Journal of Environmental Science and Health, Part A (2014) 49, 787–797 C Taylor & Francis Group, LLC Copyright ISSN: 1093-4529 (Print); 1532-4117 (Online) DOI: 10.1080/10934529.2014.882207
Health effects and arsenic species in urine of copper smelter workers TADEUSZ HALATEK1, HALINA SINCZUK-WALCZAK2, BEATA JANASIK1, MALGORZATA TRZCINKA-OCHOCKA1, RENATA WINNICKA2 and WOJCIECH WASOWICZ1 1
Department of Toxicology and Carcinogenesis, Nofer Institute of Occupational Medicine, Lodz, Poland Outpatient Clinic of Occupational Disease, Nofer Institute of Occupational Medicine, Lodz, Poland
2
The aim of this study was to compare indices of exposure in workers employed at different work posts in a copper smelter plant using neurophysiological tests and to evaluate the relationship between urinary arsenic species with the aid of sensitive respiratory and renal biomarkers. We have attempted to elucidate the impact of different arsenic speciation forms on the observed health effects. We focused on the workers (n = 45) exposed to atmospheres containing specific diverse mixtures of metals (such as those occurring in Departments of Furnaces, Lead and Electrolysis) compared to controls (n = 16). Subjective symptoms from the central (CNS) and the peripheral (PNS) nervous system were recorded and visual evoked potential (VEP), electroneurography (ENeG) and electroencephalography (EEG) curves were analysed. Levels of airborne lead (PbA), zinc (ZnA) and copper (CuA) and Pb levels in blood (PbB) and the relationships between airborne As concentrations (AsA) and the urinary levels of the inorganic (iAs); As(+3), As(+5) and the organic; methylarsonate (MMA(V)), dimethylarsinate (DMA(V)) and arsenobetaine (AsB) arsenic species were determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Effects of exposure were expressed in terms of biomarker levels: Clara cell protein (CC16) in serum as early pulmonary biomarker and β 2 -microglobulin (β 2 M) in urine and serum, retinol binding protein (RBP) as renal markers, measured by sensitive latex-immunoassay (LIA). Abnormal results of neurophysiological tests, VEP, EEG and ENeG showed dominant subclinical effects in CNS and PNS of workers from Departments of Lead and Furnace. In group of smelters from Departments of Furnace exposed to arsenic above current TLV, excreted arsenic species As(+3) and As(+5) seemed to reduce the level of Clara cell protein (CC16), thereby reducing anti-inflammatory potential of the lungs and increasing the levels of renal biomarker (β 2 M) and copper in urine (CuU). The study confirmed deleterious arsenic effects to the kidney by increased levels of low-molecular weight protein in urine and the extent of the renal copper accumulation/excretion. The results of our work also support the usefulness of application of the sensitive neurophysiologic tests, such as VEP, EEG and ENeG, for the detection of early subclinical effects of the exposure of the nervous system in copper smelters. Keywords: Copper smelter, arsenic speciation, neurological tests, kidney, Clara cell protein.
Introduction In copper smelter works, tasks entailing exposure to harmful chemical agents in dust and fumes containing many harmful metals, including high arsenic levels, resulted in impairment of the health of workers.[1,2] Chronic arsenic exposure involves increased risk to various forms of cancer and numerous non-cancer conditions, such as diabetes, skin diseases, chronic cough, and toxic effects in liver, kidneys, cardiovascular system, and the peripheral and central nervous systems.[3,4] Address correspondence to Tadeusz Halatek, Nofer Institute of Occupational Medicine, Sw. Teresy 8, 91-348 Lodz, Poland; E-mail:
[email protected] Received September 11, 2013. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/lesa.
