Serum biomarkers stratify disease severity in acute myocarditis cohorts

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medRxiv Published April 14, 2026 Medically reviewed April 25, 2026 Study authors: Joachimbauer, A.; Perez-Shibayama, C. I.; Payne, E.; Hanka, I.; Stadler, R.; Papadopoulou, I.; Rickl… DOI ↗ By Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease

Key Takeaway

Note that CXCL10, GREM2, and LVEF associate with severity in acute myocarditis but require validation.

This study was a prospective cohort analysis involving 103 patients with acute myocarditis recruited from two independent cohorts. The investigation utilized serum analyses and multimodal data integration, combining profiling of cytokine and chemokine dysregulation with clinical biomarkers. The primary objective was disease severity stratification, with secondary outcomes including immuno-clinical phenotypes, inflammatory signatures, T cell activation, and fibroblast dysregulation.

Immuno-proteomic profiling patterns revealed conserved inflammatory patterns across cohorts, which were dominated by T cell-related cytokines and chemokines. Additionally, dysregulation of hepatocyte growth factor (HGF), bone morphogenic protein 4 (BMP4), Gremlin-1 (GREM1), and Gremlin-2 (GREM2) was observed. Two distinct immuno-clinical phenotypes were identified that linked T cell activation and fibroblast dysregulation to disease severity. Specifically, CXCL10, GREM2, and left ventricular ejection fraction (LVEF) were identified as critical parameters for stratifying disease severity.

No adverse events, serious adverse events, discontinuations, or tolerability data were reported in this observational study. A key limitation noted is that reliable biomarkers to stratify patients and guide therapy are currently lacking. The study provides a versatile set of parameters to identify severe manifestations of acute myocarditis, but these associations must be interpreted with caution. As the evidence is observational, causal links between biomarker levels and outcomes cannot be inferred. These parameters may offer a foundation for future research but are not yet validated for immediate clinical decision-making.

Study Details

Study typeCohort

Sample sizen = 103

EvidenceLevel 3

PublishedApr 2026

View Original Abstract ↓

Background and Aims: Acute myocarditis (AM) is a T cell-mediated myocardial disease with clinical manifestations ranging from mild chest pain to cardiogenic shock. Reliable biomarkers to stratify patients and guide therapy are currently lacking. In particular, the extent of the dysregulation of inflammatory pathways, and the impact on myocardial dysfunction, remain elusive. Methods: Serum analyses were performed in prospectively recruited AM patients (n = 103) from two independent cohorts. Multimodal data integration combining profiling of cytokine and chemokine dysregulation with clinical biomarkers was used to define clinical phenotypes with distinct inflammatory signatures. Machine-learning and regression models were applied to determine biomarkers that indicate clinical severity. Results: Immuno-proteomic profiling revealed conserved inflammatory patterns across AM cohorts, dominated by T cell-related cytokines and chemokines. In addition, AM patients showed dysregulation of fibroblast-derived cytokines, including hepatocyte growth factor (HGF), bone morphogenic protein 4 (BMP4) and the BMP4 inhibitors Gremlin-1 (GREM1) and Gremlin-2 (GREM2). Data integration and unsupervised clustering revealed two immuno-clinical phenotypes, linking T cell activation and fibroblast dysregulation to disease severity. Machine learning-based analysis identified CXCL10, GREM2 and LVEF as critical parameters for stratifying disease severity. Conclusions: These findings highlight a systemic T cell activation signature as diagnostic hallmark of AM. In addition, dysregulation of fibroblast-derived tissue cytokines serves as an indicator for distinct immuno-clinical phenotypes in myocardial inflammatory disease. Thus, the clinically relevant link between T cell-driven immune activation, myocardial inflammation and fibroblast-driven remodelling provides a versatile set of parameters to identify severe manifestations of AM.