Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers.

The exhaled breath represents an ideal matrix for non-invasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review we will specifically address volatile organic compounds in the breath, with a view towards fulfilling the promise of these as actionable biomarkers, in particular for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward, if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

RATIONALE: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. METHODS: VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). MAIN RESULTS: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). CONCLUSIONS: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Biomarker Predictors of Clinical Efficacy of the Anti-IgE Biologic, Omalizumab, in Severe Asthma in Adults: Results of the SoMOSA Study.

BACKGROUND: The anti-IgE monoclonal, omalizumab, is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during one year of omalizumab treatment. METHODS: 1-year, open-label, Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 severe (GINA step 4/5) uncontrolled atopic asthmatics (≥2 severe exacerbations in previous year) on high-dose inhaled corticosteroids, long-acting ß-agonists, ± mOCS. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE), and 16-52 weeks, to assess late responses by ≥50% reduction in exacerbations or dose of maintenance oral corticosteroids (mOCS). All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. RESULTS: 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ≥50%, while 57% (37/65) on mOCS reduced their dose by ≥50%. The primary outcome 2, 3-dinor-11-ß-PGF2α, GETE and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five breathomics (GC-MS) and 5 plasma lipid biomarkers strongly predicted the ≥50% reduction in exacerbations (receiver operating characteristic area under the curve (AUC): 0.780 and 0.922, respectively) and early responses (AUC:0.835 and 0.949, respectively). In independent cohorts, the GC-MS biomarkers differentiated between severe and mild asthma. Conclusions This is the first discovery of omics biomarkers that predict improvement to a biologic for asthma. Their prospective validation and development for clinical use is justified. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Impact of sex on severe asthma: a cross-sectional retrospective analysis of UK primary and specialist care.

INTRODUCTION: After puberty, females are more likely to develop asthma and in a more severe form than males. The associations between asthma and sex are complex with multiple intrinsic and external factors. AIM: To evaluate the sex differences in the characteristics and treatment of patients with severe asthma (SA) in a real-world setting. METHODS: Demographic, clinical and treatment characteristics for patients with SA in the UK Severe Asthma Registry (UKSAR) and Optimum Patient Care Research Database (OPCRD) were retrospectively analysed by sex using univariable and multivariable logistic regression analyses adjusted for year, age and hospital/practice. RESULTS: 3679 (60.9% female) patients from UKSAR and 18 369 patients (67.9% female) from OPCRD with SA were included. Females were more likely to be symptomatic with increased Asthma Control Questionnaire-6 (UKSAR adjusted OR (aOR) 1.14, 95% CI 1.09 to 1.18) and Royal College of Physicians-3 Question scores (OPCRD aOR 1.29, 95% CI 1.13 to 1.47). However, they had a higher forced expiratory volume in 1 second per cent (FEV1%) predicted (UKSAR 68.7% vs 64.8%, p<0.001) with no significant difference in peak expiratory flow. Type 2 biomarkers IgE (UKSAR 129 IU/mL vs 208 IU/mL, p<0.001) and FeNO (UKSAR 36ppb vs 46ppb, p<0.001) were lower in females with no significant difference in blood eosinophils or biological therapy. Females were less likely to be on maintenance oral corticosteroids (UKSAR aOR 0.86, 95% CI 0.75 to 0.99) but more likely to be obese (UKSAR aOR 1.67, 95% CI 145 to 1.93; OPCRD SA aOR 1.46, 95% CI 1.34 to 1.58). CONCLUSIONS: Females had increased symptoms and were more likely to be obese despite higher FEV1% predicted and lower type 2 biomarkers with consistent and clinically important differences across both datasets.

The effects of inhaled corticosteroids on healthy airways.