The aim of this study was to assess and compare in medical examination the status of the nervous, respiratory and renal systems of the workers employed in a copper smelter plant at the Departments of Convectors, Lead and Electrolysis, exposed by inhalation to dusts differing in their content of metals depending on production processes. Each of the production steps (e.g., Department of Lead or Department of Electrolysis) is characterized by a specific diverse mixture of harmful metals with different activity to exposed workers, including several synergistic harmful (As and Pb) or protective (Zn and Cu against Pb) effects. In occupational populations exposed to such mixtures of metals, those effects may be important for predicting the outcomes of those interactions.[5] Effects of nervous system exposure to arsenic may be attributable to impaired conduction velocity in peripheral motor or sensory nerves, or symptoms in the form of paresis or numbness, or numerous
788 neurophysiological changes.[6,7] Arsenic inhalation resulted in As accumulation in lung, and in kidney - the target organ for As accumulation and excretion.[8,9] Harmful effects of arsenic to kidneys, confirmed in several studies in animal model, were accompanied by Cu accumulation. [10,11] Inorganic arsenic species: iAs, As(+3), As(+5) and the organic species: methylarsonate (MMA(+5)), dimethylarsinate (DMA(+5)) and arsenobetaine (AsB) were determined in urine of workers exposed to arsenic. It has been found that arsenic speciation forms in the work environment can influence metal toxicokinetics and toxicodynamics in worker toxicity.[12] Several studies of arsenic toxicity demonstrated the importance of the protection against oxidative stress.[13–16] The lung surfactant proteins in the epithelial fluid capable of suppressing free radical formation constitute an effective barrier of protection against oxidative stress induced by airborne pollutant particles or gases inhaled into the lungs.[17] Epithelial Clara cells secrete Clara cell protein (CC16), the main tool of respiratory tract protection against oxidative stress and inflammation.[18,19] Therefore, the inflammatory potential with particular regard to the protective role of CC16 in the respiratory system was compared to indices of exposure at different work posts in the copper smelter plant. The results of neurotoxicological tests and the association of the arsenic species in urine with sensitive respiratory and kidney biomarkers were also evaluated.
Subjects and methods In the presented study we focused on copper smelter workers employed at Departments of Convectors (n = 20), Lead (15) and Electrolysis (n = 10) and the control group (n = 16), employed elsewhere at the same plant. Samples of worker blood, urine, and copper foundry dust were collected. Blood and serum samples were collected by vein puncture into Becton Dickinson Vacutainers. Each sample (urine, blood and serum) was stored at –20◦ C until determination. All examinations were performed after prior approval of the Medical Ethical Commission (Act on Medical Profession).[20]
Methods Neurological assessment included subjective neurological symptoms (SNS) and peripheral neurological symptoms (PNS) with sensitive electrophysiological tests; electroencephalographic (EEG), visual evoked potential (VEP) and electroneurographic (ENeG) measurements. Levels of airborne copper (Cu-A), lead (Pb-A), arsenic (As-A) and zinc oxide (ZnO) were determined. Spirometric measures FVC, FEV1 , FEV1 % and FEF50 , of workers were done. Urinary levels of As, As(+3), As(+5), MMA, DMA, Asbetaine were determined by ICP-MS. Urine and serum β 2 -
Halatek et al. microglobuline (β 2 M-U, β 2 M-S), retinol binding protein (RBP) in urine and Clara cell protein (CC16) in serum as pulmonary biomarker were measured by sensitive latex immunoassay (LIA). Urinary levels of creatinine and copper (Crea-U and Cu-U, respectively) were assessed. Serum CuS, Zn-S, Fe-S and metaloproteinase-9 (MMP-9) levels and lactate dehydrogenase (LDH) activity were assayed. Blood levels of lead (Pb-B) were also determined. Neurophysiological methods Electroencephalographic (EEG) measurements were performed on a Pegasus digital EEG unit provided with the international system 10–20 electrodes using the bipolar technique. They were taken at rest and during flash activation, hyperventilation (3 min) and photo-stimulation (5, 10, 15, 20 and 25 Hz). Frequency, amplitude, morphology and localisation of the brain bioelectric function rhythms and their reaction to stimuli were assessed in EEG recordings. EEG recordings were classified into three groups: normal, borderline and abnormal. In the group of abnormal recordings, four subgroups of changes were distinguished: generalised, focal, paroxysmal and asymmetrical. The visual evoked potentials (VEP) were recorded using a Neuromatic 2000 C (Dantec, Scovlunde, Denmark) unit. The checkerboard reversal pattern stimuli were applied to each eye. The responses were received from the active electrode placed at the cranial midline, 3 cm above the inion. A total of 200 evoked responses were averaged during 300 ms analysis time. N1, P100 and N2 latencies, N1P100 and P100N2 amplitudes, as well as VEP configuration were assessed. Electroneurographic (ENeG) examination was performed using the Dantec Neuromatic 2000 C (Dantec) unit to assess typical parameters of conduction velocity, latency and amplitudes in motor fibres and in the medial nerve, perennial nerves, and in sensory fibres of the median and sural nerves. Determination of metals in air Personal air sampling at breathing zone was applied (Casella [Bedford, UK] AFC-123, flow rate 2 l/min). Total dust was collected (over a period of about seven hours a shift) onto a membrane filter (Sartorius [Goettingen, Germany] 111304, 0.8 µm, ø32 mm). In the sample collected on the filter, total dust was determined by gravimetry, arsenic was determined by hydrobromide methods, while lead, copper and zinc concentrations were measured by absorption spectrometry (using a Varian [Vosendorf, Austria] Spectra 240Z Atomic Spectrometer with graphite furnace). Determination of arsenic speciation forms by HPLC-ICP-MS High Performance Liquid Chromatography/Inductively Coupled Plasma Mass Spectrometry (HPLC-ICP-MS)
789
Mean values ± SD ∗ P < 0.05 vs. reference; ND = data not available. a Significantly different from mean control value, P < 0.05. b Significantly different from mean Electrolysis value, P < 0.05.
