Lack of autoantibody induction by mercury exposure in artisanal gold mining settings in Colombia: Findings and a review of the epidemiology literature.

http://informahealthcare.com/imt ISSN: 1547-691X (print), 1547-6901 (electronic) J Immunotoxicol, Early Online: 1–8 ! 2014 Informa Healthcare USA, Inc. DOI: 10.3109/1547691X.2014.986591

RESEARCH ARTICLE

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Lack of autoantibody induction by mercury exposure in artisanal gold mining settings in Colombia: Findings and a review of the epidemiology literature Luz Helena Sańchez Rodrı´guez1,2, Oscar Flo´rez-Vargas1, Laura Andrea Rodrı´guez-Villamizar3, Yolanda Vargas Fiallo4, Elena E. Stashenko5, and Gerardo Ramı´rez1 1

Environmental Toxicology and Toxicogenomics Laboratory, Group of Immunology and Molecular Epidemiology, Faculty of Health, 2Toxicology Unit, School of Microbiology, 3Department of Public Health, School of Medicine, 4Industrial Consulting Laboratory, School of Chemistry, and 5 Chromatography Laboratory, School of Chemistry, Universidad Industrial de Santander Bucaramanga, Colombia Abstract

Keywords

Mercury (Hg) has been implicated as an immunotoxicant in experimental animal models, but its role in the induction of human autoimmunity remains unclear due to contradictory findings. Therefore, it has been claimed that it is important to examine other populations in order to clarify the role of Hg in these diseases. The aim of this study was to investigate whether occupational Hg exposure due to artisanal gold mining is associated with the prevalence of autoimmune biomarkers. A cross-sectional study was conducted comparing Hg-exposed gold miners (n ¼ 164) with a control population (n ¼ 127). Hair, blood, and 24-h urine samples were collected for measures of Hg levels, as well as of anti-nuclear antibodies (ANA) and rheumatoid factor (RF). Participants were clinically evaluated by a general practice physician, a rheumatologist, and a toxicologist. Statistically significant differences (p50.001) were found between Hg-exposed and non-exposed groups for all Hg biomarkers tested: blood (7.03 versus 2.46 mg Hg/L), urine (3.96 versus 1.48 mg Hg/g creatinine), and hair (0.79 versus 0.39 mg Hg/g). No difference was observed in ANA (cut-off titre of 1:80; PR ¼ 0.93, 95% CI ¼ 0.45–1.90) and RF (cutoff ¼ 30 IU/mL; PR ¼ 0.062, 95% CI ¼ 0.03–1.08) status between the groups. In conclusion, the findings here do not support the hypothesis that Hg exposure due to artisanal gold mining activities had a significant impact on autoantibodies as biomarkers of autoimmune diseases. In a review context, the epidemiological findings were interpreted in light of the conflicting data in the literature about how Hg exposure was linked to development of autoantibodies. Validation of these findings in prospective studies is needed to firmly establish the role of Hg in development of autoimmunity in human populations.

Autoantibodies, autoimmunity, epidemiology, gold, mercury, mining

Introduction Mercury (Hg) is a toxic heavy metal with a well-documented association with environmental harm and human health hazard (WHO, 2012). While all species of Hg may cause health problems, toxicity, nevertheless, varies depending on species, dose, and rate of exposure (Bernhoft, 2012). The neurotoxicity and nephrotoxicity of Hg have been extensively associated and confirmed with Hg exposure both in epidemiological and experimental studies (Nakada & Imura, 1982; Tanaka-Kagawa et al., 1993; Meyer-Baron et al., 2002; Cunha et al., 2003; Franko et al., 2005; Li et al., 2010; Carocci et al., 2014). A link between immunomodulatory manifestations and Hg exposure has been supported by strong experimental evidence, but few epidemiological analyses.

Address for Correspondence: Dr Luz Helena Sańchez Rodrı´guez, Escuela de Microbiologıá, Facultad de Salud, Universidad Industrial de Santander, Carrera 32 #29-31, Oficina 421, Postcode 680002, Bucaramanga, Colombia. Tel: 5776344000. Fax: 5776348228. E-mail: lsanchez@uis. edu.co; [email protected]

History Received 14 August 2014 Revised 31 October 2014 Accepted 7 November 2014 Published online 5 December 2014

