Application of bioinformatics in cardiovascular genomics

Abstract

Genetic research made a remarkable progress in the past 20 years, with the Human Genome Project, which sequenced an entire genome; the HapMap project, that identified common genetic variation in hundreds of genomes from different populations; and the 1000 Genomes project, which identified common and rare variation on thousands of individuals all over the world. Knowledge on cardiovascular disease mechanisms can be significantly improved by understanding how genetic variation influences development and course of disease. The thesis is composed of four articles on meta-analyses for identification of genetic variation in the form of single nucleotide polymorphisms (SNPs) associated with cardiovascular traits, such as blood pressure and lipid levels, with functional experiments on quantitative trait loci and a discussion on the potential druggability of the signals identified. Meta-analyses are a powerful tool to increase statistical power, by aggregating results from different independent studies. Using this approach, we were able to identify 13 variants associated with an increase on blood pressure (systolic, diastolic, pulse or mean arterial pressure), and over 20 variants associated with an increase in lipid levels (LDL, HDL, total cholesterol and triglycerides). The thesis also contains a study on the genetic correlation between vessel obstruction in different vascular beds, which cause myocardial infarction but also ischemic stroke, abdominal aortic aneurysms and peripheral artery disease, and our results show a significant shared genetic etiology among those diseases. Finally, it contains a review article on the big functional datasets recently made available, such as ENCODE, and suggestions on how these data can be best employed to support future genetic research.