Electrolysis (n = 10) Control (n = 16)
Lead (n = 15)
44.3 22.9 21.9 ±12.1 0.022 ±10.3 ±9.9 ±0.025 b 41.4 18.6 5.8 ±1.4 a, b 0.007 ±9.0 ±11.6 ±0.004 0.004 42.2 16.7 12.8 ± 6.6a ±0.002 ±10.1 ±8.5 46.1 23.5 30.0 ± 5.4 NA ±9.6 ±8.4 0.042 ±0.027 0.080 ±0.051a,b 0.026 ±0.012 0.020 ±0.015
As Pb (μg/m3) (mg/m3)
Furnaces (n = 20)
Smoking pack/years
Age
Group/Department
Emp. time 0.041 ±0.016 0.025 ±0.012 0.042 ±0.026 0.050 ±0.038
0.041 ±0.031 b 0.026 ±0.031b 0.005 ±0.003 NA
30.0 ±4.4 b 29,1 ±10.0 b 13.1 ±5.5 20.0 ±5.3
73.8 ±60.3 b 47.6 ±34.9 16.5 ±12.1 19.6 ±20.6
20.9 ±36,0 13.9 ±31.1 1.9 ±1.9 NA
11.4 ±9.9 6.1 ±5.0 7.5 ±6.0 NA
5.2 ±4.3 2.8 ±3.5 2.6 ±1.7 b NA
26.2 ±17.4 b 22.4 ±16.7 9,2 ±5.8 NA
7,8 ±8.0 4,8 ±2.4 2.4 ±2.7 NA
Cu Zn Pb-B As-U As-B As +3 As +5 DMA MMA (mg/m3) (mg/m3) (μg/dL) (μg/L) (μg/L) (μg/L) (μg/L) (μg/L) (μg/L)
Table 1. Age, duration of employment and exposure indices in workers of Departments of Furnaces, Lead and Electrolysis and non-exposed reference group.
790 was used for determination of arsenic speciation forms. Urinary As speciation forms were determined in the prepared solutions by ELAN DRC-e inductively coupled plasma-mass spectrometer (ICP-MS) (PerkinElmer, SCIEX, Waltham, MA, USA) with Dynamic Reaction Cell. The frozen urine samples were defrosted at room temperature. Prior to total As and mobile-phase As speciation analysis, samples were shaken vigorously, centrifuged at 4000 rpm for 10 min, and diluted appropriately with ultrapure laboratory Milli-Q water (18.2 M.cm quality; Millipore SAS, Molsheim, France). Certified reference material SRM 2669 level II from National Institute of Standard and Technology (NIST, Gaithersburg, MD, USA) with a certified range: AsIII – 5.03 ± 0.31; AsV – 6.16 ± 0.95; MMA – 7.18 ± 0.56; DMA – 25.3 ± 0.7; AsB – 1.43 ± 0.08 and As total 50.7 ± 6.3 were determined at the beginning and at the end of the analysis. The determined values were 4.95 ± 0.76; 5.76 ± 0.31; 7.05 ± 0.55; 25.5 ± 1.5; 1.40 ± 0.08 and 50.2 ± 5.4, respectively. All urine samples were diluted in sample tubes pre-washed with 65% R Suprapur nitric acid from Merck (Darmstadt, Germany). The results of determinations of the content of arsenic species, which is the average of the two aliquots, are shown in Table 1. Determination of lead Concentrations of lead in blood were determined by graphite furnace atomic absorption spectrophotometry (GF-AAS) using a Varian Spectra 240 Z unit with autosampler, by the method of additions as described in the company’s Instruction Manual. Certified reference value BCR-634 was (Institute for Reference Materials and Measurements [IRMM], Seel, Belgium): Pb-B (µg/L) 46, range 41–51; determined value: 47.9 ± 1.4. Determination of iron Iron in serum was determined by spectrophotometry by measurement of pink complexes of ferrous ion with FeroZine (Alpha Diagnostic, Warsaw, Poland). Determination of zinc and copper Prior to the dilution, urine samples were centrifuged at 4,000 rpm for 10 min, and then the supernatant was 10-fold diluted with 1.0% HNO3 . Reference material Clincheck level I (Recipe, GmbH, Munich, Germany), reference value Zn-U (µg/L) 215, was analyzed at the beginning and at the end of the analysis: range 161–269; determined value: 196.9 ± 6.7 and Cu-U (µg/L) 58.6, range 46.9–70.3; determined value: 60.2 ± 2.4. ELAN DRC-e inductively coupled plasma-mass spectrometer (ICP-MS) (PerkinElmer) with Dynamic Reaction Cell with nickel sampler and skimmer cones, cyclonic spray chamber and a Meinhard nebulizer
