全氟和多氟烷基物质与性激素相关泛癌的关系。

IF 4.1 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Toxics Pub Date : 2025-06-14 DOI:10.3390/toxics13060501
Elizabeth Olarewaju, Emmanuel Obeng-Gyasi
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引用次数: 0

摘要

全氟和多氟烷基物质(PFASs)是普遍存在的具有潜在内分泌干扰特性的环境污染物。本研究探讨了暴露于多种PFASs与与性激素相关的泛癌症(PCSH)之间的关系,同时考虑了潜在的非线性关系和相互作用。我们分析了国家健康和营养检查调查(NHANES)的数据,这些数据从1999年到2012年跨越两年的周期,包括14,373名参与者。研究人员评估了六种pfas的血清浓度——全氟辛酸(PFOA)、全氟辛烷磺酸(PFOS)、全氟己磺酸(PFHxS)、全氟癸酸(PFDE)、全氟壬酸(PFNA)和全氟癸酸(PFUA)——与PCSH的关系。统计分析包括描述性统计、Spearman和Pearson相关分析以及线性和逻辑回归模型。此外,贝叶斯核机回归(BKMR)应用于捕获潜在的非线性关系和相互作用。初始t检验显示,PFOS水平在PCSH患者和非PCSH患者之间存在统计学差异(p = 0.0022), PCSH组的PFOS平均水平较高。卡方检验显示种族与PCSH之间存在显著关联(p < 0.001)。线性和逻辑回归分析显示全氟辛烷磺酸有显著相关性。BKMR分析确定PFOA具有最高的后验包涵概率,表明其在解释PCSH风险中的重要性。单变量暴露-反应分析显示,PFAS对个体的影响有限。然而,双变量分析表明,许多联合PFAS评估之间存在复杂的u型相互作用模式。总体暴露效应分析表明,在暴露水平低于0.5分位数时,与暴露水平较高时相比,所有PFASs的综合影响与PCSH的相关性更强。单变量相互作用分析强调,在评估PFOA和PFOS与所有其他全氟辛烷化合物联合暴露的相互作用时,它们是相互作用最大的全氟辛烷化合物。总之,虽然最初的研究结果表明全氟辛烷磺酸和PCSH之间存在正相关,但BKMR分析揭示了全氟辛烷磺酸之间复杂的非线性关系和相互作用。这些发现强调了将全氟磺酸作为一种混合物而不是单个化学物质进行评估的重要性,以及使用能够捕捉非线性关系和相互作用的技术的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association of Per- and Polyfluoroalkyl Substances with Pan-Cancers Associated with Sex Hormones.

Per- and polyfluoroalkyl substances (PFASs) are ubiquitous environmental contaminants with potential endocrine-disrupting properties. This study examines the association between exposure to multiple PFASs and pan-cancers associated with sex hormones (PCSH) while accounting for potential non-linear relationships and interactions. We analyzed data from the National Health and Nutrition Examination Survey (NHANES), spanning two-year cycles from 1999 to 2012 and including 14,373 participants. Serum concentrations of six PFAS-perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUA)-were assessed for their relationship with PCSH. The statistical analyses included descriptive statistics, Spearman and Pearson correlation analyses, and both linear and logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) was applied to capture potential nonlinear relationships and interactions. The initial t-tests showed a statistically significant difference in PFOS levels between individuals with and without PCSH (p = 0.0022), with higher mean PFOS levels in the PCSH group. Chi-square tests revealed a significant association between ethnicity and PCSH (p < 0.001). Linear and logistic regression analyses revealed significant associations for PFOS. BKMR analysis identified PFOA as having the highest posterior inclusion probability, indicating its importance in explaining PCSH risk. Univariate exposure-response analysis revealed limited individual PFAS effects. However, bivariate analysis indicated a complex U-shaped interaction pattern among many joint PFAS assessments. The overall exposure effect analysis suggested that the combined impact of all PFASs was more strongly associated with PCSH at exposure levels below the 0.5 quantile compared to higher levels. Single-variable interaction analyses highlighted PFOA and PFOS as the most interactive PFASs when evaluating their interaction with combined exposure to all other PFASs. In summary, while the initial findings suggested a positive association between PFOS and PCSH, the BKMR analysis revealed complex non-linear relationships and interactions among PFAS. These findings highlight the importance of evaluating PFASs as a mixture rather than as individual chemicals and using techniques that can capture non-linear relationships and interactions.

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来源期刊
Toxics
Toxics Chemical Engineering-Chemical Health and Safety
CiteScore
4.50
自引率
10.90%
发文量
681
审稿时长
6 weeks
期刊介绍: Toxics (ISSN 2305-6304) is an international, peer-reviewed, open access journal which provides an advanced forum for studies related to all aspects of toxic chemicals and materials. It publishes reviews, regular research papers, and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in detail. There is, therefore, no restriction on the maximum length of the papers, although authors should write their papers in a clear and concise way. The full experimental details must be provided so that the results can be reproduced. Electronic files or software regarding the full details of calculations and experimental procedure can be deposited as supplementary material, if it is not possible to publish them along with the text.
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