Toxicology
Relationship between occupational aluminium exposure and histone lysine modification through methylation

https://doi.org/10.1016/j.jtemb.2020.126551Get rights and content

Highlights

  • Al may decrease the levels of BDNF and EGR1 in plasma.

  • Al may affect the cognitive function of workers by affecting the expression of BDNF and EGR1.

  • Al may regulate the expression of BDNF and EGR1 by regulating H3K4me3, H3K27me3 and H3K9me2.

Abstract

Background

Aluminium is an environmental neurotoxin to which human beings are extensively exposed. However, the molecular mechanism of aluminium toxicity remains unclear.

Methods

The changes in cognitive function of aluminum exposed workers under long-term occupational exposure were evaluated, and the relationship between cognitive changes, plasma memory related BDNF and EGR1 protein expression, and variations of epigenetic markers H3K4me3, H3K9me2, H3K27me3 expression levels in blood was explored.

Results

MMSE, DSFT, DST scores in cognitive function and the levels of plasma BDNF and EGR1 protein expression decreased with the increase of blood aluminum level. H3K4me3, H3K9me2, H3K27me3 expression levels in peripheral blood lymphocytes of aluminum exposed workers were statistically different (all P<0.05). H3K4me3, H3K9me2 and H3K27me3 expression levels in lymphocytes were correlated with blood aluminum level. BDNF, EGR1 protein level and H3K4me3, H3K9me2, H3K27me3 expression levels have different degrees of correlation. There was a linear regression relationship between plasma BDNF, H3K4me3 and H3K9me2. H3K9me2 had a greater effect on BDNF than H3K4me3. There is a linear regression relationship between EGR1, H3K4me3 and H3K27me3, and the influence of H3K4me3 on EGR1 is greater than that of H3K27me3 on EGR1.

Conclusion

Alummnum may regulate the expression of BDNF and EGR1 by regulating H3K4me3, H3K27me3 and H3K9me2, and affect the cognitive function of workers by affecting the expression of BDNF and EGR1.

Introduction

Aluminium is the third most abundant element in Earth’s crust, comprising up to eight percent of Earth’s surface [1]. Aluminium intake from food accounts for more than ninety percent of the human exposure from non-occupational sources [2]. Krewski et al. [3] showed that aluminium’s effect on the nervous system was often reflected by its close association with various neurodegenerative diseases. The relationship between aluminium exposure and AD has been the focus of intense research. For example, epidemiological investigations have found a strong correlation between AD and the accumulation of aluminium in the brain, both for workers who were occupationally exposed to aluminium and for individuals who had drank tap water that contained a high content of the metal as a result of either water purification with aluminium salts or the geographical location [[4], [5], [6]]. A decline in the cognitive function of patients with AD is one of the main manifestations of this disease. Interestingly, previous studies have shown that the main neurotoxic effect of occupational aluminium exposure on workers was also cognitive impairment [7,8].

Studies have shown that aluminium can be found in the human body, including blood, lymph, cerebrospinal fluid, brain tissue fluid, sweat, urine, and other bodily fluids [9]. Aluminium exposure during electrolytic aluminium operations is primarily via its inhalation through the respiratory tract in the form of respirable alumina dust [10]. Because studies have shown that the bioavailability of inhaled alumina dust is nearly 7 times higher than that of aluminium ingested from water [3], more attention needs to be paid to the health impairment induced by occupational alumina dust exposure.Studies on the neurotoxicity of aluminium have also attracted extensive and lasting attention from scholars of all scientific fields [11].

Aluminium, combined with transferrin and albumin, enters the brain indirectly via the blood-brain barrier or directly through the olfactory nerve and olfactory bulb, where it accumulates in the brain tissue to produce serious neurotoxic effects [12]. Polizzi et al. [5] reported that the blood aluminium concentration in smelter workers who were retired for more than 10 years was still significantly higher than that in the unexposed group, and the concentrations of aluminium in the cerebral cortex and serum of patients with dialysis encephalopathy were significantly higher than those of healthy individuals. These studies fully demonstrate that aluminium has a strong accumulation characteristic. Gulf War syndrome, which is characterised by neurological damage, is thought to have been caused by the administration of excessive doses of aluminium adjuvant to U.S. soldiers [7]. Epidemiological studies have shown that the content and form of aluminium ions in Chinalco wastewaters were related to the incidence of AD in people living in the surrounding areas [13,14]. Hosovski et al. [15] were the first to report the decline of learning and memory functions (e.g. movement coordination disorder, memory loss, and reduced abstract reasoning ability and reaction speed) in aluminium foundry and smelter workers in 1990. In 1992, White et al. examined 25 aluminium smelter workers from the same factory and found that they had symptoms of neurodegenerative syndrome. It was postulated that aluminium exposure in the electrolytic aluminium workshop might have been the main cause of these symptoms [16]. In 1994, Finnish occupational health experts divided 90 aluminium welding workers into low-, medium-, or high-exposure groups according to the aluminium concentrations in the workers’ blood (0.08, 0.14, and 0.46 μmol/L, respectively) and urine (0.4, 1.8, and 7.1 μmol/L, respectively). Visual inspection of the electroencephalograms of the workers in these three groups revealed slight diffuse and epileptiform abnormalities, and the neuropsychological tests showed changes in their information processing ability, complex attention, analytical memory, abstract visual pattern recall, and learning and memory abilities, all of which were more deteriorated in the groups with higher levels of internal aluminium exposure [17]. In 2003, Giorgianni et al. [18] conducted neuropsychological tests on 50 aluminium welders and showed that occupational aluminium exposure had caused decreases in their attention and memory and cognitive functions. Through a meta-analysis and an exploration of the influence of confounding factors, German scholar Monika Meyer-Baron analysed data from 449 aluminium exposed workers and 315 unexposed and found that workers with a higher body aluminium load had greater damage to their short-term memory and visual perception ability as well as learning and memory abilities. The most significant cognitive impairment occurred in workers exposed to higher levels of aluminium, proving that there was a dose-response relationship between aluminium and damage of the nervous system [19].