Some reports in human populations have found associations between the exposure to organic/inorganic Hg species and elevated titres of detectable autoantibodies (Silva et al., 2004) and pro-inflammatory cytokines (Gardner et al., 2010b). In addition, Hg exposure has been associated with an increased risk of systemic lupus erythematosus (Cooper et al., 2004) and greater severity of scleroderma (Arnett et al., 1996). However, other studies have failed to find an association between biomarkers of immune dysfunction and occupational (Barregard et al., 1997; Ellingsen et al., 2000) or lifestyle (Alves et al., 2006) Hg exposure. Therefore, it has been claimed that the role of Hg exposure in human autoimmune diseases will not be clarified until large populations of patients have been examined (Pollard et al., 2010). In this way, it becomes particularly important to increase the pool of epidemiological evidence about immunomodulatory effects in humans caused by Hg exposure in order to better understand its role in the autoimmunity. Autoantibodies are one of the distinguishing features of autoimmunity (Rose, 2008; Tron, 2014). Since serum rheumatoid factor (RF) and anti-nuclear antibodies (ANA) are the most prominent autoantibodies, both in terms of frequency and pathogenesis in autoimmune disorders (Kawa et al., 2008), they

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L. H. Sańchez Rodrı´guez et al.

are valuable biomarkers of immune dysfunction in epidemiological studies. The aim of this study was to investigate whether occupational Hg exposure due to artisanal gold mining was associated with the prevalence of positive RF and ANA testing.

Materials and methods


Study participants, data, and sample collection This study was designed as a cross-sectional study comparing Hg-exposed gold miners from a mining community with a control population. The participants were selected through a nonprobabilistic sampling by availability; where the residents from each town were invited to participate in the study via general information meetings and messages delivered through local media and house-to-house visits, among others. Applying a random selection sampling procedure in all towns under study was logistically difficult for two reasons: (1) during the sampling collection phase (December 2011–August 2012), the Colombian Congress debated a bill to regulate mining issues, which generated concern in the gold mining community, and (2) a large part of the country, including the northeast of Colombia (where the places of study are located), was hit by heavy rain and flooding, which affected the access routes to these municipalities. The study population consisted of 291 people: 164 artisanal gold miners from four gold mining districts (Hg-exposed group) and 127 individuals from three nearby non-mining towns (nonexposed group). Both groups had similar socio-demographic characteristics; all participants were between 18–62 years old. In addition, both Hg-exposed and non-exposed populations live in different places within the same geographical region of the Andes in northeast Colombia. All these places are located &2700 m above sea level and in a temperature range of 6–18 C throughout the year. Nevertheless, these populations have different sources of water and, hence, the non-mining towns’ watersheds are not affected directly by gold-mining wastes from gold mining districts but (possibly) indirectly by Hg contamination through air; although Hg concentration in the air was not measured. All subjects were enrolled in the study following informed consent. Subjects in the Hg-exposed group were residents of the gold mining districts during (at least) the 5 years prior to the study, in the last of which they had direct contact with Hg vapors. Subjects in the non-exposed group were permanent residents of the non-mining towns and they had no life history of direct contact with Hg vapors. Clinical and epidemiological information were collected for each participant through a detailed personal interview. Medical examination included determination of general clinical status (e.g. self-reported systemic diseases diagnosed by a physician, medicine consumption, and dental amalgams) and lifestyle habits (e.g. smoking, coffee, alcohol, and fish consumption). The examination was performed by three general practice physicians; those participants with positive biomarker results were also examined by two clinicians, one of whom was a specialist in rheumatology and the other was a clinical toxicologist. Epidemiological data was collected under the guidance of trained interviewers who administered a face-to-face questionnaire in Spanish that included sections on demographics and occupational exposures (e.g. use of protective equipment and food consumption during Hg-gold amalgam manipulation). Hg lifetime exposure and the periods of time of higher use of Hg as well as the fish consumption were also registered in the questionnaire. The periods of time of exposure were registered in terms of minutes for exposures that took place in the last year and in terms of years for the lifetime exposure. Dietary intake concentration of Hg due to fish consumption was estimated according to the reported average concentration of mg Hg/kg fish by fish type in

