In this study, we conducted a two-sample Mendelian randomization approach to explore the causal effects of workplace exposures on aging at the level of genetic susceptibility, which included 9 common hazards in the work environment (including noise, hazardous chemicals, psychological stress, shift work, heavy physical activity). To examine whether genetic variants were associated with phenotypes, we compared individuals with one or more variants with those without. If the difference is large enough to be statistically significant, we say that the variant is "correlated" with the phenotype. According to our discovery analysis, SNPs associated with noise and heavy physical activity were found to be associated with telomere length, while SNPs associated with hazardous chemical pollution in the workplace (such as diesel exhaust) were associated with accelerated DNA methylation GrimAge.
Telomere length is an effective indicator of cell division potential, and it is also one of the reliable signals to evaluate cell senescence. Many external environmental stressors can lead to telomere damage and shortening, while the loss of higher-order structure of telomere may trigger senescence and/or apoptosis.(26) There are few studies on the relationship between environmental noise and telomere length, and there is even less research on the relationship between occupational noise exposure and telomere length. Current studies mostly focus on the effects of environmental noise and air pollutants on telomere length. The amount of traffic noise and the distance of residential buildings from main roads are related to telomere impairment. In addition, exposure to noise pollution during pregnancy also has a negative impact on offspring telomere length(8, 27, 28). Y. Lu et al. explored the effects of noise, lead and isopropanol exposure in the environment of electronic processing plants on telomere length. Exposure to noise and organic compounds can also lead to telomere damage, which is consistent with the results of this study that noisy working environment can lead to the damage of telomere length.
In this paper, the P value of the Mendelian randomization analysis of the sensitive SNPs of asbestos and other minerals and telomere length is close to 0.05 (P = 0.059). Current studies have also shown that occupational exposure to silica dust and asbestos also causes changes in telomerase and telomere-related genes, which provides support for our results.(29–31) In an earlier study, M. Collins et al. found abnormally shortened DNA telomeres in muscle cells of athletes with excessive physical activity, resulting in excessive production of reactive oxygen species. In a study by Chirag M Vyas et al., Consistent with our results, individuals with high physical activity (> 30 + MET-hours/week) also had shorter telomere length.(32, 33) The telomere length shortening induced by occupational exposure to environmental hazards may be caused by oxidative stress and gene regulation. From this point of view, noise exposure and high-intensity physical activity are adverse stresses for the body, which trigger a series of oxidative stress reactions in the body. The produced oxygen free radicals will attack telomeres, leading to telomere damage and even biological aging of the body.(34)
DNA methylation level has also become an important tool for assessing biological age in recent years. Using methylation array technology to identify CpG, through a specific mathematical algorithm, the biological age of biological DNA samples in years can be obtained, called DNAm age. DNA methylation is a very important part of epigenetic regulation. Exogenous factors such as nutrition, lifestyle and environmental conditions can make cells subject to a series of epigenetic regulation and affect the expression of the genome. Accelerating functional aging of organs makes individuals more susceptible to diseases, that is, environmental-gene interaction plays an important role in the risk of accelerated aging(35). We used DNA methylation Grim Age clock acceleration as one of the outcomes, which is associated with diesel engine pollution sensitivity at the genetic level. There has been a lot of evidence that diesel exhaust can cause some DNA methylation. For example, R. L. Clifford measured CpG aggregation in the airway and alveolar epithelial cells of people who inhaled diesel exhaust, and showed that diesel exhaust can cause DNA methylation by inducing oxidative stress in cells. At the same time, exposure to diesel engine exhaust can also increase the methylation level of mitochondrial DNA in workers, and the exposure during pregnancy can also lead to an increase in the DNA methylation level of myocardial cells in their offspring.(36–38) This is also consistent with our results that regular exposure to diesel exhaust in the working environment does lead to increased DNA methylation levels, which also reflects the biological aging of cells and organisms to some extent.
Advantages and Limitations
The advantages of our study are listed as follows: first, the Mendelian randomization method we used has the unique advantages of natural randomization and avoidance of reverse causality and confounding. Mendelian randomization uses genes instead of exposure and replaces the scores of genes into the regression model, which can effectively eliminate the interference of reverse causality and confounding factors in the traditional causal analysis method, and more accurately confirm the causal association. Second, we uniformly took into account risk factors in the work environment, which had not been done in previous studies, and aim to provided corresponding clues for subsequent research. Third, we did not use single aging indicator, and Phewas method was also used for two-way validation, and rs3785354 were identified after two-way validation, which increased the reliability of our study.
The limitations of our study are also discussed. First, the occurrence of aging is caused by the combined effect of individual genetics and environment. It is narrow to discuss the effect of a certain exposure on the outcome only from the perspective of genes, which can explain our test results are statistically significant, but the actual effect size is too small to reflect the real-world situation. Second, the data we used were obtained from existing databases, so complete information on exposure dose, exposure frequency, and protective equipment of workers could not be obtained, and dose-response relationship could not be explored, which is also a defect for causal inference. Thirdly, the actual genetic effect of SNPs is also worth discussing. Although both of them are indicators of aging, telomere length and DNA methylation GrimAge acceleration are related to different work hazards, and there is a correlation between the two after testing, which is worthy of further exploration and search for comprehensive indicators of aging with high accuracy.