Sub-phenotypes of pneumonia defined by pulmonary histopathological features

Area of Science:

• Pulmonary Pathology
• Host-Microbe Interactions
• Computational Biology

Background:

• Pneumonia, a common pulmonary pathophysiology, lacks precise sub-phenotyping based on host responses.
• Current therapies primarily target microbes, with limited host-directed strategies.
• Histological lung changes have not been utilized for pneumonia sub-classification.

Purpose of the Study:

• To establish distinct pneumonia sub-phenotypes using lung histopathology.
• To explore the potential for developing rational, host-directed pneumonia therapies.
• To investigate the cellular and histological basis of pneumonia heterogeneity.

Main Methods:

• Scoring of 18 histopathology features in rapid autopsy lung samples from 276 elderly pneumonia patients.
• Application of machine learning algorithms to segregate subjects into pneumonia sub-phenotypes.
• Quantitative immunofluorescence to assess immune cell infiltration (macrophages, neutrophils, T cells, B cells).
• Validation using mouse models to identify corollary sub-phenotypes.

Main Results:

• Machine learning identified seven distinct pneumonia sub-phenotypes based on histopathology signatures.
• Specific immune cells (macrophages, neutrophils, T cells, B cells) were associated with distinct histology features and sub-phenotypes.
• Mouse models partially recapitulated human pneumonia sub-phenotypes, with some human-specific features.
• A spectrum of histopathologies was illuminated, differentiating discrete pneumonia sub-phenotypes.

Conclusions:

• Histopathology-based sub-phenotyping provides a framework for understanding pneumonia heterogeneity.
• This approach lays the foundation for developing targeted, host-directed therapies for specific pneumonia patient subsets.
• Discriminating pneumonia sub-phenotypes is crucial for advancing precision medicine in pulmonary infections.