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Rationale: The past 25 years have seen huge progress in understanding of the pathobiology of type-2 (T2) asthma, identification of measurable biomarkers, and the emergence of novel monoclonal antibody treatments. Although present in a minority of patients with severe asthma, very little is known about the mechanisms underlying T2-low asthma, making it a significant unmet need in asthma research. Objectives: The objective of this study was to explore the differences between study exacerbators and nonexacerbators, to describe physiological changes at exacerbation in those who are T2 HIGH and T2 LOW at the time of exacerbation, and to evaluate the stability of inflammatory phenotypes when stable and at exacerbation. Methods: Exacerbation assessment was a prespecified secondary analysis of data from a 48-week, multicenter, randomized controlled clinical study comparing the use of biomarkers and symptoms to adjust steroid treatment in a T2-low severe asthma-enriched cohort. Participants were phenotyped as T2 LOW (fractional exhaled nitric oxide < 20 ppb and blood eosinophil count < 150 cells/ml) or T2 HIGH (fractional exhaled nitric oxide. 20 or blood eosinophil count. 150) at study enrollment and at each exacerbation. Here, we report the findings of the exacerbation analyses, including comparison of exacerbators and nonexacerbators, the physiological changes at exacerbation in those who had evidence of T2 biology at exacerbation versus those that did not, and the stability of inflammatory phenotypes when stable and at exacerbation.Measurements and Main Results: Of the 301 participants, 60.8% (183) had one or more self-reported exacerbations (total of 390). Exacerbators were more likely to be female, have a higher body mass index, and have more exacerbations requiring oral corticosteroid and unscheduled primary care attendances for exacerbations. At enrollment, 23.6% (71) were T2 LOW and 76.4% (230) T2 HIGH. The T2 LOW group had more asthma primary care attendances, were more likely to have a previous admission to HDU (high dependency unit)/ICU and to be receiving maintenance oral corticosteroids. At exacerbation, the T2 LOW events were indistinguishable from T2 HIGH exacerbations in terms of lung function (mean fall in T2 LOW FEV 1, 200 [400] ml vs. T2 HIGH 200 [300] ml; P = 0.93) and symptom increase (ACQ5: T2 LOW, 1.4 [0.8] vs. T2 HIGH, 1.3 [0.8]; P = 0.72), with no increase in T2 biomarkers from stable to exacerbation state in the T2 LOW exacerbations. The inflammatory phenotype within individual patients was dynamic; inflammatory phenotype at study entry did not have a significant association with exacerbation phenotype. Conclusions: Asthma exacerbations demonstrating a T2 LOW phenotype were physiologically and symptomatically similar to T2 HIGH exacerbations. T2 LOW asthma was an unstable phenotype, suggesting that exacerbation phenotyping should occur at the time of exacerbation. The clinically significant exacerbations in participants without evidence of T2 biology at the time of exacerbation highlight the unmet and pressing need to further understand the mechanisms at play in non-T2 asthma.

Background: The most recognizable phenotype of severe asthma comprises people who are blood eosinophil and FeNO-high, driven by type-2 (T2) cytokine biology which responds to targeted biological therapies. However, in many people with severe asthma, these T2 biomarkers are suppressed but poorly controlled asthma persists. The mechanisms driving asthma in the absence of T2 biology are poorly understood. Objectives: To explore airway pathology in T2 biomarker-high and -low severe asthma. Methods: T2 biomarker-high severe asthma (T2-high, n=17) was compared to biomarker-intermediate (T2-intermediate, n=21) and biomarker-low (T2-low, n=20) severe asthma, and healthy controls (n=28). Bronchoscopy samples were processed for immunohistochemistry, and sputum for cytokines, PGD2 and LTE4 measurements. Results: Tissue eosinophil, neutrophil and mast cell counts were similar across severe asthma phenotypes and not increased when compared to healthy controls. In contrast, the remodeling features of airway smooth muscle mass and MUC5AC expression were increased in all asthma groups compared to health, but similar across asthma subgroups. Submucosal glands were increased in T2-intermediate and T2-low asthma. In spite of similar tissue cellular inflammation, sputum IL-4, IL-5, and CCL26 were increased in T2-high versus T2-low asthma, and several further T2-associated cytokines, PGD2 and LTE4, were increased in T2-high and T2-intermediate asthma compared to healthy controls. Conclusions: Eosinophilic tissue inflammation within proximal airways is suppressed in T2 biomarker-high and T2-low severe asthma, but inflammatory and structural cell activation is present, with sputum T2-associated cytokines highest in T2 biomarker-high patients. Airway remodeling persists, and may be important for residual disease expression beyond eosinophilic exacerbations.