J Immunotoxicol, Early Online: 1–8

Colombia (Marrugo-Negrete et al., 2008). This calculus was performed using the following equation: E ¼ (C I R EF)/BW, where E ¼ exposure rate (mg Hg/kg body weight/day), C ¼ Hg concentration in fish (mg Hg/kg of most common fish type consumed), IR ¼ intake rate of fish (average in g/intake), EF ¼ exposure factor (frequency of fish consumption/day), and BW ¼ body weight (kg) (ATSDR, 2005). Samples of hair, blood, and urine were collected from each person. Hair samples ( & 50–100 hairs) were cut out from the occipital region of the head as close as possible to the scalp, and were packed in identified paper bags and protected from moisture in a desiccator until quantification of Hg. Peripheral blood samples were collected in two separate Vacutainer tubes, one treated with heparin for Hg measurement and the other without anticoagulant; containing a clot activator and a separator gel to obtain serum by centrifugation (1000 rpm, 15 min) for measures of immune biomarkers. Twenty-four-hour urine samples were collected in acid-washed plastic bottles for use in Hg and creatinine determinations. Immediately after collection, blood and urine samples for Hg analysis were stored at 4 C and processed within 48 h. Serum samples for ANA and RF testing were stored at 20 C until tested. Determinations of Hg and immune biomarkers were carried out by two chemists and one immunologist who were blinded to all information related to the study subjects. All results were reviewed by a panel of two expert researchers in the fields of toxicology and biochemistry. This study complied with the Colombian Medical Code of Ethics. It was performed in accordance with ethical standards stated in the 1964 Declaration of Helsinki. The Committee on Medical Ethics of Universidad Industrial de Santander approved the research protocol. The study was performed between June 2011 and July 2013. Mercury analysis All the reagents used in the assay procedures were of analytical reagent grade. All implements that came into contact with the samples were pre-washed with nitric acid (10%) solution. Analytical accuracy and precision were determined through use of reference standards (IAEA 086, International Atomic Energy Agency, Vienna, Austria; and SRM 955C and 2670A, National Institute of Standards and Technology, Bethesda, MD) and blanks. No more than 20–30 samples were analyzed in a day. Reference standards were within 10% of certified values. Our laboratory is accredited by the ISO/IEC 17025-2005. Limits of detection (LOD) and quantification (LOQ) were calculated by averaging the measurement of 22 blanks fortified with a known amount of Hg (0.5 mg/L for blood, 0.3 mg/L for urine) and summing the resultant 3- or 10-fold SD (standard deviation) values for the blanks, respectively (McNaught et al., 1997; Miller & Miller, 2002). In the case of Hg in hair, the LOD was calculated by multiplying the SD by the value of the t-statistic (95%, n 1) of three replicates/ sample; the LOQ was calculated as twice the LOD. Determination of Hg in hair samples Total H-Hg concentration was quantified using an RA-915+ atomic absorption spectrometer mercury analyzer with Zeeman background correction and coupled to a RP-91C pyrolysis chamber (Lumex, St. Petersburg, Russia). Briefly, the first 3 cm of the proximal segment of the root of each hair sample was finely cut into 3-mm fragments using stainless steel scissors. The hair fragments from a subject were then thoroughly mixed, then divided into equal parts (each mixed separately), and then all re-combined; this process was performed three times to ensure that all hair fragments were distributed evenly throughout the final sample. Triplicate hair samples/subject of the final mixture


DOI: 10.3109/1547691X.2014.986591

(each 5–10 mg) were placed in quartz sample holders and transferred to a pyrolyzer set at 800 C. The resultant vapor from each sample was directed to the optical window of a spectrophotometer and the absorption measured at 254 nm. All data were analyzed using software associated with the spectrophotometer. Quantitation of the amount of Hg in a given sample was done by extrapolating from a standard curve constructed using different Hg concentrations. The working range of Hg was set at 100–8500 mg/kg; the LOD and LOQ for the assay were, respectively, 55 and 109 mg/kg. The IAEA 086 reference standard and blanks were evaluated after every 20 samples to guarantee equipment was operating correctly; average recoveries for the IAEA 086 were from 825–840 mg/kg; the relative error was 510%.

Autoantibodies and mercury exposure in artisanal gold mining

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chain-specific conjugate. Slides were examined with a Leitz Dialux 20 fluorescence microscope (Leica Microsystems, Allendale, NJ) at 40 magnification. ANA patterns (nuclear, nucleolar, and cytoplasmic) were identified using a standard classification method. Antibody titre was expressed as the final dilution. Negative and positive controls with known antibody titre were used for quality control. The cut-off employed was 1:80. A Rheumatoid Factor (RF) test was performed using a commercial latex agglutination slide test (BioSystems; Barcelona, Spain) with both negative and positive controls. In this test, the presence of agglutination indicates a level of RF in the sample 30 IU/ml, while a negative result indicated a level of RF of 530 IU/ml. All assays were carried out according to manufacturer instructions. The laboratory performed well in international quality control programs; it is accredited to ISO/IEC 17025:2005.

