Introduction to Sepsis and Metabolic Reprogramming

Sepsis remains a critical global health challenge, characterized by life-threatening organ dysfunction. This condition stems from a dysregulated host response to infection. Currently, clinicians struggle with early identification because symptoms often overlap with other inflammatory states. Therefore, the search for reliable sepsis diagnostic biomarkers has become a top priority in critical care research. Recent studies suggest that metabolic reprogramming, specifically involving fumarate metabolism, plays a pivotal role in how the immune system reacts during sepsis.

During the early stages of sepsis, the body often undergoes a hyperinflammatory phase. This is frequently followed by an immunosuppressive state that leaves patients vulnerable to secondary infections. Researchers are now looking at how metabolic genes influence these shifts. By understanding these pathways, we can potentially identify patients earlier and tailor treatments more effectively.

Innovative Sepsis Diagnostic Biomarkers and Genetic Signatures

A recent comprehensive analysis has identified four core genes related to fumarate metabolism that serve as excellent sepsis diagnostic biomarkers. These genes are EPHX2, S100A8, TXN, and ANXA3. Each of these play a specific role in the inflammatory cascade and metabolic stability of immune cells.

• S100A8: This gene encodes a protein that acts as a damage-associated molecular pattern (DAMP), amplifying pro-inflammatory signaling.


• ANXA3: Frequently up-regulated in neutrophils, this gene helps distinguish sepsis from other forms of shock.


• TXN: Involved in managing oxidative stress, which is often rampant during systemic infections.


• EPHX2: This gene links metabolic processing to systemic inflammation levels.

Furthermore, machine learning models using these four genes have demonstrated high accuracy in predicting sepsis. The integration of these genetic markers into a single diagnostic model allows for a more robust assessment than traditional markers like C-reactive protein or procalcitonin.

Immune Infiltration and Molecular Subtyping

The relationship between metabolism and immunity is clearly visible in the infiltration patterns of immune cells. Analysis shows a significant increase in neutrophils and M1 macrophages in septic patients. Conversely, there is a notable reduction in adaptive immune cells, such as CD8 T cells. This imbalance contributes to the complex pathology seen in the intensive care unit.

Additionally, molecular subtyping based on these metabolic genes has identified two distinct sepsis subtypes. Each subtype possesses unique immune characteristics, which could explain why patients respond differently to the same therapies. Consequently, these findings provide a theoretical foundation for personalized treatment strategies in sepsis management.

Frequently Asked Questions

How do these biomarkers improve sepsis diagnosis?

These sepsis diagnostic biomarkers focus on metabolic pathways that change before clinical symptoms become severe. By using machine learning to analyze genes like S100A8 and ANXA3, clinicians can achieve higher sensitivity and specificity than with standard blood tests.

What is the role of fumarate metabolism in immunity?

Fumarate is a metabolic intermediate that influences inflammatory responses. Dysregulation of fumarate metabolism can lead to immune exhaustion or excessive inflammation, both of which are hallmarks of sepsis progression.

Disclaimer: This content is for informational and educational purposes only. It does not constitute medical advice or establish a doctor-patient relationship. The findings discussed are based on recent research and may not yet be part of standard clinical practice. Refer to the latest local and national guidelines for clinical practice.

References

Li M et al. Screening of Sepsis Diagnostic Biomarkers Based on Fumarate Metabolism-Related Genes with Analysis of Immune Infiltration and Subtype Identification. Immunol Invest. 2026 May 11. doi: 10.1080/08820139.2026.2667875. PMID: 42109201.

Toufiq M et al. Annexin A3 in sepsis: novel perspectives from an exploration of public transcriptome data. Scholarly Publications Leiden University. 2024.

Sarkar S et al. Integrated Transcriptomic Analysis of S100A8/A9 as a Key Biomarker and Therapeutic Target in Sepsis Pathogenesis. MDPI. 2025.