BackgroundEffectiveness studies with biological therapies for asthma lack standardised outcome measures. The COMSA (Core Outcome Measures sets for paediatric and adult Severe Asthma) Working Group sought to develop Core Outcome Measures (COM) sets to facilitate better synthesis of data and appraisal of biologics in paediatric and adult asthma clinical studies.MethodsCOMSA utilised a multi-stakeholder consensus process among patients with severe asthma, adult and paediatric clinicians, pharmaceutical representatives, and health regulators from across Europe. Evidence included a systematic review of development, validity and reliability of selected outcome measures plus a narrative review and a pan-European survey to better understand patients’ and carers’ views about outcome measures. It was discussed using a modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) Evidence to Decision framework. Anonymous voting was conducted using predefined consensus criteria.ResultsBoth adult and paediatric COM sets include forced expiratory volume in 1 s (FEV1) as z-scores, annual frequency of severe exacerbations and maintenance oral corticosteroid use. Additionally, the paediatric COM set includes the Paediatric Asthma Quality of Life Questionnaire and Asthma Control Test or Childhood Asthma Control Test, while the adult COM set includes the Severe Asthma Questionnaire and Asthma Control Questionnaire-6 (symptoms and rescue medication use reported separately).ConclusionsThis patient-centred collaboration has produced two COM sets for paediatric and adult severe asthma. It is expected that they will inform the methodology of future clinical trials, enhance comparability of efficacy and effectiveness of biological therapies, and help assess their socioeconomic value. COMSA will inform definitions of non-response and response to biological therapy for severe asthma.

BackgroundApproximately 5% to 10% of patients with asthma have severe disease, with a consistent preponderance in females. Current asthma guidelines recommend stepwise treatment to achieve symptom control with no differential treatment considerations for either sex.ObjectiveTo examine whether patient sex affects outcomes when using a composite T2-biomarker score to adjust corticosteroid (CS) treatment in patients with severe asthma compared with standard care.MethodsThis is a post hoc analysis, stratifying patient outcomes by sex, of a 48-week, multicenter, randomized controlled clinical trial comparing a biomarker-defined treatment algorithm with standard care. The primary outcome was the proportion of patients with a reduction in CS treatment (inhaled and oral corticosteroids). Secondary outcomes included exacerbation rates, hospital admissions, and lung function.ResultsOf the 301 patients randomized, 194 (64.5%) were females and 107 (35.5%) were males. The biomarker algorithm led to a greater proportion of females being on a lower CS dose versus standard care, which was not seen in males (effect estimate: females, 3.57; 95% CI, 1.14-11.18 vs males, 0.54; 95% CI, 0.16-1.80). In T2-biomarker–low females, reducing CS dose was not associated with increased exacerbations. Females scored higher in all domains of the 7-item Asthma Control Questionnaire, apart from FEV1, but with no difference when adjusted for body mass index/anxiety and/or depression. Dissociation between symptoms and T2 biomarkers were noted in both sexes, with a higher proportion of females being symptom high/T2-biomarker low (22.8% vs 15.6%; P = .0002), whereas males were symptom low/T2-biomarker high (22.3% vs 11.4%; P < .0001).ConclusionsThis exploratory post hoc analysis identified that females achieved a greater benefit from biomarker-directed CS optimization versus symptom-directed treatment.

