Evidence map›Paper›PMID 42046063›Full record

ArticleRespiratory research2026

Unsupervised comprehensive CT imaging clusters reveal distinct morphological phenotypes in asthma: insights from two prospective cohorts.

Yusuke Hayashi, Naoya Tanabe, Atsuyasu Sato, Tsunahiko Hirano, Hiroshi Iwamoto, Tomoki Maetani, Yusuke Shiraishi, Ryo Sakamoto, Hironobu Sunadome, Ayumi Fukatsu-Chikumoto and 11 more

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Article in Respiratory research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

21 authors.

Yusuke HayashiDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Naoya TanabeDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan. ntana@kuhp.kyoto-u.ac.jp.
Atsuyasu SatoDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Tsunahiko HiranoDepartment of Respiratory Medicine and Infectious Disease, Graduate School of Medicine, Yamaguchi University, Ube, Japan.
Hiroshi IwamotoDepartment of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Tomoki MaetaniDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yusuke ShiraishiDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Ryo SakamotoDepartment of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Hironobu SunadomeDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Ayumi Fukatsu-ChikumotoDepartment of Respiratory Medicine and Infectious Disease, Graduate School of Medicine, Yamaguchi University, Ube, Japan.
Toshihito OtaniDepartment of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Naoko HigakiDepartment of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Yoshihiro AmanoDepartment of Internal Medicine, Division of Medical Oncology and Respiratory Medicine, Shimane University Faculty of Medicine, Izumo, Japan.
Tamio OkimotoDepartment of Internal Medicine, Division of Medical Oncology and Respiratory Medicine, Shimane University Faculty of Medicine, Izumo, Japan.
Mayuka YamaneDepartment of Respiratory Medicine and Allergology, Kochi Medical School, Kochi University, Nankoku, Japan.
Akihito YokoyamaDepartment of Respiratory Medicine and Allergology, Kochi Medical School, Kochi University, Nankoku, Japan.
Hiroshi DateDepartment of Thoracic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Susumu SatoDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Noboru HattoriDepartment of Molecular and Internal Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Kazuto MatsunagaDepartment of Respiratory Medicine and Infectious Disease, Graduate School of Medicine, Yamaguchi University, Ube, Japan.
Toyohiro HiraiDepartment of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Funding

Japan Society for the Promotion of Science 22K08233
6 · The paper itself

Abstract

backgroundAsthma is a heterogeneous disease with diverse underlying structural abnormalities. Comprehensive evaluation of computed tomography (CT)-derived features may uncover novel morphological phenotypes with clinical relevance. This study aimed to identify and validate the morphological phenotypes of asthma using comprehensive inspiratory and expiratory CT features and assess their associations with clinical outcomes.

methodsWe analyzed two independent prospective asthma cohorts (Kyoto asthma cohort, n = 223; PACTAS study, n = 94) and a cross-sectional healthy control cohort (n = 88). Quantitative CT measures—airway morphology, mucus plugs, parenchyma, extrapulmonary structures, and pulmonary arteries—were quantified. Unsupervised clustering using these parameters was performed separately in each asthma cohort. Associations with lung function, type 2 inflammation, symptom burden, and exacerbations were examined.

resultsFour reproducible morphological phenotypes were identified. Cluster 1 (airway remodeling) was characterized by reduced airway lumen area (LA), and lower total airway count (TAC), along with higher mucus plug scores and elevated small airway dysfunction (SAD%) measured from inspiratory and expiratory lung density. Patients were older, had a longer asthma duration, and exhibited a lower forced expiratory volume in 1 s to forced vital capacity ratio (FEV₁/FVC). Cluster 2 (airway dilatation) showed enlarged LA, higher modified Reiff scores, and increased TAC. Patients tended to be younger, with a shorter disease duration and preserved lung function. Cluster 3 (metabolic abnormality) was characterized by reduced pectoralis muscle density and higher body mass index, and included predominantly female patients. This cluster was associated with a lower %FVC and greater symptom burden. Cluster 4 (parenchymal-dominant) consisted mainly of male smokers with emphysematous changes and higher SAD%, who exhibited lower FEV₁/FVC. Across both cohorts, Clusters 2–4 had exacerbation rates similar to or higher than in Cluster 1 in both unadjusted and adjusted analyses.

conclusionsComprehensive CT-based clustering revealed four reproducible morphological phenotypes of asthma—airway remodeling, airway dilatation, metabolic abnormality, and parenchymal-dominant—each associated with distinct structural and clinical features. These findings underscore the morphological heterogeneity of asthma and suggest that CT-based phenotyping may support more precise phenotype-specific treatment strategies.

Indexed as

AsthmaLungTomography, X-Ray ComputedAdultAirway RemodelingCluster AnalysisClustering AlgorithmsCohort StudiesCross-Sectional StudiesFemaleHumansMaleMiddle AgedPhenotypeProspective StudiesAirway dilatationAirway remodelingAsthmaCluster analysisComputed tomographyImagingPhenotype

Identifiers

PMID42046063
PMCPMC13289446

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