BACKGROUND: The effects of inhaled corticosteroids (ICS) on healthy airways are poorly defined. OBJECTIVES: To delineate the effects of ICS on gene expression in healthy airways, without confounding caused by changes in disease-related genes and disease-related alterations in ICS responsiveness. METHODS: Randomized open-label bronchoscopy study of high-dose ICS therapy in 30 healthy adult volunteers randomized 2:1 to (i) fluticasone propionate 500 mcg bd daily or (ii) no treatment, for 4 weeks. Laboratory staff were blinded to allocation. Biopsies and brushings were analysed by immunohistochemistry, bulk RNA sequencing, DNA methylation array and metagenomics. RESULTS: ICS induced small between-group differences in blood and lamina propria eosinophil numbers, but not in other immunopathological features, blood neutrophils, FeNO, FEV1, microbiome or DNA methylation. ICS treatment upregulated 72 genes in brushings and 53 genes in biopsies, and downregulated 82 genes in brushings and 416 genes in biopsies. The most downregulated genes in both tissues were canonical markers of type-2 inflammation (FCER1A, CPA3, IL33, CLEC10A, SERPINB10 and CCR5), T cell-mediated adaptive immunity (TARP, TRBC1, TRBC2, PTPN22, TRAC, CD2, CD8A, HLA-DQB2, CD96, PTPN7), B-cell immunity (CD20, immunoglobulin heavy and light chains) and innate immunity, including CD48, Hobit, RANTES, Langerin and GFI1. An IL-17-dependent gene signature was not upregulated by ICS. CONCLUSIONS: In healthy airways, 4-week ICS exposure reduces gene expression related to both innate and adaptive immunity, and reduces markers of type-2 inflammation. This implies that homeostasis in health involves tonic type-2 signalling in the airway mucosa, which is exquisitely sensitive to ICS.

Eosinophils and tissue remodeling: Relevance to airway disease.

The ability of human tissue to reorganize and restore its existing structure underlies tissue homeostasis in the healthy airways, but in disease can persist without normal resolution, leading to an altered airway structure. Eosinophils play a cardinal role in airway remodeling both in health and disease, driving epithelial homeostasis and extracellular matrix turnover. Physiological consequences associated with eosinophil-driven remodeling include impaired lung function and reduced bronchodilator reversibility in asthma, and obstructed airflow in chronic rhinosinusitis with nasal polyps. Given the contribution of airway remodeling to the development and persistence of symptoms in airways disease, targeting remodeling is an important therapeutic consideration. Indeed, there is early evidence that eosinophil attenuation may reduce remodeling and disease progression in asthma. This review provides an overview of tissue remodeling in both health and airway disease with a particular focus on eosinophilic asthma and chronic rhinosinusitis with nasal polyps, as well as the role of eosinophils in these processes and the implications for therapeutic interventions. Areas for future research are also noted, to help improve our understanding of the homeostatic and pathological roles of eosinophils in tissue remodeling, which should aid the development of targeted and effective treatments for eosinophilic diseases of the airways.

Safety and Efficacy of Dexpramipexole in Eosinophilic Asthma (EXHALE): A randomized controlled trial.

BACKGROUND: There is a need for new and effective oral asthma therapies. Dexpramipexole, an oral eosinophil-lowering drug, has not previously been studied in asthma. OBJECTIVE: We sought to evaluate the safety and efficacy of dexpramipexole in lowering blood and airway eosinophilia in subjects with eosinophilic asthma. METHODS: We performed a randomized, double-blind, placebo-controlled proof-of-concept trial in adults with inadequately controlled moderate to severe asthma and blood absolute eosinophil count (AEC) greater than or equal to 300/µL. Subjects were randomly assigned (1:1:1:1) to dexpramipexole 37.5, 75, or 150 mg BID (twice-daily) or placebo. The primary end point was the relative change in AEC from baseline to week 12. Prebronchodilator FEV1 week-12 change from baseline was a key secondary end point. Nasal eosinophil peroxidase was an exploratory end point. RESULTS: A total of 103 subjects were randomly assigned to dexpramipexole 37.5 mg BID (N = 22), 75 mg BID (N = 26), 150 mg BID (N = 28), or placebo (N = 27). Dexpramipexole significantly reduced placebo-corrected AEC week-12 ratio to baseline, in both the 150-mg BID (ratio, 0.23; 95% CI, 0.12-0.43; P < .0001) and the 75-mg BID (ratio, 0.34; 95% CI, 0.18-0.65; P = .0014) dose groups, corresponding to 77% and 66% reductions, respectively. Dexpramipexole reduced the exploratory end point of nasal eosinophil peroxidase week-12 ratio to baseline in the 150-mg BID (median, 0.11; P = .020) and the 75-mg BID (median, 0.17; P = .021) groups. Placebo-corrected FEV1 increases were observed starting at week 4 (nonsignificant). Dexpramipexole displayed a favorable safety profile. CONCLUSIONS: Dexpramipexole demonstrated effective eosinophil lowering and was well tolerated. Additional larger clinical trials are needed to understand the clinical efficacy of dexpramipexole in asthma.

