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Transcriptome analysis of controlled and therapy-resistant childhood asthma reveals distinct gene expression profiles

Persson, Helena LU ; Kwon, Andrew T; Ramilowski, Jordan A; Silberberg, Gilad; Söderhäll, Cilla; Orsmark-Pietras, Christina LU ; Nordlund, Björn; Konradsen, Jon R; de Hoon, Michiel J L and Melén, Erik, et al. (2015) In Journal of Allergy and Clinical Immunology 136(3). p.48-638
Abstract

BACKGROUND: Children with problematic severe asthma have poor disease control despite high doses of inhaled corticosteroids and additional therapy, leading to personal suffering, early deterioration of lung function, and significant consumption of health care resources. If no exacerbating factors, such as smoking or allergies, are found after extensive investigation, these children are given a diagnosis of therapy-resistant (or therapy-refractory) asthma (SA).

OBJECTIVE: We sought to deepen our understanding of childhood SA by analyzing gene expression and modeling the underlying regulatory transcription factor networks in peripheral blood leukocytes.

METHODS: Gene expression was analyzed by using Cap Analysis of Gene... (More)

BACKGROUND: Children with problematic severe asthma have poor disease control despite high doses of inhaled corticosteroids and additional therapy, leading to personal suffering, early deterioration of lung function, and significant consumption of health care resources. If no exacerbating factors, such as smoking or allergies, are found after extensive investigation, these children are given a diagnosis of therapy-resistant (or therapy-refractory) asthma (SA).

OBJECTIVE: We sought to deepen our understanding of childhood SA by analyzing gene expression and modeling the underlying regulatory transcription factor networks in peripheral blood leukocytes.

METHODS: Gene expression was analyzed by using Cap Analysis of Gene Expression in children with SA (n = 13), children with controlled persistent asthma (n = 15), and age-matched healthy control subjects (n = 9). Cap Analysis of Gene Expression sequencing detects the transcription start sites of known and novel mRNAs and noncoding RNAs.

RESULTS: Sample groups could be separated by hierarchical clustering on 1305 differentially expressed transcription start sites, including 816 known genes and several novel transcripts. Ten of 13 tested novel transcripts were validated by means of RT-PCR and Sanger sequencing. Expression of RAR-related orphan receptor A (RORA), which has been linked to asthma in genome-wide association studies, was significantly upregulated in patients with SA. Gene network modeling revealed decreased glucocorticoid receptor signaling and increased activity of the mitogen-activated protein kinase and Jun kinase cascades in patients with SA.

CONCLUSION: Circulating leukocytes from children with controlled asthma and those with SA have distinct gene expression profiles, demonstrating the possible development of specific molecular biomarkers and supporting the need for novel therapeutic approaches.

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@article{ea3c65b8-3a9f-4449-af90-d593667a59b8,
  abstract     = {<p>BACKGROUND: Children with problematic severe asthma have poor disease control despite high doses of inhaled corticosteroids and additional therapy, leading to personal suffering, early deterioration of lung function, and significant consumption of health care resources. If no exacerbating factors, such as smoking or allergies, are found after extensive investigation, these children are given a diagnosis of therapy-resistant (or therapy-refractory) asthma (SA).</p><p>OBJECTIVE: We sought to deepen our understanding of childhood SA by analyzing gene expression and modeling the underlying regulatory transcription factor networks in peripheral blood leukocytes.</p><p>METHODS: Gene expression was analyzed by using Cap Analysis of Gene Expression in children with SA (n = 13), children with controlled persistent asthma (n = 15), and age-matched healthy control subjects (n = 9). Cap Analysis of Gene Expression sequencing detects the transcription start sites of known and novel mRNAs and noncoding RNAs.</p><p>RESULTS: Sample groups could be separated by hierarchical clustering on 1305 differentially expressed transcription start sites, including 816 known genes and several novel transcripts. Ten of 13 tested novel transcripts were validated by means of RT-PCR and Sanger sequencing. Expression of RAR-related orphan receptor A (RORA), which has been linked to asthma in genome-wide association studies, was significantly upregulated in patients with SA. Gene network modeling revealed decreased glucocorticoid receptor signaling and increased activity of the mitogen-activated protein kinase and Jun kinase cascades in patients with SA.</p><p>CONCLUSION: Circulating leukocytes from children with controlled asthma and those with SA have distinct gene expression profiles, demonstrating the possible development of specific molecular biomarkers and supporting the need for novel therapeutic approaches.</p>},
  author       = {Persson, Helena and Kwon, Andrew T and Ramilowski, Jordan A and Silberberg, Gilad and Söderhäll, Cilla and Orsmark-Pietras, Christina and Nordlund, Björn and Konradsen, Jon R and de Hoon, Michiel J L and Melén, Erik and Hayashizaki, Yoshihide and Hedlin, Gunilla and Kere, Juha and Daub, Carsten O},
  issn         = {1097-6825},
  keyword      = {Adolescent,Asthma,Case-Control Studies,Child,Child, Preschool,Drug Resistance,Female,Gene Expression Profiling,Genome-Wide Association Study,Glucocorticoids,Humans,JNK Mitogen-Activated Protein Kinases,Male,Nuclear Receptor Subfamily 1, Group F, Member 1,RNA, Messenger,Receptors, Glucocorticoid,Severity of Illness Index,Transcriptome},
  language     = {eng},
  number       = {3},
  pages        = {48--638},
  publisher    = {Elsevier},
  series       = {Journal of Allergy and Clinical Immunology},
  title        = {Transcriptome analysis of controlled and therapy-resistant childhood asthma reveals distinct gene expression profiles},
  url          = {http://dx.doi.org/10.1016/j.jaci.2015.02.026},
  volume       = {136},
  year         = {2015},
}