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  • Systematic Review
  • Open access
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Candidate gene polymorphisms associated with silicosis and coal workers’ pneumoconiosis: a systematic review and meta-analysis

BMC Pulmonary Medicine volume 24, Article number: 580 (2024) Cite this article

Abstract

Background

Silicosis and coal worker’s pneumoconiosis primarily result from exposure to silica and coal dust. Despite similar exposure levels, individuals exhibit varying responses. This study aimed to address these gaps to explore the genetic factors influencing the development, severity, and associated complications.

Methods

A systematic literature search was performed across four databases—PubMed, Embase, Web of Science, and Cochrane Library—until July, 2023. Qualitative and quantitative analyses were applied to identify candidate genes.

Results

This study involved 83 articles and encompassed 545 individual studies, reviewing a total of 378 gene loci. After rigorous evaluation, we selected 8 candidate genes (TNFα-308, TNFα-238, GSTT1, IL-1α + 4845, IL-1β-511, IL-1β + 3953, IL-1RA + 2018, and IL-6–174) for meta-analysis. The analysis revealed that allele A of TNFα-308, allele A of TNFα-238, and allele C of IL-1RA + 2018 were identified as risk factors for the development of diseases.

Conclusions

This study established associations between specific genetic polymorphisms (TNFα-308, TNFα-238, and IL-1RA + 2018) and susceptibility to silicosis and coal worker’s pneumoconiosis.

Peer Review reports

Introduction

Silicosis and coal workers’ pneumoconiosis (CWP) are the main occupational diseases caused by the inhalation of silica dust or the mixture of silica and carbon dust, belonging to the category of pneumoconiosis, and poses a significant threat to human health by inducing pulmonary fibrosis [1]. Silica, the most abundant mineral, exists in both crystalline and amorphous forms. Traditionally, silicosis and CWP have been associated with respiratory crystalline silica dust [2]. Quartz, the most common type of crystalline silica, occurs naturally in rocks like sandstone and granite at varying concentrations [3]. Traditional industries with exposure to crystalline silica dust are commonly linked to natural stone, such as mining, construction, manufacturing and so on [4]. Many of these industries are prevalent in low and middle-income countries like China, India, Brazil, and others. For example, China recorded over 500,000 patients of silicosis between 1991 and 1995, with an annual addition of 6,000 new patients, while in India, approximately 10 million workers are exposed to silica dust [5]. The risk of suffering from silicosis in these industries has been recognized for several decades. In response, the World Health Organization (WHO) and the International Labour Organization (ILO) initiated a public awareness and prevention campaign in 1995 with the aim of eliminating silicosis worldwide by 2030 [2].

Unfortunately, since 2010, outbreaks of the diseases have been reported outside the mining sector, particularly in developed countries such as Spain, the USA, and Austria [6,7,8,9]. The reason behind these outbreaks is the widespread application of artificial stone in modern industries, used for fabricating kitchen and bathroom benchtops [10]. It is also extensively used in other industries, including finishing, cutting, demolishing, and grinding high silica-containing materials, as well as installation and hydraulic fracturing in the oil and gas industry [8, 9]. New occupations are being recognized as high-risk work due to exposure to artificial stone [11]. Artificial stone contains higher concentrations of silica than natural stone, resulting in greater harm to health [7, 12]. Crystalline silica levels in the alveoli of patients exposed to artificial stone are greater than those of workers without silicosis or workers without occupational exposure [13].

Recent studies have demonstrated that amorphous silica also has adverse effects on human health, including fibrosis [14, 15]. Amorphous silica is prevalent in various fields, such as material science, manufacturing, biotechnology, food, medicine, diagnostics, and healthcare industries [16]. The extensive use of amorphous silica has increased the difficulty of controlling silica exposure-related diseases.

