ArticleGenomics & informatics2019
Evaluation and Interpretation of Transcriptome Data Underlying Heterogeneous Chronic Obstructive Pulmonary Disease.
Article in Genomics & informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- TET1-mediated DNA demethylation and transcription activation of MRPS17 induces lung adenocarcinoma through PI3K-AKT-mTOR pathway.Journal of molecular histology · 2026Article
- An integrated investigation of mitochondrial genes in COPD reveals the causal effect of NDUFS2 by regulating pulmonary macrophages.Biology direct · 2025Article
- Smoking induces shifts in cellular composition and transcriptome within the bronchial mucus barrier.Respirology (Carlton, Vic.) · 2023Article
- Recent evidence from omic analysis for redox signalling and mitochondrial oxidative stress in COPD.Journal of inflammation (London, England) · 2022Review
- Mitochondrial ribosomal stress in lung diseases.American journal of physiology. Lung cellular and molecular physiology · 2022Review
- Integrated analysis reveals lung fibrinogen gamma chain as a biomarker for chronic obstructive pulmonary disease.Annals of translational medicine · 2021Article
- Effect of Smoking and Its Cessation on the Transcript Profile of Peripheral Monocytes in COPD Patients.International journal of chronic obstructive pulmonary diseaseArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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Registered trials
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