ArticleMolecular medicine (Cambridge, Mass.)2020
Identification of biomarkers in common chronic lung diseases by co-expression networks and drug-target interactions analysis.
Article in Molecular medicine (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.
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- Establishment of an artificial particulate matter-induced lung disease model through analyzing pathological changes and transcriptomic profiles in mice.Scientific reports · 2023Article
- Duration of exposure to epidural anesthesia at delivery, DNA methylation in umbilical cord blood and their association with offspring asthma in Non-Hispanic Black women.Environmental epigenetics · 2023Article
- Recent evidence from omic analysis for redox signalling and mitochondrial oxidative stress in COPD.Journal of inflammation (London, England) · 2022Review
- Proteomic Analysis of Human Sputum for the Diagnosis of Lung Disorders: Where Are We Today?International journal of molecular sciences · 2022Review
- Integrative transcriptomic and proteomic analysis reveals mechanisms of silica-induced pulmonary fibrosis in rats.BMC pulmonary medicine · 2022Article
- Role of FK506-sensitive signals in asthmatic lung inflammation.Frontiers in immunology · 2022Article
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- Pentraxin 3 is a diagnostic and prognostic marker for ovarian epithelial cancer patients based on comprehensive bioinformatics and experiments.Cancer cell international · 2021Article
- Sex-specific associations of asthma acquisition with changes in DNA methylation during adolescence.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundasthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF) are three serious pulmonary diseases that contain common and unique characteristics. Therefore, the identification of biomarkers that differentiate these diseases is of importance for preventing misdiagnosis. In this regard, the present study aimed to identify the disorders at the early stages, based on lung transcriptomics data and drug-target interactions.
methodsTo this end, the differentially expressed genes were found in each disease. Then, WGCNA was utilized to find specific and consensus gene modules among the three diseases. Finally, the disease-disease similarity was analyzed, followed by determining candidate drug-target interactions.
resultsThe results confirmed that the asthma lung transcriptome was more similar to COPD than IPF. In addition, the biomarkers were found in each disease and thus were proposed for further clinical validations. These genes included RBM42, STX5, and TRIM41 in asthma, CYP27A1, GM2A, LGALS9, SPI1, and NLRC4 in COPD, ATF3, PPP1R15A, ZFP36, SOCS3, NAMPT, and GADD45B in IPF, LRRC48 and CETN2 in asthma-COPD, COL15A1, GIMAP6, and JAM2 in asthma-IPF and LMO7, TSPAN13, LAMA3, and ANXA3 in COPD-IPF. Finally, analyzing drug-target networks suggested anti-inflammatory candidate drugs for treating the above mentioned diseases.
conclusionIn general, the results revealed the unique and common biomarkers among three chronic lung diseases. Eventually, some drugs were suggested for treatment purposes.
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