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Updated: Aug 17, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Construction of m7G subtype classification on heterogeneity of sepsis
Jinru Gong1, Jiasheng Yang1, Yaowei He1
1Department of Pulmonary and Critical Care Medicine, Guangdong Second Provincial General Hospital, Guangzhou, China.
Abstract:
Sepsis is a highly heterogeneous disease and a major factor in increasing mortality from infection. N7-Methylguanosine (m7G) is a widely RNA modification in eukaryotes, which involved in regulation of different biological processes. Researchers have found that m7G methylation contributes to a variety of human diseases, but its research in sepsis is still limited. Here, we aim to establish the molecular classification of m7G gene-related sepsis, reveal its heterogeneity and explore the underlying mechanism. We first identified eight m7G related prognostic genes, and identified two different molecular subtypes of sepsis through Consensus Clustering. Among them, the prognosis of C2 subtype is worse than that of C1 subtype. The signal pathways enriched by the two subtypes were analyzed by ssGSEA, and the results showed that the amino acid metabolism activity of C2 subtype was more active than that of C1 subtype. In addition, the difference of immune microenvironment among different subtypes was explored through CIBERSORT algorithm, and the results showed that the contents of macrophages M0 and NK cells activated were significantly increased in C2 subtype, while the content of NK cells resting decreased significantly in C2 subtype. We further explored the relationship between immune regulatory genes and inflammation related genes between C2 subtype and C1 subtype, and found that C2 subtype showed higher expression of immune regulatory genes and inflammation related genes. Finally, we screened the key genes in sepsis by WGCNA analysis, namely NUDT4 and PARN, and verified their expression patterns in sepsis in the datasets GSE131761 and GSE65682. The RT-PCR test further confirmed the increased expression of NUDTA4 in sepsis patients. In conclusion, sepsis clustering based on eight m7G-related genes can well distinguish the heterogeneity of sepsis patients and help guide the personalized treatment of sepsis patients.
Insights
This study classifies sepsis based on N7-Methylguanosine (m7G) RNA modification genes, identifying two subtypes with distinct prognoses and immune profiles. This molecular classification aids in understanding sepsis heterogeneity and guiding personalized treatment strategies.
Area of Science:
- Molecular Biology
- Immunology
- Genetics
Background:
- Sepsis is a life-threatening condition characterized by significant heterogeneity.
- N7-Methylguanosine (m7G) RNA modification is implicated in various diseases, but its role in sepsis remains under-investigated.
- Understanding sepsis heterogeneity is crucial for developing effective, personalized treatments.
Purpose of the Study:
- To establish a molecular classification of sepsis based on m7G-related genes.
- To reveal the heterogeneity within sepsis subtypes.
- To explore the underlying molecular and immunological mechanisms driving sepsis subtypes.
Main Methods:
- Identification of eight m7G-related prognostic genes.
- Consensus Clustering to define molecular subtypes (C1 and C2).
- ssGSEA for pathway enrichment analysis, CIBERSORT for immune microenvironment assessment, WGCNA for key gene identification, and RT-PCR for validation.
Main Results:
- Two distinct molecular subtypes of sepsis (C1 and C2) were identified, with C2 exhibiting a worse prognosis.
- The C2 subtype showed heightened amino acid metabolism, increased M0 macrophages and activated NK cells, and decreased resting NK cells.
- C2 subtype displayed higher expression of immune regulatory and inflammation-related genes. NUDT4 and PARN were identified as key genes.
- Increased expression of NUDT4 was confirmed in sepsis patients via RT-PCR.
Conclusions:
- Clustering sepsis patients based on m7G-related genes effectively distinguishes patient heterogeneity.
- The identified subtypes offer insights into distinct molecular and immune landscapes within sepsis.
- This classification framework supports the development of personalized treatment strategies for sepsis.
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