Associations of GST Gene Polymorphisms and GST Enzyme Activity with the Development of Noise-Induced Hearing Loss in Chinese Han Males

Long-term exposure to a noisy environment can lead to an acquired, progressive sensorineural hearing loss called noise-induced hearing loss (NIHL). NIHL is a major public health concern identified by the World Health Organization (WHO), causing irreversible damage to workers exposed to loud noises. With industrialization, the risk of NIHL is increasing, with over 1.5 billion people (20% of the global population) currently affected and expected to rise to 2.5 billion by 2050. Unaddressed, hearing loss imposes a global cost of more than USD 980 billion annually [1, 2]. It is estimated that occupational noise-induced hearing loss caused over 4 million disability-adjusted life-years 16% of adult-onset hearing loss globally [3]. In the USA, 2.5 healthy years were lost caused by occupational noise-induced hearing loss each year for every 1,000 noise-exposed workers [4]. According to relevant reports, the incidence of hearing loss related to occupational noise exposure varies between 11.2% and 58% [5]. The prevalence of NIHL has been reported to be approximately 20% in the European Union [6], 25% in the USA [4], and 20% in Australia [7].

Since 2015, there has been a notable increase in the prevalence of occupational noise-induced deafness in China, making it the second most common occupational disease after pneumoconiosis [8]. According to a statistical survey conducted in 2020 on the current state of occupational hazards in China, 71.95% of workers in industrial enterprises and 88.81% of enterprises were found to be exposed to noise hazards [9]. Based on a 2020 survey, the prevalence of hearing impairment among employees in noisy industrial establishments in China was determined to be 26.88%. Extrapolating this figure to the estimated 32.6 million noisy workers in industrial enterprises, it is projected that over 9 million workers may be affected by hearing impairment [10]. The prevalence of visible noise as an occupational hazard in the workplace in China has led to a multitude of impacts affecting a significant portion of the workforce. This underscores the inadequacy of current measures in effectively managing hearing loss among occupational populations in China, particularly those with occupational noise-induced deafness, highlighting a critical and urgent occupational health concern.

NIHL is a prevalent occupational disease on a global scale and has become a global public health issue. Given the limited efficacy of treatment effect, strengthening the research on the ethology and pathogenesis of NIHL, screening reliable biomarkers for predicting the occurrence and development of NIHL, has become a focus of occupational disease prevention and control research in China and even globally. NIHL is a complex disorder caused by the interaction of genetics and environment [11]. Studies conducted on long-term animal experimentation and population epidemiology have demonstrated that even under identical noise exposure, hearing thresholds displace differently among different types of animals and populations, which shows that individuals have different susceptibilities to noise sensitivity. In addition to the influence of other confounding factors, genetic factors play a key role in NIHL development [12]. A major role played by oxidative stress in NIHL’s pathogenesis has been established [13]. As a result of mutations in oxidative stress-related genes, reactive oxygen species oxidative damage is not fully eliminated since the oxidative and antioxidative systems are disturbed in the cochlea, a structural and functional disorder of the cochlea that ultimately results in hearing loss [14].

Known as a crucial set of phase II drug-metabolizing enzymes, glutathione S-transferases (GSTs) have a significant antioxidant role in cochlear protection and catalyze the conjugation of numerous endogenous and exogenous substances with depleted glutathione [15]. In this way, GSTs protect body cells from harmful compounds by protecting them daily from detoxification, such as reactive oxygen species. This process of detoxification is closely associated with the capacity of each individual, which is influenced by the individual’s genetic background. Among the GST enzyme subclasses, GSTT1, GSTM1, and GSTP1 encode GST-θ, GST-μ, and GST-π, respectively. In the population, these three genes have been well described for their genetic polymorphisms. GSTT1, GSTM1, and GSTP1 genes are located on chromosome 22q11.23 and chromosome 1.p13.3 and 11q13.2, respectively [16, 17]. Deletions of GSTM1 and GSTT1 genes as well as the polymorphism c.313A >G (rs1695) in GSTP1 have been associated with an increased susceptibility to various multifactorial diseases and potentially impact therapeutic outcomes [18], individuals with these genetic variations may have higher risk to develop NIHL [19].

