The EXIMIOUS project—Mapping exposure-induced immune effects: connecting the exposome and the immunome. Issue 1 (1st February 2022)

• Record Type: Journal Article
• Authors: Ronsmans, Steven; Hougaard, Karin Sørig; Nawrot, Tim S.; Plusquin, Michelle; Huaux, François; Cruz, María Jesús; Moldovan, Horatiu; Verpaele, Steven; Jayapala, Murali; Tunney, Michael; Humblet-Baron, Stéphanie; Dirven, Hubert; Nygaard, Unni Cecilie; Lindeman, Birgitte; Duale, Nur; Liston, Adrian; Flachs, Esben Meulengracht; Kastaniegaard, Kenneth; Ketzel, Matthias; Goetz, Julia; Vanoirbeek, Jeroen; Ghosh, Manosij; Hoet, Peter H. M.
• Is Part Of: Environmental epidemiology. Volume 6:Issue 1(2022)
• Page Start: e193
• Publication Date: 2022-02-01
• Subjects: External exposome -- Immunome -- Immune-mediated diseases -- Multi-omics; Epidemiology -- Periodicals; Epidemiology -- Environmental aspects -- Periodicals; 614.4
• DOI: 10.1097/EE9.0000000000000193
• Languages: English
• ISSNs: 2474-7882

Abstract

Abstract : Immune-mediated, noncommunicable diseases—such as autoimmune and inflammatory diseases—are chronic disorders, in which the interaction between environmental exposures and the immune system plays an important role. The prevalence and societal costs of these diseases are rising in the European Union. The EXIMIOUS consortium—gathering experts in immunology, toxicology, occupational health, clinical medicine, exposure science, epidemiology, bioinformatics, and sensor development—will study eleven European study populations, covering the entire lifespan, including prenatal life. Innovative ways of characterizing and quantifying the exposome will be combined with high-dimensional immunophenotyping and -profiling platforms to map the immune effects (immunome) induced by the exposome. We will use two main approaches that "meet in the middle"—one starting from the exposome, the other starting from health effects. Novel bioinformatics tools, based on systems immunology and machine learning, will be used to integrate and analyze these large datasets to identify immune fingerprints that reflect a person's lifetime exposome or that are early predictors of disease. This will allow researchers, policymakers, and clinicians to grasp the impact of the exposome on the immune system at the level of individuals and populations.