Imperial College London

Dr Marc Chadeau-Hyam

Faculty of MedicineSchool of Public Health

Reader in Computational Epidemiology & Exposome Science



+44 (0)20 7594 1637m.chadeau




520Medical SchoolSt Mary's Campus





My main research interest resides in the application of novel statistical approaches to answer biologically/epidemiologically-driven questions. My main focus has been on:

1- Computationally efficient models for profiling and integrating data from high-throughput platform

2- Dynamic models for disease progression: development of models to identify features driving disease dynamics and progression.

After graduating my PhD in statistics from the University Paris XI in 2005, working of the modelling of the French epidemic of variant Creutzfeldt-Jakob disease, I was awarded a personal grant to join the London School of Hygiene and Tropical Medicine. I joined Imperial College in 2005 as a Research Associate, and in 2009 I was appointed as a Research Fellow, in Prof Paolo Vineis's group. In 2011 I was promoted Lecturer, and Senior Lecturer (2016) in Statistical Bioinformatics in the Department of Epidemiology and Biostatistics. In 2013, I was awarded an Honorary Reader position at the Institute for Risk Assessment Sciences, at Utrecht University (NL). I also hold a degree of engineer in food sciences, majors in Statistics from a French `grande école’ from the 'Agro group' (ONIRIS, former ENITIAA).

While my background is in disease modelling, my post-doctoral experience focused on the development and application of statistical models to analyse OMICs data. From my involvement in several large-scale projects I gained experience in the analysis of genetic, epigenetic, transcriptomic, proteomic and metabolomic profiles.

Alongside my project-based research, I have maintained methodological activities relating to the development of longitudinal models for the risk and progression of chronic disease.

At the confluence of these two research streams, my current research focuses on the analysis and integration of OMICs markers in relation to complex exposures and or health outcomes. This work aims at characterising molecular signatures of the exposome (including environmental exposures and social factors) and to explore the mechanisms involved in the mediation of these effects.

Teaching - Supervision

Since 2018, I have been the programme director of the MSc in Health Data Analytics and Machine Learning, in collaboration with the Data Science Institute. In the course I also lead two modules.

I am also involved in the MSc Epidemiology where I lead the Advanced Topics in Biostatistics module. 

I coordinate the `Exposome short couse series, which includes three one-week courses on statistical methods to explore the Exposome:

  1. Exposome Basis (Lead: R Vermeulen - Utrecht University)
  2. Exposome Advanced (Lead: M Chadeau-Hyam - ICL)
  3. Exposome Practice (Co-Lead: M Chadeau-Hyam - ICL - B Liquet UPPA, France)

 I have or still am (co-)supervised 6 PhD students.

Publically available code: 

Selected Publications

Journal Articles

Niedzwiecki MM, Walker DI, Vermeulen R, et al., 2019, The Exposome: Molecules to Populations., Annu Rev Pharmacol Toxicol, Vol:59, Pages:107-127

Alfano R, Guida F, Galobardes B, et al., 2018, Socioeconomic position during pregnancy and DNA methylation signatures at three stages across early life: epigenome-wide association studies in the ALSPAC birth cohort., Int J Epidemiol

Campanella G, Gunter MJ, Polidoro S, et al., 2018, Epigenome-wide association study of adiposity and future risk of obesity-related diseases., Int J Obes (lond), Vol:42, Pages:2022-2035

Sandanger TM, Nost TH, Guida F, et al., 2018, DNA methylation and associated gene expression in blood prior to lung cancer diagnosis in the Norwegian Women and Cancer cohort, Scientific Reports, Vol:8, ISSN:2045-2322

Vermeulen R, Hosnijeh FS, Bodinier B, et al., 2018, Pre-diagnostic blood immune markers, incidence and progression of B-cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses, International Journal of Cancer, Vol:143, ISSN:0020-7136, Pages:1335-1347

Jain P, Vineis P, Liquet B, et al., 2018, A multivariate approach to investigate the combined biological effects of multiple exposures, Journal of Epidemiology and Community Health, Vol:72, ISSN:0143-005X, Pages:564-571

Plusquin M, Chadeau-Hyam M, Ghantous A, et al., 2018, DNA Methylome Marks of Exposure to Particulate Matter at Three Time Points in Early Life, Environmental Science & Technology, Vol:52, ISSN:0013-936X, Pages:5427-5437

