environMENTAL

Reducing the impact of major environmental challenges on mental health

environMENTAL is an EU-funded project, studying the impact of climate, pollution, urbanicity, regional socioeconomic conditions, as well as the Covid19 pandemic on brain health, and characterize its underlying biological mechanisms. We will analyse data from more than one million European citizens and patients to uncover brain mechanisms linked to environmental adversity and leading to
symptoms of depression, anxiety, stress and substance abuse.

News

Events

3rd General Assembly meeting in Neuhardenberg

3rd General Assembly meeting in Neuhardenberg

This week we wrapped up our 2.5-days General Assembly meeting filled with partner updates & in-depth discussions on key sub-projects, including computer brain & mental health, -omics, and geodata analysis.Excited for the progress ahead! Thanks to everyone for...

read more

Participate in the project

Digital prevention and early intervention are important targets in non-pharmacological treatment. environMENTAL will pursue two parallel approaches, developing a mental health app and virtual reality interventions to reduce the impact of significant environmental challenges on human well-being.

StreetMind
Environment and the brain

StreetMind

Contribute to a better understanding of how the environment influences mental health

Consensus Conference

Your opportunity to shape the course of research

Seminars

The environMENTAL seminar series was established to inform our stakeholders about the environMENTAL project targets and to create a platform of active discussion and knowledge exchange.  

Challenges and opportunities for drug discovery in mental disorders

There is an undisputed need for better therapies addressing mental illnesses. However, despite major advances in the understanding of the molecular basis of disorders such as depression, anxiety schizo­phrenia and autism in the past decades, efforts to discover and develop new drugs for neuropsychiatric disorders have remained relatively unsuccessful. The disappointments can be traced to failures in the target identification and target validation effort, as reflected by the poor ability of current cellular and animal models to predict efficacy and side-effects. Here will I discuss how patient-based disease mod­elling can be implemented in the early drug discovery process as a crucial component in addressing current problems.

Implementation of a patient-derived disease model of Phelan McDermid Syndrome for the identification of SHANK3-specific chemical modifiers

Autism Spectrum Disorders (ASD) are a heterogeneous group of neurodevelopmental disorders which complicates the identification of an effective therapeutic solution. More than 75 % of people suffering from Phelan McDermid Syndrome (PMS) exhibits ASD symptoms. This rare disease is due to a dele­tion/alteration in chromosome chromosome 22 (22q13) leading to a haploinsufficiency of SHANK3 expression. SHANK3 encodes a scaffolding protein in the postsynaptic density of excitatory synapses. A reduced expression of SHANK3 leads to an alteration in neuron morphology and synapse connectivity via unknown mechanism.
After the identification of a developmental hyperdifferentiation phenotype in patient-derived iPS cells during the first 6-14 days of differentiation into glutamatergic neurons, a fully automated process was developed allowing us to perform a >7000 molecules screening to reverse hyperdifferentiation. Valida­tion of identified hit compounds was performed in a synaptic imaging assay after 28 days of differentia­tion. In summary, we performed phenotypic screening using specific pathological hallmarks of a neuro­developmental disease in patient-derived of cells.

EBRAINS user engagement

Our twin goals:

  • the scientific work of the Human Brain Project(HBP)
  • the ongoing development of the state-of-the art Research Infrastructure for brain studie: France Nivelle, Chief Communications and Content Officer, EBRAINS

environMENTAL Methodological approaches for MRI data integration biomarker discovery and validation within the environmental project

In this talk, I will give an overview of the analytical strategy we will employ for biomarker discovery in the environMENTAL project. To find generalisable biomarkers to predict and stratify mental disorders, we will need to solve many methodological challenges including how to meaningfully aligning data from heterogeneous cohorts spanning the whole lifespan, fusing data from modalities with very different characteristics, accounting for complex patterns of missing data and extracting generalisable and interpretable low dimensional representations from complex datasets.
Moreover, many of these analyses need to be performed in a decentralised and distributed manner. I will give an overview of some of the analytical techniques that we will employ to solve these challenges, including federated machine learning techniques, normative modelling, deep learning, transfer learning and classical penalised multivariate regression techniques. I will illustrate by discussing in detail how such techniques can be applied to neuroimaging data but it should be remembered that they are all more widely applicable.

environMENTAL Making the MOSTest of genetics multivariate approaches to variant discovery and disorder prediction

Brain and behavioural measures related to mental illness have complex genetic architectures, involving many common polymorphisms with small individual effects, challenging psychiatric genetic research. Given the distributed nature of genetic signal across brain regions, and high levels of pleiotropy across mental disorders, joint analysis of sets of neuroimaging or mental health measures in a multivariate statistical framework provides a way to substantially enhance discovery of genetic markers with cur­rent sample sizes.
In this presentation, I will introduce the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable permutation-based inference. I will provide an overview of findings from a series of studies applying MOSTest to data from tens of thousands of individuals from large population cohorts, enabling the discovery of thousands of genetic markers associated with a range of traits. I will further illustrate how the enhanced statistical power achieved through joint analysis of brain and behavioural measures can be leveraged to improve genetics-based prediction of mental disorders in clinical cohorts. As such, these multivariate approaches can signifi­cantly contribute to achieving the goals of environMENTAL.

