Project Summary Cardiovascular diseases are one of the leading causes of death in the United States. Large genome-wide association studies have been able to detect links between cardiovascular phenotypes and a number of regions in the genome. However, given the sample sizes available in the majority of studies and the effect sizes on these phenotypes, the associations are limited to common variants (minor allele frequency >1%). Furthermore, these studies can only implicate regions of the genome without identifying what the causal variants may be. I propose to develop a pipeline to better understand the contribution of rare variants to cardiovascular disease architectures. First, I will use a much larger dataset than previously available to determine associations between rare variants and cardiovascular traits. I will then filter this list using additional information about linkage disequilibrium and variant impact to create a short-list of putatively causal, high- impact, rare coding variants. Second, using the same large dataset, I will create collapsed by gene genotypes of whether individuals carry ultrarare coding and loss-of-function variants. This will allow me to detect associations between phenotypes and genes that were not detected through traditional association tests by examining the contribution of ultrarare variants. Finally, I will investigate the relationship between variants that modify gene expression and the effects of rare coding variants. In the case where individuals carry one copy of a rare loss-of-function mutation, an increased amount of wildtype protein produced from their other haplotype might be able to mitigate their expected phenotype. By examining, whether this appears to be the case, I will better be able to predict the variable penetrance of rare coding variants that contribute to some cardiovascular traits. Characterizing the role of rare coding variants in cardiovascular diseases will enhance our understanding of the genetic architecture of these traits and the genes and pathways involved.