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Article

Impact of Chronic Beryllium Exposure on Liver and Lung Function and Hematologic Parameters

1
National Center for Occupational Safety and Health, National Health Commission of the People’s Republic of China, Beijing 102308, China
2
Medical Laboratory Department, Shandong Medical College, Linyi 276000, China
3
Xinjiang Uygur Autonomous Region Center for Disease Control and Prevention, Urumqi 830002, China
4
Fuyun County Center for Disease Control and Prevention, Fuyun 836199, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Atmosphere 2024, 15(9), 1086; https://doi.org/10.3390/atmos15091086
Submission received: 14 June 2024 / Revised: 26 July 2024 / Accepted: 30 July 2024 / Published: 7 September 2024
(This article belongs to the Section Air Quality and Health)

Abstract

:
Beryllium is a lightweight metal that is toxic to humans. The critical health effects related to beryllium exposure are liver toxicity, immune system toxicity, and chronic beryllium disease (CBD). This study investigated the effects of occupational beryllium exposure on liver and lung function and hematologic parameters among beryllium smelter workers. A cross-sectional study was performed by comparing 65 exposed workers and 34 non-exposed workers. Health information was collected through questionnaire surveys and biochemical tests. The concentration of urinary beryllium was determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The findings indicated that the urinary beryllium levels of the exposed workers and the controls were 0.48 (0.115, 1.19) μg/mL and 0.0125 (0.005, 0.005) μg/mL, respectively (p < 0.001). Compared with the controls, the exposed workers showed a significant increase in serum alanine aminotransferase (ALT) level, hemoglobin (HGB) concentration, white blood cell (WBC) count, red blood cell (RBC) count, and systolic and diastolic blood pressure (SBP, DBP) (p < 0.05). Furthermore, the HGB concentration and ALT level were significantly correlated with the concentration of beryllium in urine (p < 0.05). The exposed workers had increased urinary concentrations of beryllium, in contrast to the control subjects. Moreover, the urinary beryllium levels among the exposed workers are much higher than that in the Chinese general population. Beryllium-exposed workers may be at risk of liver and hematologic impairments.

1. Introduction

Beryllium, a lightweight stable metallic element, has been studied and developed since the 1930s. Beryllium is widely used in the industries of rockets, missiles, satellites, aerospace, electronics, and metallurgical owing to its high melting point, electrical conductivity, and many other excellent physical and chemical properties [1]. The main products on the beryllium industry chain include metallic beryllium, beryllium alloys, and beryllium oxide. A large amount of flue gas containing beryllium and its compounds is produced in the smelting process [2].
Beryllium and its compounds have significant toxicity. The strength of toxicity is closely related to factors such as the type, physicochemical properties, dosage, contact time, invasion pathway, and individual sensitivity [3]. Exposure to beryllium can have both acute and chronic negative effects on human health. Acute beryllium disease is a chemical pneumonitis thought to be caused by direct toxicity to cells in the lungs from exposure to high levels of the more soluble forms of beryllium. It had high morbidity and mortality in the beryllium production industry in the 1940s, though few cases have been reported recently [4]. Long-term exposure to low concentrations of beryllium can cause chronic beryllium disease (CBD), mainly characterized by pulmonary granulomas and interstitial fibrosis [5]. In addition, it may also cause contact dermatitis, liver toxicity, and immune system toxicity [6,7,8]. High levels of beryllium exposure are also considered to have a potential lung cancer risk [9].
Animal experiments have shown associations between exposure to beryllium and changes in biochemical and hematological parameters. Sharma’s study found that marked decreases in hemoglobin percentage occurred after the administration of beryllium. In addition, serum ALT and AST from mice also increased significantly following beryllium exposure, indicating severe hepatotoxicity [10]. Another study found that the AST/ALT ratio activity tended to decrease in beryllium-injected mice [11].
The Occupational Safety and Health Administration (OSHA) promulgated a comprehensive occupational exposure standard for beryllium that lowered the permissible exposure limit to 0.2 μg/m3 and established a short-term exposure limit of 2 μg/m3 [12]. Despite the implementation of beryllium exposure standards, cases of beryllium-induced disease continue to occur. Air monitoring can control and improve beryllium exposure in the workplace, but it cannot evaluate the overall exposure outcomes of workers. Due to the differences in the use of protective equipment, individual occupational activities, and the ages and genders of exposed workers, the impact of beryllium on different individuals in the work environment is not the same [13]. Therefore, it is necessary to conduct biological monitoring of exposed workers. Urinary beryllium level is a reliable indicator for monitoring the dose level of beryllium in the human body. Studies have shown that more than 90% of beryllium entering the body through the respiratory tract or skin is excreted through urine [14,15].
At present, most studies focus primarily on the determination of urinary beryllium concentration [13,16,17], with there being a lack of data on long-term exposure of workers to beryllium and its adverse effects on health. Herein, we report a study in which we measured urinary beryllium levels in beryllium-exposed workers and analyzed the blood plasma levels of liver functions and selected biochemical parameters. The objectives of this study were to explore the health effects of beryllium exposure in workers and to evaluate the correlation between urinary beryllium level and liver functions and biochemical parameters.

