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

This is our “proof of concept” study and resulting paper, which is at the very heart of Phenome Health. It outlines our holistic approach to P4 Medicine, or healthcare that is able to predict and prevent disease, and that is individually personalized, allowing for life-long participation in support of your overall wellness.

This paper demonstrates how we are able to consolidate and access your own personal health data, which is constantly changing and evolving over the course of your life, or what we call your personal “healthspan.” It also explains the tools we’ve created to extract actionable insights by considering all your health data as inter-related information that creates a personal context for disease prevention and personal wellness.

Results roundup:

  • Your genes determine your potential: they are not your destiny. For many conditions, a change in behavior can address genetic limitations. 
  • Personalized, comprehensive, and real-time data are empowering. With this knowledge, it is easier and more motivating for one to take responsibility for one’s health—one important factor in controlling healthcare costs.
  • Using standard cutoff values for fasting serum glucose, we identified 43 individuals (∼40%) whose fasting glucose levels were in the prediabetic range at baseline. After only 5–6-months of health coaching, seven of these individuals returned their glucose levels to the healthy range, and the overall trend in glucose levels in the population decreased.
  • The integration of two or more different data types (such as blood proteins, gut microbiome, genetics, and digital data from wearables) was much more informative than any single data type in isolation. For example, we divided the Pioneers into five risk categories according to their genetic propensity for Crohn’s disease. When we integrated the bacterial populations in the gut microbiome we identified two strains of “pathogenic” bacteria that increased as the genetic risk for each group of individuals increased. Thus, we observed an association between the genetics of Crohn’s disease susceptibility and changing microbial populations in the gut microbiome. It is not yet clear what the causal association might be or whether there may be a strong actionable possibility here—but this establishes a testable hypothesis for treatment that would have gone unnoticed with a single data type.
  • Individual genetic risk for disease can inform longitudinal measures for tracking disease manifestation. For example, a known genetic variant (C282Y) causes hemochromatosis, and a subset of individuals carrying this variant can experience high iron and ferritin levels in the blood. High blood iron levels can attack the skin, joints, pancreas, liver, and/or the heart—potentially leading to arthritis, diabetes, liver cirrhosis/cancer, and/or cardiac decompensation in various combinations. Since this disease often presents with these cardiac complications, individuals may be already chronically ill with potentially undetected diabetes or liver disease. The treatment is simple: send the individuals with the C282Y mutations to their physician to perform the necessary tests for a clinical diagnosis; if positive, the individual can have regular blood draws until normal iron levels are reached. We identified the two individuals with homozygous C282Y genotypes before any serious tissue damage had been done, providing an early diagnosis and allowing them to avoid the economic and physical tolls associated with chronic disease that would have been missed without the genetic analysis.

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https://doi.org/10.1038/nbt.3870

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