Evaluation and Interpretation of Transcriptome Data Underlying Heterogeneous Chronic Obstructive Pulmonary Disease
- Author:
Seokjin HAM
1
;
Yeon Mok OH
;
Tae Young ROH
Author Information
- Publication Type:Original Article
- Keywords: chronic obstructive pulmonary disease; deconvolution; gene co-expression; gene heterogeneity; protein sublocalization
- MeSH: Gene Expression Profiling; Humans; Lung; Lung Diseases; Mitochondria; Pathology; Population Characteristics; Pulmonary Disease, Chronic Obstructive; Transcriptome
- From:Genomics & Informatics 2019;17(1):e2-
- CountryRepublic of Korea
- Language:English
- Abstract: Chronic obstructive pulmonary disease (COPD) is a type of progressive lung disease, featured by airflow obstruction. Recently, a comprehensive analysis of the transcriptome in lung tissue of COPD patients was performed, but the heterogeneity of the sample was not seriously considered in characterizing the mechanistic dysregulation of COPD. Here, we established a new transcriptome analysis pipeline using a deconvolution process to reduce the heterogeneity and clearly identified that these transcriptome data originated from the mild or moderate stage of COPD patients. Differentially expressed or co-expressed genes in the protein interaction subnetworks were linked with mitochondrial dysfunction and the immune response, as expected. Computational protein localization prediction revealed that 19 proteins showing changes in subcellular localization were mostly related to mitochondria, suggesting that mislocalization of mitochondria-targeting proteins plays an important role in COPD pathology. Our extensive evaluation of COPD transcriptome data could provide guidelines for analyzing heterogeneous gene expression profiles and classifying potential candidate genes that are responsible for the pathogenesis of COPD.