Interestingly, despite workers in the same factory being exposed to similar concentrations of silica dust, they exhibit diverse health outcomes, suggesting variable individual responses to silica dust. These individual responses may, in part, be attributed to genetic polymorphisms. Genetically, alleles refer to pairs of genes situated at the same locus on homologous chromosomes. Within the population, two or more different alleles can exist at a specific gene locus, with a gene frequency greater than 1%. This occurrence is known as gene polymorphism, which manifests as genetic variations among individuals. Since the initial documentation of gene polymorphisms associated with silicosis in the 1970s [17], studies investigating gene variations in relation to silicosis have proliferated over the past 50 years. The present study evaluated the genes qualitatively and quantitatively, focusing on the development of silicosis and CWP, the severity of disease, and the complications associated with silicosis and CWP, especially complications with pulmonary tuberculosis.

Methods

Literature search strategy

The performance of this systematic review and meta-analysis followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [18], and its adherence was confirmed using the PRISMA 2020 statement [19](see Table and Figure, Supplemental Content 1, PRISMA 2020 item checklist and flow diagram). A comprehensive literature search was conducted in four English databases, namely PubMed, Embase, Web of Science, and Cochrane Library, using specific search terms and combinations. Details of the query formulations for each database were not showed in this article (see Table, Supplemental Content 2, search strategy). Additionally, a manual search was conducted by reviewing relevant reviews and other articles. The search was limited to articles published in English, The first search limited to silicosis was updated until October 4th, 2022. Then, the literature was updated until July 27th, 2023. The second search adding CWP was updated until July 27th, 2023.

The inclusion and exclusion criteria were guided by the population-exposure-comparator-outcome (PECO) framework [20]. The following inclusion criteria were applied. (1) Studies involving patients with silicosis or CWP or workers exposed to silica. (2) Studies investigating genetic polymorphisms in the corresponding population. (3) Study designs including patient-control, cohort, or cross-sectional studies, with or without a control group.(4) Availability of data that could be extracted entirely or partially for qualitative analysis, and data that could be used to calculate odds ratios (OR) and 95% confidence intervals (CI) for quantitative analysis. The exclusion criteria were as follows. (1) Studies not conducted on humans. (2) Duplicate or repeated data. (3) For quantitative analysis, studies in which the genotype distributions in control groups did not conform to the Hardy–Weinberg equilibrium (HWE). Data extraction was performed by two independent reviewers who reviewed each article.

The following information was collected from each study: first author, publication year, study country, ethnicity, sample numbers, source of the control population if applicable, age, study type, genetic loci, specimen type, genotype analysis method, outcomes, during the data collection process, both reviewers ensured that the information was documented according to the specified criteria.

Quality assessment of each included article in the meta-analysis was conducted using the Newcastle–Ottawa Scale (NOS) [21]. The assessment involved three components(see Text, Supplemental Content 3, NOS). The total scores ranged from 0 to 9, with scores equal to or greater than 7 considered indicative of high-quality studies. Two independent reviewers evaluated the quality of each article, and any disagreements were resolved through negotiation and consensus.

Statistical analysis

For the meta-analysis of gene loci that were studied in three or more studies, at first, Hardy–Weinberg equilibrium (HWE) in the control group of each study was explored by using the χ2 test. For studies that p value of HWE above 0.05, pooled effect was calculated by Stata 17.0 software [22]. We calculated odds ratios (ORs) with 95% confidence intervals (CIs) to assess the relationship between gene loci and the disease or condition, with a significance threshold set at a marginal two-tailed p-value of 0.05 [23]. Pooled effect was calculated for the allele model, recessive model, dominant model and co-dominant model respectively. The results were presented using forest plots. Heterogeneity among the included studies was assessed using Cochran's Q test and quantified using the I2 metric, ranging from 0 to 100% [24]. If I2 was less than or equal to 50%, a fixed-effects model was applied; Otherwise, a random-effects model was used. Publication bias was evaluated using Begg’s and Egger's test in Stata 17.0 software, and a funnel plot was constructed [25]. The significance threshold for the two-tailed P-value was set at 0.1. For sensitivity analysis, we sequentially removed each article using Stata 17.0 software and visualized the results using sensitivity analysis plots generated in Stata 17.0 [23]. Subgroup analyses were performed based on different diseases to observe the stability of the results. In cases where other factors, such as age and exposure duration, could potentially affect the results, meta-regression analysis would have been applied. However, it was not necessary for the studies included in this article.

