Human metabolic correlates of cardiovascular risk factors
Contents
Background
Systems biology refers to the measurement of as many entities as possible at any level of biological organization to understand the complete network of changes within an organism. In this regard, metabolomics is the application of tools from analytical chemistry to profile the maximum number of metabolites found within an organism, tissue, cell, or biofluid as is feasible. Metabolites are small molecules that are chemically transformed during metabolism and, as such, they provide a functional readout of cellular state. Indeed, metabolites serve as direct signatures of biochemical activity and are therefore easier to correlate with phenotypes. In this context, metabolomics has become a powerful approach that has been widely adopted for clinical diagnostics. Additionally, the high-throughput nature of metabolomics makes it ideal to perform biomarker screens for diseases.
Aim
In this project, we will explore the role of metabolomics in the search for novel biomarkers for cardiovascular disease.
Materials and Methods
We will make use of existing metabolomics and phenotype data from the "CoLaus" study, a longitudinal and population-based study to investigate the epidemiology and genetic determinants of cardiovascular diseases and risk factors. Because metabolomics data is only available at baseline, we will study the relationships between metabolome features and cardiovascular risk factors (e.g. waist circumference, systolic blood pressure, glucose, HDL-C, and triglycerides) at baseline. We will then investigate the relationship between the baseline concentrations of metabolome features and longitudinal changes in the levels of cardiovascular risk factors during the follow-up (using linear regression analysis), as well as the incidence of cardiovascular disease at 5 year follow-up (using logistic regression analysis).
Mathematical Tools
Students will use MATLAB to perform standard statistical analyses, such as regression analysis, to investigate the association between metabolomics data and cardiovascular risk factors and the presence of CVD. Various visual data representation techniques will also be studied. Results will be contrasted with existing literature.
Biological or Medical aspects
This project will allow students to get familiar with the promising field of metabolomics and its use as a tool for biomarker discovery.
