PROJECT SUMMARY One in three liver transplant recipients will experience a cardiovascular event within one year of transplant due to the effects of immunosuppression and a high prevalence of potentially modifiable cardiovascular risk factors, such as high blood pressure. However, early or intensive blood pressure-lowering may potentially cause harm in liver transplant recipients by reducing liver graft and renal function. Indeed, for liver transplant recipients, the clinical outcomes associated with blood pressure-lowering, treatment timing and treatment strategies are unknown. For this application, we assembled a team of experts in liver transplantation, cardiovascular epidemiology, hypertension, and biostatistics, in order to determine patterns of blood pressure in liver transplant recipients in the United States; quantify associations between blood pressure levels and optimal clinical outcomes in liver transplant recipients; and identify treatment strategies of liver transplant-associated hypertension that lower blood pressure and minimize cardiovascular events, using innovative statistical techniques. To achieve these goals, we will measure blood pressure using both in-office and out-of-office (7- day home blood pressure monitoring and 24-hour ambulatory blood pressure monitoring) approaches in a prospective, observational, cohort study of 1,268 adult liver transplant recipients, recruited from five tertiary care transplant networks (Northwestern University, University of California San Francisco, Baylor Transplant Institute, Columbia University, University of Pennsylvania) over five years. These data will be used to assess associations between the main exposure of blood pressure and the main outcome of incident cardiovascular events in liver transplant recipients. Secondary outcomes will include changes in markers of liver graft or renal function and mortality in this population. We will then merge the cohort data with the rich data contained within the electronic health record at each participating site including information on blood pressure-lowering medication prescribing patterns and comorbidity data. We will apply novel statistical techniques, including Q- learning to estimate dynamic treatment regimes in liver transplant recipients, to the merged data set to assess treatment strategies of liver transplant-associated hypertension that are differentially associated with (a) lower blood pressure and (b) lower cardiovascular events in liver transplant recipients. These data will fill a critical gap in our knowledge by precisely quantifying the associations between blood pressure levels and cardiovascular events among liver transplant recipients. We will also identify treatment strategies that are most likely to effectively reduce blood pressure as a key modifiable risk factor for cardiovascular events in liver transplant recipients. These data are essential as the ground work for future blood pressure intervention trials in liver transplan...