic agents released from multiple sources (MacArthur et al. 2009). Foundry work is a specific condition of exposure to inhalable metal-rich PM that has been associated with increased risk of lung cancer in several early investigations (International Agency for Research on Cancer 1987). Even in modern foundry facilities, PM exhibits levels that are well above the concentrations found in ambient outdoor air and also have a larger proportion of toxic metal components (Alley et al. 2009; Fang et al. 2009; Roy et al. 2009; Vijay Bhaskar et al. 2009). In the present investigation in a steel furnace plant, we investigated whether metals in inhalable PM determined changes in H3K4me2 and histone 3 lysine 9 acetylation (H3K9ac), two histone modifications associated with open chromatin states, in peripheral blood leukocytes from workers with well-characterized exposure.

Exposure assessment. PM metal components (aluminum, manganese, nickel, zinc, arsenic, lead, iron) and PM mass [PM with aerodynamic diameters ≤ 10 μm and ≤ 1 μm (PM₁₀ and PM₁, respectively)] were measured in each of the 11 work areas of the steel production plant. We measured air concentrations of individual metal PM components in PM₁₀, through multielement analysis performed by means of inductively coupled-plasma mass spectrometer (ELAN DRC II; PerkinElmer, Waltham, MA, USA) using the total quant method. External calibration was performed using calibration standard 3, stock multielement (10 μg/mL; PerkinElmer). PM₁₀ and PM₁ were measured using a Grimm 1100 light-scattering dust analyzer (Grimm Technologies, Inc., Douglasville, GA, USA).

Study subjects recorded in a personal log the time they spent in each of the work areas. Personal exposure was calculated as the average of work area levels weighted by the time spent in each area. All metal and PM levels were expressed in micrograms per cubic meter. In the plant, exposure levels have shown very little variability over time, as measures repeated over 3 years in a subset of the study population showed very high correlations (r² > 0.90). Therefore, the time-weighted levels of metals and PM represented, in addition to the exposure during the week of the study, also a measure of the usual exposure of the study subjects (Tarantini et al. 2009). We estimated cumulative exposures as the product of the time-weighted levels of metals and PM during the study by the years of employment in the plant.

Total histone extraction and histone modification analysis. We obtained buffy coat from peripheral blood collected in EDTA tubes centrifuged at room temperature (22–25°C) for 15 min at 1,500 × g. Red blood cell lysis solution (s.r.l. cod.A7933; Promega, Madison, WI, USA) was added to the buffy coat to wash out red blood cells. After 10 min at room temperature, the mixture was centrifuged at 2,500 × g for 15 min, and the supernatant was discarded. Remaining monolayer cells were processed according to protocol used by Chen et al. (2006). Briefly, cells were lysed in 1 mL ice-cold radioimmunoprecipitation assay buffer (Santa Cruz Biotechnology, Santa Cruz, CA, USA) supplemented with a protease inhibitor mixture (Roche Applied Sciences, Indianapolis, IN, USA) for 10 min. The sample was then collected and centrifuged at 10,000 × g for 10 min. After discarding supernatant, remaining pellet was resuspended in 0.4 N H₂SO₄. After incubation on ice for 90 min, the sample was centrifuged at 14,000 × g for 15 min. The supernatant was mixed with cold acetone and kept at –20°C overnight. The histones were collected by centrifugation at 14,000 × g for 15 min. After one wash with acetone, the histones were air dried and resuspended in 500 μL water. We measured total proteins in each sample by means of the Bradford assay according to manufacturer’s instructions (protein assay kit 500-0002; Bio-Rad Laboratories, Milan, Italy). We used equal amounts of proteins (4 μg) to normalize results of the subsequent analysis on histones.

We used a solid-phase sandwich enzyme-linked immunosorbent assay (ELISA), using monoclonal antibodies, to detect endogenous levels of H3K4me2 and H3K9ac (PathScan Sandwich ELISA Kits; Cell Signaling Technology, Beverly, MA, USA) according to the manufacturer’s protocol. The assays we used in our study are the PathScan dimethyl-histone H3 (Lys4) Sandwich ELISA Kit 7124 and PathScan acetyl-histone H3 (Lys9) Sandwich ELISA Kit 7121. The assays use dimethyl-histone H3 (Lys4) (C64G9) rabbit monoclonal antibody 9725 and acetyl-histone H3 (Lys9) antibody 9671, respectively, which have been shown by the manufacturer to be specific for the histone modifications of concern. Sample measurements were performed in duplicate. We used a Synergy HT-BioTek spectrophotometer (Winooski, VT, USA) to read 450 nm absorbance. The absorbance values at 450 nm directly reflected the concentration of modified histones (Deligezer et al. 2010). According to the Beer–Lambert law, optical density (OD; absorbance) is used for colorimetric analysis so that readings relate directly to concentration. The coefficient of variation in replicate samples of the assays was 0.30% for H3K4me2 and 0.42% for H3K9ac.

