Background
Takotsubo syndrome (TTS) and sepsis often co-occur with poor outcomes, yet their underlying molecular mechanisms remain to be elucidated. Transcriptomic analysis is employed to detect diagnostic biomarkers and reveal shared pathophysiological mechanisms in sepsis-associated TTS.
Methods
Myocardial gene expression data (TTS, sepsis, and controls) from GEO were analyzed to identify shared differentially expressed genes. WGCNA and PPI networks were used for candidate gene selection. Key genes were further refined using random forest and LASSO algorithms. Immune cell infiltration was assessed using CIBERSORT. Myocardial injury and gene expression in rat models were evaluated using HE staining, TUNEL assay, immunohistochemistry, qPCR, and Western blotting. Clinical validation was conducted using plasma samples from the China TTS Registry. t-tests and ANOVA were conducted via GraphPad Prism 8 software. A P-value < 0.05 was considered statistically significant.
Results
Lipocalin-2 (LCN2) was recognized as an important biomarker through WGCNA, PPI network analysis, and machine learning algorithms, showing strong predictive performance. Its expression was significantly associated with neutrophil infiltration and myocardial injury in TTS. Consistent with the bioinformatics findings, the TTS-sepsis comorbidity model showed elevated mRNA and protein levels of LCN2 in myocardial tissue, accompanied by increased neutrophil infiltration and severe cardiac injury. Clinical validation confirmed elevated plasma LCN2 levels in patients with sepsis-associated TTS, correlating with neutrophil counts, NT-proBNP, and cTnI levels.
Conclusion
LCN2 is identified as a key inflammatory mediator linking neutrophil-driven inflammation to myocardial injury in sepsis-associated TTS, with dual potential as a diagnostic biomarker and therapeutic target.
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