The genetic heterogeneity of hearing loss is substantial, with variations in hotspot mutations, mutation frequencies, and mutation modes of genes observed across different regions and ethnic groups. There is no consistency in the results regarding the relationship between GST gene polymorphisms and NIHL, as well as GST enzyme activity and GST gene polymorphisms. Additionally, genetic factors are only considered valid when their effects have been replicated in an independent population instead of contradicting results in various studies. Hence, nations and territories are dedicated to acquiring data on mutations in genes associated with hearing loss within their specific regions. China, being a multi-ethnic nation with the Han ethnic group as the predominant population, has a total Han population of 1,286,311,334, representing 91.11% of the country’s population according to the seventh national population census [20]. To ensure genetic homogeneity, representativeness and sufficient sample size, this study focused on the Han population in Beijing, China, as the subject of investigation, examining the correlation between GST gene polymorphisms (specifically GSTT1, GSTM1, and GSTP1 rs1695), total plasma GST activity, and NIHL.

A matched case-control study was conducted, involving the recruitment of 1,145 male workers exposed to noise, who were employed in a large mechanical maintenance facility in Beijing. In this cross-sectional study, Chinese Han males who had been exposed to hazardous noise (≥80 dBA) in their occupation for at least 3 years were eligible for the study. Exclusion criteria included (1) subjects with a previous history of ototoxic drug consumption, acoustic trauma, congenital or familial hearing loss, contagious disease-related hearing loss, Ménière’s syndrome, sudden deafness, exaggerated hearing loss, and feigned deafness; (2) subjects with external and/or middle ear deformities or diseases and conductive hearing loss; and (3) subjects with incomplete or missing survey data and occupational health monitoring data.

After applying the inclusion and exclusion criteria, the results of the audiometry were used to create a two-group classification. In the case group, subjects had an average binaural HTL greater than 25 dB at high frequencies (3 kHz, 4 kHz, 6 kHz). In the control group, subjects were selected based on a maximum age difference of 5 years, a maximum difference in the duration of occupational noise exposure of 3 years, and having the same type of work. Additionally, they had an HTL of 25 dB or lower in any one ear at linguistic frequencies (0.5 kHz, 1 kHz, 2 kHz) and an average binaural HTL of 25 dB or lower at high frequencies (dB(A)). Lastly, this study included a total of 144 cases and 144 controls by employing the 1:1 approach of matching cases with control. All participants provided informed consent, and the Ethics Committee of the Beijing Institute of Occupational Disease Prevention and Treatment approved the study (Ethical approval codes ZFY2019003).

A questionnaire that included individual demographic characteristics (sex, nation, date of birth, etc.), occupational history and occupational exposure history (type of work, duration of employment in current job, duration of noise, etc.), behavioral factors (smoking, alcohol), past use of ototoxic drugs (aminoglycosides, vancomycin antibiotics), history of hearing-related diseases (ear trauma, ear operation, sudden deafness, chronic otitis media, etc.), and family history of deafness was completed for each subject. In this study, smoking status of individuals was classified into two groups: smokers (defined as individuals who currently smoking at least one cigarette per day for over a year) and non-smokers (including individuals who have never smoked, who have occasionally smoked, and who have quit smoking for over 6 months). Drinking status was categorized into two groups: drinkers (defined as individuals who currently consume alcohol at least once a week for over 1 year) and non-drinkers (including individuals who have never consumed alcohol, who have occasionally consumed alcohol, and who have refrained from alcohol consumption for more than 6 months).

Following the typical otoscopic assessment, the participants underwent measurement with a pure-tone audiometer (Intera, Denmark) in a soundproof room to determine the air and bone conduction thresholds for both ears at frequencies of 0.5, 1, 2, 3, 4, and 6 kHz. During the measurement, the surrounding environment remained tranquil, with a noise background value below 25 dB(A). The audiometric raw data were adjusted according to the Diagnostic Criteria of Occupational NIHL (Chinese National Criteria, GBZ49-2014), considering factors like age and sex.

Equation (1) – interpretation of the CNE equation: CNE is the cumulative noise exposure in dB (A)/year; Tref is the reference time, equal to 1 year; n denotes the overall count of job positions where workers experience noise exposure; i represents the code assigned to different occupational positions; T_i signifies the duration of the work history for each occupational position in years; and L_Aeq,8h indicates the A-weighted equivalent continuous sound level for 8 h in dB(A).

