Identification of asthma clusters in two independent Korean adult asthma cohorts

Tae Bum Kim; An Soo Jang; Hyouk Soo Kwon; Jong Sook Park; Yoon Seok Chang; Sang Heon Cho; Byoung Whui Choi; Jung Won Park; Dong Ho Nam; Ho Joo Yoon; Young Joo Cho; Hee Bom Moon; You Sook Cho; Choon Sik Park

doi:10.1183/09031936.00100811

Identification of asthma clusters in two independent Korean adult asthma cohorts

Tae Bum Kim, An Soo Jang, Hyouk Soo Kwon, Jong Sook Park, Yoon Seok Chang, Sang Heon Cho, Byoung Whui Choi, Jung Won Park, Dong Ho Nam, Ho Joo Yoon, Young Joo Cho, Hee Bom Moon, You Sook Cho, Choon Sik Park

Department of Internal Medicine

Research output: Contribution to journal › Article › peer-review

115 Scopus citations

Abstract

Asthma is a heterogeneous airway disease with various clinical phenotypes. It is crucial to clearly identify clinical phenotypes to achieve better asthma management. We used cluster analysis to classify the clinical groups of 724 asthmatic patients from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), and in 1843 subjects from another independent Korean asthma cohort of Soonchunhyang University Asthma Genome Research Centre (SCH) (Bucheon, Republic of Korea). Hierarchical cluster analysis was performed by Ward's method, followed by k-means cluster analysis. Cluster analysis of the COREA cohort indicated four asthma subtypes: 1) smoking asthma; 2) severe obstructive asthma; 3) early-onset atopic asthma; and 4) late-onset mild asthma. An independent cluster analysis of the SCH cohort also indicated four clusters that were similar to the COREA clusters. Our results indicate that adult Korean asthma patients can be classified into four distinct clusters. Copyright

Original language	English
Pages (from-to)	1308-1314
Number of pages	7
Journal	European Respiratory Journal
Volume	41
Issue number	6
DOIs	https://doi.org/10.1183/09031936.00100811
State	Published - 1 Jun 2013

Keywords

Asthma
Classification
Cluster analysis
Phenotype

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10.1183/09031936.00100811

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title = "Identification of asthma clusters in two independent Korean adult asthma cohorts",

abstract = "Asthma is a heterogeneous airway disease with various clinical phenotypes. It is crucial to clearly identify clinical phenotypes to achieve better asthma management. We used cluster analysis to classify the clinical groups of 724 asthmatic patients from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), and in 1843 subjects from another independent Korean asthma cohort of Soonchunhyang University Asthma Genome Research Centre (SCH) (Bucheon, Republic of Korea). Hierarchical cluster analysis was performed by Ward's method, followed by k-means cluster analysis. Cluster analysis of the COREA cohort indicated four asthma subtypes: 1) smoking asthma; 2) severe obstructive asthma; 3) early-onset atopic asthma; and 4) late-onset mild asthma. An independent cluster analysis of the SCH cohort also indicated four clusters that were similar to the COREA clusters. Our results indicate that adult Korean asthma patients can be classified into four distinct clusters. Copyright",

keywords = "Asthma, Classification, Cluster analysis, Phenotype",

author = "Kim, {Tae Bum} and Jang, {An Soo} and Kwon, {Hyouk Soo} and Park, {Jong Sook} and Chang, {Yoon Seok} and Cho, {Sang Heon} and Choi, {Byoung Whui} and Park, {Jung Won} and Nam, {Dong Ho} and Yoon, {Ho Joo} and Cho, {Young Joo} and Moon, {Hee Bom} and Cho, {You Sook} and Park, {Choon Sik}",

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T1 - Identification of asthma clusters in two independent Korean adult asthma cohorts

AU - Kim, Tae Bum

AU - Jang, An Soo

AU - Kwon, Hyouk Soo

AU - Park, Jong Sook

AU - Chang, Yoon Seok

AU - Cho, Sang Heon

AU - Choi, Byoung Whui

AU - Park, Jung Won

AU - Nam, Dong Ho

AU - Yoon, Ho Joo

AU - Cho, Young Joo

AU - Moon, Hee Bom

AU - Cho, You Sook

AU - Park, Choon Sik

PY - 2013/6/1

Y1 - 2013/6/1

N2 - Asthma is a heterogeneous airway disease with various clinical phenotypes. It is crucial to clearly identify clinical phenotypes to achieve better asthma management. We used cluster analysis to classify the clinical groups of 724 asthmatic patients from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), and in 1843 subjects from another independent Korean asthma cohort of Soonchunhyang University Asthma Genome Research Centre (SCH) (Bucheon, Republic of Korea). Hierarchical cluster analysis was performed by Ward's method, followed by k-means cluster analysis. Cluster analysis of the COREA cohort indicated four asthma subtypes: 1) smoking asthma; 2) severe obstructive asthma; 3) early-onset atopic asthma; and 4) late-onset mild asthma. An independent cluster analysis of the SCH cohort also indicated four clusters that were similar to the COREA clusters. Our results indicate that adult Korean asthma patients can be classified into four distinct clusters. Copyright

AB - Asthma is a heterogeneous airway disease with various clinical phenotypes. It is crucial to clearly identify clinical phenotypes to achieve better asthma management. We used cluster analysis to classify the clinical groups of 724 asthmatic patients from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), and in 1843 subjects from another independent Korean asthma cohort of Soonchunhyang University Asthma Genome Research Centre (SCH) (Bucheon, Republic of Korea). Hierarchical cluster analysis was performed by Ward's method, followed by k-means cluster analysis. Cluster analysis of the COREA cohort indicated four asthma subtypes: 1) smoking asthma; 2) severe obstructive asthma; 3) early-onset atopic asthma; and 4) late-onset mild asthma. An independent cluster analysis of the SCH cohort also indicated four clusters that were similar to the COREA clusters. Our results indicate that adult Korean asthma patients can be classified into four distinct clusters. Copyright

KW - Asthma

KW - Classification

KW - Cluster analysis

KW - Phenotype

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JO - European Respiratory Journal

JF - European Respiratory Journal

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Identification of asthma clusters in two independent Korean adult asthma cohorts

Abstract

Keywords

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