Circulating microRNAs as predictive biomarkers of myocardial infarction – the HUNT study
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Coronary heart disease (CHD) is the most common single cause of death, and in Norway the number of people at risk is increasing. Several cardiovascular disease (CVD) risk prediction models have been developed to identify the individuals at risk so that they could be targeted for preventive measures, but the models only explain a modest proportion of the incidence. The aim of this study was to test the clinical relevance of circulating microRNAs (miRs) as risk markers, by determining if they could add value on top of traditional risk factors in algorithms for calculating CVD risk, more specifically the Framingham Risk Score (FRS) for hard CHD. This was a case-control study with 10-year observation period, and the primary endpoints were fatal and non-fatal myocardial infarction (MI). Eleven miRs were quantified by real-time polymerase chain reaction in serum from 198 participants at baseline. Of these participants, 98 experienced either a fatal (n=37) or a non-fatal MI (n=61) during the followup, whereas the controls (n=100) remained healthy. Nine of eleven miRs were differently expressed in cases and controls (p<0.05). By best subset regression we identified the miRs that together with the FRS for hard CHD best predicted future MI. For women, the model included let-7g-5p, miR-21-5p and miR-26a-5p, and for men, the model included miR-26a- 5p, miR-144-3p and miR-424-5p. Addition of these miRs to the FRS for hard CHD increased the area under the curve (AUC) from 0.65 to 0.76 (Δ0.11) in women, and from 0.67 to 0.80 (Δ0.13) in men. Our study supports previous studies indicating that circulating levels of miRs can add value on top of traditional risk markers in predicting future MI in healthy individuals. However, the discrepancies revealed in this study demonstrate that these small molecules are not yet ready for the clinical practice.