Determination of Hg in blood and urine samples Total B-Hg and U-Hg concentrations were measured using a S4 atomic absorption spectrometer equipped with a VP100 hydride generation system (Thermo Electron Co., Cambridge, UK). The working range of Hg was established between 0–20 mg/L, with a dynamic range from 2.45–20.00 mg/L. Quantitation was made using a standard curve constructed with different Hg concentrations from an Hg standard of 1000 mg/L. Nitrogen was used as the carrier gas at a flow rate of 100 ml/min and with a sample fluid flow rate of 7 ml/min. The solutions for hydride generation were NaBH4 (1% [w/v]), NaOH (1% [w/v]), and HCl (10% [v/v]) for B-Hg determinations, and NaBH4 (3% [w/v]), NaOH (1.5% [w/v]), and HCl (50% [v/v]) for U-Hg determinations. Hg detection was performed at 253.7 nm. Data were collected using software provided with the equipment. The LOD and LOQ were, respectively, 1.07 and 2.45 mg/L for B-Hg and 0.74 and 2.49 mg/L for U-Hg. The SRM 955C and 2670A reference standards and blanks were tested every 10 samples to guarantee the equipment was operating correctly. Average recoveries ranged from 70–95% for SRM 955C and from 80–115% for SMR 2670A. The relative error did not exceed 10%. Sample preparation for B-Hg determination was briefly as following: 2.5 ml heparinized whole blood was treated with 3.5 ml KMnO4 (5% [w/v]), 0.75 ml HNO3 (65% [w/w]), and 1.25 ml of H2SO4 (98% w/w) to remove both organic matter and fatty acids, and so release the Hg. The tubes were thoroughly mixed after each reagent was added and then left undisturbed for 15 min. After 2 ml K2S4O8 (5% [w/v]) was added, the sample was thoroughly mixed and incubated in a waterbath at 85–95 C for 2 h. Finally, and after the solution was allowed to cool to room temperature, 0.5 ml NH2OHHCl (10% [w/v]) and 2 ml HCl (37% [w/w]) solutions were added and the sample then thoroughly mixed and filtered through Whatman filter paper No. 41. The volume of the filtrate made up to 25 ml with distilled water; 0.5 ml pure octanol was added as an anti-foaming agent. The samples were then analyzed. Sample preparation for U-Hg determination was as follows: 10 ml urine was treated with 7 ml KMnO4 (5% w/v), 1.2 ml HNO3 (65% w/w), and 1.2 ml H2SO4 (98% w/w) to remove both organic matter and fatty acids, and thereby release the Hg. The Hg in the sample was then reduced to elemental Hg by action of the NaBH4 in acid medium as described above, and the samples were then analyzed. Urinary creatinine was measured by the Jaffe spectrophotometric method; this value was used to adjust the results of the urinary Hg concentration. Immunology testing Anti nuclear antibodies (ANA) were detected by standard immunofluorescence using commercial Hep-2 ANA slides (INOVA Diagnostics, San Diego, CA), which use an IgG heavy

Data analysis Statistical analysis was performed using STATA Version 11.1 (StataCorp., 2009). Study sample size was determined by using ¼ 0.05 and a power of 80% to detect differences between the Hg-exposed and non-exposed groups. Normal distribution of the variables was tested using the Shapiro-Wilk test. As most of the clinical and Hg variables showed a non-normal distribution, the differences between groups were examined using the MannWhitney U-test for continuous variables and Chi-squared test for categorical variables; the differences were considered statistically significant when p50.05. Both arithmetic and geometric means were calculated for all Hg concentrations. The results of ANA and RF were described using central tendency measures and dichotomized according to their cut-off values for multivariate analyses. Binomial multiple regression analysis was used to adjust the relationship between the prevalence of increased titre of ANA and RF using the cut-off values described above as outcome variables and exposure status (exposed versus controls) as the main explanatory variable. Also, potential confounder variables were considered in this analysis. A purpose-guide approach was used for data modeling. The prevalence ratio (PR) and coefficients of the models are presented with 95% confidence intervals (95% CI).

Results A descriptive summary of the study groups is presented in Table 1. Distribution of age, sex, smoking status, coffee consumption and estimated Hg intake due to fish consumption were significantly different between both groups (p50.05). During the house-to-house survey we knew in detail how the artisanal gold mining procedure was carried out: i.e. most of the miners took the Hg-gold amalgams from caves or rivers to their houses and, once there, they were burned intermittently (a procedure in which women were commonly involved). As a result, the house was the most common place of exposure to Hg vapors (Table 1), with a median frequency of exposure of 12 times/year (IQR ¼ 3–52) and 30 min/time (IQR ¼ 15–60). On the other hand, Hg-exposed and non-exposed groups showed a similar proportion of participants with previous diagnostics of diabetes mellitus (3.7% versus 5.5%; p ¼ 0.469), high arterial pressure (14.9% versus 9.2%; p ¼ 0.130) and renal disease (3.1% in both groups; p ¼ 0.979). Statistically significant differences (p50.001) were found between the groups for all Hg biomarkers tested (Table 2). The levels of Hg found in both groups exceeded the normal concentration (Veiga & Baker, 2004) for blood (10 mg Hg/L) in 29.8% of the Hg-exposed and 4% of the non-exposed participants, whereas the action level for urine in exposed (20 mg Hg/g creatinine) and the alert level non-exposed (5 mg Hg/g creatinine)

