Improving risk prediction of myocardial infarction by including new types of circulating biomarkers

Improving risk prediction of myocardial infarction by including new types of circulating biomarkersmicroRNAs (miRs) have emerged as promising new risk markers of cardiovascular disease (CVD). As miR-analyses are expensive, we want to establish a cost-efficient method for quantification of miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of miRs can improve CVD risk prediction.CVD is the leading cause of death globally, and the number of individuals at risk is expected to increase in the years to come. Hence, it will be increasingly important for the healthcare system to identify individuals at high risk for CVD, to initiate cost-efficient prevention strategies as lifestyle interventions and pharmacotherapy to decrease the number of events and hospitalization. In the clinical setting, risk prediction models are available for determining the 10-year risk of CVD. However, the currently available risk prediction models only explain a modest proportion of the incidence, and currently fail to discover 15-20 % of the individuals at risk for CVD. Thus, there is a clinical need for new risk markers that could complement the assessment of traditional risk factors, to identify the individuals at risk with greater precision than today. During the last years, microRNAs (miRs) have emerged as promising new risk markers of CVD. We have, as one of few research groups around the world, explored their potential to improve risk prediction models for myocardial infarction (MI), and have reported very promising results. As miR-analyses are expensive, we want to establish a more cost-efficient method for quantification of circulating miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of candidate miRs can improve the precision of the NORRISK2 score to predict 10-year risk of MI. Aim1. Establish new cost-efficient, ultra-sensitive methodology for quantification of circulating microRNAs at St.Olavs University Hospital. Status (February 2022): We have tested droplet digital PCR for analysis of microRNAs in blood. The method shows promising technical results for most of the microRNAs tested. However, the currently available droplet generator limits the possibilities of high-throughput analyses. We are therefore currently testing next-generation sequencing. As microRNA sequencing is expensive, we have approached several laboratories for quotes. Due to the more expensive analyses we would like to perform at least one pilot study in a limited number of participants before using precious blood samples from HUNT. As for now, we are applying RT-PCR analyses for the microRNA studies, but closely monitor the technical development. Aim 2. Determine whether adding information on microRNA-levels can improve the precision of the NORRISK2 score to predict myocardial infarction Status (February 2022): We have published two new papers on microRNAs and CVD, and is currently working on a new paper testing the potential for microRNAs to improve risk prediction for myocardial infarction in a cohort of 300 participant from HUNT. The results are promising, and we are hoping to present results at two international conferences during 2022.

Improving risk prediction of myocardial infarction by including new types of circulating biomarkersmicroRNAs (miRs) have emerged as promising new risk markers of cardiovascular disease (CVD). As miR-analyses are expensive, we want to establish a cost-efficient method for quantification of miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of miRs can improve CVD risk prediction.CVD is the leading cause of death globally, and the number of individuals at risk is expected to increase in the years to come. Hence, it will be increasingly important for the healthcare system to identify individuals at high risk for CVD, to initiate cost-efficient prevention strategies as lifestyle interventions and pharmacotherapy to decrease the number of events and hospitalization. In the clinical setting, risk prediction models are available for determining the 10-year risk of CVD. However, the currently available risk prediction models only explain a modest proportion of the incidence, and currently fail to discover 15-20 % of the individuals at risk for CVD. Thus, there is a clinical need for new risk markers that could complement the assessment of traditional risk factors, to identify the individuals at risk with greater precision than today. During the last years, microRNAs (miRs) have emerged as promising new risk markers of CVD. We have, as one of few research groups around the world, explored their potential to improve risk prediction models for myocardial infarction (MI), and have reported very promising results. As miR-analyses are expensive, we want to establish a more cost-efficient method for quantification of circulating miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of candidate miRs can improve the precision of the NORRISK2 score to predict 10-year risk of MI. Aim1. Establish new cost-efficient, ultra-sensitive methodology for quantification of circulating microRNAs at St.Olavs University Hospital. Status (February 2021): We have tested droplet digital PCR for analysis of microRNAs in blood. The method shows promising technical results for most of the microRNAs tested. However, the currently availible droplet generator limits the possibilities of high-throuhput analyses. We are therefore currently testing next-generation sequencing. We still believe that ddPCR will be the optimal choise for clinical utilisation applying ddPCR equipment better suited for high-throughput analysis. Aim 2. Determine whether adding information on microRNA-levels can improve the precision of the NORRISK2 score to predict myocardial infarction Status (February 2020): We have published two papers testing during the last year reporting the potential of microRNAs in risk prediction of CVD. The results are promising, and we are hoping to present results at 2 conferences during 2021.

Improving risk prediction of myocardial infarction by including new types of circulating biomarkersmicroRNAs (miRs) have emerged as promising new risk markers of CVD. As miR-analyses are expensive, we want to establish a cost-efficient method for quantification of miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of miRs can improve risk prediction for myocardial infarction.Cardiovascular disease (CVD) is the leading cause of death globally, and the number of individuals at risk is expected to increase in the years to come. Hence, it will be increasingly important for the healthcare system to identify individuals at high risk for CVD, to initiate cost-efficient prevention strategies as lifestyle interventions and pharmacotherapy to decrease the number of events and hospitalization. In the clinical setting, risk prediction models are available for determining the 10-year risk of CVD. However, the currently available risk prediction models only explain a modest proportion of the incidence, and currently fail to discover 15-20 % of the individuals at risk for CVD. Thus, there is a clinical need for new risk markers that could complement the assessment of traditional risk factors, to identify the individuals at risk with greater precision than today. During the last years, microRNAs (miRs) have emerged as promising new risk markers of CVD. We have, as one of few research groups around the world, explored their potential to improve risk prediction models for myocardial infarction (MI), and have reported very promising results. As miR-analyses are expensive, we want to establish a more cost-efficient method for quantification of circulating miRs in blood using less material and improving reproducibility. Furthermore, we will determine whether incorporation of candidate miRs can improve the precision of the NORRISK2 score to predict 10-year risk of MI. Primary aims 1. Establish new cost-efficient, ultra-sensitive methodology for quantification of circulating microRNAs at St.Olavs University Hospital. Status (february 2020): We are currently testing using droplet digital PCR for analysis of microRNAs in blood. The method shows promising results for the microRNAs that we have tested so far, in collaboration with SINTEF. Due to the use of a droplet generator, quantifying large sample volumes might be an issue, however, NINA (in Trondheim) has a method that would allow for high-throughput analysis. We will continue to work on establishing this method in our lab. 2. Determine whether adding information on microRNA-levels can improve the precision of the NORRISK2 score to predict myocardial infarction Status (february 2020): We have so far published two papers testing the potential of improving precision of currently available risk prediction algorithms for myocardial infarction. A new paper was published in February 2020 in collaboration with researchers at Karolinska Institutet. The results are promising, and we are planning to present results at 3 conferences during 2020. We will also be submitting a new paper on microRNAs in risk prediction togheter with our collegues at Department of Cardiology, St.Olavs hospital during 2020.