Aluminium ions that enter into an organism can be transferred to the cell nucleus. Such activity in nerve cells would inhibit normal transcription function, causing epigenetic modifications which in turn lead to changes in protein synthesis and cell function [20,21]. Epigenetics refers to the heritable change of the expression of genes through regulation of their transcriptional activity, without changing the DNA sequence itself. Epigenetic modification plays a very important role in mediating the toxic effects of exogenous chemicals [22], such as their methylation of DNA and covalent modification of histones [[23], [24], [25]]. Studies have suggested that changes in epigenetic patterns are likely to be involved in the end-point effects of aluminium neurotoxicity [26]. Histone modification by methylation can affect entire processes of cellular responses and the cell life cycle, and is a relatively stable form of epigenetic modification [27].

Histone methylation occurs mainly on the lysine residues of histones H3 and H4. Currently, there are six sites that have been widely studied: five are located at K4, K9, K27, K36, and K79 in the spherical region of the N-terminal domain of H3, and the sixth is located at K20 in the N-terminal domain of H4. The histone lysine residues can be monomethylated, dimethylated, or trimethylated. Heterochromatin formation and transcriptional regulation are mediated according to the methylation sites and different degrees of lysine methylation, where methylation at H3K4, H3K36, and H3K79 is involved in transcriptional activation, whereas that at H3K9, H3K27, and H4K20 is involved in transcriptional inhibition [22]. The abnormal methylation modification of histone lysine has been found to be related to a variety of human diseases, such as neurodegeneration [28] and cancer [29].

A study published in the Journal of Neuroscience showed that histone lysine methylation regulates the formation of learning and memory: after 1 h of memory stimulation in mice, the levels of trimethylated lysine 4 on histone H3 (H3K4me3) and dimethylated lysine 9 on histone H3 (H3K9me2) in the hippocampus were increased; and moreover, the levels of H3K4me3 in the promoter regions of the EGR1 and BDNF genes were increased, which was consistent with the increase in their mRNA transcription levels [30]. Studies have shown that the process of memory formation in rats may be accompanied by an increase in the H3K4me3 level in the promoter region of the BDNF gene, and a decrease in the H3K9me2 and trimethylated lysine 27 on histone H3 (H3K27me3) levels [31]. Studies on aging mice with learning and memory deficits revealed that the H3K27me3 levels in the hippocampus of the mice with learning and memory deficits were higher than those of the unexposed group [32].

In this present study, we used molecular epidemiological methods to evaluate changes in the cognitive functions of workers occupationally exposed to aluminium. The relationships between their blood aluminium levels and their peripheral blood lymphocyte H3K4me3, H3K9me2, and H3K27me3 and plasma BDNF and EGR1 protein levels were analysed. The data obtained provide a reference basis for the molecular epidemiological study of long-term aluminium exposure, and a molecular basis for future studies on whether the above-mentioned indicators can be used as alternative peripheral blood biomarkers for the monitoring and early diagnosis of aluminium neurotoxicity.

Section snippets

Subjects

A cluster sampling method was adopted for this study. In September 2015, 235 male workers between 27 and 53 years of age were randomly selected from the staff of SH XX Aluminium Factory. The individuals had undergone a health examination and volunteered to participate in the study. A cross-sectional survey was conducted on 100 electrolytic aluminium workers and 135 thermoelectric workers. The following were the study exclusion criteria: existing mental and neurological impairment; long-term use

Blood aluminium levels of workers exposed to aluminium

The blood aluminium level of the workers in the electrolytic aluminium workers was 155.07 ± 71.17 μg/L, whereas that of the workers in the thermoelectric workers was 142.94 ± 53.80 μg/L, but the difference was not statistically significant (F = 1.488, P > 0.05). The lower quartile of the blood aluminium level (P25) was 100.14 μg/L, the median (M) was 134.36 μg/L, and the upper quartile (P75) was 178.96 μg/L, which may have been due to the high impact of the large aluminium plant on the local

Discussion

The influence of aluminium as an important harmful factor on the health of occupationally aluminium exposed workers has attracted increasing attention for study, especially its biological effects on the nervous system. Aluminium exposure is one of the risk factors for AD because of its negative effects on cognitive function, learning, and memory [[35], [36], [37]]. A cohort study conducted by Peters et al. found that deep-hole gold miners with a long history of exposure to aluminium dust

Funding information

This work was supported by the National Natural Science Foundation of China [No. 81430078].

CRediT authorship contribution statement

Baolong Pan: Data curation, Formal analysis, Writing - original draft, Writing - review & editing. Yue Zhou: Data curation, Formal analysis, Validation. Huan Li: Formal analysis. Yaqin Li: Data curation, Validation. Xingli Xue: Validation. Li Liang: Validation. Qun Liu: Formal analysis. Xiaoyan Zhao: Formal analysis. Qiao Niu: Conceptualization, Writing - review & editing, Funding acquisition.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was financially supported by the National Natural Science Foundation of China [No. 81430078]. We sincerely thank colleagues for their help and work on the research.

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