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

**Authors:** Cindy Xinyu Ji, Majid Sorouri, Mohammad Abdollahi, Omalbanin Paknejad, Ali R. Mani, Siddharth Gosavi, Siddharth Gosavi, Siddharth Gosavi

PMC · DOI: 10.1371/journal.pone.0337333 · PLOS One · 2025-11-21

## TL;DR

This study explores how mapping physiological networks can reveal insights into diseases like COVID-19 by analyzing differences in organ system interactions between survivors and non-survivors.

## Contribution

The study introduces the use of physiological network mapping to uncover unique inter-organ correlations in non-survivors of COVID-19.

## Key findings

- Non-survivors showed a significant correlation between consciousness and liver enzymes not seen in survivors.
- A strong BUN–potassium correlation in non-survivors suggests kidney damage and potassium imbalance.
- These correlations remained significant after adjusting for age and hypoxia levels.

## Abstract

Network physiology is a multidisciplinary field that offers a comprehensive view of the complex interactions within the human body, emphasising the critical role of organ system connectivity in health and disease. This approach has the potential to provide pathophysiological insights into complex and emerging diseases. This study aims to evaluate the effectiveness of physiological network mapping in predicting outcomes for COVID-19 patients, using data from the first wave of the pandemic. Routine clinical and laboratory data from 202 patients with COVID-19 were retrospectively analysed. Twenty-one physiological variables representing various organ systems were used to construct organ network connectivity through correlation analysis. Parenclitic network analysis was also employed to measure deviations in individual patients’ organ system correlations from the reference physiological interactions observed in survivors. We observed distinct features in the correlation network maps of non-survivors compared to survivors. In non-survivors, there was a significant correlation between the level of consciousness and the liver enzyme cluster, a relationship not present in the survivor group. This relationship remained significant even after adjusting for age and degree of hypoxia. Additionally, a strong correlation along the BUN–potassium axis was identified in non-survivors, suggesting varying degrees of kidney damage and impaired potassium homeostasis in non-survivors. These findings highlight the potential of network physiology as a valuable tool for uncovering complex inter-organ interactions in emerging diseases, with applications that could support clinicians, researchers, and policymakers in future epidemics.

## Linked entities

- **Diseases:** COVID-19 (MONDO:0100096)

## Full-text entities

- **Diseases:** potassium homeostasis (MESH:D011191), kidney damage (MESH:D007674), COVID-19 (MESH:D000086382), hypoxia (MESH:D000860)
- **Chemicals:** potassium (MESH:D011188)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12637946/full.md

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12637946/full.md

## References

31 references — full list in the complete paper: https://tomesphere.com/paper/PMC12637946/full.md

---
Source: https://tomesphere.com/paper/PMC12637946