Background

There is an unmet need to identify children with poor asthma control as early as possible, in order to optimize treatment. Metabolomic profiling of exhaled breath could enable further understanding of underlying pathophysiological mechanisms during controlled and uncontrolled phases of the disease.

Aim

To differentiate between controlled and uncontrolled pediatric patients with moderate-to-severe asthma using gas chromatography-mass spectrometry (GC-MS)-driven exhaled metabolite profiles.

Methods

Uncontrolled asthma in SysPharmPediA study was defined as: ?1 exacerbation(s) requiring oral corticosteroids and/or (emergency room visits and/or hospitalizations) in the last year and/or an Asthma Control Test (ACT) score ? 19.

Exhaled metabolites were trapped on thermal desorption tubes and analyzed by GC-MS. Statistical modeling involved: 1) split of data into training (50%) and validation (50%) set,  2) sparse partial least square discriminant analysis (sPLS-DA), 3) area under the receiver operating characteristic curves (AUROCCs) calculation, 4) Identification of relevant metabolites using the NIST library.

Results

Complete data set was available for 100 patients (11.7±2.6 years, 39% female, cACT/ACT= 21.6±4.2, 65% uncontrolled). sPLS-DA models resulted in AUROCCs of 0.83 (95%CI 0.7-0.96) for the training set and 0.87 (95%CI 0.74-1.00) for the validation set. Benzaldehyde and styrene provided the highest predictive accuracy to discriminate between study groups.

Conclusions

Our data suggest that exhaled metabolites could be used for asthma control classification in children and substantiate further development of exhaled metabolites-based point-of-care tests in asthma.