Background Early and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as noninvasive biomarkers of infection to support clinical diagnosis. Methods In this study, we investigated the diagnostic potential of in vitro–confirmed mVOCs in the exhaled breath of patients under mechanical ventilation from the BreathDx study. Samples were analyzed by thermal desorption–gas chromatography–mass spectrometry. Results Pathogens from bronchoalveolar lavage (BAL) cultures were identified in 45 of 89 patients and Staphylococcus aureus was the most commonly identified pathogen (n = 15). Of 19 mVOCs detected in the in vitro culture headspace of 4 common respiratory pathogens (S. aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of 2 mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal: P < .01, area under the receiver operating characteristic curve [AUROC] = 0.81–0.87; and 3-methylbutanoic acid: P = .01, AUROC = 0.79–0.80). In addition, bacteria identified from BAL cultures that are known to metabolize tryptophan (E. coli, Klebsiella oxytoca, and Haemophilus influenzae) were grouped and found to produce higher concentrations of indole compared to breath samples with culture-negative (P = .034) and other pathogen-positive (P = .049) samples. Conclusions This study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multicenter clinical studies.

BACKGROUND: Domiciliary measurements of airflow obstruction and inflammation may assist healthcare teams and patients in determining asthma control and facilitate self-management.OBJECTIVE: We aimed to evaluate parameters derived from domiciliary spirometry and fractional exhaled nitric oxide (FeNO) in monitoring asthma exacerbations and control.METHODS: Patients with asthma were provided with hand-held spirometry and FeNO devices in addition to their usual asthma care. Patients were instructed to perform twice-daily measurements for one month. Daily symptoms and medication change were reported through a mobile health system. The Asthma Control Questionnaire was completed at the end of the monitoring period.RESULTS: One hundred patients had spirometry, of which 60 were given additional FeNO devices. Compliance rates for twice-daily measurements were poor (median [IQR]: 43 (25-62)% for spirometry; 30 [3-48]% for FeNO); at least 15% of patients took little or no spirometry measurements and 40% rarely measured FeNO. The coefficient of variation (CV) in FEV 1 and FeNO were higher, and the mean % personal best FEV 1 lower in those who had major exacerbations compared to those without (pCONCLUSION: Compliance with domiciliary spirometry and FeNO varied widely amongst patients even in the setting of a research study. However, despite significant missing data, FeNO and FEV 1 were associated with asthma exacerbations and control, making these measurements potentially clinically valuable if used.

Early detection of lung infection is critical to clinical diagnosis, treatment, and monitoring. Measuring volatile organic compounds (VOCs) in exhaled breath has shown promise as a rapid and accurate method of evaluating disease metabolism and phenotype. However, further investigations of the role and function of VOCs in bacterial-host-stress response is required and this can only be realised through representative

Early detection of lung infection is critical to clinical diagnosis, treatment, and monitoring. Measuring volatile organic compounds (VOCs) in exhaled breath has shown promise as a rapid and accurate method of evaluating disease metabolism and phenotype. However, further investigations of the role and function of VOCs in bacterial-host-stress response is required and this can only be realised through representative in vitro models. In this study we sampled VOCs from the headspace of A549 cells at an air-liquid interface (ALI). We hypothesised VOC sampling from ALI cultures could be used to profile potential biomarkers of S. aureus lung infection. VOCs were collected using thin film microextraction (TFME) and were analysed by thermal desorption-gas chromatography-mass spectrometry. After optimising ALI cultures, we observed seven VOCs changed between A549 and media control samples. After infecting cells with S. aureus, supervised principal component-discriminant function analysis revealed 22 VOCs were found to be significantly changed in infected cells compared to uninfected cells (p < 0.05), five of which were also found in parallel axenic S. aureus cultures. We have demonstrated VOCs that could be used to identify S. aureus in ALI cultures, supporting further investigation of VOC analysis as a highly sensitive and specific test for S. aureus lung infection.