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Table 1. Socio-demographic characteristics and Hg exposure of study populations. Hg-exposed (n ¼ 164), n (%) or median (IQR)


Variable Age (years)a Sexb Female Male Occupationb Gold mining activities Agriculture and livestock Building work Home care Others Smokersb Alcohol drinkersb Coffee consumptionb Fish consumptionb Estimate Hg intake by fish (mg Hg/kg/d; 105)b Amalgam fillings (number)b Total direct Hg vapor exposure last year (min) Place of Hg vapor exposure last year House Mine River Other Lifetime Hg vapor exposure (years)

40 (31–46) 61 (37.2) 103 (62.8) 74 6 18 44 22 22 80 144 155 1.5 3 720

(45.1) (3.6) (10.9) (26.8) (13.4) (13.4) (48.8) (87.8) (94.5) (0.5–3.7) (2–6) (180–3180)

111 31 47 19 19.5

(67.6) (18.9) (28.6) (11.6) (9–25)

Non-exposed (n ¼ 127), n (%) or median (IQR)

p Value

47 (39–52)

0.000

67 (52.7) 60 (47.2)

0.008

0 23 (18.1) 28 (22.1) 44 (34.6) 32 (25.2) 5 (3.9) 56 (44.1) 99 (77.9) 117 (92.1) 0.62 (0.1–2.7) 4 (2 – 6) 0

50.001

0.006 0.427 0.025 0.414 50.001 0.081

0 0 0 0 0

IQR, Inter-Quartile Range. Mann Whitney U-test/Wilcoxon rank-sum test for differences between groups. b Chi-square test. a

Table 2. Hg exposure and immunological biomarkers values in studied populations. Biomarkers Hg exposure Blood Hg (mg Hg/L)a Urine Hg (mg Hg/g creatinine)a Hair Hg (mg Hg/g hair)a Immunologic ANA 41:80b RF 430 IU/mLb

Hg-exposed (n ¼ 164), n (%) or median (IQR)

Non-exposed (n ¼ 127), n (%) or median (IQR)

p Value

7.03 (3.39–11.02) 3.96 (1.34–9.57) 0.79 (0.51–1.31)

2.46 (1.10–4.82) 1.48 (0.98–2.83) 0.39 (0.24–0.69)

50.001 50.001 50.001

15 (9.15) 2 (1.23)

15 (11.81) 7 (5.51)

0.458 0.036

IQR, Inter Quartile Range. Mann Whitney U-test/Wilcoxon rank-sum test for differences between groups. b Chi-square test. a

people were exceeded by 15.8% and 12.6% of the Hg-exposed and non-exposed participants, respectively, and the normal concentration for hair (1 mg Hg/g hair) was exceeded by 34% of the Hg-exposed and 15% of non-exposed participants. A total of 7% of the Hg-exposed people but none of the non-exposed people exceed the three normal concentrations. Statistically significant Spearman rank correlations (p50.001) were found between B-Hg and U-Hg ( ¼ 0.24); U-Hg and H-Hg ( ¼ 0.32); and H-Hg and B-Hg ( ¼ 0.49). In addition, the time of exposure to Hg vapors for the last year (in minutes) and for the lifetime (in years) were significantly correlated (p50.001) with all Hg biomarkers: B-Hg ( ¼ 0.39 and 0.41), U-Hg ( ¼ 0.35 and 0.26), and H-Hg ( ¼ 0.33 and 0.39). No difference was observed in ANA status between Hg-exposed and non-exposed groups; although a suggestive difference that is marginally statistically significant (p ¼ 0.036; PR ¼ 0.22; 95% CI ¼ 0.04–1.05) was observed in RF status (Table 2). Binomial multivariate models showed that titres of ANA41:80 and concentrations of RF 430 UI/mL were not associated with Hg-exposed people and Hg in blood, urine, and hair after adjustment for the possible confounding variables: age, sex, alcohol and coffee consumption, smoking status, estimated

dietary intake of Hg through fish consumption, and pesticide exposure (Table 3).

Discussion Despite the available knowledge about the hazards associated with Hg exposure, human populations continue to be exposed to this metal from a variety of sources. The main sources of exposure among individuals who are not occupationally exposed are dental amalgams (in the case of inorganic Hg) and contaminated fish (in the case of methyl-Hg). On the other hand, the sources of occupational exposure to Hg vary considerably worldwide. In Colombia, for example, the main occupational exposure to Hg, particularly elemental Hg, occurs during the process of separating gold by amalgamation in mines, a procedure used since colonial times. While a mining boom in Colombia has increased the levels of operations that seek to recover gold, many of the large-scale operations are in effect ‘‘Hg-free’’ as a result of changes in national policies. Nevertheless, the use of Hg by smaller-scale and artisanal gold mining operations are still very common throughout the country (UPME, 2007). Previous reports indicate that the population’s exposure to Hg may cause autoimmune dysfunction and systemic inflammation in


DOI: 10.3109/1547691X.2014.986591

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Table 3. Binomial regression models for association between immunological biomarkers and Hg exposure.