EDTA tubes were used to collect venous blood samples at the workplace, and samples were immediately stored in a light-protected container and transported to the laboratory on dry ice. The anticoagulant blood was centrifuged at a radius of 20 cm and 3,000 r/min for 15 min to obtain the serum and stored at −80°C for future use. Enzyme activity was determined using an M3200 PRO multifunctional enzyme-linked immunosorbent assay (Tecan, Switzerland), and a GST assay kit (Nanjing Jiancheng Biotechnology Research Institute, China) was used to measure GST activity. To measure the formation of the glutathione and 1-chloro-2,4-dinitrobenzene (CDNB) conjugate, the GST activity was determined spectrophotometrically at 412 nm.

Genomic DNA was extracted from venous blood samples (2 mL) using an extraction kit (Tiangen Biochemical Technology (Beijing) Co., Ltd., China) according to routine procedures. All the subjects were genotyped for a total of 3 single-nucleotide polymorphisms. Multiplex PCR was used to simultaneously amplify GSTT1 (forward primer: 5′-TTC​CTT​ACT​GGT​CCT​CAC​ATC​TC-′3, reverse primer: 5′-TCA​CCG​GAT​CAT​GGC​CAG​CA-3′) and GSTM1 (forward primer: 5′-GAA​CTC​CCT​GAA​AAG​CTA​AAG​C-3′, reverse primer: 5′-GTT​GGG​CTC​AAA​TAT​ACG​GTG​G-3′), with the human β-globin gene (forward primer: 5′-GCC​CTC​TGC​TAA​CAA​GTC​CTA​C-3′, reverse primer: 5′-GCC​CTA​AAA​AGA​AAA​TCG​CCA​ATC-3′) as a control. People possessing one or more GSTT1 alleles exhibited a 459 bp fragment, whereas those possessing one or more GSTM1 alleles displayed a 219 bp fragment. GSTP1 rs1695 polymorphism was detected using the PCR-restriction fragment length polymorphism technique (forward primer: 5′-CTT​CCA​CGC​ACA​TCC​TCT​TCC-3′, reverse primer: 5′-AAG​CCC​CTT​TCT​TTG​TTC​AGC-3′). The GSTP1 G/A genotype was determined by endonuclease Alw26I. After the PCR products were digested with restricted Alw26I, homozygous AA individuals had a fragment of 289 bp, whereas homozygous GG individuals had both 218 and 71 bp fragments and heterozygous G/A individuals had 289, 218 and 71 bp fragments.

The PCR was performed in a combined volume of 30 μL, comprising 100 ng genomic DNA, 0.2 μmol for each of the above primers, 15 μL of Master Mix 2× (MBI Fermentas, Hanover, MD) (which contains 2 mmol of MgCl₂), and ddH₂O. The PCR protocol consisted of an initial denaturation step at 94°C for 5 min, followed by 35 cycles of 30-s denaturation at 94°C, 30-s annealing at 58°C, 30-s extension at 72°C, and a final extension step at 72°C for 10 min. The PCR sample underwent digestion at a temperature of 37°C for a duration of 16 h using 5 U Alw26I (Thermo Fisher Scientific, Waltham, MA, USA) for GSTP1 rs1695. The resulting fragments were then visualized using a UV image system (ESSENTIAL V6, Bio-RAD, Hercules, CA, USA) on a 2% MetaPhor agarose gel (Sigma, USA). To ensure quality control, we chose a random 10% of DNA samples to repeat, and all of them were in agreement.

Continuous variables that conformed to a normal distribution were expressed as mean ± standard deviation (⁠$x¯$ ± s), while non-normally distributed continuous variables were described using the median (M) and interquartile range (P₂₅, P₇₅). The paired-samples t test and Wilcoxon sign test were used to compare continuous variables between two groups. The paired χ² test was used for categorical variables. Hardy-Weinberg equilibrium (HWE) test was performed using Pearson’s χ² for GSTP1 rs1695. NIHL factors were analyzed using 1:1 paired multivariate conditional logistic regression. The associations between GST enzyme activity and the development of NIHL were examined using multiple linear regression models. We conducted all two-sided statistical analyses using the SPSS 23.0 (IBM, Chicago, IL, USA) software program and set the significance level at 0.05.

