Blood transcriptome differentiates clinical clusters for asthma

Jin An, MD, PhD; Seungpil Jeong, PhD; Kyungtaek Park, PhD; Heejin Jin, PhD; Jaehyun Park, PhD; Eunsoon Shin, PhD; Ji-Hyang Lee, MD, PhD; Woo-Jung Song, MD, PhD; Hyouk-Soo Kwon, MD, PhD; You Sook Cho, MD, PhD; Jong Eun Lee, PhD; Sungho Won, PhD; Tae-Bum Kim, MD, PhD

World Allergy Organization Journal (Feb 2024)

Blood transcriptome differentiates clinical clusters for asthma

Jin An, MD, PhD,
Seungpil Jeong, PhD,
Kyungtaek Park, PhD,
Heejin Jin, PhD,
Jaehyun Park, PhD,
Eunsoon Shin, PhD,
Ji-Hyang Lee, MD, PhD,
Woo-Jung Song, MD, PhD,
Hyouk-Soo Kwon, MD, PhD,
You Sook Cho, MD, PhD,
Jong Eun Lee, PhD,
Sungho Won, PhD,
Tae-Bum Kim, MD, PhD

Affiliations

Jin An, MD, PhD: Department of Pulmonary, Allergy and Critical Care Medicine, College of Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea
Seungpil Jeong, PhD: Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea
Kyungtaek Park, PhD: Institute of Health and Environment, Seoul National University, Seoul, South Korea
Heejin Jin, PhD: Institute of Health and Environment, Seoul National University, Seoul, South Korea
Jaehyun Park, PhD: Interdisciplinary Program of Bioinformatics, Seoul National University, Seoul, South Korea
Eunsoon Shin, PhD: DNA Link, Seoul, South Korea
Ji-Hyang Lee, MD, PhD: Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
Woo-Jung Song, MD, PhD: Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
Hyouk-Soo Kwon, MD, PhD: Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
You Sook Cho, MD, PhD: Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea
Jong Eun Lee, PhD: DNA Link, Seoul, South Korea
Sungho Won, PhD: Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea; Institute of Health and Environment, Seoul National University, Seoul, South Korea; Interdisciplinary Program of Bioinformatics, College of Natural Science, Seoul National University, Seoul, South Korea; Corresponding author. Department of Public Health Sciences, Seoul National University, Kwanak-ro 1, Kwanak-gu, Seoul 151-742, South Korea.
Tae-Bum Kim, MD, PhD: Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea; Corresponding author. Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, 86 Asanbyeongwon-gil, Songpa-gu, Seoul 138-736, South Korea.

Journal volume & issue: Vol. 17, no. 2
p. 100871

Abstract

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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.

Published in World Allergy Organization Journal

ISSN: 1939-4551 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Internal medicine: Specialties of internal medicine: Immunologic diseases. Allergy
Website: https://www.sciencedirect.com/journal/world-allergy-organization-journal

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