Zhang Yongfang, Zhou Min, Wang Dongming, Liang Ruyi, Liu Wei, Wang Bin, Chen Weihong
Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
J Environ Sci (China). 2025 Jan;147:382-391. doi: 10.1016/j.jes.2023.12.002. Epub 2023 Dec 7.
Arsenic-related oxidative stress and resultant diseases have attracted global concern, while longitudinal studies are scarce. To assess the relationship between arsenic exposure and systemic oxidative damage, we performed two repeated measures among 5236 observations (4067 participants) in the Wuhan-Zhuhai cohort at the baseline and follow-up after 3 years. Urinary total arsenic, biomarkers of DNA oxidative damage (8-hydroxy-2'-deoxyguanosine (8-OHdG)), lipid peroxidation (8-isoprostaglandin F2alpha (8-isoPGF2α)), and protein oxidative damage (protein carbonyls (PCO)) were detected for all observations. Here we used linear mixed models to estimate the cross-sectional and longitudinal associations between arsenic exposure and oxidative damage. Exposure-response curves were constructed by utilizing the generalized additive mixed models with thin plate regressions. After adjusting for potential confounders, arsenic level was significantly and positively related to the levels of global oxidative damage and their annual increased rates in dose-response manners. In cross-sectional analyses, each 1% increase in arsenic level was associated with a 0.406% (95% confidence interval (CI): 0.379% to 0.433%), 0.360% (0.301% to 0.420%), and 0.079% (0.055% to 0.103%) increase in 8-isoPGF2α, 8-OHdG, and PCO, respectively. More importantly, arsenic was further found to be associated with increased annual change rates of 8-isoPGF2α (β: 0.147; 95% CI: 0.130 to 0.164), 8-OHdG (0.155; 0.118 to 0.192), and PCO (0.050; 0.035 to 0.064) in the longitudinal analyses. Our study suggested that arsenic exposure was not only positively related with global oxidative damage to lipid, DNA, and protein in cross-sectional analyses, but also associated with annual increased rates of these biomarkers in dose-dependent manners.
砷相关的氧化应激及由此引发的疾病已引起全球关注,但纵向研究却很匮乏。为评估砷暴露与全身氧化损伤之间的关系,我们在武汉 - 珠海队列的5236次观察(4067名参与者)中,于基线期及3年后的随访期进行了两次重复测量。对所有观察对象检测了尿总砷、DNA氧化损伤生物标志物(8 - 羟基 - 2'-脱氧鸟苷(8 - OHdG))、脂质过氧化(8 - 异前列腺素F2α(8 - isoPGF2α))和蛋白质氧化损伤(蛋白质羰基(PCO))。在此,我们使用线性混合模型来估计砷暴露与氧化损伤之间的横断面及纵向关联。通过利用带有薄板回归的广义相加混合模型构建暴露 - 反应曲线。在调整潜在混杂因素后,砷水平与全身氧化损伤水平及其年增长率呈显著正相关,且呈剂量反应关系。在横断面分析中,砷水平每增加1%,分别与8 - isoPGF2α、8 - OHdG和PCO水平增加0.406%(95%置信区间(CI):0.379%至0.433%)、0.360%(0.301%至0.420%)和0.079%(0.055%至0.103%)相关。更重要的是,在纵向分析中进一步发现,砷与8 - isoPGF2α(β:0.147;95% CI:0.130至0.164)、8 - OHdG(0.155;0.118至0.192)和PCO(0.050;0.035至0.064)的年变化率增加相关。我们的研究表明,砷暴露不仅在横断面分析中与脂质、DNA和蛋白质的全身氧化损伤呈正相关,而且在剂量依赖方式下还与这些生物标志物 的年增长率相关。