RATIONALE Children with preschool wheezing or school-age asthma are reported to have airway microbial imbalances. OBJECTIVE To identify clusters in children with asthma or wheezing using oropharyngeal microbiota profiles. METHODS Oropharyngeal swabs, from the Unbiased BIOmarkers for the Prediction of REspiratory Disease outcomes pediatric asthma/wheezing cohort, were characterized by 16S rRNA gene sequencing and unsupervised hierarchical clustering was performed on the Bray-Curtis β-diversity. Enrichment scores (ESs) of the MSigDB Hallmark gene sets were computed from the blood transcriptome using gene set variation analysis. Children with severe asthma or severe wheezing were followed up for 12-18 months, with assessing the frequency of exacerbations. MEASUREMENTS AND MAIN RESULTS Oropharyngeal samples of 241 children (age range: 1-17 years, 40% female) revealed 4 taxa-driven clusters dominated by Streptococcus, Veillonella, Rothia and Haemophilus, respectively. The clusters showed significant differences in atopic dermatitis, grass pollen sensitization, FEV1 % predicted post-salbutamol, and the annual asthma exacerbation frequency during follow-up. The Veillonella-cluster was the most allergic and included highest percentage of children with ≥2 exacerbations/year during follow-up. The oropharyngeal clusters were different in the ESs of transforming growth factor β (highest in Veillonella-cluster) and Wnt/β-Catenin signaling (highest in Haemophilus-cluster) transcriptomic pathways in blood (all q-values < 0.05). CONCLUSION The analysis of the oropharyngeal microbiota of children with asthma/wheezing identified four clusters with distinct clinical characteristics (phenotypes) that associate with exacerbations' risk and transcriptomic pathways involved in airway remodeling. This suggests that further exploration of the oropharyngeal microbiota may lead to novel pathophysiological insights and potentially new treatment approaches.

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; FEV 1, 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.

Fungal sensitization is associated with poor asthma control. We aimed to determine the prevalence and factors associated with fungal asthma among Ugandan adults. Individuals aged ≥18 years with a new diagnosis of asthma in the last 12 months participating in the African Severe Asthma Program constituted the study population. Skin prick test results, clinical and demographic data were retrieved from the database, and serum Aspergillus fumigatus specific antibodies and total IgE were measured in stored blood. We enrolled 374 patients, median (IQR) age 34 (25–45) years, 286 (76.5%) females and 286 (76.5%) with severe asthma. Prevalence of Aspergillus fumigatus sensitization was 42.0% (95% CI: 37.1–47.0%), allergic bronchopulmonary aspergillosis (ABPA) 3.2% (1.8–5.5%), severe asthma with fungal sensitization (SAFS) 16% (12.7–20.1%) and allergic bronchopulmonary mycosis (ABPM) 2.9% (1.7–5.2%). Older age (55–64 years) (crude odds ratio (cOR) = 2.6), sensitization to at least one allergen (cOR = 9.38) and hypertension (cOR = 1.99) were significantly associated with Aspergillus sensitization, whereas tertiary education level (cOR = 0.29), severe depression (cOR = 0.15) and strong emotions (cOR = 0.47) were not. High occupational exposure to Aspergillus (cOR = 4.26) and contact with moulds (cOR = 14.28) were significantly associated with ABPA. Palpitations (cOR = 5.54), uncontrolled asthma (cOR = 3.54), eczema/dermatitis (cOR = 3.07), poor lung function (cOR = 2.11) and frequent exacerbations (cOR = 1.01) were significantly associated with SAFS. Eczema/dermatitis (cOR = 1.55) was significantly associated with ABPM, but cold weather trigger (cOR = 0.24) was not. Fungal asthma is a significant problem among Ugandans with asthma and should be particularly considered in individuals who remain uncontrolled despite optimal standard of care for asthma, as it is responsive to available and affordable oral antifungal therapy. Lay Summary This study showed that fungal asthma is a significant problem among Ugandans with asthma with a high prevalence. Fungal asthma should be considered in patients with uncontrolled asthma despite receiving optimal standard of care. This is the first modern attempt to define these endotypes of asthma in Africa.