Model

Main outcome variable

Explanatory variables

PR

95% CIa

p Valuea

Binomial (n ¼ 290)

Prevalence of ANA 41:80

Gold miners group Blood Hg (log) Urine Hg (log) Hair Hg (log)

0.93 1.08 11.13 1.31

0.45–1.90 0.76–1.54 0.86–1.47 0.85–1.99

0.840 0.643 0.360 0.214

Binomial (n ¼ 291)

Prevalence of RF 430 IU/ml

Gold miners group Blood Hg (log) Urine Hg (log) Hair Hg (log)

0.21 0.81 0.98 1.44

0.03–1.08 0.39–1.65 0.58–1.67 0.64–3.23

0.062 0.558 0.966 0.371

PR, Prevalence Ratio; CI, Confidence Intervals. a Adjusted by age, sex, alcohol and coffee consumption, smoking status, estimated dietary intake of Hg through fish consumption and pesticide exposure.

affected people. In human populations it has been reported that exposure to either organic or inorganic Hg species is associated with elevated titres of detectable ANA and anti-nucleolar autoantibodies (ANoA) (Silva et al., 2004; Alves et al., 2006; Gardner et al., 2010b; Nyland et al., 2011) as well as thyroglobulin antibodies (Gallagher & Meliker, 2012). Furthermore, the levels of pro-inflammatory cytokines such as tumor necrosis factor (TNF)-, interferon (IFN)- , and interleukin (IL)-1 were significantly higher in Hg-exposed gold miners with ANA+ and ANoA+ as compared to non-exposed populations (Gardner et al., 2010b). Recently, a paper was published that showed that Hg exposure significantly increased titres of serum antibodies to a variety of self-antigens, e.g., glutathioneS-transferase- (Motts et al., 2014). However, our results show that occupational exposure to Hg vapors due to artisanal gold mining activities is not associated with the prevalence of biomarkers of immune dysfunction such as ANA and RF; the most common autoantibodies in autoimmune disorders (Kawa et al., 2008). On the other hand, it is important to clarify that, although certain socio-demographic characteristics were statistically different between the two studied groups (Table 1), the results were adjusted by these variables and, therefore, they are un-confounded. The contradictory findings between our study and those previously reported by other researchers might be the result of the influence of genetic, environmental, and exposure factors that are highly variable across populations, as well as the cut-off between ‘‘normal’’ and ‘‘abnormal’’ results in each assay. Overall, the levels of Hg in our study were generally low in comparison with those observed in other studies with a similar focus (Ellingsen et al., 2000; Silva et al., 2004; Alves et al., 2006; Gardner et al., 2010b; Nyland et al., 2011; Motts et al., 2014), although our levels were higher than those reported in other artisanal gold miners in Asia and Africa (Bose-O’Reilly et al., 2010a,b) and those recently reported in Madre de Dios, Peru (Yard et al., 2012). In addition, the number of women included in our study is likely sufficient to show that, even though women are more likely than men to develop autoimmune diseases (Jacobson et al., 1997), the exposure to Hg did not affect their health status in at least this respect. It is also important to note that, contrary to most previous studies in which they compared Hg exposure due to artisanal gold mining activities by using different Hg biomarkers, e.g. H-Hg in Hg-exposed group versus U-Hg in non-exposed group (Silva et al., 2004; Gardner et al., 2010b; Motts et al., 2014), we determined all Hg biomarkers in both groups and, therefore, it allows us to perform direct comparison of Hg levels between groups for each biomarker. The studies that claim that Hg exposure due to gold mining increases serum titres of autoimmune biomarkers have been carried out in populations of the Brazilian Amazon

