Health exists as a spectrum from disease to some outlier physiological optimum. To date most molecular genetic research has focused on disease states and less on extreme health populations. We hypothesize that interrogating outlier elite endurance athletes, with strict physiological eligibility criteria, will inform cardiovascular research through the identification of complementary pathways and therapeutic targets. Eligibility criteria for the ELITE study required a lifetime VO2max, which measures maximal oxygen consumption during peak aerobic exercise, at a threshold estimated to be attainable in less than 1 in 50,000 people (men 80ml/kg/min; women 65ml/kg/min). VO2max is reported to have substantial genetic influence (h2~0.5) and is correlated with endurance sport performance along with work efficiency. Several well documented cases of athletic outliers have been tied to rare genetic variants including the Finnish cross country skier Mäntyranta (EPOR) and Priscilla Lopes-Schliep (LMNA). In the later, the same domain of the LMNA gene is related to rare forms of muscular dystrophy. Additionally, adaptive hypoxia variations have been identified in high altitude populations in Tibet (EPAS1), Andes and Ethiopia. To date we have sequenced 268 ELITE participants using clinically enhanced exomes and run 550 samples on high density multi-ethnic SNP chips. Preliminary analysis has focused on a combination of rare variant curation and common variation association. Rare variation curation included prioritization of LOF variants within candidate genes related to oxygen transport, muscle physiology and metabolism (i.e. PPARA, PPARGC1A, RYR2, ACTN3) and global gene screening using in silico weighted burden testing. Common variant association (the largest GWAS of its kind) has been used to support rare variant findings and identify non-coding and structural variant association signals. We believe that our methodology of combining rare LOF variants with common variation association in a population with extreme endurance physiology will systematically identify pleiotropic genes with both protective and pathogenic features similar to PCSK9.