Development of a tool to detect small airways dysfunction in asthma clinical practice.

BACKGROUND: Small airways dysfunction (SAD) in asthma is difficult to measure and a gold standard is lacking. The aim of this study was to develop a simple tool including items of the Small Airways Dysfunction Tool (SADT) questionnaire, basic patient characteristics and respiratory tests available depending on the clinical setting to predict SAD in asthma. METHODS: This study was based on the data of the multinational ATLANTIS (Assessment of Small Airways Involvement in Asthma) study including the earlier developed SADT questionnaire. Key SADT items together with clinical information were now used to build logistic regression models to predict SAD group (less likely or more likely to have SAD). Diagnostic ability of the models was expressed as area under the receiver operating characteristic curve (AUC) and positive likelihood ratio (LR+). RESULTS: SADT item 8, "I sometimes wheeze when I am sitting or lying quietly", and the patient characteristics age, age at asthma diagnosis and body mass index could reasonably well detect SAD (AUC 0.74, LR+ 2.3). The diagnostic ability increased by adding spirometry (percentage predicted forced expiratory volume in 1 s: AUC 0.87, LR+ 5.0) and oscillometry (resistance difference between 5 and 20 Hz and reactance area: AUC 0.96, LR+ 12.8). CONCLUSIONS: If access to respiratory tests is limited (e.g. primary care in many countries), patients with SAD could reasonably well be identified by asking about wheezing at rest and a few patient characteristics. In (advanced) hospital settings patients with SAD could be identified with considerably higher accuracy using spirometry and oscillometry.

An epithelial gene signature of trans-IL-6 signaling defines a subgroup of type 2-low asthma.

BACKGROUND: Asthma is stratified into type 2-high and type 2-low inflammatory phenotypes. Limited success has been achieved in developing drugs that target type 2-low inflammation. Previous studies have linked IL-6 signaling to severe asthma. IL-6 cooperates with soluble-IL-6Rα to activate cell signaling in airway epithelium. OBJECTIVE: We sought to study the role of sIL-6Rα amplified IL-6 signaling in airway epithelium and to develop an IL-6+ sIL-6Rα gene signature that may be used to select asthma patients who potentially respond to anti-IL-6 therapy. METHODS: Human airway epithelial cells were stimulated with combinations of IL-6, sIL-6Rα, and inhibitors, sgp130 (Olamkicept), and anti-IL-6R (Tocilizumab), to assess effects on pathway activation, epithelial barrier integrity, and gene expression. A gene signature was generated to identify IL-6 high patients using bronchial biopsies and nasal brushes. RESULTS: Soluble-IL-6Rα amplified the activation of the IL-6 pathway, shown by the increase of STAT3 phosphorylation and stronger gene induction in airway epithelial cells compared to IL-6 alone. Olamkicept and Tocilizumab inhibited the effect of IL-6 + sIL-6Rα on gene expression. We developed an IL-6 + sIL-6Rα gene signature and observed enrichment of this signature in bronchial biopsies but not nasal brushes from asthma patients compared to healthy controls. An IL-6 + sIL-6Rα gene signature score was associated with lower levels of sputum eosinophils in asthma. CONCLUSION: sIL-6Rα amplifies IL-6 signaling in bronchial epithelial cells. Higher local airway IL-6 + sIL-6Rα signaling is observed in asthma patients with low sputum eosinophils.

Clinical Trial Design Innovations for Precision Medicine in Asthma.

Severe asthma is a spectrum disorder with numerous subsets, many of which are defined by clinical history and a general predisposition for T2 inflammation. Most of the approved therapies for severe asthma have required clinical trial designs with population enrichment for exacerbation frequency and/or elevation of blood eosinophils. Moving beyond this framework will require trial designs that increase efficiency for studying nondominant subsets and continue to improve upon biomarker signatures. In addition to reviewing the current literature on biomarker-informed trials for severe asthma, this chapter will also review the advantages of master protocols and adaptive design methods for establishing the efficacy of new interventions in prospectively defined subsets of patients. The incorporation of methods that allow for data collection outside of traditional study visits at academic centers, called remote decentralized trial design, is a growing trend that may increase diversity in study participation and allow for enhanced resiliency during the COVID-19 pandemic. Finally, reaching the goals of precision medicine in asthma will require increased emphasis on effectiveness studies. Recent advances in real-world data utilization from electronic health records are also discussed with a view toward pragmatic trial designs that could also incorporate the evaluation of biomarker signatures.