(Silva et al., 2004; Alves et al., 2006; Gardner et al., 2010b; Nyland et al., 2011; Motts et al., 2014). In this region people are not only exposed to both inorganic and organic species of Hg, but also have a high prevalence of malaria (Silva et al., 2004; Gardner et al., 2010b; Motts et al., 2014). In contrast, neither Hg-exposed nor non-exposed populations studied in our work are endemic areas for malaria or other tropical infectious diseases due to their geographical location, &2700 m above sea level, and this high elevation means low temperatures throughout the year, so the occurrence of most of the tropical infectious diseases (mainly those transmitted to humans through the bite of infected mosquitoes) is unlikely since these vectors need a warm climate to develop. In addition, the methyl-Hg exposure due to fish consumption is relatively low in our study population since most of the fish that they consume come from fish hatcheries located near to these towns but with a different source of water; three rivers and several brooks originate in this area, moreover in these towns the fish consumption is not that high. Since hair is an excellent biomonitoring material to evaluate methyl-Hg exposure via food ingestion (Veiga and Baker, 2004), the concentrations of H-Hg found in this study suggest that these communities have low methyl-Hg exposure because of the consumption of fish. Regarding the cut-off values used to define positive ANA test results, there is no clear consensus concerning these values. Nevertheless, as a general rule, the higher the titre, the more likely the patient has an autoimmune disease (Peene et al., 2001; Ghosh et al., 2007). In adults, it has been suggested that a titre of 1:80 can be taken as borderline, because, in the majority of cases with this titre, no diagnostically relevant ANA specificities were found (Sack et al., 2009). Supporting this view, recent findings demonstrate that the positive predictive value of ANA test positivity for any anti-nuclear antibody-associated rheumatic disease with a cut-off of 1:40 was 8.8% and it was slightly higher using higher-titre cut-offs (Abeles and Abeles, 2013). Therefore, we outline the cut-off used in each of the studies discussed here so that readers can draw their own conclusions. While it is true no previous studies carried out in Brazilian Amazon populations exposed to Hg found a correlation between autoantibodies and malaria status, it is equally true that patients with malaria have autoantibodies (Pradhan et al., 2002; Gallien et al., 2011). In a study of 173 acute hospitalized patients who were suffering from malaria, positive ANA and anti-neutrophil cytoplasmic antibodies (ANCA) test results were found in more than 20% of cases infected with Plasmodium falciparum and 15% of cases infected with Plasmodium vivax. Nevertheless, none of these autoantibodies had similar specificity to those found in systemic lupus erythematosus such as anti-double-stranded DNA (dsDNA) (Pradhan et al., 2002).


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Experimental evidence has shown that, during the blood-stage of murine malaria, the autoantibodies produced react with several nuclear antigens, e.g. anti-single-stranded (ssDNA) IgG antibodies, and that this is a critical part of the protective immune response (Mannoor et al., 2013). In addition, and regarding Hg exposure, in a study carried out in a Brazilian Amazon community an association was found between reported history of malaria and reported past exposure to Hg in gold mining. The findings of this study showed that the odds of reporting a past malaria infection in people exposed to Hg through fish consumption was 4-times higher for those who also reported a history of having worked with Hg in the mining process (Crompton et al., 2002), suggesting that Hg exposure could increase the risk of infection. This concept is supported by experiments in mice exposed to Hg in which it was observed that Hg blocks the acquisition of immunity, and, hence, impaired host resistance to malaria (Silbergeld et al., 2000). All this evidence prompts us to consider that the malaria status may influence the development of autoantibodies in people exposed to Hg. In fact, Silva et al. (2004) reported that people with low hair Hg concentrations (58 mg/g) had a positive correlation (p50.05) of personal history of malaria ( 4 infections) with detectable ANA (titre 41:40). On the other hand, it is also true that, in the case of miners from the Brazilian Amazon region, they are not only exposed to elemental Hg vapors from the occupational burning of an Hg-gold amalgam, they are also exposed to methyl-Hg through consumption of fish from the river contaminated with Hg (Gardner et al., 2010b). Both organic (methyl-Hg and ethyl-Hg) and inorganic (HgCl2) species of Hg elicit a differential immune response by human peripheral blood mononuclear cells (PBMC) (Gardner et al., 2010a). Furthermore, and regarding the development of autoantibodies, there is experimental evidence from A.SW mice studies that show that the simultaneous presence in the lymph node of methyl-Hg and Hg2+ is related with an increment in autoantibodies. The presence of these two Hg species was due to selective accumulation of Hg2+ through demethylation of methylHg following a treatment with methyl-Hg (Havarinasab et al., 2007). In the context of human populations, it has been reported that, in Hg-exposed gold miners (IQR ¼ 3.67 mg Hg/L urine) with ANA+ and ANoA+ (titre 1:40), levels of pro-inflammatory cytokines IL-1 , TNF, and IFN but not IL-17 were significantly higher compared to in diamond and emerald mining communities (IQR ¼ 0.268–0.960 mg Hg/g hair). No differences were found in the levels of anti-inflammatory cytokines IL-1Ra, IL-4, and IL-10. Nevertheless, all those populations had exposure to methyl-Hg through consumption of contaminated fish (Gardner et al., 2010b). In addition, in people mainly exposed to methylHg, a positive association was found between Hg exposure and the levels of IL-1 , IL-4, IL-6, TNFa, and IFN . However, the levels of all these cytokines were decreased in those individuals with high Hg levels (IQR ¼ 103.1 mg Hg/L blood) and ANA+ compared with those with low Hg levels (IQR ¼ 15.3 mg Hg/L blood) and ANA+ (titre41:80) (Nyland et al., 2011). Therefore, the interaction between these two species of Hg could explain, at least in part, the differences found in the profile of cytokines and their relationship with the presence of autoantibodies in people exposed to both elemental Hg and methyl-Hg and those exposed only to one species of Hg. Taking into account the previous scenarios, we hypothesized the combination of organic and inorganic species of Hg, as well as infectious diseases status, may exert a different effect on immune function and, as a consequence, foster an environment conducive to development of an autoimmune-like phenomenon. In fact, it has been claimed that the risk of autoimmune diseases is influenced not only by a genetic component, but also by


