PROJECT SUMMARY/ABSTRACT The development of clinical cardiovascular disease (CVD) is a process that occurs across the lifespan, beginning early in life and spanning late into life as clinical event rates increase. Much of our understanding of the impact of cardiovascular risk factors comes from studies examining the association between risk factor levels measured at a single point in time, often in middle age, with incident disease over the short- to intermediate-term. However, risk factor levels in young adulthood are significantly associated with the development of CVD later in life and our recent work has demonstrated that not only the levels at specific ages, but also cumulative exposures and long-term trajectories in cardiovascular health are significantly related to the risk for subsequent CVD. Therefore, a life course approach is critical in order to understand how cardiovascular risk factors develop and impact an individual's risk for CVD events later in life. Yet there is no single study that has collected detailed phenotypic data spanning young adulthood through old age on a broadly representative sample of the U.S. population. In response to NOT-HL-19-712: Innovative Data Evaluation and Analysis to Health, we propose to de- velop a statistical framework for combining longitudinal risk factors and clinical outcomes data from multiple cohort studies to create a “synthetic cohort” enabling the study of long-term cardiovascular health starting in early adulthood. The investigative team of this proposal has pooled the data from 20 community-based CVD cohorts through the Lifetime Risk Pooling Project (LRPP), which now has >11 million person-years of follow- up data on repeated measures of CVD risk factors, detailed information about medication use (including blood pressure- and cholesterol-lowering therapy), nearly 100% follow-up for vital status, and detailed CVD event adju- dication. Few cohorts in the LRPP cover the entire adult lifespan; therefore, we propose to view risk factors and outcomes at ages not included in each cohort study as missing data, and to use multiple imputation to fill in these unobserved measurements to facilitate analysis. The overall goal of this project is to identify and measure the characteristics of CVD risk factor trajectories across the adult lifespan that are most amenable to intervention. Measuring these characteristics can help identify critical periods for intervention, more precisely define thresholds for known risk factors, elucidate the role of lifestyle behaviors, explain differences in health among populations, and promote CVD prevention strategies at younger ages. Our specific aims are: 1) Develop and validate a statistical framework for imputing unobserved CVD risk factors and events across the lifespan using data from the LRPP; 2) Inform treatment strategies by identifying clinically relevant features of longitudi- nal risk factor trajectories that are associated with CVD outcomes; 3) Leverage the work...