2. Materials and Methods

2.1. Study Participants

This cross-sectional study was conducted in 2018 in Xinjiang, China, and recruited 99 volunteer workers working in a beryllium smelter. This study included 65 beryllium-exposed workers and 34 non-exposed workers. The non-exposed workers comprising the control group were administrative personnel. Furthermore, the number of working years was not significantly different for the exposed and non-exposed workers (p = 0.875).

2.2. Data Collection

The data from this study come from an in-person survey and a physical exam administered in October of 2018. A self-designed occupational worker health survey questionnaire was given to each participant to collect information. The information we sought included data on participant characteristics (age, gender, weight, height, etc.), level of education, work experience (e.g., operating post; occupational history), smoking status, alcohol use, self-reported symptoms (including irritation of the skin, cough, choking sensation in the chest, and expiratory dyspnea), personal medical history, and usage of personal protective equipment. The participants all signed informed consent forms, and the ethical review was approved by the health regulatory department of the Occupational Health Department of the Xinjiang Health Commission.
Further, medical staff collected participants’ anthropometric measurements, including measurements of blood pressure, height, and weight, and blood and urine samples were taken. Each blood sample (10 mL) was collected from the cubital vein and stored in evacuated and EDTA-containing tubes. Heparinized blood was centrifuged (10 min, 1500× g, 4 °C) to isolate blood plasma. Clean catch mid-stream urine samples were collected using sterile, wide-mouthed glass bottles with screw cap tops. All samples were transported at 4 °C until use.
The determination of beryllium was carried out according to the Chinese national standard (GBZ/T 333-2024) [18]. Briefly, 0.5 mL urine (supernatant) was transferred to a polyethylene plastic pipe, and the volume of the solution was adjusted to 5.0 mL with 1% nitric acid. The diluted solutions were analyzed using ICP-MS (Thermo Fisher Scientific, Inc., Waltham, MA, USA). ICP-MS is a sensitive, precise, and highly repeatable method for measuring beryllium and other heavy metals in biological samples [13]. The standard curve was constructed with at least five concentrations. Blank samples, parallel samples, and spiked samples were used in all sample analyses for quality assurance and quality control.
Serum biochemical parameters were detected using an automatic blood biochemical analyzer. Hematological analysis (performed using a SYSMEX-XS-500i autoanalyzer, Tokyo, Japan) included white blood cell (WBC) count, red blood cell (RBC) count, platelet (PLT) count, and hemoglobin (HGB) concentration. Liver function analyses (performed using a Dirui CS-400B autoanalyzer, Changchun, China) included assays for γ-glutamyl transferase (GGT), aspartate aminotransferase (AST), and ALT. Lung function measurements were performed on site using a lung function detector (BK-LFT-I pulmonary function tester, Jinan, China). The lung function parameters measured were forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and the FEV1/FVC ratio. Both absolute values and percentage predicted values of the lung function parameters were used in the analyses.

2.3. Statistical Methods

The data were statistically analyzed using SPSS Statistics 22.0 software. The normality of the data was tested by the Kolmogorov–Smirnov test and frequency distributions (histograms). Data obeying normal distribution were presented as mean ± standard difference (x ± s); data that did not obey normal distribution were presented as median and interquartile range. Normally distributed data were assessed using a t-test, whereas for non-normally distributed data, the Mann–Whitney U test was applied. Variables were analyzed by Sperman’s correlation. To improve the regression effect, we introduced multiple stepwise regression models. p ≤ 0.05 was considered as the statistical significance level.

