environMENTAL - Reducing the impact of major environmental challenges on mental health

environMENTAL is a Horizon Europe-funded project aimed at investigating how some of the greatest global environmental challenges, climate change, urbanisation, and regional socioeconomic condition affect brain health during the lifespan, and develop interventions aimed at prevention and early intervention (www.environmental-project.org). Leveraging federated cohort data of over 1 million European citizens and patients enriched with deep phenotyping data form large scale behavioral neuroimaging cohorts, we will identify brain mechanisms related to environmental adversity underlying symptoms of depression, anxiety, stress and substance abuse (Schumann et al. JAMA Psych 2023). In this presentation, I will first describe how environMENTAL builds upon research on quantitative neurobiological phenotypes of psychiatric illness in the IMAGEN (www.imagen-project.org) and other cohorts where we discovered brain mechanisms underlying behavior and psychopathology (e.g. Richiardi et al. Science 2014, Jia et al. Nature HB 2020, Xie et al. Nature Med 2023), established models for prediction (e.eg. Whelan et al. Nature 2014) and stratification (Ing et al. Nature HB 2019, Lett et al. in prep.) of mental illness, and developed novel methods for neuroimaging analyses (Chang et al. Nature Med. in rev, dai et al, in prep.). environMENTAL extends this work by integrating environmental factors, enabling us, for example, to model how complex, real-life exposure to living in the city relates to brain and mental health, and how it is moderated by genetic factors (Xu et al. Nature Med 2023). Going forward, we shall link population and patient data via geo-location to environmental data derived from remote sensing satellite measures (Xu et al. Nature HB 2022), climate models as well as digital health applications, to develop a neurocognitive model of multimodal environmental influences defined by transdiagnostic symptom groups of mental illness, the brain correlates and their underlying molecular mechanisms. Based on the mechanistic knowledge generated, the project will identify compounds targeting causal mechanisms of disease and develop in close collaborations with stakeholders virtual reality interventions that target symptom clusters defined by shared brain mechanisms.

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