No abstract

We collected clinical measurements, health surveys and multiomics profiles (genomics, proteomics, autoantibodies, metabolomics and gut microbiome) from 96 individuals over 16 months, along with daily activity and sleep monitoring. Between- and within-individual variability was analysed as the participants underwent data-driven health coaching. Multiomics factor analysis resulted in an unsupervised integrated view of the data, with individual factors explaining distinct aspects of variability in human health and lifestyle, such as obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, hormonal function, exercise and diet. The data revealed both known and new associations between molecular pathways, risk factors, behaviour and lifestyle aspects. Data-driven analysis of multidimensional molecular and digital signatures of participants over time enabled deep understanding of biological variability between people as well as the systemic effects of lifestyle changes. Our study facilitates a detailed evaluation of aspects impacting on health and underlines the importance of personal molecular signatures.