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

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Title: From correlation to causation: Integrating cohorts with experimental studies in mixture toxicology.
Authors: Elagali A; Minderoo Foundation, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia. Electronic address: aelagali@minderoo.org., Rüegg J; Department of Organismal Biology, Uppsala University, Uppsala, Sweden., Caporale N; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Human Technopole, Milan, Italy., Testa G; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Human Technopole, Milan, Italy., Sapounidou M; Department of Chemistry, Umea University, Umea, Sweden., Fini JB; National Muséum of Natural History, Laboratory Physiology of Molecular Adaptation, Paris, France., Andersson PL; Department of Chemistry, Umea University, Umea, Sweden., Dunlop S; Minderoo Foundation, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia., Bornehag CG; Department of Health, Karlstad University, Karlstad, Sweden; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA., Gennings C; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.
Source: Neurotoxicology [Neurotoxicology] 2026 Mar; Vol. 113, pp. 103399. Date of Electronic Publication: 2026 Feb 05.
Publication Type: Journal Article; Review
Language: English
Journal Info: Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 7905589 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-9711 (Electronic) Linking ISSN: 0161813X NLM ISO Abbreviation: Neurotoxicology Subsets: MEDLINE
Imprint Name(s): Publication: 2001- : Amsterdam : Elsevier Science
Original Publication: Park Forest South, Ill., Pathotox Publishers.
MeSH Terms: Environmental Exposure*/adverse effects , Toxicology*/methods , Complex Mixtures*/toxicity, Humans ; Animals ; Causality
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.
(Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.)
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Causal inference; Chemical mixtures; Counterfactual modeling; Hybrid epidemiology; SMACH; hMIX
Substance Nomenclature: 0 (Complex Mixtures)
Entry Date(s): Date Created: 20260207 Date Completed: 20260707 Latest Revision: 20260707
Update Code: 20260707
DOI: 10.1016/j.neuro.2026.103399
PMID: 41654310
Database: MEDLINE
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  Data: From correlation to causation: Integrating cohorts with experimental studies in mixture toxicology.
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  Data: <searchLink fieldCode="AU" term="%22Elagali+A%22">Elagali A</searchLink>; Minderoo Foundation, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia; Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia. Electronic address: aelagali@minderoo.org.<br /><searchLink fieldCode="AU" term="%22Rüegg+J%22">Rüegg J</searchLink>; Department of Organismal Biology, Uppsala University, Uppsala, Sweden.<br /><searchLink fieldCode="AU" term="%22Caporale+N%22">Caporale N</searchLink>; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Human Technopole, Milan, Italy.<br /><searchLink fieldCode="AU" term="%22Testa+G%22">Testa G</searchLink>; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Human Technopole, Milan, Italy.<br /><searchLink fieldCode="AU" term="%22Sapounidou+M%22">Sapounidou M</searchLink>; Department of Chemistry, Umea University, Umea, Sweden.<br /><searchLink fieldCode="AU" term="%22Fini+JB%22">Fini JB</searchLink>; National Muséum of Natural History, Laboratory Physiology of Molecular Adaptation, Paris, France.<br /><searchLink fieldCode="AU" term="%22Andersson+PL%22">Andersson PL</searchLink>; Department of Chemistry, Umea University, Umea, Sweden.<br /><searchLink fieldCode="AU" term="%22Dunlop+S%22">Dunlop S</searchLink>; Minderoo Foundation, Perth, WA 6009, Australia; School of Biological Sciences, The University of Western Australia, Perth, WA 6009, Australia.<br /><searchLink fieldCode="AU" term="%22Bornehag+CG%22">Bornehag CG</searchLink>; Department of Health, Karlstad University, Karlstad, Sweden; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.<br /><searchLink fieldCode="AU" term="%22Gennings+C%22">Gennings C</searchLink>; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA.
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  Data: 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.<br /> (Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.)
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  Data: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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