Discordance analysis

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Discordance of LDL-C with ApoB and the presence of coronary artery disease


Background

LDL cholesterol (LDL-C) levels have long been the main target for lipid-lowering therapies to reduce the cardiovascular disease (CVD) burden. However, many individuals experience progression of atherosclerosis and/or cardiovascular events despite having optimal LDL-C concentrations. In this regard, it has been recently published that future CVD events are better reflected with alternative measures of circulating atherogenic particles such as apolipoprotein B (ApoB) levels. At the same time, the superiority of ApoB for the assessment of CVD has been shown to be more evident when LDL-C and ApoB measures are discordant.


Aim

In this project, we will investigate if discordance analysis in CoLaus can identify those patients at higher cardiovascular risk despite showing normal LDL-C levels.


Materials and Methods

We will perform discordance analysis of LDL-C with ApoB levels and the presence of coronary artery disease (CAD). Briefly, data on ApoB and calculated LDL-C levels, as well as the presence of CAD, are available at baseline in the CoLaus (Cohorte Lausannoise) study, a monocentric, longitudinal and population-based study to investigate the epidemiology and genetic determinants of cardiovascular diseases and risk factors. CoLaus includes 6,188 people, aged 35-75 and residing in the city of Lausanne (Switzerland). The baseline examination was conducted from 2003 to 2006.


Mathematical Tools

Students will use R to perform discordance and standard statistical analyses, such as regression analysis, to investigate the association between cardiovascular risk factors and the presence of CAD. Various visual data representation techniques like discordance plots 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 burden of residual cardiovascular risk and the consequent quest for novel and better markers of CVD.


Supervisor

Roger Mallol Parera.