Evaluation and Interpretation of Transcriptome Data Underlying Heterogeneous Chronic Obstructive Pulmonary Disease.

Area of Science:

• Pulmonary Medicine
• Genomics
• Computational Biology

Background:

• Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by airflow obstruction.
• Previous transcriptome analyses of COPD lung tissue did not adequately address sample heterogeneity.
• Understanding COPD pathogenesis requires accounting for molecular variations within patient samples.

Purpose of the Study:

• To establish a novel transcriptome analysis pipeline to address sample heterogeneity in COPD.
• To identify key molecular mechanisms and pathways involved in COPD pathogenesis.
• To investigate the role of protein subcellular localization in COPD.

Main Methods:

• Developed a deconvolution-based transcriptome analysis pipeline.
• Analyzed differentially expressed and co-expressed genes within protein interaction subnetworks.
• Utilized computational protein localization prediction to identify mislocalized proteins.

Main Results:

• The pipeline successfully reduced heterogeneity, identifying data from mild to moderate COPD stages.
• Key pathways linked to mitochondrial dysfunction and immune response were identified.
• 19 proteins with altered subcellular localization, primarily affecting mitochondria, were discovered, suggesting their role in COPD.

Conclusions:

• Mitochondria-targeting protein mislocalization is a significant factor in COPD pathology.
• The developed pipeline offers a guideline for analyzing heterogeneous gene expression profiles in COPD.
• This approach aids in classifying candidate genes responsible for COPD pathogenesis.