Halatek et al. was used for zinc and copper determination. Rhodium was used as the internal standard. In blood samples Seronorm Nycomed Lot No. 704121 (Norway) was used as reference material with value Cu 130 µg/dL; range 125–143, determined value: 131.2. ± 5.5 and value Zn 148 µg/dL; range 140–168, determined value: 152.4 ± 7.6. PyeUnicam, model SP9–800 (UK) flame atomic spectrometer was used for determination of those metals. Biochemical determinations Clara cell protein and β 2 -microglobuline (β 2 M-S) in serum and urine β 2 M-U and retinol binding protein (RBP) were determined by a latex immunoassay.[21] Specific rabbit antibodies against CC16/Protein 1, β 2 M and RBP from Dako A/S, Denmark were used. To eliminate possible interference (complement, chylomicrons), the serum samples for CC16 estimation were pre-treated by heating at 56◦ C for 30 min. and by the addition of polyethylene glycol 600 (16%, v/v 1/1) and trichloroacetic acid (10%, v/v 1/40). After overnight precipitation, the samples were centrifuged and CC16 was determined in supernatants. Lactate dehydrogenase (LDH) was determined by spectrophotometry at 340 nm using a commercially available reagent kit (Alpha Diagnostics, Warsaw, Poland) according to the manufacturers’ instructions on an Epoll 20 (Warsaw, Poland) Photometer. The levels of matrix metalloproteinase-9 (MMP-9) (Amersham Biosciences UK, Buckinghamshire, UK) were measured in serum using the ELISA kit on a Bio-Rad Microplate Reader Model 550 with Bio-Rad software (Hercules, CA, USA). Spirometry After medical follow-up examination, the workers were subjected to respiratory function tests. Forced vital capacity (FVC) (in standing position), forced expiratory volume in one second (FEV1), forced expiratory flow rate at 50% of FVC (FEF50) were measured in each exposed and nonexposed worker using a Hellige CardioSys V2.51 electronic apparatus (Wendelstein, Germany) with digital readout. In addition, FEV1/FVC (Tiffeneau index) was calculated. For each subject, the observed values of ventilator parameters were expressed as a percentage of the predicted values, which were calculated according to subject’s gender, age, weight, and height. Statistical analysis The differences between mean values for the groups were tested by the analysis of variance (ANOVA) and multiple comparison test. The parameters with a skew distortion were transformed logarithmically. Statistical analysis of the results involved the analysis of Spearman rank correlation coefficients.
791
Arsenic in urine of copper smelter workers Results 80
Table 1 shows age, duration of employment and exposure indices in workers of the Departments of Furnaces, Lead and Electrolysis and non-exposed reference group. The groups did not differ significantly in respect of age and employment time. A significant difference was found in the calculated values of the smoking index (cigarette pack-years), smoking habit was less popular in workers from Department of Lead. In the Department of Furnaces, the national (Polish) threshold limit value (TLV) of 0.01 mg/m3 for arsenic concentrations in air was exceeded about twofold. In the Department of Lead the concentrations of lead exceeded 1.5× the Polish TLV of 0.05 mg/m3. Arsenic concentrations in urine varied significantly between groups, from 73.8 ± 60.3 for Department of Furnaces, 47.6 ± 34.9 for Department of Lead and 16.5 ± 12.1 for Department of Electrolysis vs. 19.6 ± 20.6 µg L−1 in the reference group. The values of the urinary arsenic in the exposed groups in the Department of Furnace and Lead exceeded by 2.1× and 1.3× the value (35 mg/L) of the corresponding biological exposure (BEI) index. The inorganic arsenic specie As(+3), As(+5) levels in urine of workers from Department of Furnace were also 2× higher than in urine of workers from the Department of Lead and Electrolysis. However, methylarsonate (MMA(V)), dimethylarsinate (DMA(V)) organic species levels in urine of workers from Department of Furnace and Lead were comparable but 2× higher than those in urine of Electrolysis workers. Arsenobetaine (AsB) in urine of Electrolysis workers in relation to Departments of Furnace and Lead workers urine levels were 10× and 5× lower, respectively. The neurological studies performed in all subjects revealed that occupational exposure to arsenic in the ambient air at the workplaces of the foundry did not induce organic lesions in the central or peripheral nervous system. Studies of functional disorders of the nervous system