Multi-Omics Analysis Identified Drug Repurposing Targets for Chronic Obstructive Pulmonary Disease

Area of Science:

• Systems Biology
• Genomics
• Proteomics
• Metabolomics
• Pharmacogenomics

Background:

• Chronic obstructive pulmonary disease (COPD) research has advanced, yet systematic identification of therapeutic targets using integrated multi-omics data remains limited.
• Novel therapeutic strategies for COPD are needed, necessitating the discovery of new drug targets through advanced computational approaches.

Purpose of the Study:

• To develop a systems biology pipeline for identifying biologically relevant genes and potential therapeutic targets for COPD.
• To facilitate the discovery of novel COPD treatments via drug repurposing or de novo drug discovery.

Main Methods:

• Integration of multi-omics COPD data (genome, transcriptome, proteome, metabolome) from over half a million human samples.
• In silico analysis of interactome and drug-target information using a distance-based network computational model.
• Ranking of candidate genes based on proximity to signature genes across all omics levels.

Main Results:

• Identification of 92 COPD signature genes involved in functions like extracellular matrix structural constituent, collagen binding, and protease binding.
• Determination of 70 druggable targets among the identified signature genes.
• In silico validation indicated that specific genes (e.g., SPP1, APOA1, CTSD) can modulate cell transcriptomics relevant to COPD.

Conclusions:

• The study successfully identified promising therapeutic targets for COPD through a hypothesis-generating pipeline.
• The identified targets, including both known and novel genes, offer potential for developing new COPD therapies.
• The pipeline leverages unbiased omics data, disease relevance, and development feasibility for robust target identification.