Evidence map›Paper›PMID 40584937›Full record

ArticleJournal of asthma and allergy2025

Induced Sputum Transcriptomics Profile and Serum C3 are Associated with Asthma Severity.

Fawang Du, Hanchao Wang, Zhihong Chen, Wei Xiong, Qin Wang, Bo Li, Rong Li, Li Li, Yongchun Shen, Tao Zhu

Abstract read
In one paragraph

Article in Journal of asthma and allergy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Fawang Du *Department of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.
Hanchao Wang *GK Health and Medical Big Data Research Center of Suining, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.ORCID 0000-0001-8931-6703
Zhihong Chen *Department of Respiratory Medicine and Critical Care Medicine, Zhongshan Hospital of Fudan University, and Shanghai Institute of Respiratory Disease, Shanghai, 20032, People's Republic of China.
Wei XiongDepartment of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.ORCID 0000-0001-7462-1342
Qin WangDepartment of Respiratory Medicine and Critical Care Medicine, Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, People's Republic of China.
Bo LiDepartment of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.
Rong LiDepartment of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.
Li LiDepartment of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.
Yongchun ShenDepartment of Respiratory Medicine and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, 610041, People's Republic of China.ORCID 0000-0002-8142-1792
Tao ZhuDepartment of Respiratory Medicine and Critical Care Medicine, Suining Central Hospital, Suining, Sichuan, 629000, People's Republic of China.ORCID 0000-0001-9622-2721

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rational: Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcriptomics profile and promising biomarkers for asthma severity prediction. Methods: In discovery cohort, induced sputum cells from 3 non-severe and 3 severe asthma patients were collected and analyzed using RNA-seq. Multivariate analysis was performed to explore asthma severity-associated transcriptomics profile and differential expressed genes (DEGs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used for pathway enrichment analysis. Subsequently, based on the previous study and clinical experience, the mRNA expressions of 6 overlapped asthma severity-associated DEGs and Results: Distinct asthma severity-associated transcriptomics profile was identified in induced sputum cells in discovery cohort. Then, 345 DEGs were found, of which 38 terms and 32 pathways were enriched using GO and KEGG, respectively. In validation cohort, the mRNA expressions of Conclusion: Collectively, this study provides the first identification of the association between induced sputum cells transcriptomics profile and asthma severity, indicating the potential value of transcriptomics for asthma management. The study also reveals the promising value of serum C3 for predicting asthma severity in clinical practice.

Indexed as

ACT scoresasthma severityFeNOinduced sputumRNA-seqserum C3

Identifiers

PMID40584937
PMCPMC12205761

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.