Asthma is the most common chronic respiratory disease in the UK; however, the misdiagnosis rate is substantial. The lack of consistency in national guidelines and the paucity of data on the performance of diagnostic algorithms compound the challenges in asthma diagnosis. Asthma is a highly rhythmic disease, characterised by diurnal variability in clinical symptoms and pathogenesis. Asthma also varies day to day, seasonally and from year to year. As much as it is a hallmark for asthma, this variability also poses significant challenges to asthma diagnosis. Almost all established asthma diagnostic tools demonstrate diurnal variation, yet few are performed with standardised timing of measurements. The dichotomous interpretation of diagnostic outcomes using fixed cut-off values may further limit the accuracy of the tests, particularly when diurnal variability straddles cut-off values within a day, and careful interpretation beyond the ‘positive’ and ‘negative’ outcome is needed. The day-to-day and more long-term variations are less predictable and it is unclear whether performing asthma diagnostic tests during asymptomatic periods may influence diagnostic sensitivities. With the evolution of asthma diagnostic tools, home monitoring and digital apps, novel strategies are needed to bridge these gaps in knowledge, and circadian variability should be considered during the standardisation process. This review summarises the biological mechanisms of circadian rhythms in asthma and highlights novel data on the significance of time (the fourth dimension) in asthma diagnosis.

Background: Asthma treatment guidelines recommend increasing corticosteroid dose to control symptoms and reduce exacerbations. This approach is potentially flawed because symptomatic asthma can occur without corticosteroid responsive type-2 (T2)-driven eosinophilic inflammation, and inappropriately high-dose corticosteroid treatment might have little therapeutic benefit with increased risk of side-effects. We compared a biomarker strategy to adjust corticosteroid dose using a composite score of T2 biomarkers (fractional exhaled nitric oxide [FENO], blood eosinophils, and serum periostin) with a standardised symptom–risk-based algorithm (control). Methods: We did a single-blind, parallel group, randomised controlled trial in adults (18–80 years of age) with severe asthma (at treatment steps 4 and 5 of the Global Initiative for Asthma) and FENO of less than 45 parts per billion at12 specialist severe asthma centres across England, Scotland, and Northern Ireland. Patients were randomly assigned (4:1) to either the biomarker strategy group or the control group by an online electronic case-report form, in blocks of ten, stratified by asthma control and use of rescue systemic steroids in the previous year. Patients were masked to study group allocation throughout the entirety of the study. Patients attended clinic every 8 weeks, with treatment adjustment following automated treatment-group-specific algorithms: those in the biomarker strategy group received a default advisory to maintain treatment and those in the control group had their treatment adjusted according to the steps indicated by the trial algorithm. The primary outcome was the proportion of patients with corticosteroid dose reduction at week 48, in the intention-to-treat (ITT) population. Secondary outcomes were inhaled corticosteroid (ICS) dose at the end of the study; cumulative dose of ICS during the study; proportion of patients on maintenance oral corticosteroids (OCS) at study end; rate of protocol-defined severe exacerbations per patient year; time to first severe exacerbation; number of hospital admissions for asthma; changes in lung function, Asthma Control Questionnaire-7 score, Asthma Quality of Life Questionnaire score, and T2 biomarkers from baseline to week 48; and whether patients declined to progress to OCS. A secondary aim of our study was to establish the proportion of patients with severe asthma in whom T2 biomarkers remained low when corticosteroid therapy was decreased to a minimum ICS dose. This study is registered with ClinicalTrials.gov, NCT02717689 and has been completed. Findings: Patients were recruited from Jan 8, 2016, to July 12, 2018. Of 549 patients assessed, 301 patients were included in the ITT population and were randomly assigned to the biomarker strategy group (n=240) or to the control group(n=61). 28·4% of patients in the biomarker strategy group were on a lower corticosteroid dose at week 48 compared with 18·5% of patients in the control group (adjusted odds ratio [aOR] 1·71 [95% CI 0·80–3·63]; p=0·17). In the per-protocol (PP) population (n=121), a significantly greater proportion of patients were on a lower corticosteroid dose at week 48 in the biomarker strategy group (30·7% of patients) compared with the control group (5·0% of patients; aOR 11·48 [95% CI 1·35–97·83]; p=0·026). Patient choice to not follow treatment advice was the principle reason for loss to PP analysis. There was no difference in secondary outcomes between study groups and no loss of asthma control among patients in the biomarker strategy group who reduced their corticosteroid dose. Interpretation: Biomarker-based corticosteroid adjustment did not result in a greater proportion of patients reducing corticosteroid dose versus control. Understanding the reasons for patients not following treatment advice in both treatment strategies is an important area for future research. The prevalence of T2 biomarker-low severe asthma was low.

