Can physiological network mapping reveal pathophysiological insights into emerging diseases? Lessons from COVID-19

Area of Science:

• Network physiology
• Systems biology
• Computational medicine

Background:

• Network physiology provides a holistic view of human body interactions.
• Organ system connectivity is crucial in understanding health and disease.
• Emerging diseases require novel approaches for pathophysiological insights.

Purpose of the Study:

• To evaluate physiological network mapping for predicting COVID-19 patient outcomes.
• To identify distinct network patterns in non-survivors versus survivors of COVID-19.
• To explore inter-organ connectivity in the context of a novel infectious disease.

Main Methods:

• Retrospective analysis of clinical and laboratory data from 202 COVID-19 patients.
• Construction of organ network connectivity using 21 physiological variables via correlation analysis.
• Application of parenclitic network analysis to assess deviations from survivor reference interactions.

Main Results:

• Distinct correlation network maps were observed between non-survivors and survivors.
• Non-survivors showed a significant correlation between consciousness and liver enzymes, absent in survivors.
• A strong BUN-potassium axis correlation in non-survivors indicated kidney dysfunction and altered homeostasis.

Conclusions:

• Physiological network mapping is a valuable tool for uncovering complex inter-organ interactions in emerging diseases.
• Distinct network features in non-survivors offer potential biomarkers for disease severity.
• Network physiology can support clinicians, researchers, and policymakers in future epidemics.