3. Results

The present study was conducted on 99 subjects (65 in the exposed group and 34 in the non-exposed group). The average age and length of employment for the exposed group were 39.0 ± 6.7 years and 7.8 ± 3.3 years, respectively, and the corresponding values for the control group were 46.09 ± 5.55 years and 7.91 ± 4.81 years, respectively. There was no significant between-group difference in length of employment, BMI, smoking status, and alcohol drinking status (p > 0.05). However, significant differences in age (p < 0.05) and sex (p < 0.01) were noted between the exposed and non-exposed groups. General characteristics are shown in Table 1. We adjusted for these confounding factors in subsequent analyses.
Table 2 shows the urinary beryllium concentration and the results of biochemical testing in the two groups. The urinary beryllium levels were 0.48 (0.115, 1.19) µg/mL and 0.005 (0.005, 0.005) µg/mL in the beryllium exposed workers and controls, respectively. The urinary beryllium level of the exposed workers was significantly higher than that of the controls (p < 0.05). Liver function indicators (ALT), blood cell count (WBC, RBC, HGB), and blood pressure (SBP, DBP) were significantly higher in the exposed group (p < 0.05). The ALT and HGB levels remained significantly higher in the exposed group after adjustment for age, gender, BMI, length of employment, cigarette smoking, and alcohol drinking (p < 0.05). The same results were observed for blood pressure after adjustment for the above-mentioned confounding factors (p < 0.05).
The results from the questionnaire showed a higher proportion of workers complained of coughing (40%), chest tightness (36%), and skin pruritus (24%). The correlation of biochemical results with the self-reported symptoms of local irritation was also evaluated. We found that the FEV1/FVC ratio was negatively correlated with coughing symptoms (r = −0.394, p < 0.001), with there being a trend toward a negative relationship with chest tightness symptoms (r = −0.284, p < 0.05) as well.
Multiple stepwise regression was performed to identify the potential factors that might be independently associated with urinary beryllium concentration. The effects of confounding variables of age, gender, BMI, length of employment, cigarette smoking, and alcohol drinking were adjusted and controlled. The results showed that after adjusting for these confounders, significant negative associations exist between urinary beryllium concentration and HGB concentration, and there were positive associations with ALT levels (Table 3).

