From correlation to causation: Integrating cohorts with experimental studies in mixture toxicology

IF 3.8 3区 医学 Q2 NEUROSCIENCES
Neurotoxicology Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI:10.1016/j.neuro.2026.103399
Ahmed Elagali , Joëlle Rüegg , Nicolò Caporale , Giuseppe Testa , Maria Sapounidou , Jean-Baptiste Fini , Patrik L. Andersson , Sarah Dunlop , Carl-Gustaf Bornehag , Chris Gennings
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引用次数: 0

Abstract

Harmful chemical mixtures are pervasive in the environment, yet traditional epidemiological designs face major challenges in establishing causal links between individual chemicals or mixture exposures and health outcomes. These challenges arise from the high dimensionality and inter-correlation of exposures, their mediation through complex molecular pathways, and the practical absence of truly unexposed control groups, due to the ubiquity of synthetic chemicals. However, environmental health research is entering a new era defined by integration of epidemiological and experimental studies as well as recent advances in molecular technologies and computational modelling. Here, we introduce four approaches designed to advance our understanding of chemical mixtures and move beyond correlation to causation and intervention: 1) ‘hMIX’ which integrates human relevant reference mixtures with experimental evidence of adverse effects; 2) the Similar Mixture Approach (SMACH) that translates hazards of chemical mixtures to risks across populations; 3) hybrid epidemiology that bridges experimental and population-based mechanistic insights; and 4) counterfactual theoretical interventions tailored to examine the health benefits of reducing exposure to specific harmful chemicals or mixtures. We propose an integrative framework combining these four approaches to move the chemical mixture field towards causality — a critical step toward predicting and preventing chemical mixture related health effects.
从相关性到因果关系:混合毒理学的综合队列与实验研究。
有害化学混合物在环境中普遍存在,但传统的流行病学设计在确定个别化学品或混合物接触与健康结果之间的因果关系方面面临重大挑战。这些挑战来自暴露的高维性和相互相关性,它们通过复杂的分子途径介导,以及由于合成化学品的普遍存在,实际上缺乏真正未暴露的对照组。然而,环境卫生研究正在进入一个新的时代,其特征是流行病学和实验研究的结合以及分子技术和计算模型的最新进展。在这里,我们介绍了四种方法,旨在提高我们对化学混合物的理解,并超越相关性,走向因果关系和干预:1)“hMIX”,将人类相关的参考混合物与不利影响的实验证据相结合;2)类似混合方法(SMACH),将化学混合物的危害转化为跨人群的风险;3)结合实验和基于人群的机制见解的混合流行病学;4)为检验减少接触特定有害化学物质或混合物对健康的益处而量身定制的反事实理论干预措施。我们提出了一个综合框架,将这四种方法结合起来,将化学混合物领域推向因果关系——这是预测和预防化学混合物相关健康影响的关键一步。
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
Neurotoxicology
Neurotoxicology 医学-毒理学
CiteScore
6.80
自引率
5.90%
发文量
161
审稿时长
70 days
期刊介绍: NeuroToxicology specializes in publishing the best peer-reviewed original research papers dealing with the effects of toxic substances on the nervous system of humans and experimental animals of all ages. The Journal emphasizes papers dealing with the neurotoxic effects of environmentally significant chemical hazards, manufactured drugs and naturally occurring compounds.
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