Evaluation and interpretation of transcriptome data underlying heterogeneous chronic obstructive pulmonary disease

Seokjin Ham, Yeon Mok Oh, Tae Young Roh

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5 Scopus citations


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.

Original languageEnglish
Article numbere2
JournalGenomics and Informatics
Issue number1
StatePublished - 2019

Bibliographical note

Funding Information:
This work was supported by a grant (NRF-2014M3C9A3064548 and NRF2017M3C9A6047625 to T.-Y. R.), funded by the National Research Foundation of Korea (NRF). S.H. was supported by the BK21 PLUS fellowship program (10Z20130012243), funded by the Ministry of Education, Korea.

Publisher Copyright:
© 2019, Korea Genome Organization.


  • Chronic obstructive pulmonary disease
  • Deconvolution
  • Gene co-expression
  • Gene heterogeneity
  • Protein sublocalization


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