Statistical analysis. We performed trend tests using the continuous variable in the regression model and presenting the corresponding two-sided p-values. We evaluated the association of PM metal components and PM mass levels with histone modifications using simple linear regression models, as well as multivariable models adjusting for age, BMI, pack-years, and percent granulocytes in the differential blood count as continuous variables and education as categorical variable. The independent variables used in multivariable models were selected a priori and included general characteristics potentially associated with cancer risks or other carcinogenic exposures. In addition, we adjusted for percent granulocytes to account for possible shifts in the proportion of leukocytes subtypes associated with the exposures. As sensitivity analyses, we fitted in the models as independent variables data from differential white blood counts (i.e., percent lymphocytes, monocytes, eosinophils, or basophils) or duration of sample storage and found no major changes in the results. Regression diagnostics were performed separately for each model. We examined whether the exposure–response relationships were linear through graphical inspection. Furthermore, we fitted a polynomial regression by including a quadratic term for exposure and compared these models with the linear model using the likelihood ratio test. Neither graphical inspection nor the likelihood ratio tests suggested any departure from linearity.

Outliers were excluded from regression analysis by dropping observations with studentized residuals that exceeded +3 or –3. The number of outliers removed ranged from a minimum of 0 to a maximum of 3.

The correlation matrix between exposure levels showed correlations of different strengths between the exposures (Table 2). We found high correlations [Pearson’s correlation coefficient (r) = 0.7–1] for aluminum with manganese, lead, and PM₁₀; for manganese with lead and PM₁₀; for nickel with arsenic and iron; and between arsenic and iron, PM₁₀ and lead, and PM₁ and PM_10. Correlations were moderate (r = 0.4–0.7) for PM₁ with aluminum, manganese, and lead, between nickel and aluminum, and between iron and zinc. Except for PM₁ and arsenic (r = –0.20), all other correlations were positive with r < 0.40.

Associations of histone modifications with subjects’ characteristics and years of employment. The range of values of the histone modifications was 0.26–1.20 OD for H3K4me2 (median, 0.99 OD) and –0.50 to 1.06 OD for H3K9ac (median, 0.37 OD).

H3K4me2 was moderately but significantly correlated with H3K9ac (Pearson’s r = 0.45, p < 0.001). H3K4me2 and H3K9ac were not associated with age, BMI, smoking, number of cigarettes/days, smoking duration, pack-years, area of residence (city center, suburbs, rural), self-reported traffic intensity near home, or percent granulocytes (Table 3). H3K9ac was positively associated with education (p = 0.04; Table 3). Both H3K4me2 and H3K9ac increased in association with the years of employment of the study subjects in the steel plant (Table 3). We confirmed the association between years of employment and histone modifications in age-adjusted regression models.

Association of levels of exposure to inhalable metals with histone modifications. We evaluated whether levels of H3K4me2 and H3K9ac were associated with the levels of personal exposure to metals in inhalable PM, as well as to PM mass, in both simple regression models and multivariable models adjusted for age, BMI, education, pack-years, and percent granulocytes. Results from unadjusted and adjusted models showed similar results (Table 4). In adjusted models, H3K4me2 increased in association with nickel, arsenic, and iron. H3K4me2 was not associated with aluminum, manganese, zinc, lead, PM₁₀, or PM₁ exposure levels in unadjusted or adjusted regression models (Table 4). H3K9ac was positively but not significantly associated with nickel and iron levels. H3K9ac was not associated with the levels of the remaining metals, PM₁₀ or PM₁ (Table 4).

Association of cumulative exposure to inhalable metals with histone modifications. Table 5 shows the associations of H3K4me2 and H3K9ac with cumulative exposures, estimated as the product of level of exposure to PM metal components or total PM mass and years of employment. Again, unadjusted and adjusted models showed similar results. In adjusted models, H3K4me2 increased in association with cumulative exposure to nickel and arsenic. H3K9ac showed significant associations with cumulative exposure to nickel and arsenic. Cumulative exposure to iron was positively but not significantly associated with both H3K4me2 and H3K9ac.