4. Discussion

In our study, the median concentration of beryllium in urine was 0.48 (0.115, 1.19) µg/mL for the exposed group and 0.005 (0.005, 0.005) µg/mL for the control group. By comparison, the median concentration of urinary beryllium was lower than 0.06 μg/L in 13,309 individuals from the Chinese general population in [19]. In addition, a study on occupational exposure to beryllium in French industries showed that based on the current French occupational exposure limit (OEL-8h), a biological limit value of 0.08 µg/L (=0.06 µg/g creatinine) could be proposed [20]. The concentration of urinary beryllium in our studies was much higher than the recommended limit. The exceeding standard rates of the exposed group and the control group were 86.1% and 11.8%, respectively. These workers are subjected to chronic repetitive exposure to beryllium, which has a higher risk of occupational exposure.
Routine blood tests are part of comprehensive clinical examination, and they can be used in conjunction with clinical symptoms for early diagnosis of diseases. The results of the present study showed significant differences in WBC count, RBC count, and HGB level between the exposed and the reference populations. The HGB level was significantly higher in the exposed group after adjustment for confounding factors (p < 0.05). However, multiple linear regression analysis showed that the HGB level was negatively correlated with urinary beryllium concentration (p < 0.001). We speculate that this may be related to beryllium-induced anemia. Stokinger et al. [21] indicated that in beryllium-poisoned rabbits which have developed mild macrocytic anemia, smaller amounts of newly formed intraerythrocytic hemoglobin was present in the systemic bloodstream compared with the control animals. Mathur et al. [22] found that after intravenous injection of beryllium nitrate into rats, the RBC count and HGB level significantly decreased.
ALT and AST have been used to show the status of hepatic functions. High ALT levels were significantly higher in the exposed group after adjustment for age, gender, BMI, length of employment, cigarette smoking, and alcohol drinking (p < 0.05). Additionally, ALT level was positively correlated with urinary beryllium concentration (p < 0.01). AST is primarily found in the liver and is also detected in the heart, skeletal muscle, kidney, and brain, but the liver is the sole source of ALT [23]. A previous study found that the liver is the primary elimination route for beryllium and that it is has the highest beryllium content in animals [24]. Therefore, we suggest that beryllium exposure primarily affects ALT levels, subsequently causing liver function damage.
Furthermore, we discovered that blood pressure (SBP, DBP) was significantly higher in the exposed group (p < 0.05) after adjustment for age, gender, BMI, length of employment, cigarette smoking, and alcohol drinking. In the present study, we found that adults who had exposure to beryllium were 4.1 times more likely to have a risk of hypertension as compared to the non-exposed individuals. This result may be related to the abnormal hematological parameters caused by beryllium exposure [25]. Hypertension is associated with significant changes in the rheological, mechanical, and biochemical properties of erythrocytes, as well as alterations in blood flow [26]. In prior studies, hematological parameters including red blood cell (RBC) count and hemoglobin (HGB) level were higher in the hypertensive group compared to the control group [27,28].
The lungs are known as the main target tissue of beryllium [29]. Following exposure to beryllium in the workplace, a subset of individuals show an accumulation of CD4 + T cells and granulomatous inflammation in the lungs [30]. Chronic beryllium disease (CBD) is listed as a class A Environmental Protection Agency (EPA) carcinogen [31]. In general, lung function parameters are indicative of the respiratory status of the lungs. In our study, FEV1%, FVC%, and the FEV1/FVC ratio for both the exposed and control study groups were greater than 80%, indicating normal lung function in all subjects. The FEV1/FVC ratio was not statistically significant between the exposed group and the control group. This is consistent with Rodrigues’ study findings [32]. It was found that there was no difference in pulmonary function between those who were beryllium-sensitized and normal. In addition, we found that the FEV1/FVC ratio was negatively correlated with self-reported coughing symptoms (r = −0.394, p < 0.001) and chest tightness symptoms (r = −0.284, p < 0.05). However, there was no significant correlation between the self-reported symptoms and urinary beryllium concentration (p > 0.05). The adverse lung health impacts of beryllium exposure need further investigation.
Beryllium was recognized as causing a spectrum of effects, from asymptomatic sensitization to clinically evident disease [5]. Chronic beryllium exposure may cause respiratory system disorders, liver dysfunction, skin lesions, and other manifestations [8,33,34,35]. An epidemiological survey for beryllium was conducted by the US Department of Energy (DOE) in 2008. The results indicated that the probability of beryllium disease due to exposure to beryllium among workers in each workplace is approximately 4% [4]. Early screening and continuous monitoring of beryllium-exposed individuals may important components of occupational safety, as well as health initiatives. As a non-invasive biomarker, the measurement of urine beryllium may be used as an early biomarker for health damage caused by occupational exposure to beryllium [36]. In this study, urinary beryllium levels were used as the measure of exposure level. These results may indicate beryllium-induced anemia and liver injury, which is asymptomatic in the early stages.
The present study also has some deficiencies. Because of limited resources, the number of controls included in the study was small, which potentially decreases the study’s statistical power. Furthermore, the cross-sectional design did not allow for the determination of causal relationships. In addition, the influence of lifestyle, diet, and exposure to other chemicals and other factors were not considered. These factors should be included in future studies.

5. Conclusions

In conclusion, we found that the urinary beryllium concentration in the exposure group was significantly higher than that in the non-exposure group. This study has shown that beryllium exposure can cause an increase in markers of hepatic and hematologic injury. Minor changes in HGB and ALT levels may be the major adverse effects after long-term occupational exposure to beryllium. Regular monitoring of urinary beryllium concentration in individuals chronically exposed to beryllium is of great significance for the prevention and screening of chronic beryllium disease.

