Asthma characteristics and biomarkers from the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) longitudinal profiling study

Abstract

BackgroundAsthma is a heterogeneous disease and development of novel therapeutics requires an understanding of pathophysiologic phenotypes. The purpose of the ADEPT study was to correlate clinical features and biomarkers with molecular characteristics, by profiling asthma (NCT01274507). This report presents for the first time the study design, and characteristics of the recruited subjects.MethodsPatients with a range of asthma severity and healthy non-atopic controls were enrolled. The asthmatic subjects were followed for 12 months. Assessments included history, patient questionnaires, spirometry, airway hyper-responsiveness to methacholine, fractional exhaled nitric oxide (FENO), and biomarkers measured in induced sputum, blood, and bronchoscopy samples. All subjects underwent sputum induction and 30 subjects/cohort had bronchoscopy.ResultsMild (n = 52), moderate (n = 55), severe (n = 51) asthma cohorts and 30 healthy controls were enrolled from North America and Western Europe. Airflow obstruction, bronchodilator response and airways hyperresponsiveness increased with asthma severity, and severe asthma subjects had reduced forced vital capacity. Asthma control questionnaire-7 (ACQ7) scores worsened with asthma severity. In the asthmatics, mean values for all clinical and biomarker characteristics were stable over 12 months although individual variability was evident. FENO and blood eosinophils did not differ by asthma severity. Induced sputum eosinophils but not neutrophils were lower in mild compared to the moderate and severe asthma cohorts.ConclusionsThe ADEPT study successfully enrolled asthmatics across a spectrum of severity and non-atopic controls. Clinical characteristics were related to asthma severity and in general asthma characteristics e.g. lung function, were stable over 12 months. Use of the ADEPT data should prove useful in defining biological phenotypes to facilitate personalized therapeutic approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-015-0299-y) contains supplementary material, which is available to authorized users.

Identification of airway mucosal type 2 inflammation by using clinical biomarkers in asthmatic patients

“…Limitations of this study include the absence of smoking, oral corticosteroid dependence, and morbidly obese asthmatic subjects, as described previously. 16 Furthermore, we did not recruit an atopic healthy subject population, which might have provided an additional group for comparison purposes. Finally, we did not have a reliable serum periostin assay available to enable comparison of expression of this gene with sCCL17 and sCCL26 measurements.…”

“…NCT01274507) have been described in detail. 16 In brief, nonatopic healthy subjects, patients with mild asthma (no controller medications and prebronchodilator FEV 1 > _80% of predicted value), patients with moderate asthma (low-to-moderate ICS dose and prebronchodilator FEV 1 60% to <80% of predicted value), and patients with severe asthma (high-dose ICS and prebronchodilator FEV 1 50% to less than 80% of predicted value) were enrolled. Healthy subjects and a subset of asthmatic patients underwent bronchoscopy.…”

“…In general, the patterns of categorical clinical biomarkers reported for airway mucosal CCL26 expression were similar for periostin (see Table E2) and IL-13-IVS expression (see Table E3 in this article's Online Repository at www.jacionline.org), although the [12] .577 70.2 6 10.3 [13] 71.2 6 11.6 [41] .785 FEV 1 , postbronchodilater (PN) 102.1 6 9.1 [15] 97.9 6 11.2 [12] .293 83.0 6 8.9 [13] 80.8 6 13.8 [41] .598 BDR, % change in FEV 1 6.25 6 8.54 [15] 6.33 6 3.25 [12] .978 19.79 6 15.86 [13] 14.63 6 10.96 [40] .195 ACQ score 0.6 6 0.5 [16] 0.9 6 0.6 [12] .176 1.7 6 0.8 [13] 1.5 6 0.9 [42] .549 AQLQ score 6.2 6 0.7 [16] 5.9 6 0.9 [12] .245 5.6 6 0.8 [13] 5.5 6 1.3 [42] .637 PC 20 . P values were calculated from log-transformed data.…”

“…The previously reported Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study 16 allowed us to evaluate airway mucosal gene expression associated with type 2 inflammation, including periostin expression, which has been associated with enhanced responses to the anti-IL-13 mAb lebrikizumab 13 ; CCL26, which in our hands was the most highly expressed gene in IL-13-treated human cells lines; and a multigene in vitro signature (IVS) from the same cell lines (IL-13-IVS). We also ascertained whether type 2 gene expression profiles for CCL26, IL-13-IVS, and periostin could be classified by using clinically accessible biomarkers, namely FENO values, bEOS counts, and less commonly used serum markers, such as CCL17/TARC (thymus and activation-regulated chemokine) and activation-regulated chemokine and CCL26/eotaxin-3, which are type 2 chemokines reliably measured in serum.…”

Integrating personalized gene expression profiles into predictive disease-associated gene pools

“…35 The asthma dataset contains 55 case subjects with moderate or severe asthma, and 25 gender-matched and age-matched healthy control subjects, see ref. 36 for a detailed description of the cohort. The asthma samples were collected from bronchoscopy (endobronchial biopsies and brushings), preserved immediately in RNAlater ® solution and then maintained at −70 °C.…”