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Drp1-associated genes implicated in sepsis survival
Marissa D Pokharel1,2, Anlin Feng1,3, Ying Liang1,3
1Center for Translational Science, Florida International University, Port Saint Lucie, FL, United States.
Frontiers in Immunology
|January 23, 2025
Summary
New blood biomarkers predicting sepsis survival risk have been developed. These markers, based on mitochondrial dynamics genes, can improve early patient identification and treatment strategies, potentially reducing sepsis mortality.
Area of Science:
- Biochemistry
- Genetics
- Critical Care Medicine
Background:
- Sepsis is a life-threatening condition with high mortality, necessitating improved prognostic markers.
- Current treatments for sepsis are often inadequate, highlighting the need for better patient management tools.
- Mitochondrial dynamics, involving fission and fusion, are increasingly recognized as relevant to sepsis severity and inflammation.
Purpose of the Study:
- To engineer novel, reliable blood-borne biomarkers for predicting sepsis survival risk.
- To identify gene signatures associated with mitochondrial dynamics and sepsis prognosis.
- To validate these biomarkers in human transcriptomic datasets.
Main Methods:
- Utilized dynamin-related protein 1 (Drp1) and its associated genes.
- Developed a 12-gene signature (GS) based on differentially expressed genes (DEGs).
- Created a 7-gene protein-protein interaction (PPI)-based GS by comparing Drp1 interactors with sepsis survival genes.
- Validated both GSs using public human blood transcriptomic data from sepsis patients.
Main Results:
- Both DEG-based and PPI-based gene signatures demonstrated successful prediction of sepsis survival.
- The PPI-based 7-gene GS exhibited enhanced prognostic performance compared to the DEG-based GS.
- The developed biomarkers showed high sensitivity and specificity in both discovery and validation cohorts.
Conclusions:
- A novel, validated blood-borne biomarker (PPI-based 7-gene GS) for sepsis survival risk prediction has been engineered.
- This biomarker can aid in the early identification of high-risk sepsis patients.
- The findings support the potential for optimizing personalized treatment strategies to reduce sepsis mortality.
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