A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD

Abstract The swift transmission rate and unfavorable prognosis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have prompted the pursuit of more effective therapeutic interventions. Azithromycin (AZM) has garnered significant attention for its distinctive pharmacological...

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Main Authors: Yining Xie, Guangshu Chen, Weiling Wu, Xueman Wen, Meizheng Lai, Li Che, Jianmin Ran
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-94801-9
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author Yining Xie
Guangshu Chen
Weiling Wu
Xueman Wen
Meizheng Lai
Li Che
Jianmin Ran
author_facet Yining Xie
Guangshu Chen
Weiling Wu
Xueman Wen
Meizheng Lai
Li Che
Jianmin Ran
author_sort Yining Xie
collection DOAJ
description Abstract The swift transmission rate and unfavorable prognosis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have prompted the pursuit of more effective therapeutic interventions. Azithromycin (AZM) has garnered significant attention for its distinctive pharmacological mechanisms in the treatment of SARS-CoV-2. This study aims to elucidate the biological rationale for employing AZM in patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) who are infected with SARS-CoV-2. Genetic data about COVID-19, COPD, and IPF were independently obtained from the GeneCards database. And 40 drug targets about AZM were retrieved from the STITCH database. The analysis revealed that 311 DEGs were common among COPD, IPF, and COVID-19, and we further found eight genes that interacted with AZM targets. We conducted an analysis of hub genes and their corresponding signaling pathways in these patient cohorts. Additionally, we explored the inhibitory effects of AZM on these hub genes. AZM demonstrated a significant inhibitory effect on eight key genes, except for AR and IL-17 A. These findings suggest that AZM may serve as a promising therapeutic agent for patients with COPD and IPF and SARS-CoV-2 infection.
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issn 2045-2322
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spelling doaj-art-eea23942d00a43b793781af5027d21622025-08-20T02:17:05ZengNature PortfolioScientific Reports2045-23222025-03-0115111310.1038/s41598-025-94801-9A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPDYining Xie0Guangshu Chen1Weiling Wu2Xueman Wen3Meizheng Lai4Li Che5Jianmin Ran6Department of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Jinan UniversityDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan UniversityAbstract The swift transmission rate and unfavorable prognosis associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have prompted the pursuit of more effective therapeutic interventions. Azithromycin (AZM) has garnered significant attention for its distinctive pharmacological mechanisms in the treatment of SARS-CoV-2. This study aims to elucidate the biological rationale for employing AZM in patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) who are infected with SARS-CoV-2. Genetic data about COVID-19, COPD, and IPF were independently obtained from the GeneCards database. And 40 drug targets about AZM were retrieved from the STITCH database. The analysis revealed that 311 DEGs were common among COPD, IPF, and COVID-19, and we further found eight genes that interacted with AZM targets. We conducted an analysis of hub genes and their corresponding signaling pathways in these patient cohorts. Additionally, we explored the inhibitory effects of AZM on these hub genes. AZM demonstrated a significant inhibitory effect on eight key genes, except for AR and IL-17 A. These findings suggest that AZM may serve as a promising therapeutic agent for patients with COPD and IPF and SARS-CoV-2 infection.https://doi.org/10.1038/s41598-025-94801-9COPDIPFSARS-Cov-2AzithromycinBioinformatics
spellingShingle Yining Xie
Guangshu Chen
Weiling Wu
Xueman Wen
Meizheng Lai
Li Che
Jianmin Ran
A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
Scientific Reports
COPD
IPF
SARS-Cov-2
Azithromycin
Bioinformatics
title A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
title_full A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
title_fullStr A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
title_full_unstemmed A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
title_short A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD
title_sort bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating sars cov 2 infection in patients with ipf and copd
topic COPD
IPF
SARS-Cov-2
Azithromycin
Bioinformatics
url https://doi.org/10.1038/s41598-025-94801-9
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