Evidence map›Paper›PMID 38317769›Full record

ArticleThe World Allergy Organization journal2024

Blood transcriptome differentiates clinical clusters for asthma.

Jin An, Seungpil Jeong, Kyungtaek Park, Heejin Jin, Jaehyun Park, Eunsoon Shin, Ji-Hyang Lee, Woo-Jung Song, Hyouk-Soo Kwon, You Sook Cho and 3 more

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Article in The World Allergy Organization journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Distinct blood transcriptomic profiling underlying asthma establishment and exacerbation.The journal of allergy and clinical immunology. Global · 2026
    Article
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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Jin AnDepartment of Pulmonary, Allergy and Critical Care Medicine, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea.
Seungpil JeongDepartment of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea.
Kyungtaek ParkInstitute of Health and Environment, Seoul National University, Seoul, South Korea.
Heejin JinInstitute of Health and Environment, Seoul National University, Seoul, South Korea.
Jaehyun ParkInterdisciplinary Program of Bioinformatics, Seoul National University, Seoul, South Korea.
Eunsoon ShinDNA Link, Seoul, South Korea.
Ji-Hyang LeeDepartment of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Woo-Jung SongDepartment of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Hyouk-Soo KwonDepartment of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
You Sook ChoDepartment of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Jong Eun LeeDNA Link, Seoul, South Korea.
Sungho WonDepartment of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea.
Tae-Bum KimDepartment of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In previous studies, several asthma phenotypes were identified using clinical and demographic parameters. Transcriptional phenotypes were mainly identified using sputum and bronchial cells. Objective: We aimed to investigate asthma phenotypes via clustering analysis using clinical variables and compare the transcription levels among clusters using gene expression profiling of the blood. Methods: Clustering analysis was performed using 6 parameters: age of asthma onset, body mass index, pack-years of smoking, forced expiratory volume in 1 s (FEV1), FEV1/forced vital capacity, and blood eosinophil counts. Peripheral blood mononuclear cells (PBMCs) were isolated from whole blood samples and RNA was extracted from selected PBMCs. Transcriptional profiles were generated (Illumina NovaSeq 6000) and analyzed using the reference genome and gene annotation files (hg19.refGene.gft). Pathway enrichment analysis was conducted using GO, KEGG, and REACTOME databases. Results: In total, 355 patients with asthma were included in the analysis, of whom 72 (20.3%) had severe asthma. Clustering of the 6 parameters revealed 4 distinct subtypes. Cluster 1 (n = 63) had lower predicted FEV1 % and higher pack-years of smoking and neutrophils in sputum. Cluster 2 (n = 43) had a higher proportion and number of eosinophils in sputum and blood, and severe airflow limitation. Cluster 3 (n = 110) consisted of younger subjects with atopic features. Cluster 4 (n = 139) included features of late-onset mild asthma. Differentially expressed genes between clusters 1 and 2 were related to inflammatory responses and cell activation. Th17 cell differentiation and interferon gamma-mediated signaling pathways were related to neutrophilic inflammation in asthma. Conclusion: Four clinical clusters were differentiated based on clinical parameters and blood eosinophils in adult patients with asthma form the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA) cohort. Gene expression profiling and molecular pathways are novel means of classifying asthma phenotypes.

Indexed as

AsthmaClusterPathwayTranscriptome

Identifiers

PMID38317769
PMCPMC10839776

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