Campanella G, Polidoro S, Di Gaetano C, et al., 2015, Epigenetic signatures of internal migration in Italy, International Journal of Epidemiology, Vol:44, ISSN:0300-5771, Pages:1442-1449

Guida F, Sandanger TM, Castagne R, et al., 2015, Dynamics of smoking-induced genome-wide methylation changes with time since smoking cessation, Human Molecular Genetics, Vol:24, ISSN:0964-6906, Pages:2349-2359

Fages A, Ferrari P, Monni S, et al., 2014, Investigating sources of variability in metabolomic data in the EPIC study: the Principal Component Partial R-square (PC-PR2) method, Metabolomics, Vol:10, ISSN:1573-3882, Pages:1074-1083

Chadeau-Hyam M, Vermeulen RCH, Hebels DGAJ, et al., 2014, Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis, Annals of Oncology, Vol:25, ISSN:0923-7534, Pages:1065-1072

Chadeau-Hyam M, Tubert-Bitter P, Guihenneuc-Jouyaux C, et al., 2014, Dynamics of the Risk of Smoking-Induced Lung Cancer A Compartmental Hidden Markov Model for Longitudinal Analysis, Epidemiology, Vol:25, ISSN:1044-3983, Pages:28-34

Bottolo L, Chadeau-Hyam M, Hastie DI, et al., 2013, GUESS-ing Polygenic Associations with Multiple Phenotypes Using a GPU-Based Evolutionary Stochastic Search Algorithm, Plos Genetics, Vol:9, ISSN:1553-7404

Chadeau-Hyam M, Campanella G, Jombart T, et al., 2013, Deciphering the complex: Methodological overview of statistical models to derive OMICS-based biomarkers, Environmental and Molecular Mutagenesis, Vol:54, ISSN:0893-6692, Pages:542-557

Vermeulen R, Chadeau-Hyam M, 2012, Dynamic Aspects of Exposure History-Do They Matter?, Epidemiology, Vol:23, ISSN:1044-3983, Pages:900-901

Joffe M, Gambhir M, Chadeau-Hyam M, et al., 2012, Causal diagrams in systems epidemiology., Emerg Themes Epidemiol, Vol:9

Jasra A, De Iorio M, Chadeau-Hyam M, 2011, The time machine: a simulation approach for stochastic trees, Proceedings of the Royal Society A: Mathematical, Physical & Engineering Sciences, Vol:467, ISSN:1364-5021, Pages:2350-2368

Bottolo L, Chadeau-Hyam M, Hastie DI, et al., 2011, ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration, Bioinformatics, Vol:27, ISSN:1367-4803, Pages:587-588

Chadeau-Hyam M, Ebbels TMD, Brown IJ, et al., 2010, Metabolic Profiling and the Metabolome-Wide Association Study: Significance Level For Biomarker Identification, Journal of Proteome Research, Vol:9, ISSN:1535-3893, Pages:4620-4627

Chadeau-Hyam M, Clarke PS, Guihenneuc-Jouyaux C, et al., 2010, An application of hidden Markov models to the French variant Creutzfeldt-Jakob disease epidemic, Journal of the Royal Statistical Society Series C - Applied Statistics, Vol:59, ISSN:0035-9254, Pages:839-853

Chadeau-Hyam M, Hoggart CJ, O'Reilly PF, et al., 2008, Fregene: Simulation of realistic sequence-level data in populations and ascertained samples, BMC Bioinformatics, Vol:9, ISSN:1471-2105

Hoggart CJ, Chadeau-Hyam M, Clark TG, et al., 2007, Sequence-level population simulations over large genomic regions, Genetics, Vol:177, ISSN:0016-6731, Pages:1725-1731

Chadeau-Hyam M, Alperovitch A, 2005, Risk of variant Creutzfeldt-Jakob disease in France, International Journal of Epidemiology, Vol:34, ISSN:0300-5771, Pages:46-52

Chadeau-Hyam M, Tard A, Bird S, et al., 2003, Estimation of the exposure of the French population to the BSE agent: comparison of the 1980-95 consumption of beef products containing mechanically recovered meat in France and the UK, by birth cohort and gender, Statistical Methods in Medical Research, Vol:12, ISSN:0962-2802, Pages:247-260

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