Results

Literature search

The initial search yielded a total of 543 articles, with 537 identified through the query formulation in the databases, and an additional 6 articles were found through manual search until July 27th, 2023.After the screening process, 83 articles were included for systematic review, and out of those, 23 articles met the criteria for inclusion in the meta-analysis. The selection process was illustrated in Fig. 1.

Fig. 1
figure 1

Flow diagram of literature selection

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Characteristics of the enrolled studies

A total of 545 studies from 83 articles were included in the systematic review [26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108]. Among these studies, 450 focused on the development of silicosis and CWP, 109 examined the severity of silicosis and CWP (with 56 of the 109 studies overlapping with those investigating the development of silicosis and CWP), 15 studies explored the association between pulmonary tuberculosis and silica dust exposure in workers. Furthermore, 17 studies investigated the relationship between lung cancer and silica dust exposure in workers (with 3 of these studies overlapping with those on the development of silicosis and CWP). Then 7 studies, 3 studies, 3 studies, 44 studies focused on complications with urinary bladder cancer, hypertension, dyslipidemia, and abnormal immune markers, respectively. The characteristics of all included studies were shown in supplementary materials(see Table, Supplemental Content 4, characteristics of all studies included in systematic review).

The selected gene loci and the development of silicosis and CWP

A total of 378 gene loci were included in this paper. Out of these gene loci, 346 were associated with the development of silicosis and CWP. Detailed gene names were shown in supplemental materials (Supplemental Content 4 and 5).

A meta-analysis was conducted for 8 gene loci (TNFα−308 (G > A), TNFα−238 (G > A), IL-1α + 4845(G > T), IL-1β−511 (C/T), IL-1β + 3953 (C > T), IL-1RA + 2018 (T > C), and IL-6–174 (G > C), GSTT1 (positve/null)) related to the development of silicosis or CWP, which were studied in at least three articles with available integrated data. The results of quality assessment were shown(see Table, Supplemental Content 6, NOS scores for studies included in meta-analysis).The results of HWE for control groups in each study was shown in Table 1. In some studies, patients with silicosis or CWP were in control groups, then HWE would not be applied. The characteristics of the included studies can be found in Table 1, while the pooled effects are presented in Table 2.

Table 1 The characteristics of included studies
Full size table
Table 2 Pooled effects of gene loci about the development, severity and combination with tuberculosis
Full size table

TNFα−308 was found to be associated with the development of silica-related pneumoconiosis, with forest plots illustrating the findings in Fig. 2A and B. The results for the alleles of TNFα−308 showed an OR of 1.37 with a 95% CI of 1.18–1.58 and a P-value of 0.000. The results for the dominant model (AA + GA vs GG) of TNFα−308 indicated an OR of 1.50 with a 95% CI of 1.26–1.79 and a P-value of 0.000. The results for the co-dominant model 2 (GA vs GG) showed an OR of 1.46 with a 95% CI of 1.21–1.75, and a P-value of 0.000. Egger's test was showed a P-value less than 0.1 in these three genetic models. After performing trim and fill analysis to account for publication bias, the result was consistent with the initial finding. OR adjusted was 1.65 with a 95% CI of 1.01–2.70, 1.81 with a 95% CI of 1.04–3.13 and 1.84 with a 95% CI of 1.23–2.75, for allele model, the dominant model and the co-dominant model 2, respectively. It is suggested a significant association with the development of silica-related pneumoconiosis. Regarding the recessive model (AA vs GG + GA) of TNFα−308, there was no significant association with the development of silica-related pneumoconiosis (OR 1.42, 95%CI 0.94–2.15, P = 0.100, after correction for publication bias, OR 2.06, 95% CI 0.78–5.43, P = 0.146). Subgroup analysis revealed significant differences for allele model Avs G, dominant genetic model (AA + GA) vs GG and co-dominant genetic model 2 GA vs GG of TNFα−308 between the patient and control groups in the silicosis and CWP respectively.

