Evidence map›Paper›PMID 41879310›Full record

SynthesismSystems2026

The respiratory microbiome in pulmonary tuberculosis: a meta-analysis reveals niche-specific microbial and functional signatures.

Mingyang Qin, Yanhua Wen, Shanshan Li, Song Li, Xuming Li, Yuting Lin, Long Hu, Han Xia, Yu Pang, Liang Li

Abstract readMeta-Analysis
In one paragraph

Synthesis in mSystems, 2026. 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

10 authors.

Mingyang Qin *Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID 0000-0002-2010-905X
Yanhua Wen *Department of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.ORCID 0009-0002-6867-4602
Shanshan Li *Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID 0000-0003-4475-4536
Song Li *Department of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.
Xuming LiDepartment of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.ORCID 0000-0002-5049-9706
Yuting LinDepartment of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.
Long HuDepartment of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.
Han XiaDepartment of Scientific Affairs, Hugobiotech Co., Ltd., Beijing, China.ORCID 0000-0002-5179-0255
Yu PangBeijing Key Laboratory for Key Technologies in Tuberculosis Prevention and Control, Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China.ORCID 0000-0001-6803-9807
Liang LiDepartment of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.ORCID 0000-0001-5212-5890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) remains a major global health challenge. The close relationship between the microbiome and the host is becoming increasingly notable. While studies on the respiratory microbiome in pulmonary tuberculosis (PTB) exist, a comprehensive understanding of microbial characteristics across the entire respiratory tract is still lacking. To address this, we conducted a meta-analysis by integrating data from common and representative respiratory samples. We integrated 16S rRNA data from 11 public datasets encompassing upper respiratory tract specimens (URTs), sputum, and bronchoalveolar lavage fluid (BALF). Ecological patterns were investigated through co-occurrence networks and neutral community modeling, while taxonomic and functional analyses were conducted with QIIME2 and PICRUSt2. The respiratory microbiota in PTB exhibited dynamic variations while sharing common genera, such as IMPORTANCE: Pulmonary tuberculosis (PTB) remains a leading cause of global mortality, yet the ecological principles shaping its respiratory microbiome are poorly understood. By integrating 16S rRNA datasets from upper and lower airway specimens, this study provides the first comprehensive meta-analysis of respiratory microbial diversity and function in PTB. We reveal distinct community structures and functional potentials among upper airways, sputum, and bronchoalveolar lavage fluid, driven by niche-specific ecological processes rather than stochastic assembly. These findings establish a baseline framework for interpreting microbial biogeography across the respiratory tract and highlight potential microbial biomarkers for site-specific monitoring and therapeutic targeting in PTB.

Indexed as

BacteriaMicrobiotaRespiratory SystemTuberculosis, PulmonaryBronchoalveolar Lavage FluidHumansRNA, Ribosomal, 16SSputumRNA, Ribosomal, 16S16Smetamicrobiomerespiratory tracttuberculosis

Identifiers

PMID41879310
PMCPMC13098208

What Socratic holds

Textmetadata
LicenceCC BY
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.