in workers employed in the Departments of Furnaces, Lead and Electrolysis and non-exposed reference group showed irregularities in the form of subjective syndrome consisting of headache (31.5%, 26.7%, 20.0% and 12,5%) respectively, vertigo (21.0%, 26.7%, 10.0% and 0), increased emotional irritability (42.1%, 13.3%, 10.0% and 12.5%), dysmnesia (15.8%, 14.3%, 6.3% and 6.3%), and concentration difficulties (15.83%, 6.3%, 10.0% and 0), excessive sleepiness (26.3%, 6.7%, 0, and 18.8%), changing moods (21.0%, 0, 10.0% and 0), states of limb muscle cramps (15.8%, 33.3%, 0, and 12.5%), fatigue of the lower limbs (26.3%, 47.6%, 0 and 0), paresthesia (26.3%, 26.7%, 20.0, and 0). Figure 1 compares results of examinations of subclinical symptoms in study workers with those for references from the copper smelter plant and data for non-exposed population. Reported subclinical symptoms from CNS were found in 55% in Furnace and Lead Department workers (vs. 37% in controls). In electrophysiological tests, higher scores
70 60 50
%
40 30 20 Lead Furnaces Electrolysis Control from Smelter
10 0 CNS
EEG
VPV
PNS
ENeG
Fig. 1. Results of neurological examinations of subclinical symptoms in study workers from Department of Lead, Department of Furnaces, Department of Electrolysis and references from the copper smelter plant. Percentage (%) of the cases in the study population. CNS: central nervous system, EEG: electroencephalography, VEP: visual evoked potentials, PNS: peripheral nervous symptoms, ENeG: electroneurography.
were noted in Lead Department workers compared to Furnace and much less impairment in Electrolysis Department workers. The individual assessment of visual evoked potentials (VEP) in Furnace Department workers showed abnormalities in 40% cases (latency P100, 90–134 ms) vs. 37% in controls; in peripheral nervous system (ENeG) examination, the highest number of abnormal cases, 72%, was recorded in Lead Department workers (vs. 12% in controls). Table 2 shows the biochemical and spirometry indices of workers employed in Departments of Furnaces, Lead and Electrolysis and non-exposed reference group. f Mean serum CC16 levels in Department of Furnace, Lead and Electrolysis workers were significantly lower than in the references, 15.3 ± 4.5 µg L−1. The renal biomarkers: levels of retinol binding protein and β 2 -microglobulin (β 2 M) in urine and serum were significantly higher in urine of workers from departments of Furnace and Lead compared to controls levels; however, high levels of β 2 M in serum were shown also in Department of Electrolysis workers. All metals measured in serum: Fe, Cu and Zn, were lower in workers from Departments of Lead in relation to references; however, only for Fe the differences were statistically significant. Spirometric indices were also not significantly different. Table 3 presents values of significances (P) obtained in the analysis of r-Spearman correlation coefficients of individual examinations analysed in the Department of Furnace workers., Arsenic exposure indices in terms of urinary levels of arsenic speciation forms, i.e., As-U, As(+3), As(+5), DMA and MMA, significantly correlated with renal biomarkers: β 2 -microglobulin (β 2 M) and retinol binding protein (µg/g crea) in urine. There was also a significant relationship between Cu-U and β 2 M/g creatinine (r = 0.47, P = 0.013), and Cu-U and RBP/g creatinine (r = 0.38,
792
11.0 ±4.4 a 11.5 ±3.6 a 8.5 ±2.9 a 15.3 ±4.5
Furnaces (n = 20) Lead (n = 15) Electrolysis (n = 10) Control (n = 16)
147.0 ±53.9 a 92.2 ±96.6 76.9 ±88.7 48.0 ±31.9
151.0 ±60.8 a 173.1 ±92.6a 148.7 ±102.3 79.5 ±37.2
β 2 m-U RBP (μg (μg/L) /L) 1917.0 ±743.1 a,c 2854.5 ±976.1 3225.6 ±1091.7 a 1792.4 ±389.3
β 2 m -S (μg /L) 1.25 ±0.6 1.4 ±0.7 1.1 ±0.7 NA
Mean values ± SD ∗ P < 0.05 vs. reference; ND = data not available. a Significantly different from mean control value, P < 0.05. b Significantly different from mean Electrolysis value, P < 0.05. c Significantly different from mean Lead value, P < 0.05.
