| 1. |
- Ostaszewski, Marek, et al.
(author)
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COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
- 2021
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In: Molecular Systems Biology. - : John Wiley & Sons. - 1744-4292 .- 1744-4292. ; 17:10
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Journal article (peer-reviewed)abstract
- We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
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| 2. |
- Abdel-Aziz, Mahmoud I., et al.
(author)
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A multi-omics approach to delineate sputum microbiome-associated asthma inflammatory phenotypes
- 2022
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In: European Respiratory Journal. - : European Respiratory Society. - 0903-1936 .- 1399-3003. ; 59:1
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Journal article (peer-reviewed)abstract
- A multi-omics approach revealed the underlying biological pathways in the microbiome-driven severe asthma phenotypes. This may help to elucidate new leads for treatment development, particularly for the therapeutically challenging neutrophilic asthma.
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| 3. |
- Brinkman, Paul, et al.
(author)
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Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma
- 2019
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In: Journal of Allergy and Clinical Immunology. - : Elsevier. - 0091-6749 .- 1097-6825. ; 143:5, s. 1811-1820.e7
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Journal article (peer-reviewed)abstract
- Background: Severe asthma is a heterogeneous condition, as shown by independent cluster analyses based on demographic, clinical, and inflammatory characteristics. A next step is to identify molecularly driven phenotypes using “omics” technologies. Molecular fingerprints of exhaled breath are associated with inflammation and can qualify as noninvasive assessment of severe asthma phenotypes.Objectives: We aimed (1) to identify severe asthma phenotypes using exhaled metabolomic fingerprints obtained from a composite of electronic noses (eNoses) and (2) to assess the stability of eNose-derived phenotypes in relation to withinpatient clinical and inflammatory changes.Methods: In this longitudinal multicenter study exhaled breath samples were taken from an unselected subset of adults with severe asthma from the U-BIOPRED cohort. Exhaled metabolites were analyzed centrally by using an assembly of eNoses. Unsupervised Ward clustering enhanced by similarity profile analysis together with K-means clustering was performed. For internal validation, partitioning around medoids and topological data analysis were applied. Samples at 12 to 18 months of prospective follow-up were used to assess longitudinal within-patient stability.Results: Data were available for 78 subjects (age, 55 years [interquartile range, 45-64 years]; 41% male). Three eNosedriven clusters (n = 26/33/19) were revealed, showing differences in circulating eosinophil (P = .045) and neutrophil (P = .017) percentages and ratios of patients using oral corticosteroids (P = .035). Longitudinal within-patient cluster stability was associated with changes in sputum eosinophil percentages (P = .045).Conclusions: We have identified and followed up exhaled molecular phenotypes of severe asthma, which were associated with changing inflammatory profile and oral steroid use. This suggests that breath analysis can contribute to the management of severe asthma.
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| 4. |
- Emma, Rosalia, et al.
(author)
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Enhanced oxidative stress in smoking and ex-smoking severe asthma in the U-BIOPRED cohort
- 2018
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In: PLOS ONE. - : Public Library Science. - 1932-6203. ; 13:9
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Journal article (peer-reviewed)abstract
- Oxidative stress is believed to be a major driver of inflammation in smoking asthmatics. The U-BIOPRED project recruited a cohort of Severe Asthma smokers/ex-smokers (SAs/ex) and non-smokers (SAn) with extensive clinical and biomarker information enabling characterization of these subjects. We investigated oxidative stress in severe asthma subjects by analysing urinary 8-iso-PGF(2 alpha) and the mRNA-expression of the main pro-oxidant (NOX2; NOSs) and anti-oxidant (SODs; CAT; GPX1) enzymes in the airways of SAs/ex and SAn. All the severe asthma U-BIOPRED subjects were further divided into current smokers with severe asthma (CSA), ex-smokers with severe asthma (ESA) and non-smokers with severe asthma (NSA) to deepen the effect of active smoking. Clinical data, urine and sputum were obtained from severe asthma subjects. A bronchoscopy to obtain bronchial biopsy and brushing was performed in a subset of subjects. The main clinical data were analysed for each subset of subjects (urine-8-iso-PGF(2 alpha); IS-transcriptomics; BB-transcriptomics; BBrtranscriptomics). Urinary 8-iso-PGF(2 alpha) was quantified using mass spectrometry. Sputum, bronchial biopsy and bronchial brushing were processed for mRNA expression microarray analysis. Urinary 8-iso-PGF(2 alpha) was increased in SAs/ex, median (IQR) = 31.7 (24.5 +/- 44.7) ng/mmol creatinine, compared to SAn, median (IQR) = 26.6 (19.6 +/- 36.6) ng/mmol creatinine (p< 0.001), and in CSA, median (IQR) = 34.25 (24.4 +/- 47.7), vs. ESA, median (IQR) = 29.4 (22.3 +/- 40.5), and NSA, median (IQR) = 26.5 (19.6 +/- 16.6) ng/mmol creatinine (p = 0.004). Sputum mRNA expression of NOX2 was increased in SAs/ex compared to SAn (probe sets 203922_PM_s_at fold-change = 1.05 p = 0.006; 203923_PM_s_at fold-change = 1.06, p = 0.003; 233538_PM_s_at fold-change = 1.06, p = 0.014). The mRNA expression of antioxidant enzymes were similar between the two severe asthma cohorts in all airway samples. NOS2 mRNA expression was decreased in bronchial brushing of SAs/ex compared to SAn (fold-change = -1.10; p = 0.029). NOS2 mRNA expression in bronchial brushing correlated with FeNO (Kendal's Tau = 0.535; p< 0.001). From clinical and inflammatory analysis, FeNO was lower in CSA than in ESA in all the analysed subject subsets (p< 0.01) indicating an effect of active smoking. Results about FeNO suggest its clinical limitation, as inflammation biomarker, in severe asthma active smokers. These data provide evidence of greater systemic oxidative stress in severe asthma smokers as reflected by a significant changes of NOX2 mRNA expression in the airways, together with elevated urinary 8-iso-PGF(2 alpha) in the smokers/ex-smokers group.