Fig. 2
figure 2

Forest plots of the development of silicosis and coal worker’s pneumoconiosis (CWP) and TNFα−308. a The development of silicosis and CWP and alleles (A vs G) of TNFα−308(G > A). b The development of silicosis and CWP and dominant model (AA + GA vs GG) of TNFα−308(G > A). c The development of silicosis and CWP and recessive model (AA vs GG + GA) of TNFα−308(G > A). Forest plots of the development of silicosis and coal worker’s pneumoconiosis (CWP) and TNFα−308. d The development of silicosis and CWP and co-dominant model 1 (AA vs GG) of TNFα−308(G > A). e The development of silicosis and CWP and co-dominant model 2 (GA vs GG) of TNFα−308(G > A)

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TNFα−238 was associated with the development of silica-related pneumoconiosis, with forest plots illustrating the findings in Fig. 3A and B. Compared case group with control group, the alleles showed an OR of 1.56 with a 95% CI of 1.03–2.36 and a P-value of 0.037, indicating a significant association. Similarly, the dominant model (AA + GA) vs GG displayed an OR of 1.55 with a 95% CI of 1.22–1.98 and a P-value of 0.000. Additionally, the co-dominant model 2 (GA vs GG) showed an OR of 1.53 with a 95% CI of 1.19–1.98 and a P-value of 0.001. They also demonstrated a significant association. For the allele model, heterogeneity analysis showed a higher heterogeneity, subgroup analysis according diseases (CWP or sillicosis) and different ethinics (Asian or Caucasian) did not reduce the value of I2 in subgroup. Regarding the recessive model (AA vs GG + GA) of TNFα−238, there was no significant association with the development of silica-related pneumoconiosis (OR 1.49, 95%CI 0.75–2.97, P = 0.254).

Fig. 3
figure 3

Forest plots of the development of silicosis and coal worker’s pneumoconiosis(CWP) and TNFα−238. a The development of silicosis and CWP and alleles (A vs G) of TNFα−238(G > A). b The development of silicosis and CWP and dominant model (AA + GA vs GG) of TNFα−238(G > A). c The development of silicosis and CWP and recessive model (AA vs GG + GA) of TNFα−238(G > A). Forest plots of the development of silicosis and coal worker’s pneumoconiosis(CWP) and TNFα−238. d The development of silicosis and CWP and co-dominant model 1 (AA vs GG) of TNFα−238(G > A). e The development of silicosis and CWP and co-dominant model 2 (GA vs GG) of TNFα−238(G > A)

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IL-1RA + 2018 was associated with the development of silicosis, with forest plots illustrating the findings in Figure S1(see Figure, Supplementary Content 7 forest plots).The results for the allele model showed an OR of 1.80, with a 95% CI of 1.17–2.75, and a P-value of 0.007. For the CC + TC vs TT comparison, the OR was 1.89, with a 95% CI of 1.08–3.31, and a P-value of 0.026. Futhermore, for the CC vs TT + TC comparison, the OR was 2.40, with a 95% CI of 1.29–4.45, and a P-value of 0.006. Additionally, for the CC vs TT comparison, the OR was 2.74, with a 95% CI of 1.44–5.20, and a P-value of 0.002.Regarding the genetic model TC vs TT, there was no significant association with the development of silica-related pneumoconiosis(OR 1.71, 95% CI 0.93–3.13, P = 0.082).For allele model and dominant model, studies demonstrated high heterogeneity. Subgroup analysis showed that in subgroup of patients with silicosis, I2 was 0.0% in both models, indicating a homogeneity between studies.

