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Updated: Dec 22, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Contribution of m6A subtype classification on heterogeneity of sepsis
Shi Zhang1, Feng Liu1, Zongsheng Wu1
1Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
Background:
Sepsis is a highly heterogeneous syndrome with diverse immune status and varied bioprocesses among individuals. The heterogeneity of sepsis could be associated with N6-methyladenosine (m6A) RNA methylation, due to m6A as a common and reversible posttranscriptional RNA modification involved in the regulation of whole bioprocesses. Therefore, we aim to identify m6A induced molecular subtypes of sepsis and furthermore explore the probable mechanism.
Methods:
Gene expression datasets with 479 consecutive patients admitted for sepsis to the intensive care unit (ICU) in the Amsterdam Academic Medical Center were included in present study at first. Secondly, twelve m6A methylation regulatory genes were determined via systematic review in published researches. Furthermore, we utilized unsupervised clustering (consensus k means clustering) to identify m6A induced molecular subtypes in sepsis based on m6A prognostic molecular, and assess the association of these subtypes with clinical traits and survival outcomes. Moreover, the probable mechanism and regulatory relationship of m6A in sepsis was also explored through Gene Set Enrichment Analysis (GSEA), Weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) analysis and Co-expression analysis.
Results:
Three m6A subtypes with different outcome were identified in sepsis cohort through unsupervised clustering on m6A prognostic molecular, designated Cluster 1/2/3 (log-rank P=0.004). The best outcome was found for patients classified as having cluster 3, and at 28 days, 21 of 144 people with cluster 3 had died [hazard ratio (HR) vs. all other clusters 5.42 (95% CI: 0.359-0.819); P=0.011], compared with 57 of 224 people with cluster 1 (HR 0.579, 95% CI: 0.364-0.920; P=0.037), and 36 of 112 people with cluster 2 (HR 0.477, 95% CI: 0.272-0.833; P=0.003). For exploration of the relationship between m6A subtypes and immunity, the GSEA found that patients in cluster 1 suffered from hyper-activated immunocompetent status; patients in cluster 2 indicated immunosuppressive status; and patients in cluster 3 showed the moderate immune activity (P<0.05). Co-expression analysis furthermore identified 82 immune molecules and 40 autophagy-related molecules could be regulated by prognostic m6A RNA methylation regulators (P<0.05) and correlation coefficient >0.6. In addition, WGCNA and GO analysis indicated that autophagy was significantly and widely activated in patients with cluster 3 (P<0.05).
Conclusions:
According to the heterogeneity in m6A methylation regulatory genes, three distinct subtypes in sepsis were identified with different RNA epigenetics, immune status, biological processes and outcomes, which initially uncovered that heterogeneity of sepsis may be largely caused by m6A RNA methylation.
Insights
Sepsis heterogeneity is linked to N6-methyladenosine (m6A) RNA methylation. Three distinct m6A-defined sepsis subtypes were identified, each with unique immune profiles and outcomes, suggesting m6A RNA methylation drives sepsis complexity.
Area of Science:
- Molecular biology
- Immunology
- Genomics
Background:
- Sepsis is a complex syndrome with significant individual variability in immune responses and biological processes.
- This heterogeneity may be influenced by N6-methyladenosine (m6A) RNA methylation, a critical posttranscriptional regulator.
- m6A modifications are involved in regulating diverse cellular functions, potentially contributing to sepsis variability.
Purpose of the Study:
- To identify molecular subtypes of sepsis based on m6A RNA methylation patterns.
- To investigate the underlying mechanisms and regulatory relationships of m6A in sepsis.
- To correlate these subtypes with clinical characteristics and patient survival outcomes.
Main Methods:
- Utilized gene expression data from 479 ICU sepsis patients.
- Identified 12 m6A methylation regulatory genes through a systematic literature review.
- Applied consensus k-means clustering to define m6A-induced sepsis subtypes.
- Performed Gene Set Enrichment Analysis (GSEA), Weighted Gene Co-expression Network Analysis (WGCNA), Gene Ontology (GO) analysis, and co-expression analysis to explore mechanisms.
Main Results:
- Three distinct m6A-defined sepsis subtypes (Cluster 1, 2, and 3) were identified, showing significant differences in survival (log-rank P=0.004).
- Cluster 3 exhibited the best survival outcomes, while Clusters 1 and 2 were associated with poorer prognoses.
- GSEA revealed distinct immune statuses: hyper-activated in Cluster 1, immunosuppressed in Cluster 2, and moderately active in Cluster 3.
- WGCNA and GO analysis indicated significant autophagy activation in Cluster 3 patients.
Conclusions:
- Sepsis heterogeneity can be attributed to variations in m6A RNA methylation.
- Three distinct sepsis subtypes characterized by unique RNA epigenetic profiles, immune statuses, and biological processes were identified.
- These findings provide initial insights into the role of m6A RNA methylation in driving sepsis heterogeneity and influencing patient outcomes.

