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Updated: Mar 21, 2026

Digital PCR for Quantifying Circulating MicroRNAs in Acute Myocardial Infarction and Cardiovascular Disease
Published on: July 3, 2018
Circulating microRNAs predict future fatal myocardial infarction in healthy individuals - The HUNT study
Anja Bye1, Helge Røsjø2, Javaid Nauman1
1K.G. Jebsen Center of Exercise in Medicine at Dept. of Circulation and Medical Imaging, Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway.
Insights
Circulating microRNAs (miRs) can predict future fatal acute myocardial infarction (AMI) in healthy individuals. A panel of five miRs significantly improved risk prediction, outperforming traditional methods and showing gender-specific associations.
Area of Science:
- Cardiovascular Medicine
- Molecular Biology
- Biomarker Discovery
Background:
- Coronary heart disease is a leading cause of death globally, with increasing prevalence.
- Accurate risk prediction tools and novel biomarkers are crucial for managing cardiovascular disease.
- Current risk assessment models may benefit from enhanced predictive capabilities.
Purpose of the Study:
- To evaluate the predictive utility of circulating microRNAs (miRs) for future fatal acute myocardial infarction (AMI) in healthy individuals.
- To identify specific miRs associated with AMI risk.
- To assess gender-specific differences in miR-associated AMI risk.
Main Methods:
- A prospective nested case-control study involving 112 healthy participants (40-70 years) with a 10-year follow-up for fatal AMI.
- Quantification of 179 miRs in serum using real-time polymerase chain reaction.
- Validation of candidate miRs in an independent cohort of 100 healthy individuals.
Main Results:
- Twelve miRs showed differential expression between cases and controls in the derivation cohort, with 10 validated in the independent cohort.
- Specific miRs, miR-424-5p and miR-26a-5p, were associated with AMI risk exclusively in men and women, respectively.
- A panel of 5 miRs (miR-106a-5p, miR-424-5p, let-7g-5p, miR-144-3p, miR-660-5p) achieved 77.6% correct classification and significantly improved the AUC from 0.72 to 0.91 when added to the Framingham Risk Score.
Conclusions:
- Several circulating miRs are significantly associated with the risk of future fatal AMI in healthy individuals.
- Gender-specific associations between certain miRs and AMI risk were identified.
- A panel of five miRs offers a promising tool to enhance the prediction of AMI risk, particularly when combined with existing risk scores.
Abstract:
Coronary heart disease is the most common cause of death, and the number of individuals at risk is increasing. To better manage this pandemic, improved tool for risk prediction, including more accurate biomarkers are needed. The objective of this study was to assess the utility of circulating microRNAs (miRs) to predict future fatal acute myocardial infarction (AMI) in healthy participants. We performed a prospective nested case-control study with 10-year observation period and fatal AMI as endpoint. In total, 179 miRs were quantified by real-time polymerase chain reaction in serum of 112 healthy participants (40-70years) that either (1) suffered from fatal AMI within 10years [n=56], or (2) remained healthy [n=56, risk factor-matched controls]. Candidate miRs were validated in a separate cohort of healthy individuals (n=100). Twelve miRs were differently expressed in cases and controls in the derivation cohort (p<0.05). Among these, 10 miRs differed significantly between cases and controls in the validation cohort (p<0.05). We identified gender dimorphisms, as miR-424-5p and miR-26a-5p were associated exclusively with risk in men and women, respectively. The best model for predicting future AMI consisted of miR-106a-5p, miR-424-5p, let-7g-5p, miR-144-3p and miR-660-5p, providing 77.6% correct classification for both genders, and 74.1% and 81.8% for men and women, respectively. Adding these 5 miRs to the Framingham Risk Score, increased the AUC from 0.72 to 0.91 (p<0.001). In conclusion, we identified several miRs associated with future AMI, revealed gender-specific associations, and proposed a panel of 5 miRs to enhance AMI risk prediction in healthy individuals.
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