Author Contributions

Conceptualization, F.W., H.Y. and X.B.; methodology, X.M.; validation, Y.Y.; formal analysis, J.D. and Q.M.; resources, H.Y.; data curation, J.D. and X.W.; writing—original draft preparation, J.D.; writing—review and editing, X.B., C.D. and F.W.; supervision, X.B.; project administration, H.Y.; funding acquisition, F.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Foundation of Xinjiang Uygur Autonomous Region, grant number 2016D01B055, and the Project of National Center for Occupational Safety and Health, National Health Commission of the People’s Republic of China, grant number 2019009.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the health regulatory department of the Occupational Health Department of the Xinjiang Health Commission (No. 20180812) for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy reasons.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Demographic characteristics of the study participants.
Table 1. Demographic characteristics of the study participants.
CharacteristicExposed
(n = 65)
Non-Exposed
(n = 34)
Result
Female6 (9.2%)5 (14.7%)χ2 = 0.237, p = 0.627
Male59 (90.8%)29 (85.3%)
Age (y)39.03 ± 6.6946.09 ± 5.55t = −5.275, p = 0.048 *
Length of employment (y)7.78 ± 3.347.91 ± 4.81t = −0.158, p = 0.875
BMI (kg·m−2)25.56 ± 3.1125.99 ± 2.72t = −0.670, p = 0.504
Smoking rate (%)41 (63.1%)15 (44.1%)χ2 = 3.840, p = 0.051
Drinking rate (%)34 (52.3)16 (47.1%)χ2 = 0.246, p = 0.620
* independent sample t-test.
Table 2. Comparison of urine beryllium concentration and biochemical results between non-exposed and exposed groups.
Table 2. Comparison of urine beryllium concentration and biochemical results between non-exposed and exposed groups.
TestExposed
(n = 65)
Non-Exposed
(n = 34)
Result
Urinary beryllium (µg/mL)0.48 (0.115, 1.19)0.005 (0.005, 0.005)Z = −6.379, p < 0.001
Pulmonary function test
FEV13.83 ± 0.713.60 ± 0.88t = 1.413, p = 0.161
FVC4.44 ± 0.804.20 ± 0.99t = 1.318, p = 0.191
FEV1/FVC (%)86.34 ± 6.986.14 ± 9.7t = 0.119, p = 0.905
Liver function test
GGT (IU/L)28 (16, 61.5)26.5 (21.25, 31.5)Z = −1.486, p = 0.137
ALT (IU/L)28.4 (18.3, 40)24.05 (18.9, 29.75)Z = −2.263, p = 0.024
AST (IU/L)24.5 (20.3, 31.5)21.1 (18.2, 26.0)Z = −1.964, p = 0.05
Blood cell count
WBC (×109/L)7.0 (6.1, 8.3)5.85 (5.04, 6.91)Z = −3.796, p < 0.001
RBC (×1012/L)4.77 ± 0.454.08 ± 0.51t = −3.061, p = 0.003 *
HGB (g/L)151 (141.5, 161)138.5 (136, 153.7)Z = −2.544, p = 0.011
PLT (×109/L)230.8 ± 50.45223.2 ± 50.52t = −0.705, p = 0.482
Blood pressure
SBP (mmHg)131.22 ± 12.185123.71 ± 14.870t = 2.696, p = 0.008 *
DBP (mmHg)84.77 ± 9.87277.06 ± 9.62t = 3.722, p < 0.001 *
* independent sample t-test; Mann–Whitney U test.
Table 3. Association between exposure to urinary beryllium concentration and biochemical parameters using the multiple stepwise regression model.
Table 3. Association between exposure to urinary beryllium concentration and biochemical parameters using the multiple stepwise regression model.
ModelUnstandardized CoefficientsStandardized
Coefficients
tp
BStd. ErrorBeta
(Constant)13.6713.664 3.731<0.001 *
HGB−0.1010.026−0.381−3.934<0.001 *
ALT0.0800.0270.2842.9380.004 *
Dependent variable: urinary beryllium concentration. * independent sample t-test.
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Dai, J.; Bi, X.; Yuan, H.; Meng, Q.; Yang, Y.; Wang, X.; Ma, X.; Ding, C.; Wang, F. Impact of Chronic Beryllium Exposure on Liver and Lung Function and Hematologic Parameters. Atmosphere 2024, 15, 1086. https://doi.org/10.3390/atmos15091086

AMA Style

Dai J, Bi X, Yuan H, Meng Q, Yang Y, Wang X, Ma X, Ding C, Wang F. Impact of Chronic Beryllium Exposure on Liver and Lung Function and Hematologic Parameters. Atmosphere. 2024; 15(9):1086. https://doi.org/10.3390/atmos15091086

Chicago/Turabian Style

Dai, Jing, Xinlin Bi, Hui Yuan, Qingyu Meng, Yina Yang, Xueqin Wang, Xiaoying Ma, Chunguang Ding, and Fen Wang. 2024. "Impact of Chronic Beryllium Exposure on Liver and Lung Function and Hematologic Parameters" Atmosphere 15, no. 9: 1086. https://doi.org/10.3390/atmos15091086

APA Style

Dai, J., Bi, X., Yuan, H., Meng, Q., Yang, Y., Wang, X., Ma, X., Ding, C., & Wang, F. (2024). Impact of Chronic Beryllium Exposure on Liver and Lung Function and Hematologic Parameters. Atmosphere, 15(9), 1086. https://doi.org/10.3390/atmos15091086

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