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| 5. |
- Gandaglia, Giorgio, et al.
(author)
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Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management : A PIONEER Analysis Based on Big Data
- 2023
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In: European Urology. - 0302-2838.
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Journal article (peer-reviewed)abstract
- Background: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. Objective: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. Design, setting, and participants: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). Outcome measurements and statistical analysis: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. Results and limitations: The most common comorbidities were hypertension (35–73%), obesity (9.2–54%), and type 2 diabetes (11–28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12–25%) and emergency department visits (10–14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. Conclusions: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. Patient summary: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.
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| 6. |
- George, Leena, et al.
(author)
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Blood eosinophil count and airway epithelial transcriptome relationships in COPD versus asthma
- 2020
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In: Allergy. European Journal of Allergy and Clinical Immunology. - : WILEY. - 0105-4538 .- 1398-9995. ; 75:2, s. 370-380
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Journal article (peer-reviewed)abstract
- Background: Whether the clinical or pathophysiologic significance of the "treatable trait" high blood eosinophil count in COPD is the same as for asthma remains controversial. We sought to determine the relationship between the blood eosinophil count, clinical characteristics and gene expression from bronchial brushings in COPD and asthma.Methods: Subjects were recruited into a COPD (emphysema versus airway disease [EvA]) or asthma cohort (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes, U-BIOPRED). We determined gene expression using RNAseq in EvA (n = 283) and Affymetrix microarrays in U-BIOPRED (n = 85). We ran linear regression analysis of the bronchial brushings transcriptional signal versus blood eosinophil counts as well as differential expression using a blood eosinophil > 200 cells/mu L as a cut-off. The false discovery rate was controlled at 1% (with continuous values) and 5% (with dichotomized values).Results: There were no differences in age, gender, lung function, exercise capacity and quantitative computed tomography between eosinophilic versus noneosinophilic COPD cases. Total serum IgE was increased in eosinophilic asthma and COPD. In EvA, there were 12 genes with a statistically significant positive association with the linear blood eosinophil count, whereas in U-BIOPRED, 1197 genes showed significant associations (266 positive and 931 negative). The transcriptome showed little overlap between genes and pathways associated with blood eosinophil counts in asthma versus COPD. Only CST1 was common to eosinophilic asthma and COPD and was replicated in independent cohorts.Conclusion: Despite shared "treatable traits" between asthma and COPD, the molecular mechanisms underlying these clinical entities are predominately different.
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| 7. |
- Hou, Ruihua, et al.
(author)
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The role of inflammation in anxiety and depression in the European U-BIOPRED asthma cohorts
- 2023
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In: Brain, behavior, and immunity. - : Academic Press. - 0889-1591 .- 1090-2139. ; 111, s. 249-258
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Journal article (peer-reviewed)abstract
- Background: Growing evidence indicates high comorbid anxiety and depression in patients with asthma. However, the mechanisms underlying this comorbid condition remain unclear. The aim of this study was to investigate the role of inflammation in comorbid anxiety and depression in three asthma patient cohorts of the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project. Methods: U-BIOPRED was conducted by a European Union consortium of 16 academic institutions in 11 European countries. A subset dataset from subjects with valid anxiety and depression measures and a large blood biomarker dataset were analysed, including 198 non-smoking patients with severe asthma (SAn), 65 smoking patients with severe asthma (SAs), 61 non-smoking patients with mild-to-moderate asthma (MMA), and 20 healthy non-smokers (HC). The Hospital Anxiety and Depression Scale was used to measure anxiety and depression and a series of inflammatory markers were analysed by the SomaScan v3 platform (SomaLogic, Boulder, Colo). ANOVA and the Kruskal-Wallis test were used for multiple-group comparisons as appropriate. Results: There were significant group effects on anxiety and depression among the four cohort groups (p < 0.05). Anxiety and depression of SAn and SAs groups were significantly higher than that of MMA and HC groups (p < 0.05. There were significant differences in serum IL6, MCP1, CCL18, CCL17, IL8, and Eotaxin among the four groups (p < 0.05). Depression was significantly associated with IL6, MCP1, CCL18 level, and CCL17; whereas anxiety was associated with CCL17 only (p < 0.05). Conclusions: The current study suggests that severe asthma patients are associated with higher levels of anxiety and depression, and inflammatory responses may underlie this comorbid condition.