Considering biomarkers in asthma disease severity.

Among patients with asthma, reliance on the type/dose of prescribed medication and symptom control does not adequately capture those at risk of adverse outcomes, and we need biomarkers for risk and treatment stratification that are consistently accurate, readily quantifiable, and reproducible. Most patients with severe asthma, regardless of age, have predominant type-2 inflammation-mediated disease, making airway/blood eosinophils, fractional exhaled nitric oxide, periostin, and/or allergic sensitization potentially important biomarkers for severe disease. In both adult and pediatric asthma, there is scope to improve prediction of severe attacks by using a composite type-2 biomarker of blood eosinophils and fractional exhaled nitric oxide. Technological advances in component-resolved diagnostics microarray technologies coupled with the development of interpretation software offer a possibility to use component-resolved diagnostics as biomarkers of asthma severity among sensitized patients with asthma. Genetic predisposition and polygenic risk scores of relevant traits (eg, lung function, host immune responses, biomarkers of exposure from the indoor and outdoor environment, infection, and microbial dysbiosis) may also contribute to prediction algorithms. We challenge the idea that asthma can be accurately defined in an individual patient by a discrete and static "endotype" (eg, type-2-high asthma). As we traverse the new era of molecular endotyping in asthma, we need to understand how relevant mechanisms impact patient outcomes, and in parallel develop new tools and approaches to stratify therapies and define individual patient trajectories.

IoT-based disease prediction using machine learning.

COVID-19 disrupted lives and livelihoods and affected various sectors of the economy. One such domain was the already overburdened healthcare sector, which faced fresh challenges as the number of patients rose exponentially and became difficult to deal with. In such a scenario, telemedicine, teleconsultation, and virtual consultation became increasingly common to comply with social distancing norms. To overcome this pressing need of increasing 'remote' consultations in the 'post-COVID' era, the Internet of Things (IoT) has the potential to play a pivotal role, and this present paper attempts to develop a novel system that implements the most efficient machine learning (ML) algorithm and takes input from the patients such as symptoms, audio recordings, available medical reports, and other histories of illnesses to accurately and holistically predict the disease that the patients are suffering from. A few of the symptoms, such as fever and low blood oxygen, can also be measured via sensors using Arduino and ESP8266. It then provides for the appropriate diagnosis and treatment of the disease based on its constantly updated database, which can be developed as an application-based or website-based platform.

Biologic therapy practices in severe asthma; outcomes from the UK Severe Asthma Registry and survey of specialist opinion.

BACKGROUND: several biological treatments have become available for management of severe asthma. There is a significant overlap in the indication of these treatments with lack of consensus on the first-line biologic choice and switching practice in event of treatment failure. AIMS: to evaluate outcomes of biologic treatments through analysis of the UK Severe Asthma Registry (UKSAR), and survey of the UK severe asthma specialists' opinion. METHODS: patients registered in the UKSAR database and treated with biologics for severe asthma in the period between January 2014 and August 2021, were studied to explore biologic treatments practice. This was complemented by survey of opinion of severe asthma specialists. RESULTS: a total of 2,490 patients from 10 severe asthma centres were included in the study (mean age 51.3 years, 61.1% female, mean BMI 30.9kg/m2 ). Biologics use included mepolizumab 1,115 (44.8%), benralizumab 925 (37.1%), omalizumab 432 (17.3%), dupilumab 13 (0.5%), and reslizumab 5 (0.2%). Patients on omalizumab were younger and had earlier age of onset asthma than those prescribed mepolizumab or benralizumab. Patients prescribed mepolizumab and benralizumab had similar clinical characteristics. Those on benralizumab were more likely to continue treatment at approximately one year follow up (93.9%), than those on mepolizumab (80%), or omalizumab (69.6%). The first choice biologic differed between centres and changed over the study time period. Experts' opinion also diverged in terms of biologic initiation choice and switching practice. CONCLUSION: We observed significant variation and divergence in the prescribing practices of biologics in severe asthma that necessitates further research and standardisation.