IL-1α + 4845, IL-1β−511, IL-1β + 3953, IL-6–174, and GSTT1 was not found to be associated with the development of silicosis and CWP, with corresponding forest plots displayed in Figures S2-6 (see Figure, Supplementary Content 8–12 forest plots).

The selected gene loci and the severity of silicosis and CWP

88 gene loci were associated with the severity of silicosis and CWP. Detailed gene names were shown in supplemental materials (Supplemental Content 4 and 5). A meta-analysis was conducted for 2 gene loci (TNFα−308 (G > A), TNFα−238 (G > A)), associated with the severity of silicosis or CWP. Here we classified the diseases into two subgroup: complicated cases (also called progressive massive fibrosis, PMF) and simple cases(simple pneumoconiosis, SP). The results of quality assessment were shown(see Table, Supplemental Content 6, NOS scores for studies included in meta-analysis). The characteristics of the included studies can be found in Table 1, while the pooled effects were presented in Table 2.

TNFα−238 was associated with the severity of silica-related pneumoconiosis, with forest plots illustrating the findings in Fig. 4A and B. Compared complicated group (progressive massive fibrosis, PMF) with simple group, the alleles (A vs G) showed an OR of 3.19 with a 95% CI of 2.27–4.48 and a P-value of 0.000, indicating a significant association. Similarly, the dominant model (AA + GA) vs GG displayed an OR of 3.67 with a 95% CI of 1.35–9.98 and a P-value of 0.011, also demonstrating a significant association.Futhermore, the co-dominant model 1 AA vs GG showed an OR of 5.17 with a 95% CI of 1.58–16.99 and a P-value of 0.007. The co-dominant model 2 GA vs GG demonstrated an OR of 3.16 with a 95% CI of 1.05–9.57 and a P-value of 0.041. These two comparisions also indicated a significant association between severe and mild cases.For dominant model and co-dominant model, heterogeneity analysis between studies showed a high heterogeneity, while subgroup analyisis showed I2 was 0.0% in subgroup of silicosis and subgroup of CWP respectively.

Fig. 4
figure 4

Forest plots of the severity of silicosis and coal worker’s pneumoconiosis(CWP) and TNFα−238. a The severity of silicosis and CWP and alleles (A vs G) of TNFα−238(G > A). b The severity of silicosis and CWP and dominant model (AA + GA vs GG) of TNFα−238(G > A). c The severity of silicosis and CWP and recessive model (AA vs GG + GA) of TNFα−238(G > A). Forest plots of the severity of silicosis and coal worker’s pneumoconiosis(CWP) and TNFα−238. d The severity of silicosis and CWP and co-dominant model 1 (AA vs GG) of TNFα−238(G > A). e The severity of silicosis and CWP and co-dominant model 2 (GA vs GG) of TNFα−238(G > A)

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TNFα−308 was not associated with the severity of silicosis and CWP, with forest plots illustrating the findings in Fig. 5A and B.

Fig. 5
figure 5

Forest plots of the severity of silicosis and coal worker’s pneumoconiosis (CWP) and TNFα−308. a The severity of silicosis and CWP and alleles (A vs G) of TNFα−308(G > A). b The severity of silicosis and CWP and dominant model (AA + GA vs GG) of TNFα−308(G > A). c The severity of silicosis and CWP and recessive model (AA vs GG + GA) of TNFα−308(G > A). Forest plots of the severity of silicosis and coal worker’s pneumoconiosis (CWP) and TNFα−308. d The severity of silicosis and CWP and co-dominant model 1 (AA vs GG) of TNFα−308(G > A). e The severity of silicosis and CWP and co-dominant model 2 (GA vs GG) of TNFα−308(G > A)

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The selected gene loci and complication with pulmonary tuberculosis

13 gene loci were associated with pulmonary tuberculosis in workers exposed to silica dust. Details were shown in supplemental materials (Supplemental Content 4 and 5). A meta-analysis was conducted for 1 gene locus (TNFα−308) associated with workers exposed to silica and pulmonary tuberculosis in at least three papers with integrated data. The results of quality assessment were shown (see Table, Supplemental Content 6, NOS scores for studies included in meta-analysis). The characteristics of the included studies can be found in Table 1, while the pooled effects were presented in Table 2. TNFα−308 was not associated with the development of pulmonary tuberculosis in population of workers exposed to silica (Fig. 6).

