The ’Obesity Prevention through risk-factor identification, prognostics and early-stage intervention’ project, also known by its acronym EprObes, aims to address the public health concern of obesity and its context through the use Artificial Intelligence (AI). The study is coordinated by Manuel Tena-Sempere, Empar Lurbe and Fernando Fernández-Aranda, all researchers from CIBER-- the Biomedical Research Networking Centre.
The use of AI is one of the most innovative aspects of the project, which incorporates the analysis of data and the use of machine learning algorithms to design decision support tools for doctors and health professionals in the prevention and treatment of overweightness and obesity. During the 5 years of the study scientists from countries like Germany, France, Denmark, Turkey, Poland, Belgium and Estonia will come together to collaborate.
Also participating in the project are leading Spanish institutions, such as the Universitat de València, the Biomedical Research Institute (Incliva), the University of Cordoba (UCO), the Biomedical Research Institute Foundation (Idibell), the Foundation for Biomedical Research of Cordoba (Fibico) and the Spanish Research Council (CSIC), along with 18 international organisations.
AI models, such as artificial neural network or recurrent neural network models, will be used to analyse the time series data of the sample cohorts and make predictions about the risk of developing obesity in determined periods of time. àlex Bravo, a researcher specialised in Machine Learning, stresses that the use of these models, which are based on descriptive data such as age and gender, "will allow for the prediction of obesity trajectories based on the likelihood of individuals being overweight or obese."
According to Manuel Tena-Sempere, coordinator of the project and principal investigator at CIBEROBN and the University of Cordoba, "Despite extensive research efforts, up until now, treatment for the most common forms of obesity have shown limited effectiveness. Therefore, effective prevention strategies, especially in the early stages of life, are essential to avoid the full spectrum of life-long metabolic complications caused by overweightness."
To implement personalised measures against obesity and its comorbidities, the EprObes project aims to identify the risk and protective factors and the underlying mechanisms of excessive weight gain in critical periods of maturation. The research will start at the very first stage of life-pregnancy-in which researchers Carlos Simon and Felipe Vilella from the Universitat de València and Incliva seek to identify epigenetic modifiers that are secreted by the mother and are related to the start of the disease, and from there will move to understanding early childhood development and later puberty and adolescence.
Determining factors of obesityEnvironmental compounds, family conditions, maternal metabolic state, foetal growth and epigenetic factors are some of the determinants of obesity and are all present at early stages of human development. Therefore, as the EprObes coordinator explains, the European projects seeks to contribute to "implementing preventative strategies from the earliest stages of life."
The study is also designed from a comparative gender perspective, which allows for a better understanding of how hormones, metabolism, gender roles, social disparities and other factors may interact and contribute specifically to obesity and its comorbidities in each gender.
The project also incorporates, in a cross-cutting manner, the analysis of psychological and socio-economics factors, most notably mental health and eating disorders as aspects that have an impact on and increase the risk of obesity, a public health problem of increasing incidence in both developed and developing countries.
To better address the multi-faceted nature of obesity causality, especially in the critical period of childhood, the EprObes project is divided into nine interconnected work packages, which include clinical and preclinical studies, mechanistic and molecular analyses and, as aforementioned, the use of bioinformatics tools and AI.
In any case, all data that will be used in the EprObes project will be treated with the highest standards and implementing the applicable regulations at European level and at national level by each participating entity.