ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Clinical and Translational Cardiovascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1640788
Serum S100A12 in the Clinical Diagnosis of Sepsis-Induced Myocardial Dysfunction: An Integrated Bioinformatics and Clinical Data Analysis
Provisionally accepted
- 1The First People's Hospital of Guiyang, Guiyang, China
- 2The First People’s Hospital of Guiyang, Guiyang, China
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Objective: Sepsis is a common and life-threatening syndrome in intensive care units, frequently accompanied by myocardial dysfunction, which significantly worsens patient outcomes. S100A12, a calcium-binding protein associated with inflammation, is upregulated in various inflammatory conditions. However, its role in sepsis and related cardiac injury remains unclear.Methods: This study performed differential expression analysis using datasets from GEO to evaluate changes in S100A12 expression in sepsis and sepsis-induced myocardial dysfunction (SIMD), followed by GO and KEGG pathway enrichment analyses. Patients diagnosed with sepsis were assigned into SIMD and non-SIMD groups, along with healthy controls. Serum S100A12 expression was evaluated by ELISA and RT-qPCR. Correlations with cardiac enzymes, inflammatory markers, and cardiac function indicators were assessed.Results: Bioinformatics analysis showed upregulation of S100A12 in sepsis and SIMD, enriched in multiple inflammation-related pathways. Clinically, S100A12 mRNA and protein levels were higher in the SIMD group. There was a positive association between S100A12 concentrations and cTnI, CK-MB, PCT, and IL-6, whereas MAP and LVEF exhibited a negative correlation. Logistic regression identified S100A12 as an independent risk factor for SIMD.As an inflammatory biomarker, S100A12 has independent predictive value, and its combination with cardiac enzymes enables the development of an efficient clinical warning model.The study highlights a potential new biomarker and treatment focus that could aid in early detection and management of sepsis-related cardiac injury.
Keywords: Sepsis, Myocardial dysfunction, S100A12, Inflammatory biomarker, receiver operating characteristic curve, Logistic regression, Bioinformatics analysis
Received: 04 Jun 2025; Accepted: 11 Aug 2025.
Copyright: © 2025 Wu, Hong, Tian and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaoyan Wang, The First People’s Hospital of Guiyang, Guiyang, China
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