CC16 (μg/L)
Group
Creat inine (mg /dL)
27.1 ±33.1 23.4 ±24.9 38.1 ±40.2
NA
11.0 ±5.0 b, c 21.8 ±13.4 a 22.2 ±8.6a 12.1 ±8.7
HA (μg MMP-9 /L) (μg/L) 91.0 ±31.9 99.5 ±44.2 111.2 ±39.3 NA
LDH (U/L) 92.5 ±24.8 66.4 ±33.4b 106.2 ±27.4 85.5 ±17.3
108.9 ±24.7 86.7 ±15.8 106.0 ±17.3 109.3 ±20.2
68.6 ±19.5 55.3 ±17.5 67.4 ±16.3 67.5 ±13.0
Fe-S Cu-S Zn-S (μg/dL) (μg/dL) (μg/dL)
98.5 ±9.1 105.5 ±14.7 100.3 ±13.6 97.9 ±11.8
FVC (%)
101.2 ±8.0 100.2 ±16.1 103.6 ±15.0 100.1 ±11.5
FEV1 (%)
101.4 ±25.9 96.5 ±19.8 118.4 ±30.8 105.4 ±33.8
FEF50 (%)
Table 2. Biochemical and spirometrical indices of workers employed in Departments of Furnaces, Lead and Electrolysis and non-exposed reference group.
103.6 ±6.5 100.6 ±12.1 105.6 ±12.7 105.0 ±11.1
%FEV1 (%)
793
Age Emp. time As-U As-U/g c. As-Betaine As(+3) As(+5) DMA MMA Pb-B CC16 B2M-S B2M-U RBP Creatinine B2M-U/g c RBP/g c. Cu-U Fe-S Zn-S Cu-S MMP-9 LDH
0.000 × 0.039 0.000 0.013 0.006 0.003
0.018
0.002
0.015 0.004 0.007 0.000 0.008
× 0.000 0.000 0.000 0.000 0.000 0.000
0.004
0.026
0.036
0.000 0.039 × 0.003 × 0.005 0.004
× 0.003 0.000 0.000
0.002 0.021
0.040
0.018 0.033
(−)0.033 (−)0.003
0.000 0.013
0.000 0.000
0.021
0.002 0.001 0.006 0.017
0.037 0.000 0.006 0.036 0.000 0.005 × 0.001
0.055 0.012 0.014 0.000
(−)0.042
0.000 0.004 0.001 ×
0.000 0.004
0.021
0.054
×
As-U As +3 As +5 DMA MMA Pb-B As-U mg/g As-B mg/L crea (μg/L) (μg/L) (μg/L) (μg/L) (μg/L) mg/dL
0.035
(−)0.041
×
(−)0.033 (−)0.003
CC16 mg/L
0.052
×
(−)0.042
(-)0.027
β 2 m –S mg /L
0.039
0.023
0.014 0.015 0.000 × 0.000 0.013
0.040 0.033 0.001 0.012
0.004
β 2 m-U mg /g crea
0.008
0.000 0.000 0.000 ×
0.006 0.014
0.007
RBP mg /g crea
0.013 0.052 ×
(−)0.041
0.017 0.000
0.000 0.008 0.026 0.002
Cu-U mg/L
(−)0.021 0.043
×
0.021
Fe-S mg/dL
×
0.023
0.035
0.021
0.004
Zn-S mg/dL
(−)0.048 ×
0.043
(−)0.025
0.021
0.002
0.038
LDH U/L
Table 3. Spearman correlation (p) of exposure indices and biological parameters in neurologically examined copper smelters from Department of Furnaces (n = 20).
794 P = 0.052). Urinary excretion of copper in the workers significantly correlated with all the tested urinary indicators of exposure to arsenic. Cu-U has been shown to be most correlated with As-U (r = 0.6, P = 0.001) As(+3) (r = 0.57, P = 0.002) and MMA (r = 0.62, P = 0.001). Statistically significant inverse relationship was also observed between Cu-U and serum levels of CC16 (r = −0.39, P = 0.044). Serum levels of CC16 showed statistically significant inverse association with urinary arsenic speciation forms As(+3) (r = −0.41, P = 0.033 and As(+5) (r = −0.56, P = 0.003) (Table 3). On the other hand, positive correlation of serum CC16 levels with serum levels of Zn (Zn-S) (r = 0.629, P = 0.038) was observed. Serum levels of Zn µg/dL (Zn-S) also correlated with urinary As-B (r = 0.763, P = 0.006), DMA (r = 0.673, P = 0.0233) and β 2 M/g crea (r = 0.664, P = 0.0259). Serum levels of Fe µg/dL (Fe-S) correlated positively with As(+3) (r = 0.669, P = 0.024), LDH (r = 0.636, P = 0.0479) and inversely with MMP-9 (r = −0.669, P = 0.0241). LDH U/L correlated also positively with age (r = 0.648, P = 0.042) and Pb-B (r = 0.762, P = 0.028) and inversely with MMP-9 (r = −0.624, P = 0.053) levels. Employment time correlated positively with DMA levels (r = 0.42, P = 0.037) and inversely with β 2 M-S levels (r = −0.45, P = 0.027).
