The EarlyCause Project


It has been shown that ELS can have long-lasting consequences on human health, and impact psychological and physiological processes later in life. Some of the diseases which are most frequently linked with stressful experiences in early life are depression, cardiovascular diseases and metabolic disorders, such as diabetes. Unfortunately, these three diseases are often multi-morbid – that is, they often appear together in the same patient. However, the potential role of ELS in this multi-morbidity is currently unclear.


To better understand the links between ELS and depression, cardiovascular diseases and metabolic disorders, the EarlyCause project aims to find mechanisms that might link these diseases on a molecular/biological level. Therefore, the project studies biological mechanisms, but also considers lifestyle and behavioural factors. Once (potential) causes and protective mechanisms have been identified, so called “intervention strategies” will be studied and proposed  to actively prevent the disease outbreak. Furthermore, strategies to reverse causative mechanisms will be explored in order to reduce the effect of ELS in individuals at high risk of developing such multi-morbidities.


The EarlyCause project will use big data in humans, cellular and animal experiments as well as artificial intelligence to expand the current knowledge base, identify quantitative biomarkers and develop clinical tools to assess disease and comorbidity induced by ELS. This highly multi-disciplinary and experienced consortium combines state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including causal inference methods such as Mendelian randomisation, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods.


WP1 (UB, Katharina Heil)

Coordination, dissemination and communication

WP2 (EMBL, Guy Cochrane)

Centralised data coordination

WP3 (EMC, Charlotte Cecil/Janine Felix)

Association studies and biological markers

WP4 (OULU, Sylvain Sebert)

Causal interference

WP5 (UZH, Isabelle Mansuy)

Animal models

WP6 (KCL, Carmine Pariante & Alessandra Borsini)

Cellular models

WP7 (UB, Karim Lekadir)

Integrated Models and Computational Tools

WP8 (EMP, Rainer Thiel)

Impact Evaluation and Exploitation Planning

WP9 (UB, Karim Lekadir)

Ethics work package

This project is funded by
Grant no. 848158

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