The environMENTAL Team

an interdisciplinary team of excellence

Driving a highly innovative and interdisciplinary approach, the project teams the ideas and expertise of neuroscientists, psychiatrists, geo-scientists, climatologists, psychologists, epidemiologists, anthropologists, computer scientists, experts in digital interventions as well as non-academic stakeholders such as patient associations.
The consortium will be supported by a Stakeholder Board, which will advise on ethical and societal questions to ensure a responsible research and innovation programme.

The environMENTAL Team

environMENTAL latest news

Newsletter

About environMENTAL

Find out the latest news about environMENTAL and register for our quarterly newsletter!

Career

About environMENTAL

Find out about all open positions in the environMENTAL project and join an innovative team of excellence!

News

First amendment accepted by the EU! The environMENTAL consortium welcomes new partners!

The University of Nottingham (UoN), concentris, NAKO e.V. and Norwegian Institute of Public Health (NIPH) will support the environMENTAL consortium with achieving their goals.Prof. Bernd Stahl and Dr. George Ogoh moved from De Montfort University (DMU) to The...
Visualisation of a data life cycle. Seven small circles arranged overlapping in a large circle and representing the following parts of a data life cycle: plan, collect, process, analyse, preserve, share and reuse. Written in the centre is "data life cycle", surrounded by three arrows that form a circle and indicate the reading direction in a clockwise direction.

WP12: we are FAIR!

The Berlin Institute of Health (BIH) Digital Health Center leads work package (WP) 12 and is responsible for implementing FAIR principles1 to ensure the integrity of the data life cycle. The team lead by Dr. Sven Twardziok supports collection, processing, analysis,...

Poster Awards at environMENTAL General Assembly Meeting

Congratulations to Emin Serin, Paul Renner and Antoine Bernas for winning the Poster Awards at this year’s environMENTAL General Assembly Meeting! Emin’s poster presents a novel neural network architecture that can generate synthetic task-based fMRI images. It enables...

3rd General Assembly meeting in Neuhardenberg

This week we wrapped up our 2.5-days General Assembly meeting filled with partner updates & in-depth discussions on key sub-projects, including computer brain & mental health, -omics, and geodata analysis.Excited for the progress ahead! Thanks to everyone for...

WP10: SAVE THE DATE for the first Summit of Artificial Intelligence in Mental Health!

We are excited to announce that environMENTAL will be hosting the first Summit of Artificial Intelligence in Mental Health. This event, organized by the environMENTAL consortium in collaboration with the Shanghai Brain Health Initiative, the German Centre for Mental...
Reports

Watch the environMENTAL Consensus Conference Video Now!

We are thrilled to announce the release of the highly anticipated video from the environMENTAL Consensus Conference! This thrilling event brought together a diverse panel of experts to discuss pressing issues related to mental health, environmental factors, and...

WP5: Milestone reached in the collaborative characterization of omics data

We are thrilled to share a significant update for our work package (WP5), which is dedicated to omics characterization in deeply phenotyped longitudinal cohorts. Our teams led by Prof. Sylvane Desrivieres at King’s College London (KCL), and Prof. Markus Nöthen at the...

WP4: Global collaboration: environMENTAL x Yale’s ABCD Study and EC IMAGEN

Understanding the interplay between our environment, the brain, and human behaviors is challenging. Antoine Bernas and the team at Donders Institute for Brain, Cognition, and Behaviour are developing fresh perspectives into the brain-behavior relationship in...

WP2: 1st environMENTAL x iMap Workshop

🌍 Exciting news from the world of environmental research! 🌿 The partnership between environMENTAL and the Chinese "iMapWorld" team has just kicked off after a successful workshop. Led by Prof. Peng Gong and Prof. Gunter Schumann, we'll uncover how surroundings affect...
StreetMind

WP3: Become Part of our Community and become a Citizen Scientist with Streetmind

In the Sailing City Kiel, work package 3 is looking forward to 2024 and the growing community on our citizen-science platform StreetMind (https://www.streetmind.eu/). Become a citizen scientist! Download the app (android or apple), register and start exploring Your...