MSACL 2025 Abstract

Targeted UPLC-MRM-MS Analysis of Circulating Protein Biomarkers in a Nested Case-Control Study for Myocardial Infarction Risk

Kári Arnarson (1,2), Finnur F. Eiríksson (3,4), Valborg Guðmundsdóttir (2,5), Margret Thorsteinsdottir (1,4), Vilmundur G. Guðnason (2,5).
(1) University of Iceland Faculty of Pharmaceutical Sciences, Reykjavík, Iceland. (2) University of Iceland Faculty of Medicine, Reykjavík, Iceland. (3) MassHei Core Facility, School of Health Sciences, University of Iceland, Reykjavik, Iceland. (4) ArcticMass, Reykjavík, Iceland. (5) Icelandic Heart Association, Reykjavík, Iceland.

Kári Arnarson, MSc (Presenter) University of Iceland

Presenter Bio: I am a PhD student at the Univeristy of Iceland, doing a joint project at the faculty of medicine and faculty of pharmaceutical sciences. My BSc in pharmacy was at the Univeristy of Iceland, and my MSc was split between the Univeristy of Iceland, Københavns Universitet, Copenhagen Denmark and a traineeship at the Center for Proteomics and Metabolomics at Leids Universitair Medisch Centrum, Leiden Netherlands.

Focus of my work is targeted mass spectrometry methods for clinical research. Specifically, my project is aimed at assay development for absolute quantification of protein biomarkers for cardiovascular disease.

Relevant Financial Disclosures (within past 24 months, reported on Apr 22, 2026) No relevant financial relationship(s) to disclose.

INTRODUCTION:
Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for approximately 45% of all non-communicable disease fatalities (1). Many individuals who eventually suffer from myocardial infarction (MI) are initially classified as low-to-moderate risk by traditional 10-year risk assessment tools. This highlights a critical need for novel biomarkers capable of detecting biological risk factors for MI, both in patients overlooked by conventional CVD risk prediction models and for individuals at-risk for imminent MI.

OBJECTIVES:
This study aims to develop a mass spectrometry-based targeted proteomics platform to; investigate the relationship between circulating proteins and incident MI, identify protein biomarkers that may provide insights into acute MI risk, and assess whether these biomarkers offer additional predictive value beyond traditional clinical risk factors.

METHODS:
The study investigated individuals from the population-based Reykjavík REFINE cohort (2). Serum samples from 300 individuals (age 58.7 ± 7.23 years; mean follow-up of 13 years) in a nested case control design were selected for analysis. An automated bottom-up proteomic sample preparation was developed and serum samples analyzed using an ultra-performance liquid chromatography multiple reactor monitoring mass spectrometry platform (UPLC-MRM-MS). The platform uses 275 synthetic isotope-labeled and non-labeled peptides for simultaneous absolute quantification of 270 proteins. Paired conditional logistic regression analysis was applied between protein concentrations and incident MI within 1 year, 5 years or the full follow-up. Multiple testing was accounted for using Benjamini-Hochberg adjustment. Additionally, correlations between protein concentrations and known cardiometabolic risk factors were investigated (3).

RESULTS:
The automated workflow was successfully implemented, and 170 proteins were within quantitation range in the study population. Over the full follow-up, 28 proteins were significantly associated with incident MI, of which 23 retained their nominal significance when adjusted for clinical risk factors. Further 4 and 5 proteins were uniquely associated to acute risk of MI in the 5-year and 1-year groups, respectively. Cluster analysis showed strong correlation between protein groups and known cardiometabolic risk factors.

DISCUSSION:
The results indicate that circulating proteins provide valuable information about imminent risk of MI. Correlation between the protein concentrations and cardiometabolic risk factors for MI suggest that the proteins measured reflect CVD progression. Proteins which independently associated with MI when adjusted for clinical risk factors may have the potential to further improve risk prediction models. A one-day bottom-up proteomics platform using Evosep-MRM-MS for the analysis of the proteins associated with incident MI is in development for validation of these results in a population cohort.

REFERENCES:
1. Townsend N, Wilson L, Bhatnagar P, Wickramasinghe K. Corrigendum to: Cardiovascular disease in Europe: epidemiological update 2016. European Heart Journal. 2019 Jan 7;40(2):189–189.
2. Thorsson B, Eiriksdottir G, Sigurdsson S, Gudmundsson EF, Bots ML, Aspelund T, et al. Population distribution of traditional and the emerging cardiovascular risk factors carotid plaque and IMT: the REFINE-Reykjavik study with comparison with the Tromsø study. BMJ Open. 2018 May;8(5):e019385.
3. McClelland RL, Jorgensen NW, Budoff M, Blaha MJ, Post WS, Kronmal RA, et al. 10-Year Coronary Heart Disease Risk Prediction Using Coronary Artery Calcium and Traditional Risk Factors. Journal of the American College of Cardiology. 2015 Oct;66(15):1643–53.