EarlyCause ("Causative mechanisms & integrative models linking early-life-stress to psycho-cardio-metabolic multi-morbidity ") is a 4-year (2020-2024) Research and Innovation Action funded by the European Union’s Horizon 2020 programme (grant agreement No 848158), under the call H2020-SC1-2019-Two-Stage-RTD.

The project will use big data, animal experiments and artificial intelligence to identify new clinical knowledge, quantitative biomarkers and clinical tools to assess disease and comorbidity induced by early life stress.

Early life stress (ELS) is a widely prevalent phenomenon which affects about 75 % of pregnant women – thus their fetus– and nearly 50% of young children, which long-lasting consequences on human health. Among the adversities and traumas that can cause it are, for instance, job loss, illnesses, death of a relative during pregnancy, physical and sexual abuse, violence or bullying by peers, and parental separation or loss during childhood. It has been suggested that the accumulated effects  of stress hormones during child development can lead to both mental and physical dysregulations, potentially resulting in major diseases later in life.

The EarlyCause project will study the hypothesis that ELS, a well-established risk factor for depressive, cardiovascular and metabolic disorders individually, is a cause of multi-morbidity in these disorders. The project wants to identify the causative mechanisms and molecular pathways that link ELS with these comorbid conditions. In addition, it will quantify the environmental, sex and gender, socioeconomic, lifestyle and behavioural factors to find potential intervention strategies that could reverse causative mechanisms and reduce the effect of ELS in individuals at high risk of developing multi-morbidity. 

To achieve these goals, the multi-disciplinary consortium of EarlyCause will combine 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 machine learning techniques.

https://earlycause.eu/