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Updated: Jul 18, 2025

Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events
Hannes Helgason1,2, Thjodbjorg Eiriksdottir1, Magnus O Ulfarsson1,2
1deCODE genetics/Amgen, Inc, Reykjavik, Iceland.
Insights
A novel protein risk score shows promise for assessing atherosclerotic cardiovascular disease (ASCVD) risk. This score, when combined with existing clinical factors and polygenic risk scores, modestly improves risk prediction accuracy.
Area of Science:
- Cardiovascular Medicine
- Proteomics
- Genetics
Background:
- Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of mortality worldwide.
- Current risk assessment models rely on clinical factors and polygenic risk scores, but their predictive power can be limited.
- The utility of protein biomarkers in plasma for enhancing ASCVD risk prediction is an area of active investigation.
Purpose of the Study:
- To develop and validate protein risk scores for predicting ASCVD events.
- To compare the performance of protein risk scores against traditional clinical risk factors and polygenic risk scores.
- To assess the additive value of protein risk scores in both primary and secondary prevention populations.
Main Methods:
- Retrospective analysis of a primary event population (13,540 individuals) in Iceland with proteomics data.
- Analysis of a secondary event population from a clinical trial (6,791 individuals) with stable ASCVD.
- Development of protein risk scores using 4963 plasma protein levels; comparison with polygenic risk scores and clinical factors (age, sex, statin use, hypertension, diabetes, BMI, smoking).
Main Results:
- The protein risk score demonstrated significant association with ASCVD events in both primary (HR 1.93/SD) and secondary (HR 1.62/SD) populations.
- Addition of the protein risk score to clinical risk factor models significantly improved discrimination (increased C-index by 0.014-0.022).
- The protein risk score also showed significant associations across different ancestries in the secondary population.
Conclusions:
- A protein risk score derived from plasma proteomics is a significant predictor of ASCVD events.
- Integrating protein risk scores with clinical and polygenic risk scores offers a modest but statistically significant improvement in risk prediction.
- These findings suggest protein risk scores could be a valuable addition to current ASCVD risk assessment strategies.
Importance:
Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain.
Objective:
To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations.
Design, Setting, And Participants:
The primary analysis was a retrospective study of primary events among 13 540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals.
Exposures:
Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling.
Main Outcomes And Measures:
Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death.
Results:
In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical risk factor model (C index change, 0.022 [95% CI, 0.007 to 0.038]). Addition of the protein risk score alone to a clinical risk factor model also led to a significantly increased C index (difference, 0.014 [95% CI, 0.002 to 0.028]). Among White individuals in the secondary event population (6307 participants; 432 events; median follow-up, 2.2 years), the protein risk score had an HR of 1.62 per SD (95% CI, 1.48 to 1.79) and significantly increased C index when added to a clinical risk factor model (C index change, 0.026 [95% CI, 0.011 to 0.042]). The protein risk score was significantly associated with major adverse cardiovascular events among individuals of African and Asian ancestries in the secondary event population.
Conclusions And Relevance:
A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.
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