Asymmetric Ru/Cinchonine Dual Catalysis for the One-Pot Synthesis of Optically Active Phthalides from Benzoic Acids and Acrylates.

Herein, we report the asymmetric Ru/cinchonine dual catalysis that provides straightforward access to enantioselective synthesis of C-3 substituted phthalides via tandem C-H activation/Michael addition cascade. The use of readily accessible and less expensive [RuCl2(p-cym)]2 and cinchonine catalyst for the one-pot assembly of chiral phthalides greatly overcomes the present trend of using highly sophisticated catalysts. The developed method provides access to both enantiomers of a product using pseudoenantiomeric cinchona alkaloids as catalysts streamlining the synthesis of phthalide in both the optically active forms.

Peripheral and proximal lung ventilation in asthma: Short-term variation and response to bronchodilator inhalation.

BACKGROUND: The relative involvement of the large and small airways in asthma is not clear. Hyperpolarized gas magnetic resonance imaging (MRI) provides high-resolution 3-dimensional images of ventilation distribution that can be quantified by the ventilated volume percentage (VV%) of the lungs. OBJECTIVE: Our aims were to (1) quantify the baseline reproducibility of VV%, (2) assess the ventilation distribution between the proximal and peripheral lungs, and (3) investigate regional ventilation response to bronchodilator inhalation in a cohort of patients with asthma. METHODS: A total of 33 patients with poorly controlled, moderate-to-severe asthma were scanned with hyperpolarized 3He MRI. Two image data sets were acquired at baseline, and 1 image data set was acquired after bronchodilator inhalation. Images were divided into proximal and peripheral regions for analysis. RESULTS: Bland-Altman analysis showed strong reproducibility of VV% (bias = 0.12%; LOA = -1.86% to 2.10%). VV% variation at baseline was greater in the periphery than in the proximal lung. The proximal lung was better ventilated than the peripheral lung. Ventilation increased significantly in response to bronchodilator inhalation, globally and regionally, and the ventilation increase in response to bronchodilator inhalation was greater in the peripheral lung than in the proximal lung. Hyperpolarized gas MRI was more sensitive to changes in response to bronchodilator inhalation (58%) than spirometry (33%). CONCLUSION: The peripheral lung showed reduced ventilation and a greater response to bronchodilator inhalation than the proximal lung. The high level of baseline reproducibility and sensitivity of hyperpolarized gas MRI to bronchodilator reversibility suggests that it is suitable for low subject number studies of therapy response.

Breathomics for the clinician: the use of volatile organic compounds in respiratory diseases.

Exhaled breath analysis has the potential to provide valuable insight on the status of various metabolic pathways taking place in the lungs locally and other vital organs, via systemic circulation. For years, volatile organic compounds (VOCs) have been proposed as feasible alternative diagnostic and prognostic biomarkers for different respiratory pathologies.We reviewed the currently published literature on the discovery of exhaled breath VOCs and their utilisation in various respiratory diseasesKey barriers in the development of clinical breath tests include the lack of unified consensus for breath collection and analysis and the complexity of understanding the relationship between the exhaled VOCs and the underlying metabolic pathways. We present a comprehensive overview, in light of published literature and our experience from coordinating a national breathomics centre, of the progress made to date and some of the key challenges in the field and ways to overcome them. We particularly focus on the relevance of breathomics to clinicians and the valuable insights it adds to diagnostics and disease monitoring.Breathomics holds great promise and our findings merit further large-scale multicentre diagnostic studies using standardised protocols to help position this novel technology at the centre of respiratory disease diagnostics.

The causes of a peripheral blood eosinophilia in a secondary care setting.

