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Pre-infection cerebral cortex structure predicts murine sepsis outcome
Robert M Gallant1,2,3,4, Shahinur Alam5, Krishnan Venkataraman5
1Molecular and Systems Physiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
Plos One
|September 17, 2025
Summary
Brain structure variations can predict sepsis survival. Mice surviving sepsis showed greater cortical volume, solidity, and thickness before infection, enabling accurate outcome prediction.
Area of Science:
- Neuroscience
- Infectious Disease Research
- Medical Diagnostics
Background:
- Sepsis is a critical condition resulting from the body's dysregulated response to infection, often leading to organ failure and mortality.
- Effective sepsis management requires reliable predictive markers to guide treatment and improve patient survival rates.
Purpose of the Study:
- To investigate if pre-infection variations in brain structure can predict sepsis trajectory and outcome.
- To test the hypothesis that structural brain metrics can serve as non-genetic markers for sepsis prognosis.
Main Methods:
- Utilized the concept of Lethal Dose 50 (LD50) to establish sepsis severity in a murine model.
- Performed high-resolution structural brain scans on mice one week before infection.
- Analyzed cortical volume, solidity, and thickness as potential predictive indicators.
Main Results:
- Mice destined to survive sepsis exhibited significantly greater cortical volume, solidity, and thickness compared to those that succumbed.
- Predictive models trained on these structural brain metrics achieved accuracies ranging from 75% to 94% in forecasting sepsis outcomes.
- Identified specific brain structural characteristics as reliable predictors of sepsis prognosis in mice.
Conclusions:
- Pre-infection structural brain metrics offer a readily measurable, non-genetic marker for predicting sepsis prognosis in mice.
- High-resolution structural brain scans hold potential for predicting infection outcomes in humans, informing early clinical interventions.
- This research opens avenues for novel diagnostic approaches in critical care settings.
