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Shin HY, Park JH, Cha KC, Kim HJ, Jung WJ, Choi S, Moon JH, Roh YI, Ro YS, Hwang SO, Do Shin S. Exploratory study of serum protein biomarkers for sudden cardiac arrest using protein extension assay: A case-control study. PLoS One 2025; 20:e0319466. [PMID: 39992996 PMCID: PMC11849859 DOI: 10.1371/journal.pone.0319466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Accepted: 02/04/2025] [Indexed: 02/26/2025] Open
Abstract
BACKGROUND 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. METHODS 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. RESULTS 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). CONCLUSION 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.
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Affiliation(s)
- Ha Yeon Shin
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Jeong Ho Park
- Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Republic of Korea
- Disaster Medicine Research Center, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Kyoung-Chul Cha
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
- Research Institute of Resuscitation Science, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Hyun Je Kim
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Department of Microbiology and Immunology, Seoul National University College of Medicine, Republic of Korea
- Genomic Medicine Institute, Seoul National University College of Medicine, Republic of Korea
| | - Woo Jin Jung
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
- Research Institute of Resuscitation Science, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Seulki Choi
- Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Republic of Korea
- Disaster Medicine Research Center, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Ji Hwan Moon
- Samsung Genome Institute, Samsung Medical Center, Seoul, Republic of Korea
| | - Young Il Roh
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
- Research Institute of Resuscitation Science, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Young Sun Ro
- Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Republic of Korea
- Disaster Medicine Research Center, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Sung Oh Hwang
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
- Research Institute of Resuscitation Science, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Sang Do Shin
- Department of Emergency Medicine, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
- Laboratory of Emergency Medical Services, Seoul National University Hospital Biomedical Research Institute, Seoul, Republic of Korea
- Disaster Medicine Research Center, Seoul National University Medical Research Center, Seoul, Republic of Korea
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