environmental exposure to both pathogens and xenobiotics (Rioux & Abbas, 2005; Rooney et al., 2012; Smyk et al., 2012). In this way, the proposed phenomenon may alternatively explain the changes observed among populations noted by Silva et al. (2004), where people exposed to inorganic Hg from gold mining activities and methyl-Hg via fish consumption (median ¼ 4 mg Hg/L urine), as well as malaria status (490%) had more prevalent ANA+ compared to those exposed only to methyl-Hg (51% versus 3.6% for titres 41:40 and 17% versus 1% for titres 41:80; median ¼ 8 mg Hg/g hair). Moreover, a high ANA titre does not necessarily mean autoimmunity is present. There is clinical evidence that shows patients presenting a high-titre ANA (1:640)—but without a clinically diagnosable anti-nuclear antibody-associated rheumatic disease at the time of evaluation—do not develop connective tissue disease over a 10-year follow-up period (Wijeyesinghe & Russell, 2008). Regarding RF, the suggestive significant difference we found with the RF status might be due to the smoking status (Table 2), although this difference did not remain statistically significant after adjustments (Table 3). Nevertheless, it has been reported that tobacco smoking increases the prevalence of RF positivity in the general population (Tuomi et al., 1990; Jonsson et al., 1998). In addition, due to the few cases with a positive RF test result (nonexposed ¼ 2 and Hg-exposed ¼ 7) it is not clear whether Hg vapors in this population play a protective role in the development of RF; a larger sample size would be required to validate this trend. On the other hand, the genetic component could explain a substantial part of this phenotype. A study carried out in this geographical area has reported an association of the polymorphisms +148A and +1902G in the IL-4 receptor alpha gene (IL4RA) with the presence of RF and high RF titres in patients with rheumatoid arthritis; where the minimum allele frequency in the control population for these two alleles was, respectively, 47.1% and 34.3% (Moreno et al., 2007). Finally, in an interesting paper, Shoenfeld (2013) called attention to the fact the immune response is everywhere and that, due to the ubiquitous nature of the innate and adaptive response, everything is potentially autoimmune until proven otherwise. Therefore, ANA and RF tests, despite being useful clinical tools, need to be used in conjunction with other evidence and clinical judgement in order to validate the diagnosis of autoimmunity. Regarding this no clinical signs and symptoms of autoimmune diseases were observed in the participants of this study. In conclusion, the results here suggest that Hg exposure due to artisanal gold mining activities do not have a significant impact on the biomarkers of immune dysfunction ANA and RF. Nevertheless, both positive and negative results must be treated with caution, since this was an exploratory study and the sample size was limited for logistical and safety reasons. However, despite a relatively wide confidence interval (95%), it is powerful enough to detect significant clinical and epidemiological differences between occupationally exposed and non-exposed groups. In this way, validation of these findings in prospective studies is required to firmly establish the role of Hg in the development of autoimmunity in human populations.

Acknowledgments The authors want to thank all people who participated in the study by allowing access to the hair, blood, and urine samples and for their patience and kindness. The authors also pay especially thanks to Sara Sańchez, Query Mora and Diana Go´mez for their excellent work in the communities, as well as to Carmen C. Cabrales, Lina Flo´rez and Xiomara Gonza´lez for their technical assistance, and to Diana Jaimes, Brigith Sierra, and Alejandro Estevez for their assistance in the clinical evaluation of participants. Thanks also go to Michael Bramhall for his proofreading of the MS and suggestions.

DOI: 10.3109/1547691X.2014.986591

Declaration of interest The authors report no conflicts of interest. This work was funded by Colciencias, grant No. 1102-519-29272, and Universidad Industrial de Santander, Bucaramanga, Colombia.


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