Stratification of asthma phenotypes by airway proteomic signatures

© 2019 Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies

Diagnosis and definition of severe refractory asthma: an international consensus statement from the Innovative Medicine Initiative (IMI)

Patients with severe refractory asthma pose a major healthcare problem. Over the last decade it has become increasingly clear that, for the development of new targeted therapies, there is an urgent need for further characterisation and classification of these patients. The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) consortium is a pan-European public-private collaboration funded by the European Commission Innovative Medicines Initiative of the European Union. U-BIOPRED aims to subphenotype patients with severe refractory asthma by using an innovative systems biology approach. This paper presents the U-BIOPRED international consensus on the definition and diagnosis of severe asthma, aligning the latest concepts in adults as well as in children. The consensus is based on existing recommendations up to 2010 and will be used for the selection of patients for the upcoming U-BIOPRED study. It includes the differentiation between 'problematic', 'difficult' and 'severe refractory' asthma, and provides a systematic algorithmic approach to the evaluation of patients presenting with chronic severe asthma symptoms for use in clinical research and specialised car

Perioperative outcomes of robotic and laparoscopic simple prostatectomy: a European-American multi-institutional analysis

Background: Laparoscopic and robotic simple prostatectomy (SP) have been introduced with the aim of reducing the morbidity of the standard open technique. Objective: To report a large multi-institutional series of minimally invasive SP (MISP). Design, setting, and participants: Consecutive cases of MISP done for the treatment of bladder outlet obstruction (BOO) due to benign prostatic enlargement (BPE) between 2000 and 2014 at 23 participating institutions in the Americas and Europe were included in this retrospective analysis. Intervention: Laparoscopic or robotic SP. Outcome measurements and statistical analysis: Demographic data and main perioperative outcomes were gathered and analyzed. A multivariable analysis was conducted to identify factors associated with a favorable trifecta outcome, arbitrarily defined as a combination of the following postoperative events: International Prostate Symptom Score 15 ml/s, and no perioperative complications. Results and limitations: Overall, 1330 consecutive cases were analyzed, including 487 robotic (36.6%) and 843 laparoscopic (63.4%) SP cases. Median overall prostate volume was 100 ml (range: 89-128). Median estimated blood loss was 200 ml (range: 150-300). An intraoperative transfusion was required in 3.5% of cases, an intraoperative complication was recorded in 2.2% of cases, and the conversion rate was 3%. Median length of stay was 4 d (range: 3-5). On pathology, prostate cancer was found in 4% of cases. Overall postoperative complication rate was 10.6%, mostly of low grade. At a median follow-up of 12 mo, a significant improvement was observed for subjective and objective indicators of BOO. Trifecta outcome was not significantly influenced by the type of procedure (robotic vs laparoscopic; p = 0.136; odds ratio [OR]: 1.6; 95% confidence interval [CI], 0.8-2.9), whereas operative time (p = 0.01; OR: 0.9; 95% CI, 0.9-1.0) and estimated blood loss (p = 0.03; OR: 0.9; 95% CI, 0.9-1.0) were the only two significant factors. Retrospective study design, lack of a control arm, and limited follow-up represent major limitations of the present analysis. Conclusions: This study provides the largest outcome analysis reported for MISP for BOO/BPE. These findings confirm that SP can be safely and effectively performed in a minimally invasive fashion in a variety of healthcare settings in which specific surgical expertise and technology is available. MISP can be considered a viable surgical treatment in cases of large prostatic adenomas. The use of robotic technology for this indication can be considered in centers that have a robotic program in place for other urologic indications. Patient summary: Analysis of a large data set from multiple institutions shows that surgical removal of symptomatic large prostatic adenomas can be carried out with good outcomes by using robot-assisted laparoscopy

Predictors and associations of the persistent airflow limitation phenotype in asthma: a post-hoc analysis of the ATLANTIS study

Background: Persistent airflow limitation (PAL) occurs in a subset of patients with asthma. Previous studies on PAL in asthma have included relatively small populations, mostly restricted to severe asthma, or have no included longitudinal data. The aim of this post-hoc analysis was to investigate the determinants, clinical implications, and outcome of PAL in patients with asthma who were included in the ATLANTIS study. Methods: In this post-hoc analysis of the ATLANTIS study, we assessed the prevalence, clinical characteristics, and implications of PAL across the full range of asthma severity. The study population included patients aged 18–65 years who had been diagnosed with asthma at least 6 months before inclusion. We defined PAL as a post-bronchodilator FEV1/forced vital capacity (FVC) of less than the lower limit of normal at recruitment. Asthma severity was defined according to the Global Initiative for Asthma. We used Mann-Whitney U test, t test, or χ2 test to analyse differences in baseline characteristics between patients with and without PAL. Logistic regression was used for multivariable analysis of the associations between PAL and baseline data. Cox regression was used to analyse risk of exacerbation in relation to PAL, and a linear mixed-effects model was used to analyse change in FEV1 over time in patients with versus patients without PAL. Results were validated in the U-BIOPRED cohort. Findings: Between June 30, 2014 and March 3, 2017, 773 patients were enrolled in the ATLANTIS study of whom 760 (98%) had post-bronchodilator FEV1/FVC data available. Of the included patients with available data, mean age was 44 years (SD 13), 441 (58%) of 760 were women, 578 (76%) were never-smokers, and 248 (33%) had PAL. PAL was not only present in patients with severe asthma, but also in 21 (16%) of 133 patients with GINA step 1 and 24 (29%) of 83 patients with GINA step 2. PAL was independently associated with older age at baseline (46 years in PAL group vs 43 years in non-PAL group), longer duration of asthma (24 years vs 12 years), male sex (51% vs 38%), higher blood eosinophil counts (median 0·27 × 109 cells per L vs 0·20 × 109 cells per L), more small airway dysfunction, and more exacerbations during 1 year of follow-up. Associations between PAL, age, and eosinophilic inflammation were validated in the U-BIOPRED cohort, whereas associations with sex, duration of asthma, and risk of exacerbations were not validated. Interpretation: PAL is not only present in severe disease, but also in a considerable proportion of patients with milder disease. In patients with mild asthma, PAL is associated with eosinophilic inflammation and a higher risk of exacerbations. Our findings are important because they suggest that increasing treatment intensity should be considered in patients with milder asthma and PAL. Funding: Chiesi Farmaceutici and Dutch Ministry of Economic Affairs and Climate Policy (by means of the public–private partnership programme)

Stratification of asthma phenotypes by airway proteomic signatures

Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms.Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification.Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms.Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysisidentified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms.Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies.</p