Integrative Modeling of Urinary Metabolomics and Metal Exposure Reveals Systemic Impacts of Electronic Waste in Exposed Populations.

IF 3.4 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Metabolites Pub Date : 2025-07-05 DOI:10.3390/metabo15070456
Fiona Hui, Zhiqiang Pang, Charles Viau, Gerd U Balcke, Julius N Fobil, Niladri Basu, Jianguo Xia
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引用次数: 0

Abstract

Background: Informal electronic waste (e-waste) recycling practices release a complex mixture of pollutants, particularly heavy metals, into the environment. Chronic exposure to these contaminants has been linked to a range of health risks, but the molecular underpinnings remain poorly understood. In this study, we investigated the alterations in metabolic profiles due to e-waste exposure and linked these metabolites to systemic biological effects. Methods: We applied untargeted high-resolution metabolomics using dual-column LC-MS/MS and a multi-step analysis workflow combining MS1 feature detection, MS2 annotation, and chemical ontology classification, to characterize urinary metabolic alterations in 91 e-waste workers and 51 community controls associated with the Agbogbloshie site (Accra, Ghana). The impacts of heavy metal exposure in e-waste workers were assessed by establishing linear regression and four-parameter logistic (4PL) models between heavy metal levels and metabolite concentrations. Results: Significant metal-associated metabolomic changes were identified. Both linear and nonlinear models revealed distinct sets of exposure-responsive compounds, highlighting diverse biological responses. Ontology-informed annotation revealed systemic effects on lipid metabolism, oxidative stress pathways, and xenobiotic biotransformation. This study demonstrates how integrating chemical ontology and nonlinear modeling facilitates exposome interpretation in complex environments and provides a scalable template for environmental biomarker discovery. Conclusions: Integrating dose-response modeling and chemical ontology analysis enables robust interpretation of exposomics datasets when direct compound identification is limited. Our findings indicate that e-waste exposure induces systemic metabolic alterations that can underlie health risks and diseases.

尿代谢组学和金属暴露的综合建模揭示了暴露人群中电子废物的系统性影响。
背景:非正式的电子废物(电子废物)回收做法向环境释放复杂的污染物混合物,特别是重金属。长期接触这些污染物与一系列健康风险有关,但对其分子基础仍知之甚少。在这项研究中,我们调查了电子垃圾暴露导致的代谢谱变化,并将这些代谢物与系统生物学效应联系起来。方法:我们使用双柱LC-MS/MS和结合MS1特征检测、MS2注释和化学本体分类的多步骤分析工作流程,应用非靶向高分辨率代谢组学技术,对与Agbogbloshie站点(加纳阿克拉)相关的91名电子垃圾工人和51名社区对照者的尿液代谢变化进行了表征。通过建立重金属水平与代谢物浓度之间的线性回归和四参数logistic (4PL)模型,评估了电子废物工人重金属暴露的影响。结果:发现了显著的金属相关代谢组学变化。线性和非线性模型都揭示了不同的暴露反应化合物,突出了不同的生物反应。本体信息注释揭示了脂质代谢,氧化应激途径和异种生物转化的系统性影响。该研究展示了如何将化学本体和非线性建模相结合,促进复杂环境中的暴露解释,并为环境生物标志物的发现提供了可扩展的模板。结论:在直接化合物鉴定有限的情况下,整合剂量-反应模型和化学本体分析可以对暴露组学数据集进行可靠的解释。我们的研究结果表明,电子垃圾暴露会引起全身代谢改变,从而可能成为健康风险和疾病的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Metabolites
Metabolites Biochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
5.70
自引率
7.30%
发文量
1070
审稿时长
17.17 days
期刊介绍: Metabolites (ISSN 2218-1989) is an international, peer-reviewed open access journal of metabolism and metabolomics. Metabolites publishes original research articles and review articles in all molecular aspects of metabolism relevant to the fields of metabolomics, metabolic biochemistry, computational and systems biology, biotechnology and medicine, with a particular focus on the biological roles of metabolites and small molecule biomarkers. Metabolites encourages scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on article length. Sufficient experimental details must be provided to enable the results to be accurately reproduced. Electronic material representing additional figures, materials and methods explanation, or supporting results and evidence can be submitted with the main manuscript as supplementary material.
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