Medication Adherence in Patients With Severe Asthma Prescribed Oral Corticosteroids in the U-BIOPRED Cohort

BACKGROUND: Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high.RESEARCH QUESTIONS: What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity?STUDY DESIGN AND METHODS: Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry.RESULTS: Data from 166 participants were included in this study: mean (SD) age, 54.2 (+/- 11.9) years; FEV1, 65.1% (+/- 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels.INTERPRETATION: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice

Medication Adherence in Patients With Severe Asthma Prescribed Oral Corticosteroids in the U-BIOPRED Cohort.

BACKGROUND Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. RESEARCH QUESTIONS What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity? STUDY DESIGN AND METHODS Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry. RESULTS Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV1, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in the 35% of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels. INTERPRETATION Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice

Urinary Leukotriene E4 and Prostaglandin D2 Metabolites Increase in Adult and Childhood Severe Asthma Characterized by Type 2 Inflammation: A Clinical Observational Study

Rationale: New approaches are needed to guide personalized treatment of asthma. Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping. Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12–18 months and externally in 95 adolescents with asthma. Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE4 and the PGD2 metabolite 2,3-dinor-11β-PGF2α. High concentrations of LTE4 and PGD2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers. Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale Asthma phenotyping requires novel biomarker discovery. Objectives To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). Methods An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. Results In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. Conclusions The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale: Asthma phenotyping requires novel biomarker discovery.Objectives: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs).Methods: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED.Results: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation.Conclusions: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.</p

Medication adherence in patients with severe asthma prescribed oral corticosteroids in the U-BIOPRED cohort

Background: Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. Research Questions: What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity? Study Design and Methods: Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry. Results: Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV1, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels. Interpretation: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice

Urinary Leukotriene E 4 and Prostaglandin D 2 Metabolites Increase in Adult and Childhood Severe Asthma Characterized by Type 2 Inflammation. A Clinical Observational Study

International audienc

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways