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Published on: September 27, 2024
The Evolving Landscape of COPD Typization.
Alberto Fantin1,2, Nadia Castaldo1, Giulia Sartori2
1Department of Pulmonology, S. Maria della Misericordia University Hospital, 33100 Udine, Italy.
Chronic obstructive pulmonary disease (COPD) is complex. New methods like biomarkers and AI offer personalized treatments beyond traditional diagnoses for better COPD care.
Area of Science:
- Pulmonary Medicine
- Genomics
- Medical Imaging
Background:
- Chronic obstructive pulmonary disease (COPD) presents significant global health challenges due to its heterogeneity.
- Current diagnostic methods based on spirometry and broad phenotypes inadequately address the molecular complexity for precision medicine.
Purpose of the Study:
- To review advancements in COPD characterization beyond traditional diagnostics.
- To explore the integration of biomarkers, quantitative imaging, and multi-omics for personalized COPD management.
Main Methods:
- Narrative review synthesizing current literature on COPD characterization.
- Analysis of biomarker validation, quantitative imaging, multi-omics, and AI applications.
- Exploration of the proposed GETomics framework (Genetics, Environment, and Time).
Main Results:
- Clinical validation of biologics targeting type 2 inflammation signifies a move towards treatable traits.
- Artificial intelligence and deep learning show promise in improving radiological and body composition analysis.
- Integration of diverse data sources is crucial for advanced COPD phenotyping.
Conclusions:
- A paradigm shift is occurring from generic COPD management to precision medicine targeting specific traits.
- The proposed GETomics framework offers a foundation for future personalized COPD care.
- Advanced technologies are essential for overcoming limitations of traditional COPD classification systems.
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