Fig. 6
figure 6

Forest plots of workers exposed to silica complicated with pulmonary tubercolosis and TNFα−308. a Workers exposed to silica complicated with pulmonary tubercolosis and alleles (A vs G) of TNFα−308(G > A). b Workers exposed to silica complicated with tubercolosis and dominant model (AA + GA vs GG) of TNFα−308(G > A). c Workers exposed to silica complicated with pulmonary tubercolosis and co-dominant model 2 (GA vs GG) of TNFα−308(G > A)

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The selected gene loci and complications

17, 5, 3, 3 and 44 gene loci were involved in complications with lung cancer, urinary bladder cancer, hypertension, dyslipidemia and abnormal immune markers, respectively. Detailed gene names about these eight aspects were not shown in the article (Supplemental Content 4 and 5). No gene about any complications above in exposed workers met the requirement for meta analysis.

Heterogeneity analysis and publication bias during meta-analysis

Heterogeneity analysis and publication bias were recorded in supplementary materials (see Text, Supplementary Content 13, heterogeneity analysis and publication bias). Funnel plots were presented in Figures S7,8 (see Figure, Supplementary Content 14–15 funnel plots).

Sensitivity analysis during meta-analysis

Sensitivity analysis was conducted by systematically excluding each included study in the meta-analysis with five or more articles. The results of the sensitivity analysis were presented in Figures S9,10 (see Figure, Supplementary Content 16–17 sensitivity analysis). The associations between the development of silicosis and CWP and TNFα−308 remained stable, indicating the robustness of the findings.

Discussion

This study provided a comprehensive review of genes from three aspects, that were, the development of silicosis and CWP, the severity of silicosis and CWP, and the development of their complications. A total of 378 gene loci were examined in various publications, with a significant focus on human leukocyte antigen (HLA) genes, cytokines, apoptotic signaling factors, and genes involved in signal transduction. With the emergence of genome-wide association studies (GWAS), there has been an increased focus on gene loci associated with circular RNA (circRNA) and long non-coding RNA (lncRNA), which possess yet unknown functions. Moreover, emerging research is shedding light on additional genes that may play a role in the development and progression of silicosis, although further investigation is needed to understand their specific functions. Additionally, this paper conducted a meta-analysis to investigate the association between genes and the development and the severity of silicosis and CWP, as well as the occurrence of pulmonary tuberculosis in workers exposed to silica.

