Integrative Bioinformatics in Post-GWAS cardiovascular genomics

Abstract

Cardiovascular diseases (CVDs) are the leading cause of death in the world. Genome-wide association (GWAS) studies have identified many genetic loci robustly associated to CVDs. Because most CVD-associated loci are non-coding, one of the main challenges in the post-GWAS era is interpretation of these statistical signals. This thesis presents bioinformatics applications that integrate genome, regulome and transcriptome information to address this challenge. Integrative approaches such as the ones presented in this thesis can help expand our knowledge of the biological mechanisms involved in CVDs, which in turn can be translated into better prevention and treatment.