A wellness study of 108 individuals using personal, dense, dynamic data clouds

This is the first publication from the Lee Hood/Arivale P4 medicine intiative; a pilot/POC study based on 108 individuals (the Pioneer 100 Wellness Project). Samples were collected every 3 months over a 9 month period and “personal dense dynamic data clouds” were created for each individual. Data was collected from multiple sources, such as whole genome sequencing, a range of >200 clinical tests, measurement of >600 metabolites and extensive gut microbiome charachterization. Proteomics was also a key part of these data clouds, with 262 different proteins measured (>60% of those using Olink CVD I and Inf). Activity and lifestyle parameters were also monitored, and a behavioural coach was provided for each participant. Changes in data over time (including those in response to behaviourial changes after coaching) were assessed, as well as correlations between different multi-omics parameters. This was analyzed in an “unsupervised” manner to reveal ~70 densely interconnected “communities” of correlating parameters. These often turned out represent physiologically related analytes, such as for cardiometabolic health. Several specific observations were highlighted, including levels of gamma-glutamyltyrosine being densely connected with a range of clinical analytes for cardiometabolic disease, and the genetic risk of inflammatory bowel disease being negatively correlated with plasma cystine. Overall though, this is presented as a proof of concept rather than to establish specific associations, and as the pilot for a much larger project to assess 100 000 subjects.