Integrating omics technologies to study pulmonary physiology and pathology at the systems level

Area of Science:

• Pulmonary Medicine
• Systems Biology
• Computational Biology

Background:

• Omics technologies (genomics, proteomics, metabolomics) have transformed medical research.
• Interpreting vast omics data requires a systems biology approach, linking molecular information at the organismic level.
• Pulmonary medicine increasingly integrates omics, network, and computational biology for disease diagnosis, prognosis, and treatment.

Purpose of the Study:

• To describe a "systomic" approach for understanding pulmonary diseases at the systems level.
• To explain how to leverage emerging omics technologies in pulmonary medicine.
• To guide biomedical scientists and clinical researchers in applying systems-level analysis to lung diseases.

Main Methods:

• Conceptualizing diseased genome, proteome, and metabolome at the systems level.
• Integrating diverse omics data (genomics, epigenomics, proteomics, metabolomics).
• Utilizing network, systems, and computational biology approaches.

Main Results:

• The "systomic" approach offers a comprehensive view of pulmonary disease pathogenesis and progression.
• Integration of omics data facilitates differential diagnosis and prognostication.
• Improved understanding at the systems level can enhance therapy and treatment modalities.

Conclusions:

• A systems-level "systomic" approach is crucial for advancing pulmonary medicine.
• Despite current user-friendliness challenges, omics technologies are vital for interpreting complex lung disease data.
• This review provides strategies and tools for effective systems-level study of pulmonary diseases.