To the best of our knowledge, this is the first study showing associations between metal exposures, such as nickel, arsenic, and iron, and histone modifications in human subjects. Our study was based on measures of histone modifications in blood leukocyte samples from healthy subjects, thus suggesting that exposure-related alterations of histone modifications may occur in normal tissues and possibly anticipate the onset of disease. Estimated effects of metal exposures on H3K4me2 in blood leukocytes were consistent with previous in vitro toxicology studies that showed that carcinogenic metals increased H3K4me2 in A549 human lung carcinoma cells (Sun et al. 2009; Zhou X et al. 2009). In particular, nickel and arsenic, which were most consistently associated with increased H3K4me2 in our analyses, were also previously found to increase H3K4me2 in vitro (Zhou X et al. 2009). In our study, we found that H3K4me2 was correlated with the levels of exposure to nickel, arsenic, and iron, but only nickel and arsenic showed significant associations with H3K4me2 when we evaluated cumulative exposures. Also, we found significant associations of cumulative exposures to nickel and arsenic with increased H3K9ac.

The changes observed in previous in vitro studies on lung carcinoma cells (Sun et al. 2009; Zhou X et al. 2009) and in our study in blood leukocyte samples suggest that induction of gene-activating histone modifications such as H3K4me2 and H3K9ac might be a systemic process detectable across different tissues. However, whether H3K4me2 and H3K9ac are induced in human lung tissues exposed in vivo to carcinogenic metals needs to be confirmed in future investigations. Metal components of inhaled PM have been shown to induce oxidative stress and inflammatory processes, which are known to affect histone modifications (Donaldson et al. 2003; Gilmour et al. 2003) and might specifically affect blood leukocyte measures. A series of experimental studies using ambient PM₁₀ collected in Utah Valley (USA) near a local steel plant demonstrated that anthropogenic PM containing bioavailable transition metals have heightened acute inflammatory effects, and that PM oxidant generation ability was enhanced in PM with higher metal content (Dye et al. 2001; Frampton et al. 1999; Ghio and Devlin 2001). Previous studies have shown that exposures to PM or related airborne pollutants are associated with changes in proinflammatory and cancer-related gene expression in blood leukocytes (Feinberg and Tycko 2004; Franklin et al. 2008; MacNee and Donaldson 2003; Salnikow and Zhitkovich 2008) and with markers of gene expression control such as DNA methylation (Baccarelli et al. 2009; Bollati et al. 2007; Pavanello et al. 2009; Tarantini et al. 2009).

We investigated a population with well-characterized exposure that allowed us to compare subjects over a wide range of different exposure levels. We controlled for several potential confounders by fitting multivariable models that included several individual characteristics as independent variables. However, we cannot exclude the possibility that other unmeasured exposures that are present in foundry facilities, such as heat, carbon monoxide, and nonionizing radiation (Gomes et al. 2002; Lewis et al. 1992), might have influenced H3K4me2 and H3K9ac. In univariate analyses, we found that H3K9ac was positively associated with the education level of the study subjects. Although our study did not provide information to evaluate the biological basis for this association, our results showed that adjusted and unadjusted estimates for metal effects on histone modifications were remarkably similar, so confounding from education and other variables included in our models is unlikely.

Because of the limited number of study subjects, it is possible that the associations observed were attributable to chance. However, the occupational exposure and relatively controlled environment of a foundry provide a good setting for evaluating these mechanistic questions and limit bias and chance findings. Our study was based on subjects working in several work areas of the same factory and did not include a different population of subjects without a specific condition of exposure to inhaled pollutants. Limiting our investigation to individuals who have all been working in the same work facility avoided potential concerns related to the selection of external referents who might have differed from the exposed population in terms of socioeconomic factors and other characteristics determining hiring into the plant (Pearce et al. 2007). Nonetheless, the differences in the personal levels of exposure in our study group were large, providing sufficient contrast for identifying exposure-related changes in histone modifications. For example, the lowest level of PM₁₀ observed in our study population (73.72 μg/m³) was only marginally higher than ambient PM₁₀ levels measured in the geographic area in which the plant is located (average annual ambient PM₁₀ levels between 41 and 57 μg/m³ were recorded in the year of the study by different ambient monitoring stations in Brescia area) (Anselmi and Patelli 2006), whereas the highest level was 1220.17 μg/m³. The subjects with the highest exposures to arsenic and nickel had exposure levels that were 36 and 31 times higher, respectively, than those for the least-exposed subjects. Although we based our study on a group of steel workers with average exposures higher than that of the general population, the levels of exposure to metals in our study were all lower than the commonly accepted threshold limits for industrial settings (American Conference of Governmental Industrial Hygienists 2009).