Exploratory study of serum protein biomarkers for sudden cardiac arrest using protein extension assay: A case-control study.

<h4>Background</h4>Biomarkers associated with the occurrence of sudden cardiac arrest (SCA) are not currently utilized in clinical practice. We aimed to identify novel protein biomarkers associated with sudden cardiac arrest (SCA) using proteomic profiling and evaluate their predictive p...

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Main Authors: Ha Yeon Shin, Jeong Ho Park, Kyoung-Chul Cha, Hyun Je Kim, Woo Jin Jung, Seulki Choi, Ji Hwan Moon, Young Il Roh, Young Sun Ro, Sung Oh Hwang, Sang Do Shin, for CAPTURES-II Investigators
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0319466
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Summary:<h4>Background</h4>Biomarkers associated with the occurrence of sudden cardiac arrest (SCA) are not currently utilized in clinical practice. We aimed to identify novel protein biomarkers associated with sudden cardiac arrest (SCA) using proteomic profiling and evaluate their predictive power alongside traditional cardiovascular risk factors.<h4>Methods</h4>A total of 42 SCA patients with medical causes, aged ≤ 65 years and whose initial rhythm was shockable, and 42 age- and sex-matched controls were analyzed. The initial serum samples obtained after emergency department visits were used for SCA cases. Using a protein extension assay, we identified significant biomarkers through correlation analysis with SCA and extracted proteins with no or weak correlation with the initial lactate level and arrest-to-sampling time to account for post-cardiac arrest changes. The area under the receiver operating characteristic curve (AUROC) was calculated to assess the predictive performance of the extracted proteins.<h4>Results</h4>Among the 246 distinct proteins that met quality criteria, 97 showed a strong correlation with SCA. Among these 97 proteins, 44 showed weak or no correlation with lactate levels, and 12 showed weak or no correlation with onset-to-sampling time. Two proteins (AXL receptor tyrosine kinase [AXL] and TIMP Metallopeptidase inhibitor 4 [TIMP-4]) met all the criteria for biomarker extraction. Both showed significant associations with SCA and enhanced predictive power when combined with traditional risk factors in multivariable analysis. The AUROC for the baseline model using traditional risk factors was 0.692 (95% confidence interval [CI] 0.578-0.806), which improved significantly with the addition of AXL and TIMP-4 (AUROC [95% CI] 0.891 [0.817-0.964] and 0.910 [0.910-0.997], respectively).<h4>Conclusion</h4>AXL and TIMP-4 may be crucial role in the early detection and risk assessment of SCA. Future research to verify the utility of AXL and TIMP-4 in large cohorts is warranted.
ISSN:1932-6203