Imperial College London

Prof Sonia Dagnino

Faculty of MedicineSchool of Public Health

Visiting Professor



+44 (0)20 7594 2067sonia.dagnino




512Norfolk PlaceSt Mary's Campus





Dr. Sonia Dagnino is a Visiting Professor in Computational Epidemiology in the MRC Centre for Environment and Health at Imperial College London, School of Public Health. She joined Imperial College in 2016 winning a prestigious Marie Sklodowska-Curie Fellowship. She was awarded her PhD in Environmental Science at the University of Montpellier for her work investigating sources of exposure to endocrine disruptors. She then pursued her research as a post-doctoral fellow at the United States Environmental Protection Agency in the National Research Laboratory and the University of Arizona working on the development of new untargeted mass spetrometry approach for the identification of biomarkers of exposures to xenobiotics in humans.

Dr. Sonia Dagnino's research is focused on the analysis and integration of OMICs data in relation to exposures to xenobiotics and or health outcomes. She is currently working on the development of OMICs-based and complutational methodologies to characterize the molecular signatures of the xeno-exposome and the mechanism related to adverse health outcomes.

Dr. Dagnino is also currently involved in two Horizon2020 projects on the exposome EXPOsOMICs and EXPANSE (EXposome Powered tools for healthyliving in urbAN SEttings) Mechanomics (Investigating molecular mechanisms involved in smoking-induced lung cancer ).

Sonia is the editor of the first book on the Exposome "Unravelling the exposome" published by Springer. She is also an associated editor for the journal Frontiers of Public Health Exposome.



Vermeulen R, Bodinier B, Dagnino S, et al., 2024, A prospective study of smoking‐related white blood cell DNA methylation markers and risk of bladder cancer, European Journal of Epidemiology, ISSN:0393-2990

Wada R, Peng F-J, Lin C-A, et al., 2024, Hair-derived exposome exploration of cardiometabolic health: piloting a Bayesian multi-trait variable selection approach, Environmental Science and Technology (washington), Vol:58, ISSN:0013-936X, Pages:5383-5393

Marchiandi J, Alghamdi W, Dagnino S, et al., 2024, Exposure to endocrine disrupting chemicals from beverage packaging materials and risk assessment for consumers., J Hazard Mater, Vol:465

Alcolea J, Donat-Vargas C, Chrysovalantou Chatziioannou A, et al., 2023, Metabolomic signatures of exposure to nitrate and trihalomethanes in drinking water and colorectal cancer risk in a Spanish multicentric study (MCC-Spain), Environmental Science and Technology (washington), Vol:57, ISSN:0013-936X, Pages:19316-19329

Segrado F, Cavalleri A, Cantalupi A, et al., 2022, A software-assisted untargeted liquid chromatography-mass spectrometry method for lipidomic profiling of human plasma samples, International Journal of Biological Markers, Vol:37, ISSN:0393-6155, Pages:368-376

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