The sequencing of the human genome promised to revolutionize diagnosis and treatment of disease. This revolution had as its ultimate goal personalized and predictive medicine, in which treatment is tailored to each individual patient as informed by his or her own unique genome sequence. More recently the precision and cost-effectiveness of additional ‘omic technologies, such as metabolomics and proteomics, have increased dramatically, and their potential to personalized medicine has become readily apparent. By integrating these various data using computational frameworks, systems biology and systems medicine allow for the widespread adoption of the personalized medicine framework.
In 2014, the Price Lab along with the Institute for Systems Biology initiated the 100K Wellness Project, a study to monitor the health and wellness of 100,000 individuals over time. Upon enrollment, each individual’s whole genome is sequenced, while throughout the course of the study their metabolome, proteome, and microbiome are analyzed quantitatively. The end result is an unprecedented wealth of systems medicine information, in which individual is represented by millions of linked data points.
Multivariate analysis and predictive modeling of these data reveals molecular signatures associated with shifts in individuals’ wellness state, providing a deeper understanding of the molecular drivers of health and disease. Furthermore, integrating genome-scale models using systems approaches goes a step further, potentially elucidating causal mechanisms. Finally, actionable lifestyle intervention provides the first large scale validation of the personalized medicine paradigm.