Patient genetic data can be used to predict disease risk and medication selection. However, our understanding of how a given DNA variant will impact a person is extremely limited. As a result, the accuracy of genetic predictions for many complex diseases is poor. This research proposal seeks to increase the accuracy of genetic predictions using new datasets that describe how DNA variants result in changes to a person's cells. The first aim will focus on cardiovascular disease. The second aim will focus on autoimmune conditions. The final aim will attempt to improve genetic predictions of side effects for a commonly prescribed autoimmune medication. The project will span approximately 18 months. If this study is successful, the accuracy of genetic predictions will be increased. This increased predictive ability can be used for early preventative efforts and to inform medication selection for patients in the future.