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| 8. |
- Kuo, Chih-Hsi Scott, et al.
(author)
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A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED
- 2017
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In: American Journal of Respiratory and Critical Care Medicine. - 1073-449X .- 1535-4970. ; 194:4, s. 443-455
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Journal article (peer-reviewed)abstract
- RATIONALE AND OBJECTIVES: Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms. We used transcriptomic profiling of airway tissues to help define asthma phenotypes.METHODS: The transcriptome from bronchial biopsies and epithelial brushings of 107 moderate-to-severe asthmatics were annotated by gene-set variation analysis (GSVA) using 42 gene-signatures relevant to asthma, inflammation and immune function. Topological data analysis (TDA) of clinical and histological data was used to derive clusters and the nearest shrunken centroid algorithm used for signature refinement.RESULTS: 9 GSVA signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper type 2 (Th-2) cytokines and lack of corticosteroid response (Group 1 and Group 3). Group 1 had the highest submucosal eosinophils, high exhaled nitric oxide (FeNO) levels, exacerbation rates and oral corticosteroid (OCS) use whilst Group 3 patients showed the highest levels of sputum eosinophils and had a high BMI. In contrast, Group 2 and Group 4 patients had an 86% and 64% probability of having non-eosinophilic inflammation. Using machine-learning tools, we describe an inference scheme using the currently-available inflammatory biomarkers sputum eosinophilia and exhaled nitric oxide levels along with OCS use that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity.CONCLUSION: This analysis demonstrates the usefulness of a transcriptomic-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target Th2-mediated inflammation and/or corticosteroid insensitivity.
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| 9. |
- Lefaudeux, Diane, et al.
(author)
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U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics
- 2017
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In: Journal of Allergy and Clinical Immunology. - : Elsevier BV. - 0091-6749 .- 1097-6825. ; 139:6, s. 1797-1807
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Journal article (peer-reviewed)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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| 10. |
- Perotin-Collard, Jeanne-Marie, et al.
(author)
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Subtypes of eosinophilic asthma with discrete gene pathway phenotypes
- 2019
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In: European Respiratory Journal. - : European Respiratory Society Journals. - 0903-1936 .- 1399-3003. ; 54
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Journal article (other academic/artistic)abstract
- Background: Blood eosinophil counts ≥0.3x109/L are used to define Type-2, eosinophilic asthma. However, differential responses to T2 biologics of patients with eosinophilic asthma suggests that this may be a heterogeneous phenotype with subsets driven by different molecular mechanisms.Methods: Blood transcriptomic data, acquired from 99 severe asthmatics from the U-BIOPRED study (62% female, mean age 54 yr, 41% on oral steroids), were clustered by topological data analysis and cluster boundaries defined by the MORSE method. Gene pathway signatures were identified by Ingenuity Pathway Analysis.Results: Analysis revealed 3 clusters with different modulated gene pathways, i.e. molecular phenotypes. Subtype 1 had high IFN-γ, low IL5, low IL13 and low IL17 gene expression, with reduced glucocorticoid-induced gene expression. Subtype 2 had low IFNγ, high IL5, high IL13 and low IL17 gene expression. Subtype 3 had low IFNγ, high IL5, high IL13 and high IL17 gene expression. Pathway analysis suggested a strong steroid response in Subtypes 2 and 3. Clinically, the three clusters were not different in respect of age, gender, prevalence of atopy, blood or sputum eosinophil counts. Subtype 3 was characterized by high neutrophil counts in blood and bronchial epithelium, frequent sinus disease and asthma exacerbations, OCS treatment, low allergic sensitisation and low exhaled NO. Subtype 1 was characterized by high exhaled NO and more frequent IgE therapy.Conclusion: This study suggests that eosinophilic severe asthma (≥0.3x109/L) can be stratified further into 3 subtypes with distinct gene expression profiles that could be developed as molecular diagnostic biomarkers to guide treatment and thereby improve patient outcomes.
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| 11. |
- Rajwa, Pawel, et al.
(author)
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Research protocol for an observational health data analysis on the adverse events of systemic treatment in patients with metastatic hormone-sensitive prostate cancer : big data analytics using the PIONEER platform
- 2024
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In: European Urology Open Science. - : Elsevier. - 2666-1691 .- 2666-1683. ; 63, s. 81-88
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Journal article (peer-reviewed)abstract
- Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.
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| 12. |
- Schofield, James P. R., et al.
(author)
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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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In: European Respiratory Journal. - : European Respiratory Society. - 0903-1936 .- 1399-3003. ; 52
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Journal article (other academic/artistic)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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