According to Table 1, the study involved 288 subjects, 144 cases and 144 controls. A well-matched case and control group showed no significant differences in age, noise-exposed age, or CNE (p > 0.05). GST activity was significantly lower in case subjects than in control subjects (W = 4,076.500, p = 0.031). There were no significant differences between the case and control subjects in terms of their smoking or drinking habits (p = 1.000 and 0.215, respectively).

1:1 paired multivariate conditional logistic regression was performed, with GST activity, smoking, and alcohol consumption as the independent variables and NIHL as the dependent variable. The findings indicated a statistically significant association between NIHL and GST enzyme activity, after adjusting for potential confounding variables (p < 0.05), shown in Table 2.

1:1 paired multivariate conditional logistic regression was performed, with GSTT1, GSTM1, GSTP1 rs1695 gene polymorphisms and smoking and alcohol consumption as the independent variables and NIHL as the dependent variable. According to Table 3, the frequency of individuals with the GSTT1 null genotype was 46.18%, and there was no notable distinction between the case and control groups concerning GSTT1 null genotypes in relation to NIHL (50.00% vs. 42.36%, p > 0.05). The percentage of subjects with the GSTM1 null genotype was 56.94%, and there was a notable disparity between the case and control groups regarding GSTT1 null genotypes (64.5% vs. 49.31%, p = 0.013, adjusted OR = 0.55, 95% CI: 0.34–0.88). The HWE for the GSTP1 gene was determined using the χ² test. GSTP1 genotype distribution was consistent with HWE (χ² = 1.21, p = 0.27), suggesting that the selected subjects were representative. There were 60.76% homozygous wild-type AA, 35.76% heterozygous AG, and 3.47% homozygous mutant GG genotypes observed for GSTP1 rs1695. However, a statistical association with NIHL was not found according to the distribution of rs1695 genotypes and allele frequencies between the two groups.

A multiple linear regression model was conducted to assess the relationship between plasma GST enzyme activity, ranked as the dependent variable, and GSTT1, M1, and P1 gene polymorphisms, smoking status, and alcohol consumption as independent variables. According to Table 4, indicating no significant statistical association between GST enzyme activity and the genotype of GST T1, M1, and P1.

This study aimed to identify factors related to NIHL by focusing on the GST gene, which plays a role in cochlear damage caused by noise. The gene is a candidate for research on NIHL susceptibility. Through a comprehensive literature review and thorough understanding of the subject, the selection of the GST gene as a candidate gene for research on NIHL susceptibility is theoretically justified. Numerous reports have been published both domestically and internationally regarding the association between GST gene polymorphism and genetic susceptibility to NIHL [11, 22‒27]. However, limited research exists on the connection between GST gene polymorphism, enzyme activity, and NIHL risk. Our study aimed to fill this gap by providing data and scientific evidence for identifying NIHL biomarkers and understanding the role of the GST gene in NIHL development.

The GST genes exhibit significant polymorphism. Mutation frequency is relatively high in humans and varies greatly according to environmental differences and racial differences. In the present study, it was found that the observed frequency of the null genotypes of GSTT1 was 46.18%, which is on the low end of the range of 45.52–60.3% reported in some Chinese populations [17, 22]. Our results showed that the observed genotype frequencies of AA, AG, and GG of GSTP1 rs1695 were 60.76%, 35.76%, and 3.47%, respectively. The allele frequencies of A and G were 78.65% and 21.35%, respectively, which are similar to those found in some previous studies on Chinese individuals [12, 23‒25].