BACKGROUND: Electronic noses (eNoses) are emerging point-of-care tools that may help in the subphenotyping of chronic respiratory diseases such as asthma.OBJECTIVE: We aimed to investigate whether eNoses can classify atopy in pediatric and adult patients with asthma.METHODS: Participants with asthma and/or wheezing from 4 independent cohorts were included; BreathCloud participants (n = 429), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adults (n = 96), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes pediatric participants (n = 100), and Pharmacogenetics of Asthma Medication in Children: Medication with Anti-Inflammatory Effects 2 participants (n = 30). Atopy was defined as a positive skin prick test result (≥3 mm) and/or a positive specific IgE level (≥0.35 kU/L) for common allergens. Exhaled breath profiles were measured by using either an integrated eNose platform or the SpiroNose. Data were divided into 2 training and 2 validation sets according to the technology used. Supervised data analysis involved the use of 3 different machine learning algorithms to classify patients with atopic versus nonatopic asthma with reporting of areas under the receiver operating characteristic curves as a measure of model performance. In addition, an unsupervised approach was performed by using a bayesian network to reveal data-driven relationships between eNose volatile organic compound profiles and asthma characteristics.RESULTS: Breath profiles of 655 participants (n = 601 adults and school-aged children with asthma and 54 preschool children with wheezing [68.2% of whom were atopic]) were included in this study. Machine learning models utilizing volatile organic compound profiles discriminated between atopic and nonatopic participants with areas under the receiver operating characteristic curves of at least 0.84 and 0.72 in the training and validation sets, respectively. The unsupervised approach revealed that breath profiles classifying atopy are not confounded by other patient characteristics.CONCLUSION: eNoses accurately detect atopy in individuals with asthma and wheezing in cohorts with different age groups and could be used in asthma phenotyping.

Aims This study sought to assess the volatile organic compound (VOC) profiles of ampicillin-resistant and -susceptible Escherichia coli to evaluate whether VOC analysis may be utilized to identify resistant phenotypes. Methods and Results An E. coli BL21 (DE3) strain and its pET16b plasmid transformed ampicillin-resistant counterpart were cultured for 6 h in drug-free, low- and high-concentrations of ampicillin. Headspace analysis was undertaken using thermal desorption-gas chromatography-mass spectrometry. Results revealed distinct VOC profiles with ampicillin-resistant bacteria distinguishable from their susceptible counterparts using as few as six compounds. A minimum of 30 compounds (fold change >2, p ≤ 0.05) were differentially expressed between the strains across all set-ups. Furthermore, three compounds (indole, acetoin and 3-methyl-1-butanol) were observed to be significantly more abundant (fold change >2, p ≤ 0.05) in the resistant strain compared to the susceptible strain both in the presence and in the absence of drug stress. Conclusions Results indicate that E. coli with acquired ampicillin resistance exhibit an altered VOC profile compared to their susceptible counterpart both in the presence and in the absence of antibiotic stress. This suggests that there are fundamental differences between the metabolisms of ampicillin-resistant and -susceptible E. coli which may be detected by means of VOC analysis. Significance and Impact of the Study Our findings suggest that VOC profiles may be utilized to differentiate between resistant and susceptible bacteria using just six compounds. Consequently, the development of machine-learning models using VOC signatures shows considerable diagnostic applicability for the rapid and accurate detection of antimicrobial resistance.

