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Human Performance

A core research theme in Ashley Lab is the study of clinical, molecular and genomic aspects of physical activity and fitness. One hallmark project involves studying the genomics of the fittest humans on the planet -- The ELITE Study (Exercise at the Limit - Inherited Traits of Endurance). Eligibility is limited to lifetime VO2max thresholds only attainable by less than 1 in 50,000 people (females:63, males:75 ml/kg/min). The overarching hypothesis is that by studying the extreme of human performance, one can uncover mechanisms and therapeutic targets for the treatment of cardiovascular, pulmonary, neuromuscular and metabolic disease. These candidate variations with large effect are assumed to be very rare. As the study matures we are broadening our inclusion to better capture ethnic diversity and local adaptations such as to high altitude. Moreover, we are increasing the number of traits to better capture alternative subsets of extreme athletic physiology. Please take a look at elite.stanford.edu if you are interested in participating.  

We are also working with large population cohorts such as the UK Biobank, the Million Veterans Program, and Cooper Institute that measure fitness, physical activity, genetics, and health outcomes. Our own ResearchKit app MyHeart Counts has collected activity signatures on over 50,000 subjects and fitness estimates based on 6 minute walk test in over 5,000. Through integration with 23andMe we are better able to translate some of these genetic insights into clinical care and population health.

Our group also acts as the Bioinformatics Core for the Molecular Transducers of Physical Activity (MoTrPAC) Project - a $170M, NIH-funded consortium aimed at building the molecular map of physical activity. The consortium includes six clinical sites, three preclinical animal sites, seven chemical analysis sites (for multiomics), a three site coordinating center, and a single Bioinformatics core. As the Bioinformatics core, we coordinate the integration, dissemination, and analysis of high dimensional physiological, mobile health, and molecular phenotyping data.
 
Photos taken by: Nils Ericson