Exhaled Biomarkers and Gene Expression at Preschool Age Improve Asthma Prediction at 6 Years of Age

Rationale: A reliable asthma diagnosis is difficult in wheezing preschool children. Objectives: To assess whether exhaled biomarkers, expression of inflammation genes, and early lung function measurements can improve a reliable asthma prediction in preschool wheezing children. Methods: 202 preschool recurrent wheezers (aged two-four years) were prospectively followed-up until age six years. At age six, a diagnosis (asthma or transient wheeze) was based on symptoms, lung function and asthma medication use. The added predictive value (area under the receiver operating characteristic curve [AUC]) of biomarkers to clinical information (assessed with the Asthma Predictive Index [API]) assessed at preschool age, in diagnosing asthma at age six was determined with a validation set. Biomarkers in exhaled breath condensate [EBC], exhaled volatile organic compounds [VOCs], gene expression, and airway resistance were measured. Measurements and Main Results: At age six, 198 children were diagnosed (76 asthmatics, 122 transient wheezers). Information on exhaled VOCs significantly improved asthma prediction (AUC: 89% (increase of 28%), positive predictive value (PPV)/negative predictive value (NPV) 82/83%) which persisted in the validation set. Information on expression of toll-like receptor 4, catalase and tumor-necrosis-factor alpha significantly improved asthma prediction (AUC: 75% (increase of 17%), PPV/NPV 76/73%). This could not be confirmed after validation. Biomarkers in EBC and airway resistance (pre- and post- bronchodilator) did not improve an asthma prediction. The combined model with VOCs, gene expression and API had an AUC of 95% (PPV/NPV 90/89%). Conclusions: Adding information on exhaled VOCs and possibly expression of inflammation genes to the API significantly improves an accurate asthma diagnosis in preschool children.