| 1. |
- Alahmadi, Fahad, et al.
(författare)
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Measures of adherence in patients with severe asthma prescribed systemic steroids in the U-BIOPRED cohort
- 2018
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Ingår i: European Respiratory Journal. - : European Respiratory Society. - 0903-1936 .- 1399-3003. ; 52
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Introduction: Rates of sub-optimal adherence to medications in asthma range up to 70%; the impact in severe asthma is likely to be particularly high. We measured self-reported adherence in participants in the U-BIOPRED cohort prescribed daily prednisolone using the Medication Adherence Response Scale (MARS), and compared to measured urinary prednisolone and metabolites in order to determine: 1. the prevalence of suboptimal adherence by each method; 2. the ability of MARS to predict urinary steroid detection.Methods: Participants completed the MARS, and/or provided urine samples (analysed for prednisolone and metabolites by LCMS). The performance characteristics of the MARS predicting undetected urinary steroid were calculated in the subgroup having both tests.Results: 181 participants currently taking regular oral corticosteroids were included, 59% female, mean (SD) age 54(12)yrs, FEV1 64.7(20.4)% predicted. Sub-optimal adherence (MARS score < 4.5) was reported in 62 participants, and 76 did not have detectable urinary prednisolone or metabolites. Good adherence by both methods was detected in only 52 participants (34%, see table). There was no difference in daily prednisolone dose between detectable and undetectable metabolites groups (p=0.848).Conclusion: Low levels of adherence to treatment in severe asthma is a common problem, when measured either directly or self-reported. There was very poor agreement (48% concordance) between these two methods, and we suggest that, for now both approaches should be used.
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| 2. |
- Lefaudeux, Diane, et al.
(författare)
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U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
- 2017
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Ingår i: Journal of Allergy and Clinical Immunology. - : Elsevier BV. - 0091-6749 .- 1097-6825. ; 139:6, s. 1797-1807
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Schofield, James P. R., et al.
(författare)
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Topological data analysis (TDA) of U-BIOPRED paediatric peripheral blood gene expression identified asthma phenotypes characterised by alternative splicing of glucocorticoid receptor (GR) mRNA
- 2018
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Ingår i: European Respiratory Journal. - : European Respiratory Society. - 0903-1936 .- 1399-3003. ; 52
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Molecular stratification of childhood asthma could enable targeted therapy.Aims: Unbiased analysis of gene expression in paediatric severe (SA) and moderate/mild asthma (MA) blood samples to identify sub-phenotypes.Methods: Transcriptomic profiling by microarray analysis of blood from the U-BIOPRED paediatric cohort (Fleming ERJ 2015), pre- and school-age children, (SApre, n=62; MApre, n=42; SAsc, n=75 and MAsc, n=37). Topological data analysis (TDA) was used for unbiased clustering.Results: Sub-phenotypes, P1, P2, P3 and P4 were identified and are highlighted in the TDA network in the figure and a heatmap of selected variables. P1 (38% of the cohort, median 11 yrs) was characterised by low expression of glucocorticoid receptor (GR) mRNA splice variant with a long 3’ UTR (q = 2.43E-17), but no significant difference in the expression of glucocorticoid receptor (GR) mRNA splice variant with a short 3’ UTR. In P1, COX2 expression was up (q = 1.89E-06) and IFN-γ was down (q = 5.61E-06), characteristics of a decreased steroid response.Conclusion: Unbiased analysis of U-BIOPRED paediatric peripheral blood gene expression identified a sub-phenotype, P1, with an inhibited steroid response. P1 is associated with low expression of a splice variant of GR with a long 3’ UTR.
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