I Am Frontier - A pilot study exploring new avenues for personalized prevention

Due to an increasingly ageing population the prevalence of chronic diseases and multi-morbidity increase. The accompanying shift in disease burden will have important implications for our health system, and requires innovative approaches. New technologies and digital services such as improved molecular profiling, wearables, and artificial intelligence are on the rise. Better '-omics' technologies are developed to acquire the full picture on the individual phenotype. This will have a profound impact on monitoring and managing one's health and offers the potential to set up new approaches in the prevention of disease. Longitudinal phenotyping is essential in exploring and understanding mechanisms of onset of disease, detecting deviations in an early stage, and developing targeted prevention approaches based on better stratification and personalized risk profiling. To start investigating this potential we set up the I AM frontier study, in which we explore the possibility and necessary conditions to 1) collect and analyse comprehensive integrated multi-omics, clinical and wearables data, and 2) develop innovative approaches towards personal health monitoring, early detection of disease and individual risk assessment. Thirty healthy participants are followed up on a monthly basis, to generate different omics data sets including genomics, epigenetics, clinical biomarkers, microbiome, proteomics and metabolomics. Moreover, we collect information on heart rate, sleep patterns, and lifestyle (activity, food intake, stress, ...) via questionnaires and wearables. We are setting up a scalable data infrastructure that allows analyzing large and complex personal datasets with advanced statistical and bio-informatics tools, and combining them with insights from systems biology. In this presentation, we explain the study design and organization of our study. We will present results from the first 9 months of data collection and analysis, focusing on intra- and interindividual differences in clinical variables. We will provide a brief overview of our data integration efforts and future directions, i.e. on evaluation and refinement of population level reference intervals, on molecular or physiological changes that are indicative of onset of disease, and how these can be used in prevention. Finally, we will present some general learnings on participant involvement, and on the ethical and legal challenges encountered.