Sammendrag
Cardiovascular disease (CVD) is a major health burden and the leading cause of death worldwide, and myocardial infarction (MI) accounts for most CVD-related deaths. Risk prediction models are important tools in the primary prevention of MI. Current models are based on traditional CVD risk factors and intend to predict the individual’s 10-year risk of MI. However, it fails to detect all incidences, as many who experience MI had no previously recognized symptoms or CVD risk factors. It is therefore of clinical interest to identify new risk markers that can improve the accuracy of today’s risk prediction models.
Lipid accumulation play an important role in the development of coronary artery disease (CAD), and high lipid content within the coronary plaques increases the risk of MI. A non-invasive circulating biomarker in the blood that reflect lipid content in coronary plaques may add valuable and easily
assessable information about the risk of future MI. microRNA (miRs) and lipoprotein subfractions are involved in many pathological processes related to CAD, and we therefore aimed to explore their potential as biomarkers and risk predictors of lipid content in coronary plaques and future MI. In the CENIT study, we investigated the association between lipid content in coronary plaques,assessed with advanced intracoronary imaging, and serum lipoprotein subfractions (Paper I) and plasma miRs (Paper II) in stable CAD patients. In Paper I, we found lipoprotein(a) and free cholesterol
in the smallest HDL particles (HDL-4) to be most strongly associated with lipid content, but the evidence for an association was reduced after inclusion of traditional CVD risk factors. Their potential as risk predictors of lipid content still exceeded that of traditional lipid easurements. In Paper II, we found miR-133b to be associated with risk of lipid-rich coronary plaques, and this association was not
attenuated by the inclusion of CVD risk factors.
In Paper III, we investigated the association between the risk of a future coronary event (percutaneous coronary intervention and/or MI) and serum miRs and lipoprotein subfractions in participants from the Trøndelag Health Study. The participants were apparently healthy and had a predicted low 10-year risk of MI, calculated by the Norwegian risk prediction model NORRISK 2, at time of inclusion and blood sampling. We found that miR-424-5p and triglycerides within the medium sized LDL particles (LDL-4) were most strongly associated with a future coronary event. We further assessed the predictive performance of different sets of potential predictors, including the CVD risk factors that are used in the calculation of NORRISK 2. We found that the set of variables that best predicted a future coronary event included miR-424-5p, triglycerides within LDL-4, and Apo-A2
in HDL-4. We also demonstrated differences in the risk profile between men and women.
Taken together, our findings support the assumption that circulating biomarkers may add to traditional risk factors in the evaluation of MI risk. Although our studies show moderate evidence, our findings provide valuable insights for future efforts toward more precise risk prediction. Larger studies
should be performed to evaluate and assess the clinical relevance of our findings.
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