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. 2023 Mar;20(3):414-422.
doi: 10.1016/j.hrthm.2022.12.014. Epub 2022 Dec 13.

A panel of blood biomarkers unique to sudden cardiac arrest

Faye L Norby  1 , Kotoka Nakamura  1 , Qin Fu  2 , Vidya Venkatraman  2 , Niveda Sundararaman  2 , Mitra Mastali  2 , Kyndaron Reinier  1 , Angelo Salvucci  3 , Jonathan Jui  4 , Jennifer E Van Eyk  2 , Sumeet S Chugh  5
Affiliations

A panel of blood biomarkers unique to sudden cardiac arrest

Faye L Norby et al. Heart Rhythm. 2023 Mar.

Abstract

Background: The identification of circulating biomarkers specific for sudden cardiac arrest (SCA) could enhance risk prediction. Of particular interest are biomarkers specific to SCA, independent of coronary artery disease (CAD).

Objective: The purpose of this study was to identify biomarkers of SCA obtained close to the SCA event.

Methods: Twenty cases (survivors of SCA) and 40 age- and sex-matched controls were compared, with a replication analysis of 29 cases matched to 57 controls. A secondary analysis compared 20 SCA cases to 20 controls with CAD. Blood samples were obtained from SCA survivors at a median of 11 months after the SCA event. Proteins were analyzed on a mass spectrometer using data-independent acquisition; a subset of cytokines were analyzed using immunoassays; and 1153 lipids (13 classes) were analyzed. A false discovery rate P value of <.05 identified associated proteins.

Results: Patients had a mean age of 58 years (range 25-87 years), and 70% were male. A total of 26 protein biomarkers associated with SCA when cases were compared with controls, of which 20 differentiated SCA from CAD. The replication analysis identified 8 of 26 biomarkers, of which 6 were not overlapping with CAD. The top identified biological processes involved the extracellular matrix, coagulation cascades, and platelet activation. Lipids in the lysophosphatidylcholine class were implicated in SCA through the CAD pathway.

Conclusion: We identified a panel of novel blood biomarkers specifically associated with SCA, including several that may be involved outside the CAD pathway. These biomarkers could have mechanistic significance and the potential to enhance clinical prediction of SCA.

Keywords: Biomarker; Cardiac arrest; Death; Prediction; Prevention; Proteomics; Risk stratification; Sudden cardiac.

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Conflict of interest statement

Conflicts of Interest

All authors state explicitly that there are no conflicts of interest.

Figures

Figure 1.
Figure 1.
Study design and characteristics for the comparisons between sudden cardiac arrest (SCA) cases and controls
Figure 2.
Figure 2.
Six top GO biological processes based on differentially expressed protein biomarkers between SCA cases and normal controls in the main analysis. Panel A depicts the relationships between each GO term (in an octagon) and each protein node. Inhibited GO terms are in blue. Upregulated proteins are shades of red and downregulated proteins are shades of blue. Panel B shows a different grouping of the same analysis. Here, proteins are grouped by each GO term, and each donut is color-coded according to the influence of each GO term.
Figure 3.
Figure 3.
Enriched function networks generated by comparing SCA cases to healthy controls. The one activated pathway is shown as an orange node and the 5 inhibited pathways are blue nodes. Upregulated proteins are shades of red and downregulated proteins are shades of blue.
Figure 4.
Figure 4.
Comprehensive summary of study design, novel biomarkers discovered, potential mechanistic pathways and future directions.
See this image and copyright information in PMC

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