DESCRIPTION (provided by applicant): This application seeks support to support the infrastructure of the Women's Health Study (WHS) for an additional 5 years, to accrue and validate a substantially increased number of cardiovascular disease (CVD) endpoints. With extensive information already available on randomized treatments, epidemiological risk factors, and genetic and biochemical data, this support will allow the evaluation of clinically important questions related to CVD at a low cost of about $19 per participant per year. The WHS is a randomized trial of low-dose aspirin and vitamin E in the primary prevention of CVD and cancer among 39,876 female health professionals aged 45 years or older. Yearly questionnaires ascertain relevant health outcomes and demographic, lifestyle, and medical risk factor information. Morbidity and mortality follow-up rates are 96% and 100%, respectively. As part of NIH support for the trial, pre-randomization blood samples from 28,345 participants were frozen and stored. With support from nonfederal sources, DMA from all samples has been extracted and is now undergoing extensive genotyping for markers of hemostasis, thrombosis, and inflammation. All plasma samples have been assayed for a full lipid panel, high sensitivity C-reactive protein, and creatinine, and are now undergoing extensive phenotyping for additional inflammatory and hematologic markers. Trial support will end in August 2004, with a mean treatment duration of 10 years and an expected total of 1004 CVD endpoints, 71% of which have bloods. With support to extend endpoint ascertainment for 5 years, an additional 849 CVD events will accrue, with substantial increases in specific CVD events, including myocardial infarction, ischemic stroke, coronary heart disease, congestive heart failure, and venous thromboembolism. The primary aim is to develop improved prediction scores for total and specific CVD outcomes that are based not only on traditional risk factors but also on novel plasma and genetic markers. Secondary aims are to develop similar prediction scores for health conditions that are major CVD risk factors (including type 2 diabetes, hypertension, and metabolic syndrome), and to evaluate genotype-phenotype interactions and interactions between traditional and novel CVD risk factors in the prediction of CVD events.