Evidence map›Paper›PMID 40122903›Full record

ArticleScientific reports2025

A bioinformatics approach combined with experimental validation analyzes the efficacy of azithromycin in treating SARS-CoV-2 infection in patients with IPF and COPD These authors contributed equally: Yining Xie, Guangshu Chen, and Weiling Wu.

Yining Xie, Guangshu Chen, Weiling Wu, Xueman Wen, Meizheng Lai, Li Che, Jianmin Ran

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yining Xie *Department of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China.
Guangshu Chen *Department of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China.
Weiling Wu *Department of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China.
Xueman WenDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China.
Meizheng LaiDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China.
Li CheDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China. Cherry20170908@sina.com.
Jianmin RanDepartment of Endocrinology and Metabolism, Guangzhou Red Cross Hospital, Jinan University, Guangzhou, 510220, China. ran_jianmin@ext.jnu.edu.cn.

Funding

Zhongnanshan Medical Foundation of Guangdong Province ZNSJJH-XS-[2022]-[06]-[004]
6 · The paper itself

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.

Indexed as

AzithromycinComputational BiologyCOVID-19 Drug TreatmentIdiopathic Pulmonary FibrosisPulmonary Disease, Chronic ObstructiveCOVID-19HumansSARS-CoV-2AzithromycinAzithromycinBioinformaticsCOPDIPFSARS-Cov-2

Identifiers

PMID40122903
PMCPMC11930991

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.