Antimicrobial resistance is increasing in prevalence and there is a clear need for the development of rapid detection methods in clinical diagnostics. This review explores -omics studies utilising mass spectrometry to investigate the molecular phenotype associated with carbapenem resistance. Whilst the specific mechanisms of carbapenem resistance are well characterised, the resistant phenotype is poorly understood. Understanding how the acquisition of resistance affects cellular physiology and cell metabolism through molecular phenotyping is a necessary step towards detecting resistance by diagnostic means. In addition, this article examines the potential of mass spectrometry for the identification of resistance biomarkers through molecular profiling of bacteria. Developments in mass spectrometry platforms are expanding the biomarker-based diagnostic landscape. Targeted measures, such as high-resolution mass spectrometry coupled with chromatographic separation show considerable promise for the identification of molecular signatures and the development of a rapid diagnostic assay for the detection of carbapenem resistance.

IntroductionInducible laryngeal obstruction (ILO) describes transient laryngeal closure during respiration and can cause significant morbidity. Non-pharmacological behavioural therapy is the commonly cited treatment but efficacy is largely unknown.AimTo synthesise the current evidence base on the effectiveness of non-pharmacological interventions used to treat adults with ILO.MethodsElectronic databases (Medline/Embase/CINAHL/PsycINFO/AMED/CENTRAL) were systematically searched, informed by a population, intervention, comparison, outcome framework. Two reviewers independently screened a representative sample, with lead-author completion due to excellent inter-rater reliability. Data was extracted using a predefined piloted form. Methodological quality was appraised (blindly by two reviewers) using the Joanna Briggs Institute Critical Appraisal Tools. A narrative synthesis was performed due to heterogeneity of studies (PROSPERO registration number: CRD42020213187).ResultsInitial searching identified 3359 records. Full-text screening occurred in 92 records and 14 studies, comprising 527 participants, were deemed eligible. All studies were low-level evidence (observational by design, with four case reports), with a high risk of bias; none contained control arms for comparison. Intervention description was inconsistently and poorly described but direction of effect was positive in 76% of outcomes measured. The majority of studies showed a reduction in symptom scores and improved direct laryngeal imaging post intervention; there was an overall reduction, 59.5%, in healthcare utilisation.DiscussionThe literature is in an embryonic state and lacks robust data to truly inform on the effectiveness of non-pharmacological interventions used to treat adults with ILO. However, positive signals in the synthesis performed support non-pharmacological treatment approaches and further development is warranted.

Background: Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases. Objective: We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti–IL-22 (fezakinumab [FZ]) is enriched in severe asthma. Methods: An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort. Results: The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, T H2, and T H17/T H22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P H22/IL-22 pathways. Conclusions: The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

IntroductionAsthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication.MethodsBaseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12–18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods.ResultsA total of 90 metabolites were identified, with 40 significantly altered (p−20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10−4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings.ConclusionsThis is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

Patients suspected of ventilator-associated lower respiratory tract infections (VA-LRTIs) commonly receive broad-spectrum antimicrobial therapy unnecessarily. We tested whether exhaled breath analysis can discriminate between patients suspected of VA-LRTI with confirmed infection, from patients with negative cultures. Breath from 108 patients suspected of VA-LRTI was analysed by gas chromatography-mass spectrometry. The breath test had a sensitivity of 98% at a specificity of 49%, confirmed with a second analytical method. The breath test had a negative predictive value of 96% and excluded pneumonia in half of the patients with negative cultures. Trial registration number: UKCRN ID number 19086, registered May 2015.

