Application of mixture analysis methods in association between metals mixture exposure and DNA oxidative damage

Abstract

Objectives: To study the association between metals mixture exposure and DNA oxidative damage using mixture analysis methods, and to explore the most significant exposure factors that cause DNA oxidative damage. Methods: Workers from steel enterprises were recruited in Shandong Province. Urinary metals were measured by using the inductively coupled plasma mass spectrometry method. The level of urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG) was determined by using the ultra-high performance liquid chromatography-mass spectrometry method. Bayesian kernel machine regression (BKMR), elastic net regression and quantile g-computation regression were used to analyze the association between urinary metals and urinary 8-OHdG. Results: A total of 768 subjects aged (36.15±7.40) years old were included in the study. BKMR, elastic net regression and quantile g-computation all revealed an overall positive association between the mixture concentration and increased urinary 8-OHdG. The quantile g-computation results showed that with a 25% increase in metal mixtures, the urinary 8-OHdG level increased by 77.60%. The elastic net regression showed that with a 25% increase in exposure risk score, the urinary 8-OHdG level increased by 26%. The BKMR summarized the contribution of individual exposures to the response, and selenium, zinc, and nickel were significant contributors to the urinary 8-OHdG elevation. Conclusion: Exposure to mixed metals causes elevated levels of DNA oxidative damage, and selenium, zinc, and nickel are significant exposure factors.