Liu Sishi, Wang Hao, Cao Yifei, Lu Liping, Wu Yinyin, Lian Fuzhi, Yang Jun, Song Qin
Department of Nutritional and Toxicological Science, Hangzhou Normal University School of Public Health, Hangzhou, China.
Department of Occupational and Environmental Health, Hangzhou Normal University School of Public Health, Hangzhou, 311121, Zhejiang, China.
Sci Rep. 2025 Apr 2;15(1):11320. doi: 10.1038/s41598-025-96016-4.
Although the association between pollution exposure and chronic kidney disease (CKD) has been explored, previous studies have focused on specific effects observed via in vitro or animal experiments. We first conducted a priority screening of pollutants for population CKD risk by using machine learning approaches. We then used the National Health and Nutrition Examination Survey (NHANES) 2007-2016 data from 2415 adults aged 40 years and over to study the joint effects of low-concentration metal exposure and the mediating effects of α-klotho by using Bayesian kernel machine regression (BKMR) and mediation analyses. Priority screening revealed that cadmium (Cd), mercury (Hg), lead (Pb), and thallium (Tl) were associated with the highest risk of developing CKD. The BKMR model revealed a negative joint effect of mixed-metal exposure on CKD risk. Tl presented the highest posterior inclusion probability (PIP) of 1.0000, followed by Pb, with a PIP of 0.6080. Significant mediating effects of α-klotho on Hg-CKD associations were observed. Mendelian randomization demonstrated that a high level of α-klotho is associated with a decreased risk of developing CKD. This is the first study to reveal the risk prioritization of various pollutants in CKD patients, as well as the coexposure effects of metals. Our study also provides insight into the potential mechanisms underlying the association between metal exposure and CKD risk.
尽管已经探讨了污染暴露与慢性肾脏病(CKD)之间的关联,但先前的研究主要集中在通过体外或动物实验观察到的特定影响。我们首先使用机器学习方法对污染物进行了优先筛选,以评估人群患CKD的风险。然后,我们使用2007 - 2016年美国国家健康与营养检查调查(NHANES)中2415名40岁及以上成年人的数据,通过贝叶斯核机器回归(BKMR)和中介分析,研究低浓度金属暴露的联合效应以及α-klotho的中介效应。优先筛选显示,镉(Cd)、汞(Hg)、铅(Pb)和铊(Tl)与患CKD的最高风险相关。BKMR模型显示混合金属暴露对CKD风险有负向联合效应。铊的后验包含概率(PIP)最高,为1.0000,其次是铅,PIP为0.6080。观察到α-klotho对汞与CKD关联有显著的中介效应。孟德尔随机化表明,高水平的α-klotho与患CKD风险降低相关。这是第一项揭示CKD患者中各种污染物风险优先级以及金属共同暴露效应的研究。我们的研究还深入了解了金属暴露与CKD风险之间关联的潜在机制。