Discussion Exposure to metals appearing in the copper smelter plant is extremely diverse. Each department and type of production at the mill presents other risks related to the composition of the metal concentration in the inhaled air.[22] However, exposure to arsenic associated with the steps in the production of copper occurs at all workplaces. Only at the Department of Furnaces, the exposure is 2× above the TLV (Table 1). The main risks to human health from heavy metals are associated with exposure to lead, cadmium and arsenic; those risks have been generally recognized and monitored by international organizations, including the WHO.[23] Current studies on speciation of metals such as arsenic can expand and upgrade those efforts. Knowledge on trace element speciation can contribute to a better understanding of the transport of metals across the neural barriers and potentially of their role in the diseases of human brain.[24] Yokel et al.[12] has suggested that because speciation can influence metal metabolism and toxicity, different exposure standards should be established for different metal species. In the body, inorganic arsenic is metabolised to monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA).[4] The fraction of urinary MMA is considered as a marker for susceptibility to As-related diseases.[25,26] Table 1 shows that in urine of workers employed in the Department of Furnaces, who were most exposed to arsenic, both inorganic arsenic species As (III), As (V) levels and organic species methylarsonate (MMA), dimethylarsinate (DMA) levels were 2× higher than in urine of Electrol-
Halatek et al. ysis workers. Many authors stress the importance of forms of MMA, which are more toxic, i.e., produce more toxic changes in both humans and animals.[27–29] Arsenic induces oxidative stress by disturbing the pro/antioxidant balance. These alterations play prominent roles in many symptoms, including e.g., nervous systems disorders.[15] The workers of the Department of Lead and Furnaces scored lowest in the neurophysiological tests (Fig. 1). Many of those changes are mostly peripheral neuropathies. Both arsenic and lead affect the peripheral nervous system but, although the effects are similar, they differ in the histopathological image of the neuronopathies.[30] As reported by Chen et al.,[31] the results of large epidemiological studies of people exposed to environmental concentrations of As in drinking water at ca. 99 ug/L pointed to neurological dysfunction and demonstrated adverse effects in terms of respiratory function biomarkers. In our study (Table 2), pulmonary function of copper foundry workers showed no statistically significant changes in spirometry results; FVC, FEV1 , FEV1 /FVC and FEF50 . There was, however, a statistically significant decrease in serum concentrations of CC16 protein, the biomarker of lung epithelial damage, in all groups of employees (Table 2). We examined the relationship between the serum level of Clara cell protein (CC16) biomarker of lung function and the total urinary As, As(+3), As(+5), and urinary As methylation indices in workers from Furnace Department exposed to xa = 0.022 mg As/m3. We observed decreased concentration of CC16 in serum of those workers. According to Broeckaert et al.,[19] in such conditions Clara cells are damaged by inflammation, which results in decreased production of CC16, whereby the ability to repair epithelium damage caused by pollutants is limited. The mechanism by which CC16 protects the epithelium is unclear. Reduced concentrations of CC16 in serum of nonsmoker subjects exposed to environmental arsenic were observed in Bangladesh populations.[32] A similar picture is observed in welders occupationally exposed by inhalation to gases and dusts from welding fumes containing Mn or in aluminum smelter workers exposed to dusts containing aluminum, and in copper smelter workers exposed to arsenic.[33,34] Exposure to arsenic causes significant changes in the kidneys. In this study we observed increased urinary levels of low molecular weight protein β 2 M and RBP, and the increase was statistically significant in Furnace Department workers (Table 2). Additional confirmation of nephrotoxic action of arsenic has been obtained from the analysis of Spearman correlation between the studied renal biomarkers and total urinary As, and urinary As methylation indices in workers from Furnace Department (Table 3). Dysfunction in renal tubular absorption under the influence of arsenic shows a statistically significant relationship between β 2 M/g creatinine and RBP/g creatinine and concentrations in the urine of As-U, As(+3), As(+5), DMA, MMA. The relationship between Cu-U and β 2 M/g creatinine
795
