Evidence map›Paper›PMID 42180681›Full record

ArticleFrontiers in medicine2026

Zaixing Jia, Bin Liu, Jing Cao, Siqin Han, Shujie Hou, Zixiao Chen, Jialun Chen, Zhenwei Liu, Weihua Chen, Jingwen Li and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 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

12 authors.

Zaixing Jia *The First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Bin Liu *Central Laboratory, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Jing Cao *The First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Siqin HanThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Shujie HouThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Zixiao ChenThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Jialun ChenThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Zhenwei LiuThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Weihua ChenThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Jingwen LiThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Rongqin LiThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Xixin YanThe First Department of Pulmonary and Critical Care Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Asthma, a complex disease, is categorized into type 2 (T2) and non-type 2 (non-T2) molecular endotypes. Growing evidence supports the overlap between endotypes and highlights a complex interplay among multiple inflammatory cell types. Combined inflammatory disease is particularly challenging to treat. Building on the background of overlapping asthma endotypes, the goal of this research was to explore common gene signatures and the underlying molecular mechanisms across different asthma subtypes. Methods: Transcriptomics data of bronchial biopsy samples were sourced from the Gene Expression Omnibus (GEO) and intersected to identify common genes in T2 and non-T2 Asthma. Gene ontology, pathway enrichment, protein-protein interaction, immune infiltration, and single-cell analysis were used to explore the roles of these genes. Finally, common genes in T2 and non-T2 asthma mice models were verified by RT-qPCR. Results: Five upregulated common genes (MS4A2, TPSAB1, FCER1A, TFF3, TSPAN13) were identified. These genes showed good diagnostic accuracy for both T2 and non-T2 asthma. Gene Set Enrichment Analysis (GSEA) analyses revealed involvement of these genes in the immune and inflammatory response. Moreover, we found that both T2 and non-T2 asthma exhibit similar patterns of immune cell infiltration, such as mast cells, suggesting that mast cell activation can span different inflammatory phenotypes. Consistently, qRT-PCR analysis confirmed that the five genes were upregulated in both T2 and non-T2 asthma, aligning with the bioinformatic predictions. Conclusion: This study revealed common genes and similar immune cell infiltration microenvironments in both T2 and non-T2 asthma. These findings may provide new insights for future studies on molecular mechanisms.

Indexed as

asthmabioinformaticscommon genesnon-T2T2

Identifiers

PMID42180681
PMCPMC13195886

What OpenQuestion holds

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Registered trials

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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.