There were no statistically significant differences between the two groups in terms of age, noise-exposed age, CNE, smoking rate, or drinking rate, suggesting a balanced distribution among the two groups. The results suggested that GSTT1 and GSTP1 gene mutations do not appear to be associated with NIHL. However, GSTM1 polymorphisms might play a role in the occurrence of NIHL in Chinese workers exposed to noise. Moreover, individuals with the GSTM1 null genotype had a 1.82 times greater risk of developing NIHL compared to those with the wild-type genotype. NIHL might be more prevalent in individuals who have the GSTT1 null genotype. There have been several previous studies that have confirmed this finding [25‒27]. As members of the GST family, whereas GSTM1 has a protective effect on NIHL, while GSTT1 and GSTP1 do not. The altered functions of GSTT1, GSTP1, and GSTM1 may be related to their diverse preferences for the tissues and substances implicated in harm to hair cells caused by noise [25]. One notable distinction among GSTT1, GSTM1, and GSTP1 appears to act as a metabolite conjugator [28]. GSTT1 has the ability to act as a conjugator or an activator of metabolites, whereas GSTP1 appears to be primarily restricted to Deiter’s cells and pillar cells [29]. Due to this difference, GSTM1 has a stronger effect on workers under noise exposure than GSTT1 and GSTP1.

Recent studies have shown that GST activity is altered by genetic polymorphisms, which contribute to the variability of xenobiotic responses among individuals [30]. In zoological experiments, animals carrying the GSTT1 null genotype or GSTM1 null genotype were unable to express the corresponding enzymes, resulting in significantly lower GST activity in their liver and kidneys compared to animals carrying the wild-type genotypes [31, 32]. Population studies have found that mutation of GSTT1, GSTM1, and GSTP1 rs1695 can lead to a decrease in serum GST activity [33‒35]. In this study, although the distribution frequency of GSTM1 genotypes was observed to have an impact on GST enzyme activity, no association was found between GSTT1, GSTM1, and GSTP1 rs1695 gene polymorphisms and GST enzyme activity. This topic still needs further research, considering that it is possible that the total enzyme activity of the entire GST family enzyme family was tested in this study, and the enzyme activities of GSTT1, GSTM1, and GSTP1 were not detected separately, thus failing to reveal the internal relationship between GST gene polymorphisms and enzyme activity.

The strengths of this study are its 1:1 paired study design (matched according to sex, age, years of noise exposure, and job type), which controls for confounding factors as much as possible, and the study population’s genetic uniformity, specifically including only individuals with Han Chinese ancestry from Beijing. This study used a 1:1 paired study design to control for confounding factors as much as possible but still has several limitations. One limitation of the study is that the population included in the study is male Han Chinese with a single occupation. Although the interference of sex and ethnic factors on health effects is excluded, there may be certain limitations in the extrapolation application of the research results. Another limitation is that we were unable to measure the different GST isoenzyme activities. Due to this, there is no direct biochemical/functional evidence for GSTT1, GSTM1, or GSTP1 polymorphisms affecting catalytic activities. Additional inquiries are necessary to establish the correlation between GST gene variations and GST isoenzyme function in the progression of NIHL.

In summary, our results suggest that people with the GSTM1 null genotype are more susceptible to NIHL, which aligns with the findings of GST activity tests, suggesting that the GSTM1 gene may be a genetic susceptibility gene and that the serum level of GST may be an effective biomarker of NIHL in the Han Chinese population. The research positively influences risk assessment and early prevention strategies for NIHL in noise-exposed populations, while also providing valuable data and scientific basis for understanding NIHL mechanisms. Identifying NIHL susceptibility biomarkers can advance studies on other auditory disorders, offering insights for similar research on various hearing impairments and potentially other diseases.

We thank the mechanical maintenance company for its cooperation in this research. We would also like to express our gratitude to all the workers for cooperating with our study.

This study protocol was reviewed and approved by the Ethics Committee of Beijing Institute of Occupational Disease Prevention and Treatment, Approval No.: ZFY2019003. Written informed consents were obtained from all participants.

The authors have no conflicts of interest to declare.

This study was funded by the Natural Science Foundation of Beijing Municipality (7222252).

Fang Ji contributed to funding acquisition, methodology, investigation, formal analysis, writing – original draft, and writing – review and editing and performed the experiments. Jian Zhang contributed to formal analysis, software, writing – original draft, and writing – review and editing. Xiaowen Ding contributed to resources and investigation. Li Rong and Xiao Dong Liu contributed to investigation and performed the experiments. Tenglong Yan contributed to supervision and writing – review and editing. Jue Li contributed to resources, supervision, and writing – review and editing. All authors approved the manuscript before submission including their names and order of authors.

Fang Ji and Jian Zhang are the first authors and contributed equally to this work.

All data generated or analyzed during this study are included in this published article. Further inquiries can be directed to the corresponding author.