Arsenic in urine of copper smelter workers (r = 0.47, P = 0.013) and RBP/g creatinine (r = 0.38, P = 0.052) also appears to be a function of renal cellular desquamation (indicated by urinary metallothionein containing Cu).[35] Rubatto Birii et al.[11] study supports the hypothesis that tubular accumulation of As and Cu may have some bearing on the arsenic-associated nephrotoxicological process because major deleterious effects were seen in tubules. Urinary excretion of copper in the workers significantly correlated with all indicators of exposure to arsenic in the urine tested. The strongest relationship appears to occur between Cu-U and As-U (r = 0.6, P = 0.001), As(+3) (r = 0.57, P = 0.002) and MMA (r = 0.62, P = 0.001). In rat study, administration of As leads to renal Cu accumulation which is dependent on the dose of arsenic; a constant molar As:Cu ratio independent of arsenic dose was obtained in the kidney.[36] Some other animal studies support the hypothesis that tubular accumulation of As-Cu may have some bearing on the arsenic-associated nephrotoxicological process.[10,27,36–38] Schmolke et al.[38] suggest that the accumulation involves the process of As-Cu incorporation to kidney metallothinein. Other authors have noted that arsenic is widely distributed and significantly accumulated at levels relatively higher in the spleen, lung and kidney compared to the liver, and affects other trace elements, and also modulates MT-1 expression in the liver and kidney.[39] In rats exposed to sodium arsenite in drinking water, the As and Cu co-distribution with peri-glomeluar accumulation, decreased Bowman’s space as well as decreased plasma blood urea nitrogen (BUN)/creatinine ratio were found.[11] We observed also a statistically significant increase in the serum level of β 2 M-S in Electrolysis Department workers, indicating altered function of glomeruli. Those workers, less exposed to As, were exposed also to Cu (Table 1). Probably those combined exposures also affected the kidneys. In Chen et al.[40] arsenic longitudinal study, positive relationship was found to occur between level of arsenic in urine and symptoms of proteinuria. In a study of rats treated with copper preservative agent, the animals displayed a thickening of the basement membrane of Bowman’s capsule and the mesangium; higher exposures caused moderate to marked expansion of the mesangial matrix and glomerular necrosis with an overall loss of glomerular structure seen at the highest dose.[11,41] Statistically significant inverse relationship between Cu-U and serum levels of CC16 were also observed (r = −0.39, P = 0.044). Spearman correlation analysis shows a statistically significant inverse association between urinary As speciation forms and serum CC16 (As(+3) r = −0.41, P = 0.033 and As(+5) r = −0.56, P = 0.003), see Table 3. A similar inverse relationship between urinary As and serum CC16 in a population exposed to arsenic in drinking water was also observed.[32] CC16 is a mediator that appears to perform important regulatory and antiinflammatory functions in the respiratory tract.[42,43] CC16 anti-inflammatory properties are supported by the fact that
the depletion of the CC16 pool in the lung is accompanied by increased concentration of As(+3), the forms responsible for respiratory diseases.[44] As(+3) correlated with the increased serum iron (Fe-S) concentration. FeS goes hand-in-hand with an increase in LDH activity, a marker of lung injury in the inflammatory process.[45] Concentration of zinc in serum (Zn-S) correlated with As-B; that fact could be explained by the observation that structured enzyme betaine-homocysteine Smethyltransferase activity undergoes a redox switch at the active site zinc.[26,46,47] Zn-S correlated with DMA (secondary methylation index in urinary As) and serum CC16 levels in study workers from Furnace Department. Parvez et al.,[32] in an arsenic longitudinal study, found a stronger correlation between urinary DMA and CC16 among people exposed to arsenic in drinking water without skin lesion, indicating that increased methylation capability may be protective against As-induced respiratory damage. These observations support the mechanisms reported by Vahter [4] of arsenic interactions, including arsenic-induced oxidative stress, and arsenic metabolism (methylation) via 1-carbon metabolism, which requires methyl groups, including betaine for the remethylation of homocysteine to methionine.
Conclusion The main mechanisms of arsenic-induced oxidative stress in the respiratory tract is attenuated by inorganic arsenic species As(+3) and As(+5) and the anti-inflammatory potential of Clara cell protein (CC16) secreted to the respiratory tract involved in the process of detoxication of inhaled agents. The study confirmed deleterious arsenic effects to the kidney by an increased level of low-molecular weight protein in urine and the extent of the renal copper accumulation/excretion. Neurological examination confirmed that the sensitive electrophysiological tests (VEP, EEG and ENeG) could be used for the detection of early subclinical effects of the exposure of the nervous system in copper smelters.
Acknowledgments The skillful work of Ms. Anna Kubiak for biochemical analysis is highly appreciated.
Funding This study was supported by Grant PB 3459/B/P01/ 2007/33 from the Committee for Scientific Research.
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