Identification of Molecular Markers associated with COPD in Non-smokers and Smokers: A Bioinformatics Analysis

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dc.contributor.authorAgede, Olalekan A
dc.contributor.authorWasagu, Isa M
dc.contributor.authorFawibe, Ademola E
dc.contributor.authorSalami, Alakija K
dc.date.accessioned2023-07-13T08:06:22Z
dc.date.available2023-07-13T08:06:22Z
dc.date.issued2023
dc.description.abstractBackground: Even though the proportional burden of chronic obstructive pulmonary disease (COPD) among never-smokers is significant in both developing and developed nations, accounting for around 30% of all COPD in the community, there is little awareness of the prevalence of COPD in this population. Understanding the molecular processes that underlie COPD in nonsmokers is essential. Methods: A dataset (GSE146560) was acquired from the Gene Expression Omnibus (GEO). The limma and clusterProfiler software tools were used to identify differentially expressed genes (DEGs) and conduct a functional enrichment analysis respectively. Results: In all, 10,583 DEGswere found, of which 1,065were up-regulated and 9,518 were down-regulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways such as neuroactive ligand-receptor interaction, taste transduction, maturity onset diabetes of the young, Hippo signaling pathway, insulin secretion, dilated cardiomyopathy, morphine addiction, and calcium signaling pathway were mainly enriched in the DEGs, along with pathways for the Byzantine arch palate, inflammation, infection, and feeding difficulties. Conclusion: Particularly downregulated COPD genes, such FBXL19-AS1, KRTAP5-AS1, and HAGLR antisense, are identified as COPD biomarkers and may play a role in the pathogenesis of the illness. However, more investigation is required to support this study’s conclusions.en_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11461
dc.language.isoenen_US
dc.publisherUniversity of Louisville, Kentuckyen_US
dc.titleIdentification of Molecular Markers associated with COPD in Non-smokers and Smokers: A Bioinformatics Analysisen_US
dc.typeArticleen_US

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