BACKGROUND: A peripheral blood eosinophilia of greater than 1.0 × 109 /L is relatively unusual and offers a clue to the underlying diagnosis. In 2003, we established a specialist service to diagnose unexplained eosinophilia. OBJECTIVE: To describe the causes of an eosinophilia in our service and the diagnostic algorithm we developed. METHODS: Subjects were referred by physician colleagues across a range of specialties and undertook standard investigations following a semi-structured protocol. Data were extracted from a bespoke database. RESULTS: Three hundred and eighty two subjects were referred over a 17-year period. Average age was 54 years and 183 (48%) of subjects were female, with 21 of 25 (84%) females in the idiopathic eosinophilic pneumonia group (p < 0001), 22 of 30 (73%) females in the gastrointestinal disease group (p < .008), but 11 of 37 (30%) females in the eosinophilic granulomatosis with polyangiitis group (p < .04). A diagnosis was assigned after systematic evaluation using a pre-defined algorithm in 361 (94.5%) of cases. Fungal allergy (82 subjects: 21%), parasitic infection (61 subjects: 16%) and severe eosinophilic asthma (50 subjects: 13%) were the three commonest individual diagnoses. Hypereosinophilic syndrome (HES) disease including eosinophilic granulomatosis with polyangiitis (EGPA) accounted for 85 subjects (20%) of which seven subjects (2%) had myeloproliferative disease (M-HES). A high IgE was common, and 79 (91%) of subjects with complete data who had an IgE of ≥1000 IU/L had fungal allergy or parasite infection. The serum tryptase was raised in 44 of 302 (14.5%) of individuals across all diagnostic groups, though none had mastocytosis. CONCLUSION: A diagnosis of an unexplained eosinophilia can usually be determined using as semi-structured algorithm. Parasitic infection and fungal allergy often with severe eosinophilic asthma were common causes, whereas HES, particularly myeloproliferative, disease was relatively rare.

LabPipe: an extensible bioinformatics toolkit to manage experimental data and metadata.

BACKGROUND: Data handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data generated locally by vendor software. RESULTS: To address this problem, we created LabPipe, a flexible toolkit which is driven through a local client that runs alongside vendor software and connects to a light-weight server. The toolkit allows re-usable configurations to be defined for experiment metadata and local data collection, and handles metadata entry and linkage of data. LabPipe was piloted in a multi-site clinical breathomics study. CONCLUSIONS: LabPipe provided a consistent, controlled approach for handling metadata and experimental data collection, collation and linkage in the exemplar study and was flexible enough to deal effectively with different data handling challenges.

Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software.

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in 1tR and 2tR was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.

Blood eosinophils as a biomarker of future COPD exacerbation risk: pooled data from 11 clinical trials.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterised by progressive airflow limitation and chronic inflammation. Predicting exacerbations of COPD, which contribute to disease progression, is important to guide preventative treatment and improve outcomes. Blood eosinophils are a biomarker for patient responsiveness to inhaled corticosteroids (ICS); however, their effectiveness as a predictive biomarker for COPD exacerbations is unclear. METHODS: This post hoc analysis pooled data from 11 Boehringer Ingelheim-sponsored Phase III and IV randomised COPD studies with similar methodologies. Exacerbation data were collected from these studies, excluding patients from the ICS withdrawal arm of the WISDOM® study. Patients were grouped according to their baseline blood eosinophil count, baseline ICS use and number of exacerbations in the year prior to each study. RESULTS: Exacerbation rate data and baseline eosinophil count were available for 22,125 patients; 45.6% presented with a baseline blood eosinophil count of ≤ 150 cells/µL, 34.3% with 150-300 cells/µL and 20.1% with > 300 cells/µL. The lowest exacerbation rates were observed in patients with ≤ 150 cells/µL, with small increases in exacerbation rate observed with increasing eosinophil count. When stratified by exacerbation history, the annual rate of exacerbations for patients with 0 exacerbations in the previous year increased in line with increasing eosinophil counts (0.38 for ≤ 150 cells/µL, 0.39 for 150-300 cells/µL and 0.44 for > 300 cells/µL respectively). A similar trend was identified for patients with one exacerbation in the previous year, 0.62, 0.66 and 0.67 respectively. For patients with ≥ 2 exacerbations, exacerbation rates fluctuated between 1.02 (≤ 150 cells/µL) to 1.10 (150-300 cells/µL) and 1.07 (> 300 cells/µL). Higher exacerbation rates were noted in patients treated with ICS at baseline (range 0.75 to 0.82 with increasing eosinophil count) compared with patients not on ICS (range 0.45 to 0.49). CONCLUSION: We found no clinically important relationship between baseline blood eosinophil count and exacerbation rate. Hence, the current analysis does not support the use of blood eosinophils to predict exacerbation risk; however, previous exacerbation history was found to be a more reliable predictor of future exacerbations. TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: NCT00168844 , NCT00168831 , NCT00387088 , NCT00782210 , NCT00782509 , NCT00793624 , NCT00796653 , NCT01431274 , NCT01431287 , NCT02296138 and NCT00975195 .