Evidence map›Paper›PMID 42130017›Full record

ArticleAllergy2026

Metabolite-Based Endotypes of Asthma Reveal Distinct Clinical Characteristics and Immune Cell Signatures.

Young Jin Pyung, Noeul Kang, Jihyun Chun, Keesun Yu, Da-Jeong Park, Do Yup Lee, Deog Kyeom Kim, Hyun Woo Lee, Cheol-Heui Yun

Abstract read
In one paragraph

Article in Allergy, 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
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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

9 authors.

Young Jin PyungDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.ORCID https://orcid.org/0000-0001-8313-8475
Noeul KangDivision of Allergy, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.ORCID https://orcid.org/0000-0003-0925-3891
Jihyun ChunDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.ORCID https://orcid.org/0009-0000-3788-3677
Keesun YuDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Da-Jeong ParkDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Do Yup LeeDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Deog Kyeom KimDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, South Korea.
Hyun Woo LeeDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, South Korea.ORCID https://orcid.org/0000-0003-4379-0260
Cheol-Heui YunDepartment of Agricultural Biotechnology, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.ORCID https://orcid.org/0000-0002-0041-2887

Funding

BK21 FOUR Program of the Department of Agricultural Biotechnology, Seoul National UniversityMinistry of Health & Welfare, Republic of Korea RS-2024-00507606Ministry of Science and ICT, South Korea RS-2023-00218476Ministry of Science and ICT, South Korea RS-2024-00454619Seoul National University 0525-20240127
6 · The paper itself

Abstract

backgroundAsthma control is commonly defined by symptom burden and recent exacerbation history. However, symptom-based clinical stability does not necessarily reflect biological quiescence, and heterogeneity in lung function and airway structure may persist despite apparent clinical control. This study aimed to determine whether blood-based metabolomic profiling can discriminate biologically distinct subgroups within a clinically stable asthma population.

methodsWe conducted a prospective observational study of adults with clinically stable asthma, defined by sustained symptom control and absence of recent exacerbations under maintenance inhaled corticosteroid-based therapy. Untargeted plasma metabolomic profiling was performed using liquid chromatography-tandem mass spectrometry, and metabolite-derived subgroups were identified by consensus clustering. Lung function, airway structure, small-airway physiology, and peripheral immune cell profiles were compared across clusters, with associations assessed using regression analyses.

resultsThree metabolite-derived subgroups were identified based on patterns in the relative abundance of selected representative metabolites. Symptom control and exacerbation history were comparable across clusters, whereas lung function, airway wall thickness, small-airway physiology, and immune cell profiles differed substantially. Cluster 1 (C1; Remodeling-prone), characterized by greater relative abundance of glycerophospholipid-related metabolites, showed lower post-bronchodilator FEV

conclusionsMetabolomic profiling reveals biologically distinct subgroups among clinically stable asthma, indicating that symptom-based stability does not necessarily reflect biological homogeneity.

Indexed as

AsthmaMetabolomeMetabolomicsAdultBiomarkersFemaleHumansMaleMiddle AgedPhenotypeProspective StudiesRespiratory Function TestsBiomarkersairway remodelingasthmacluster analysisinnate lymphoid cellsmetabolomics

Identifiers

PMID42130017
PMCPMC13569713

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.