Karim Lekadir, researcher at the Faculty of Mathematics and Computer Science of the UB, coordinates the EarlyCause project, which the European Commission (2020-2023) funded with six million euros. 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. EarlyCause started on January 1, 2020, and its kick-off meeting was held at the Historical Building of the UB on January 15 and 16.
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.
The members of the consortium will analyse the largest set of European child cohorts, with more than a million cases of longitudinal human data, which include rich information on early life stressors and biological data as well as depressive, cardiovascular and metabolic phenotypes. The generated data, tissue samples, experimental protocols and cell lines as well as best practices will be compiled into a new open-access research platform to support future researchers in the field. Moreover, the project will ensure the research, socioeconomic and clinical impacts are properly quantified and translated to allow a full exploitation of the identified biomarkers and innovative results, in particular regarding the new integrated care pathways considering ELS-induced multi-morbidity in clinical practice.
The EarlyCause project is coordinated by Karim Lekadir director of the Artificial Intelligence in Medicine Lab at the UB, also coordinator of the project euCanSHare H2020, a platform developing a data sharing and analytics platform for customized medicine research in cardiology, and Work Package leader in the LONGITOOLS H2020 project, which was recently launched to study the interactions between the environment, lifestyle and health in determining the risks of chronic cardiovascular and metabolic diseases.
The EarlyCause comprises the following fourteen institutions from eight European countries: University of Barcelona, the European Bioinformatics Institute (United Kingdom), Erasmus University Medical Centre Rotterdam (Netherlands), University of Zurich (Switzerland), King’s College London (United Kingdom), the Spanish National Research Council (CSIC, Spain), Centre Européen de Recherche en Biologie et Médicine (France), University of Oulu (Finland), Istituto di Ricovero e Cura a Carattere Scientifico – Fatebenefratelli, (Italy), University of Bristol (United Kingdom), VU Amsterdam Medical Centre (Netherlands), Empirica GmbH (Germany), Combinostics Oy (Finland) and Pompeu Fabra University (Spain).