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Different biological pathways are up-regulated in the elderly with asthma: Sputum transcriptomic analysis

  • Byung Keun Kim
  • , Hyun Seung Lee
  • , Kyoung Hee Sohn
  • , Suh young Lee
  • , Sang Heon Cho
  • , Heung Woo Park

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Background: Elderly asthma (EA) is increasing, but the pathogenesis is unclear. This study aimed to identify EA-related biological pathways by analyzing genome-wide gene expression profiles in sputum cells. Methods: A total of 3,156 gene probes with significantly differential expressions between EA and healthy elderly controls were used for a hierarchical clustering of genes to identify gene clusters. Gene set enrichment analysis provided biological information, with replication from Gene Expression Omnibus expression profiles. Results: Fifty-five EA patients and 10 elderly control subjects were enrolled. Two distinct gene clusters were found. Cluster 1 (n = 35) showed a lower eosinophil proportion in sputum and less severe airway obstruction compared to cluster 2 (n = 20). The replication data set also identified 2 gene clusters (clusters 1' and 2'). Among 5 gene sets significantly enriched in cluster 1 and 3 gene sets significantly enriched in cluster 2, we confirmed that 2 were significantly enriched in the replication data set (OXIDATIVE_PHOSPHORYLATION gene set in cluster 1 and EPITHELIAL MESENCHYMAL TRANSITION gene set in cluster 2'). Conclusions: The findings of 2 distinct gene clusters in EA and different biological pathways in each gene cluster suggest 2 different pathogenesis mechanisms underlying EA.

Original languageEnglish
Pages (from-to)104-115
Number of pages12
JournalAllergy, Asthma and Immunology Research
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

Bibliographical note

Publisher Copyright:
Copyright © 2019 The Korean Academy of Asthma, Allergy and Clinical Immunology • The Korean Academy of Pediatric Allergy and Respiratory Disease.

Keywords

  • Asthma
  • Cluster analysis
  • Elderly
  • Gene expression

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