Wang Fei, Lin Yuanxin, Qin Lian, Zeng Xiangtai, Jiang Hancheng, Liang Yanlan, Wen Shifeng, Li Xiangzhi, Huang Shiping, Li Chunxiang, Luo Xiaoyu, Yang Xiaobo
Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Guangxi Key Laboratory on Precise Prevention and Treatment for Thyroid Tumor, The Second Affiliated Hospital, Guangxi University of Science and Technology, Liuzhou, Guangxi, China; Guangxi Key Laboratory of Environment and Health Research, Guangxi Medical University, Nanning, Guangxi, China.
Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Guangxi Key Laboratory on Precise Prevention and Treatment for Thyroid Tumor, The Second Affiliated Hospital, Guangxi University of Science and Technology, Liuzhou, Guangxi, China.
Environ Int. 2025 Jan;195:109203. doi: 10.1016/j.envint.2024.109203. Epub 2024 Dec 11.
Exposure to per- and polyfluoroalkyl substances (PFAS) may linked to thyroid cancer (TC) risk, but inconsistent findings and a lack of studies on mixed exposures exist, especially regarding novel PFAS compounds. Additionally, little is known about the potential mechanisms underlying the association.
Explore the effects of PFAS exposure on the serum metabolome and its correlation with TC.
A 1:1 age- and sex-matched case-control study was administered with 746 TC cases and healthy controls. Liquid chromatography-high resolution mass spectrometry determined serum 11 PFAS and untargeted metabolome profile. ENET and LightGBM models were used to explore the exposure patterns and perform variable selection. The mixed exposure effects were assessed using Weighted quantile sum regression and Bayesian kernel machine regression. Metabolome-wide association analyses were performed to assess metabolic dysregulation associated with PFAS, and a structural synthesis analysis was used to detect latent groups of individuals with TC based on PFAS levels and metabolite patterns.
Ten of the 11 PFAS were detected in > 80 % of the population. PFHxA and PFDoA exposure associated with increased TC risk, while PFHxS and PFOA associated with decreased TC risk in single compound models (all P < 0.05). Machine learning algorithms identified PFHxA, PFDoA, PFHxS, PFOA, and PFHpA as the key PFAS influencing the development of TC, and mixed exposures have an overall positive effect on TC risk, with PFHxA making the primary contribution. A novel integrative analysis identified a cluster of TC patients characterized by increased PFHxA, PFDoA, PFHpA and decreased PFOA, PFHxS levels, and altered metabolite patterns highlighted by the upregulation of free fatty acids.
PFAS exposure is linked to a higher risk of TC, possibly through changes in fatty acid metabolism. Larger, prospective studies are needed to confirm these findings, and the role of short-chain PFAS requires more attention.
接触全氟和多氟烷基物质(PFAS)可能与甲状腺癌(TC)风险相关,但研究结果不一致,且缺乏关于混合暴露的研究,尤其是关于新型PFAS化合物的研究。此外,对于这种关联的潜在机制知之甚少。
探讨PFAS暴露对血清代谢组的影响及其与TC的相关性。
对746例TC患者和健康对照进行1:1年龄和性别匹配的病例对照研究。采用液相色谱-高分辨率质谱法测定血清中11种PFAS和非靶向代谢组谱。使用ENET和LightGBM模型探索暴露模式并进行变量选择。采用加权分位数和回归及贝叶斯核机器回归评估混合暴露效应。进行代谢组全关联分析以评估与PFAS相关的代谢失调,并使用结构综合分析根据PFAS水平和代谢物模式检测TC患者的潜在亚组。
在超过80%的人群中检测到11种PFAS中的10种。在单一化合物模型中,PFHxA和PFDoA暴露与TC风险增加相关,而PFHxS和PFOA与TC风险降低相关(所有P<0.05)。机器学习算法确定PFHxA、PFDoA、PFHxS、PFOA和PFHpA是影响TC发生的关键PFAS,混合暴露对TC风险具有总体正向影响,其中PFHxA起主要作用。一项新的综合分析确定了一组TC患者,其特征为PFHxA、PFDoA、PFHpA升高,PFOA、PFHxS水平降低,以及游离脂肪酸上调突出显示的代谢物模式改变。
PFAS暴露与较高的TC风险相关,可能是通过脂肪酸代谢的变化。需要更大规模的前瞻性研究来证实这些发现,并且短链PFAS的作用需要更多关注。