Despite advances in diagnostic and therapeutic paradigms, cardiovascular disease (CVD) remains a primary cause of death across the world. Traditional risk factors for CVD are primarily metabolic in origin, including obesity, sedentary lifestyle and insulin resistance. Cardiometabolic diseases are associated with inflammation and chronic exercise training has been shown to decrease inflammation. Clonal hematopoiesis of indeterminate potential (CHIP) is the age- related expansion of somatic clones in hematopoietic stem cells secondary to mutations associated with the development of hematologic malignancy and represents a state of heightened inflammation. CHIP is associated with coronary artery disease (CAD) and incident cardiovascular outcomes, however the relationship between CHIP and CRF has not been evaluated. We have identified metabolic biomarkers that are associated with CRF and incident cardiovascular events; as well as CHIP, suggesting a potential link between CHIP-induced inflammation and impaired metabolic function leading to CVD. It is unknown whether CHIP is associated with worse baseline CRF and whether it may predict response to chronic exercise training, providing an opportunity to improve personalized care for CVD prevention. The overall objectives of this application is to determine the role of CHIP, an emerging inflammatory aging biomarker, in CRF and cardiometabolic responses to chronic exercise interventions and identify metabolic dysregulation underlying this relationship. Our specific aims are (1) Determine if CHIP is associated with worse baseline CRF and predicts heterogeneity in response to chronic exercise training in patients with cardiometabolic disease and (2) Evaluate potential metabolic mechanisms underlying CHIP, CRF and response to chronic exercise training. To achieve these aims we will leverage two randomized clinical trials of patients with metabolic syndrome and perform targeted sequencing of CHIP driver genes. For Aim 1, we will test associations of CHIP with baseline peak oxygen uptake (pVO2) and change in pVO2. For Aim 2, we will use inflammatory marker, plasma and skeletal muscle metabolite data to determine whether metabolic dysregulation mediates the relationship between CHIP and CRF. The research proposed here will allow me to build on the following skills: 1) analysis of somatic genetic variant; 2) computational and statistical skills in multi-omic datasets; and 3) metabolomic analyses including systems biology approaches to analyses. The data gathered during this award period coupled with ongoing mentorship and a multi-disciplinary research environment will prepare me to fulfill my long-term goal of becoming an independent physician-scientist.