Evidence map›Paper›PMID 40859318›Full record

ArticleJournal of translational medicine2025

Airway microbiota and immunity associated with chronic obstructive pulmonary disease severity.

Zhiwei Lin, Yueting Jiang, Huifang Liu, Juhua Yang, Bin Yang, Ke Zhang, Peiren Tang, Bo Xiang, Baoqing Sun

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Zhiwei Lin *Department of Clinical Laboratory of the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China.
Yueting Jiang *Department of Clinical Laboratory of the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China.
Huifang Liu *Vision Medicals Co., Ltd., Guangzhou, 510000, China.
Juhua YangVision Medicals Co., Ltd., Guangzhou, 510000, China.
Bin YangVision Medicals Co., Ltd., Guangzhou, 510000, China.
Ke ZhangRespiratory Mechanics Laboratory, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China.
Peiren TangRespiratory Mechanics Laboratory, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China.
Bo XiangDepartment of Clinical Laboratory of the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China. djxb11@126.com.
Baoqing SunDepartment of Clinical Laboratory of the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China. sunbaoqing@vip.163.com.ORCID 0000-0002-1671-0723

Funding

Guangdong Provincial Key Laboratory of Prevention and Control for Severe Clinical Animal Diseases 2023B110008Major clinical research project of Guangzhou Medical University GMUCR2024-02009
6 · The paper itself

Abstract

backgroundChronic Obstructive Pulmonary Disease (COPD) is characterized by progressive airflow limitation and chronic inflammation. Although airway microbes and host immunity are known contributors, the molecular mechanisms underlying disease severity remain unclear. This study explores microbial dysbiosis and host immune responses across varying COPD severities.

methodsWe conducted integrated metagenomic and transcriptomic analyses on bronchoalveolar lavage fluid from two cohorts: a discovery cohort and a validation cohort. We investigated microbial diversity, pathogenic bacterial enrichment, and host gene expression patterns. Functional metagenomics was used to assess antibiotic resistance genes. Host-microbe network analyses explored correlations between pathogens and immune-metabolic pathways. Diagnostic models utilizing microbial-immune biomarkers were developed, trained on a subset of the discovery cohort, tested on remaining discovery samples, and validated by quantitative polymerase chain reaction (qPCR) in the validation cohort to distinguish COPD from controls and stratify disease severity.

resultsSevere COPD exhibited reduced microbial diversity and an increased presence of pathogenic bacteria, including Moraxella osloensis and Streptococcus species. These pathogens were associated with dysregulated inflammatory signaling, and significant neutrophil activity, evidenced by the formation of Neutrophil Extracellular Traps (NETs), and oxidative stress, which correlated with airway remodeling and a decline in lung function. Functional metagenomics showed a significant increase in antibiotic resistance genes in severe cases, linked to chronic treatment pressures. Host-microbe network analyses revealed strong correlations between these pathogens and disrupted immune-metabolic pathways, such as altered energy metabolism and inflammatory cascades, consistent across both cohorts. Diagnostic models based on microbial-immune biomarkers demonstrated high accuracy in differentiating COPD patients from controls and in stratifying disease severity.

conclusionsThis study identifies microbial and immune signatures associated with COPD severity, providing mechanistic insights into its pathophysiology. The findings may inform precision medicine strategies by targeting airway dysbiosis and immune dysregulation. While causal relationships could not be established in this cross-sectional study, the findings provide a foundation for future mechanistic investigations using advanced in vitro and in vivo models.

Indexed as

ImmunityMicrobiotaPulmonary Disease, Chronic ObstructiveRespiratory SystemSeverity of Illness IndexAgedBacteriaBiomarkersBronchoalveolar Lavage FluidCohort StudiesDysbiosisFemaleHumansMaleMetagenomicsMiddle AgedBiomarkersChronic obstructiveDysbiosisImmune systemMetagenomicsOxidative stressPrecision medicinePulmonary diseaseTranscriptome

Identifiers

PMID40859318
PMCPMC12382185

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.