In the pathogenesis of silicosis and CWP, cytotoxic damage, oxidative stress and inflammation all participate in the process. Pulmonary alveolar macrophages play an important role [109]. The receptors in the macrophage membrane, lysosomes, enzymes in lysosomes, inflammasomes, mediators during the signal transduction in macrophages, and cytokines produced by macrophages all participate in the pathological process of silicosis and CWP [110, 111]. These factors contribute to the development of silicosis and CWP from eliciting oxidative stress, cell damage, cell apoptosis, activating fibroblasts and others. In our systematic review, some genes like BASP, caspase1, CPM, FAM13A, FAS, GST, DSP, IL-4, IL-6, IL-12, IL-17, TNFα, iNOS, NLRP3, NFKB1, COX, ATG, CYBA, GITR, LAMB1 and some circRNAs, lncRNAs, miRNAs are reported to be associated with the development of silicosis or CWP. Many papers focus on TNF and IL. TNF and IL-1 are all important cytokines. In vitro and in vivo experiments have shown that increased expression of TNF is associated with fibrosis in the lung, liver, and kidney [112,113,114,115,116]. Decades ago, some studies found that gene polymorphisms of TNF were associated with the expression of TNF protein [117, 118]. In the disease of silicosis, some publications intended to illustrate the association of TNF gene polymorphisms and the pathogenesis of silicosis, but failed to form a consistent conclusion. Our meta-analysis results shed light on this matter. We revealed a significant relationship between the development of silicosis and CWP and TNFα−308, as well as TNFα−238. Similarly, interleukins are also associated with fibrosis through several molecular pathways. Some studies have demonstrated the association of interleukins and fibrosis [110, 119, 120]. In the disease of silicosis and CWP, IL-1 was focused on in early years. IL-1 includes IL-1α, IL-1β, and IL-1RA. The first two factors are proinflammatory cytokines, and IL-1RA is the antagonist of the IL1 receptor. In vitro, the production of IL-1 was paralleled with the production of collagenase [121, 122]. In animal experiments, the expression of IL-1 secreted by alveolar macrophages isolated from rats with silicosis increased compared to the control group [123]. Neutralization of IL-1β attenuated the silica-induced fibrosis in lung tissue sections in rats [124]. Some studies showed that there was an association of IL-1 gene polymorphisms and the expression of IL-1 was studied [125]. Our meta-analysis showed that the presence of allele C of IL-1RA + 2018 was identified as a risk factor in the development of silicosis. Glutathione S-transferases (GST) is a group of enzymes that play an important role in antioxidant defense. In this meta analysis, no association was detected between CWP susceptibility and polymorphisms of GSTT1, a subclass of GST enzyme family.

Referring to the severity of silicosis and CWP, PMF is an advanced stage of the diseases, and leads to higher mortality than SP. In this article, we compared PMF and SP. At present, little is known about the mechanisms of the progression from SP to PMF. Previous in vitro and vivo studies has shown that some molecular factors has differentiated expression between patients with SP and PMF. These molecular factors referring to pro-inflammation and eliciting fibrosis may indicate their contribution in the progression to PMF. Increased TGFβ expression level was detected in PMF group compared to SP group in rats [126]. IL-8 and ICAM1 were expressed different significantly between SP and PMF [127]. In our systematic review, from the genetic perspective, FASL, IL-12 were associated with PMF in single study respectively.Whether TGF has relation with PMF did not have consistent conclusion. In our meta analysis, the proportion of individuals with the AA and GA genotypes of TNFα−238 was higher in the PMF group compared to the simple group. These results suggest that TNFα−238 genotypes may play a role in determining the severity of silicosis. But TNF α−308 has negative result in PMF.

Additionally, in the systematic review, we tried to detect the relationship of genetic polymorphisms and complications in exposed workers. Some studies focused on the relationship between TNF and pulmonary tuberculosis, though the serum level of TNF was elevated in patients with tuberculosis compared with controls [128], no positive result was found in the association of TNF gene polymorphisms and pulmonary tuberculosis. The meta-analysis showed a consistent result, that is, gene polymorphisms of TNFα−308 did not associate with pulmonary tuberculosis in workers exposed to silica. Recently, additional single nucleotide polymorphisms, such as NOD2 + 802, NOD2 + 2105, and TRAF1/C5 rs10818488, known to impact serum TNF levels, have been investigated in patients with pulmonary tuberculosis. Positive results were observed in these studies [129, 130]. However, there is a lack of further research specifically focusing on exposed workers with pulmonary tuberculosis complications.

It is crucial to recognize the limitations inherent in this study. The heterogeneity test solely focused on types of pneumoconiosis, neglecting other significant factors like dust concentration, specific occupations, and duration of silica exposure during the data extraction process. This omission may have affected the overall analysis. Consequently, furture research should comprehensively incorporate these additional factors to ensure a more nuanced understanding of the relationship between genes and silicosis. Subsequent large-scale studies are warranted to thoroughly assess the impact of diverse variables, including age, ethnicity, and other potential factors, contributing to a more comprehensive comprehension of their effects.

