Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control - 05/05/16
, Matthew Moll, MD b, Scott T. Weiss, MD c, d, e, Benjamin A. Raby, MD c, d, e, Wei Wu, PhD f, Eric P. Xing, PhD gAbstract |
Background |
Recent studies have used cluster analysis to identify phenotypic clusters of asthma with differences in clinical traits, as well as differences in response to therapy with anti-inflammatory medications. However, the correspondence between different phenotypic clusters and differences in the underlying molecular mechanisms of asthma pathogenesis remains unclear.
Objective |
We sought to determine whether clinical differences among children with asthma in different phenotypic clusters corresponded to differences in levels of gene expression.
Methods |
We explored differences in gene expression profiles of CD4+ lymphocytes isolated from the peripheral blood of 299 young adult participants in the Childhood Asthma Management Program study. We obtained gene expression profiles from study subjects between 9 and 14 years of age after they participated in a randomized, controlled longitudinal study examining the effects of inhaled anti-inflammatory medications over a 48-month study period, and we evaluated the correspondence between our earlier phenotypic cluster analysis and subsequent follow-up clinical and molecular profiles.
Results |
We found that differences in clinical characteristics observed between subjects assigned to different phenotypic clusters persisted into young adulthood and that these clinical differences were associated with differences in gene expression patterns between subjects in different clusters. We identified a subset of genes associated with atopic status, validated the presence of an atopic signature among these genes in an independent cohort of asthmatic subjects, and identified the presence of common transcription factor binding sites corresponding to glucocorticoid receptor binding.
Conclusion |
These findings suggest that phenotypic clusters are associated with differences in the underlying pathobiology of asthma. Further experiments are necessary to confirm these findings.
Le texte complet de cet article est disponible en PDF.Key words : Childhood asthma, asthma phenotypes, gene expression profiling, microarray analysis, longitudinal study
Abbreviations used : ADD3, CAMP, DE, FDR, GR, HDAC2, SLC33A1, SRM, TFBS
Plan
| Supported by grant R01 HL086601 from the National Heart, Lung, and Blood Institute/National Institutes of Health (NIH/NHLBI). The Childhood Asthma Management Program Genetics Ancillary Study is supported by U01 HL075419, U01 HL65899, P01 HL083069, and T32 HL07427 from the NIH/and NHLBI. This article is subject to the National Institutes of Health Public Access Policy (publicaccess.nih.gov). |
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| Disclosure of potential conflict of interest: W. Wu has received research support from the National Institutes of Health (NIH; grant R01 GM093156). E. P. Xing has received research support from the NIH (grant NIH GWAS R016M087694). The rest of the authors declare that they have no relevant conflicts of interest. |
Vol 137 - N° 5
P. 1390 - mai 2016 Retour au numéro
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