Predicting intermediate phenotypes in asthma using bronchoalveolar lavage-derived cytokines

Allan R. Brasier, Sundar Victor, Hyunsu Ju, William W. Busse, Douglas Curran-Everett, Eugene Bleecker, Mario Castro, Kian Fan Chung, Benjamin Gaston, Elliot Israel, Sally E. Wenzel, Serpil C. Erzurum, Nizar N. Jarjour, William Calhoun

Research output: Contribution to journalArticle

49 Citations (Scopus)

Abstract

An important problem in realizing personalized medicine is the development of methods for identifying disease subtypes using quantitative proteomics. Recently we found that bronchoalveolar lavage (BAL) cytokine patterns contain information about dynamic lung responsiveness. In this study, we examined physiological data from 1,048 subjects enrolled in the US Severe Asthma Research Program (SARP) to identify four largely separable, quantitative intermediate phenotypes. Upper extremes in the study population were identified for eosinophil- or neutrophil-predominant inflammation, bronchodilation in response to albuterol treatment, or methacholine sensitivity. We evaluated four different statistical (" machine" ) learning methods to predict each intermediate phenotype using BAL -cytokine measurements on a 76 subject subset. Comparison of these models using area under the ROC curve and overall classification accuracy indicated that logistic regression and multivariate adaptive regression splines produced the most accurate methods to predict intermediate asthma phenotypes. These robust classification methods will aid future translational studies in asthma targeted at specific intermediate phenotypes.

Original languageEnglish (US)
Pages (from-to)147-157
Number of pages11
JournalClinical and Translational Science
Volume3
Issue number4
DOIs
StatePublished - Aug 2010

Fingerprint

Bronchoalveolar Lavage
Asthma
Cytokines
Phenotype
Methacholine Chloride
Albuterol
Splines
Medicine
Learning systems
Logistics
Precision Medicine
Eosinophils
ROC Curve
Proteomics
Area Under Curve
Neutrophils
Logistic Models
Inflammation
Lung
Research

Keywords

  • Asthma
  • Logistic regression
  • Multivariate regression splines
  • Personalized medicine
  • Quantitative phenotypes

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Neuroscience(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)

Cite this

Predicting intermediate phenotypes in asthma using bronchoalveolar lavage-derived cytokines. / Brasier, Allan R.; Victor, Sundar; Ju, Hyunsu; Busse, William W.; Curran-Everett, Douglas; Bleecker, Eugene; Castro, Mario; Chung, Kian Fan; Gaston, Benjamin; Israel, Elliot; Wenzel, Sally E.; Erzurum, Serpil C.; Jarjour, Nizar N.; Calhoun, William.

In: Clinical and Translational Science, Vol. 3, No. 4, 08.2010, p. 147-157.

Research output: Contribution to journalArticle

Brasier, AR, Victor, S, Ju, H, Busse, WW, Curran-Everett, D, Bleecker, E, Castro, M, Chung, KF, Gaston, B, Israel, E, Wenzel, SE, Erzurum, SC, Jarjour, NN & Calhoun, W 2010, 'Predicting intermediate phenotypes in asthma using bronchoalveolar lavage-derived cytokines', Clinical and Translational Science, vol. 3, no. 4, pp. 147-157. https://doi.org/10.1111/j.1752-8062.2010.00204.x
Brasier, Allan R. ; Victor, Sundar ; Ju, Hyunsu ; Busse, William W. ; Curran-Everett, Douglas ; Bleecker, Eugene ; Castro, Mario ; Chung, Kian Fan ; Gaston, Benjamin ; Israel, Elliot ; Wenzel, Sally E. ; Erzurum, Serpil C. ; Jarjour, Nizar N. ; Calhoun, William. / Predicting intermediate phenotypes in asthma using bronchoalveolar lavage-derived cytokines. In: Clinical and Translational Science. 2010 ; Vol. 3, No. 4. pp. 147-157.
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