DPSPDNT - Relatórios científicos e técnicos
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- System biology approach for Cardiovascular MedicinePublication . Costa, Cibelle Neiva Cavalcanti Mariano da; Bourbon, Mafalda; Antunes, MaríliaCardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. The common forms of CVD have a complex aetiology in which interactions between multiple genetic and environmental factors play an important role. Of many independent cardiovascular risk factors that have been identified, namely, dyslipidaemia, arterial hypertension, diabetes, sedentarism, overweight/obesity, inadequate diet and smoking, all have a common link: all could be modifiable. In contrast, genetic risk factors are considered non-modifiable, but the associated risk can be prevented if early identified, making genetic studies a priority in cardiovascular genetics research. This research project proposes the study of interactions between biological, including genetics, and environmental factors that give rise to the cardiovascular risk profile as well as to characterise the genetic cardiovascular risk profile of the Portuguese population. It is also proposed to study the differential expression pattern between a control and disease (premature myocardial infarction) population in order to identify novel biomarkers for the early identification of at risk subjects. Overall 1700 individuals (men and women aged between 18 and 79), from e_COR project, involving Lisboa, Porto, Centro, Algarve and Alentejo regions will be included. Lipid profile will be analysed and percentiles defined and adjusted according to the lipid-lowering drugs. The different genes expression patterns will be analysed by RNA-Seq in 50 patients with premature myocardial infarction (pMI) and in 50 controls, without cardiovascular risk factors or CHD, from e_COR study. A combination of genomics and transcriptomics approaches will be performed to establish genotype/phenotype co-relation between known genetic markers and CVD disorders, as well as to investigate novel potential biomarkers. Statistical analysis will be performed with SPSS and R. The integration analysis of the effects of non-genetic risk factors and epigenetic variation, with knowledge of DNA sequence determinants and with the enormous quantities of information produced by the high-throughput technologies used to sequence the human genome, has the potential to improve the understanding of the aetiology, prediction and stratification of CVD, by connecting biological information in disease-specific network. This project will contribute for a better knowledge of the interactions between biological and/or environmental factors that give rise to cardiovascular risk, as well as determining the cardiovascular risk profile of the Portuguese population. With all the data collected it will also be possible to establish reference values for biomarkers of lipid metabolism. The results should have a high impact on the definition of criteria for identifying individuals at high risk for developing CVD.