Summary Background BNT162b2 mRNA and ChAdOx1 nCOV-19 adenoviral vector vaccines have been rapidly rolled out in the UK from December, 2020. We aimed to determine the factors associated with vaccine coverage for both vaccines and documented the vaccine effectiveness of the BNT162b2 mRNA vaccine in a cohort of health-care workers undergoing regular asymptomatic testing. Methods The SIREN study is a prospective cohort study among staff (aged ≥18 years) working in publicly-funded hospitals in the UK. Participants were assigned into either the positive cohort (antibody positive or history of infection [indicated by previous positivity of antibody or PCR tests]) or the negative cohort (antibody negative with no previous positive test) at the beginning of the follow-up period. Baseline risk factors were collected at enrolment, symptom status was collected every 2 weeks, and vaccination status was collected through linkage to the National Immunisations Management System and questionnaires. Participants had fortnightly asymptomatic SARS-CoV-2 PCR testing and monthly antibody testing, and all tests (including symptomatic testing) outside SIREN were captured. Data cutoff for this analysis was Feb 5, 2021. The follow-up period was Dec 7, 2020, to Feb 5, 2021. The primary outcomes were vaccinated participants (binary ever vacinated variable; indicated by at least one vaccine dose recorded by at least one of the two vaccination data sources) for the vaccine coverage analysis and SARS-CoV-2 infection confirmed by a PCR test for the vaccine effectiveness analysis. We did a mixed-effect logistic regression analysis to identify factors associated with vaccine coverage. We used a piecewise exponential hazard mixed-effects model (shared frailty-type model) using a Poisson distribution to calculate hazard ratios to compare time-to-infection in unvaccinated and vaccinated participants and estimate the impact of the BNT162b2 vaccine on all PCR-positive infections (asymptomatic and symptomatic). This study is registered with ISRCTN, number ISRCTN11041050, and is ongoing. Findings 23 324 participants from 104 sites (all in England) met the inclusion criteria for this analysis and were enrolled. Included participants had a median age of 46·1 years (IQR 36·0–54·1) and 19 692 (84%) were female; 8203 (35%) were assigned to the positive cohort at the start of the analysis period, and 15 121 (65%) assigned to the negative cohort. Total follow-up time was 2 calendar months and 1 106 905 person-days (396 318 vaccinated and 710 587 unvaccinated). Vaccine coverage was 89% on Feb 5, 2021, 94% of whom had BNT162b2 vaccine. Significantly lower coverage was associated with previous infection, gender, age, ethnicity, job role, and Index of Multiple Deprivation score. During follow-up, there were 977 new infections in the unvaccinated cohort, an incidence density of 14 infections per 10 000 person-days; the vaccinated cohort had 71 new infections 21 days or more after their first dose (incidence density of eight infections per 10 000 person-days) and nine infections 7 days after the second dose (incidence density four infections per 10 000 person-days). In the unvaccinated cohort, 543 (56%) participants had typical COVID-19 symptoms and 140 (14%) were asymptomatic on or 14 days before their PCR positive test date, compared with 29 (36%) with typical COVID-19 symptoms and 15 (19%) asymptomatic in the vaccinated cohort. A single dose of BNT162b2 vaccine showed vaccine effectiveness of 70% (95% CI 55–85) 21 days after first dose and 85% (74–96) 7 days after two doses in the study population. Interpretation Our findings show that the BNT162b2 vaccine can prevent both symptomatic and asymptomatic infection in working-age adults. This cohort was vaccinated when the dominant variant in circulation was B1.1.7 and shows effectiveness against this variant. Funding Public Health England, UK Department of Health and Social Care, and the National Institute for Health Research.