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P100 Wellness Study Uses Omics, Clinical Tests to Track Participants, Advance Systems Medicine

NEW YORK (GenomeWeb) – New research supports the notion that intensive, longitudinal studies of individuals can uncover molecular disease markers while providing an avenue for improving individuals' health.

For a nine-month study dubbed the Pioneer 100 Wellness Project, researchers from the Institute for Systems Biology, the wellness-focused company Arivale, and elsewhere prospectively profiled 108 individuals using whole-genome sequencing, proteomics, metabolomics, and 16S ribosomal RNA-based gut microbial community analyses — combined with hundreds of clinical tests — every three months. They also compiled activity tracker measurements for the participants.

The team went on to place these data into networks that integrated the individuals' physiological features, disease status, and more, ultimately coming up with polygenic risk scores for 127 traits or diseases previously assessed through genome-wide association studies to pinpoint potential markers for these conditions. The results appeared online today in Nature Biotechnology.

"Assessing both genetic and environmental determinants of health and their interactions takes us a significant step forward in deciphering the immense complexity of human biology and disease," co-first author Nathan Price, associate director of the ISB and Arivale co-founder, said in a statement.

"Over time," Price added, "this will enable us to identify the earliest transitions from wellness to disease, which is the key to both predictive and preventive care for the individual."

As part of an ongoing effort to advance the so-called systems medicine approach, Price and his colleagues set out to collect comprehensive datasets for each individual over time that "can be used to unravel the complexity of human biology and disease by assessing both genetic and environmental determinants of health and their interactions," according to the authors.

"We have termed this quantitative and transformational approach Scientific Wellness, which enables individuals to improve their health and wellbeing, while generating the data necessary to optimize wellness as well as avoid or slow down the transition into certain disease states," co-corresponding author Leroy Hood, president and co-founder of the ISB and senior vice president and chief scientific officer at Providence St. Joseph Health in Seattle, said in a statement.

The team focused on 108 individuals who were between the ages of 21 and 89 when the study began. Along with clinical and 'omics testing done every three months, the participants received personalized health coaching at baseline and throughout the study, which included recommendations for improving their health.

With each individual's whole-genome sequence, for example, the researchers established polygenic risk scores corresponding to 127 GWAS-assessed traits or conditions. They also got a glimpse at hundreds of blood metabolite or protein levels and gut patterns for microbes from more than 4,600 operational taxonomic units.

The team's subsequent network analyses began piecing together and visualizing the complex ties between different traits, conditions, clinical test measurements, gut microbial patterns, and genetic profiles.

In addition to cholesterol, triglycerides, insulin, and other compounds linked to heart health, such analyses turned up apparent ties between serotonin and blood platelet function, suggested that inflammatory markers declined with enhanced microbial diversity, and provided a look at other potential health or disease markers.

"We hope that analyses of personal, dense, dynamic data clouds for a much larger cohort will enable the identification of network perturbations that result in common diseases, the design of diagnostics to detect early disease transitions, and the development of drugs and other interventions to reverse disease at the earliest stages," the authors concluded. 

The team notified three individuals that they carried pathogenic or likely pathogenic variants in genes flagged for reportable incidental findings by the American College of Medical Genetics and Genomics.