Conclusions

In conclusion, our analysis revealed that allele A in alleles model, AA + GA genotype in dominant model, GA genotype in co-dominant model 2 of TNFα−308(G > A), allele A in alleles model, AA + GA genotype in dominant model and GA genotype in co-dominant model 2 of TNFα−238 (G > A) and allele C in alleles model, CC + TC in dominant model, CC in recessive model and CC in co-dominant model 2 of IL-1RA + 2018(T > C) were identified as risk factors for the development of silicosis and CWP. Furthermore, the presence of allele A of TNFα−238 was identified as a risk factor for the severity of silica related pneumoconiosis. Additionally, no gene locus was identified as a risk factor for pulmonary tuberculosis in population of workers exposed to silica.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

ATG:

Autophagy related genes

BASP:

Bursal Anti-Steroidogenic Peptide

CI:

Confidence intervals

COX:

Cyclooxygenase

CPM:

Carboxypeptidase M

CWP:

Coal workers’ pneumoconiosis

CYBA:

Cytochrome B-245 Alpha Chain

DSP:

Desmoplakin

FAM13A:

Family with sequence similarity 13, member A

FAS:

First Apoptosis Signal

FASL:

First Apoptosis Signal ligand

GITR:

Glucocorticoid-Induced TNFR-Related Protein

GST:

Glutathione S-Transferases

GSTT:

Glutathione S-Transferase Theta

GWAS:

Genome-wide association studies

HLA:

Human leukocyte antigen

HWE:

Hardy–Weinberg equilibrium

ICAM1:

Intercellular adhesion molecule 1

IL:

Interleukin

IL-1RA:

Interleukin-1 Receptor Alpha

ILO:

International Labour Organization

iNOS:

Inducible nitric oxide synthase

LAMB1:

Laminin Subunit Beta 1

NFKB1:

Nuclear factor of kappa light polypeptide gene enhancer in B-cells 1

NLRP3:

NOD-like receptor family pyrin domain-containing 3

NOD2:

Nucleotide-binding oligomerization domain 2

NOS:

New castle-Ottawa Scale

OR:

Odds ratios

PECO:

Population-exposure-comparator-outcome

PMF:

Progressive massive fibrosis

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PTB:

Pulmonary tuberculosis

SP:

Simple pneumoconiosis

TGF:

Transforming Growth Factor

TNF:

Tumour Necrosis Factor

TRAF1:

TNF Receptor Associated Factor 1

WHO:

World Health Organization

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Acknowledgements

We would like to thank Zhao Qing, director of medical services in Beijing Jingmei Group General Hospital for his contribution in the primary data extraction process.

Funding

The work was supported by High Level Public Health Technology Talent Construction Project (DL-02–21) and by Reform and Development Program of Beijing Institute of Respiratory Medicine (Ggyfz202321).

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Authors and Affiliations

  1. Department of Occupational Medicine and Toxicology, Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Workers’ Stadium South Road, Chao-Yang District, Beijing, China

    Yingying Zhang, Di Sun, Yawen Song & Qiao Ye

  2. Department of Respiratory Medicine, Beijing Jingmei Group General Hospital, Beijing, China

    Yingying Zhang

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  1. Yingying Zhang
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  2. Di Sun
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  3. Yawen Song
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  4. Qiao Ye
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Contributions

YyZ: Investigation, Methodology, Formal analysis, Writing Original Draft. DS: Investigation, Data Curation. YwS: Data Curation. QY: Conceptualization, Supervision, Funding acquisition. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Qiao Ye.

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Zhang, Y., Sun, D., Song, Y. et al. Candidate gene polymorphisms associated with silicosis and coal workers’ pneumoconiosis: a systematic review and meta-analysis. BMC Pulm Med 24, 580 (2024). https://doi.org/10.1186/s12890-024-03392-0

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Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

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