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Background: Patients with type-2 (T2) cytokine-low severe asthma often have persistent symptoms despite suppression of T2 inflammation with corticosteroids., Objectives: We sought to analyze whole blood transcriptome from 738 samples in T2-biomarker-high/-low patients with severe asthma to relate transcriptomic signatures to T2 biomarkers and asthma symptom scores., Methods: Bulk RNA-seq data were generated for blood samples (baseline, week 24, week 48) from 301 participants recruited to a randomized clinical trial of corticosteroid optimization in severe asthma. Unsupervised clustering, differential gene expression analysis, and pathway analysis were performed. Patients were grouped by T2-biomarker status and symptoms. Associations between clinical characteristics and differentially expressed genes (DEGs) associated with biomarker and symptom levels were investigated., Results: Unsupervised clustering identified 2 clusters; cluster 2 patients were blood eosinophil-low/symptom-high and more likely to be receiving oral corticosteroids (OCSs). Differential gene expression analysis of these clusters, with and without stratification for OCSs, identified 2960 and 4162 DEGs, respectively. Six hundred twenty-seven of 2960 genes remained after adjusting for OCSs by subtracting OCS signature genes. Pathway analysis identified dolichyl-diphosphooligosaccharide biosynthesis and assembly of RNA polymerase I complex as significantly enriched pathways. No stable DEGs were associated with high symptoms in T2-biomarker-low patients, but numerous associated with elevated T2 biomarkers, including 15 that were upregulated at all time points irrespective of symptom level., Conclusions: OCSs have a considerable effect on whole blood transcriptome. Differential gene expression analysis demonstrates a clear T2-biomarker transcriptomic signature, but no signature was found in association with T2-biomarker-low patients, including those with a high symptom burden., (Crown Copyright © 2023. Published by Elsevier Inc. All rights reserved.)

Background: Approximately 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., Objective: To 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., Methods: This 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., Results: Of 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)., Conclusions: This exploratory post hoc analysis identified that females achieved a greater benefit from biomarker-directed CS optimization versus symptom-directed treatment., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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/µl) 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. Clinical trial registered with www.clinicaltrials.gov (NCT02717689).

Background: Understanding why patients with severe asthma do not follow healthcare provider (HCP) advice to adjust treatment is critical to achieving personalised disease management., Methods: We reviewed patient choice to follow HCP advice to adjust asthma treatment in a UK-based randomised, controlled, single-blind (study participant), multicentre, parallel group 48-week clinical study comparing biomarker-directed treatment adjustment with standard care in severe asthma., Results: Of 1572 treatment advisories (291 participants), instructions were followed in 1377 cases (87.6%). Patients were more likely to follow advice to remain on treatment (96.7%) than to either reduce (70.3%) or increase (67.1%) their treatment, with 64% of patients following all treatment advice. Multivariate analysis associated belonging to an ethnic minority group (OR 3.10, 95% CI 1.68-5.73) and prior study medication changes (two or more changes: OR 2.77, 95% CI 1.51-5.10) with failure to follow treatment advice. In contrast, emergency room attendance in the prior year (OR 0.54, 95% CI 0.32-0.92) was associated with following treatment advice. The largest effect was seen with transition onto or off oral corticosteroids (OR 29.28, 95% CI 16.07-53.36) when compared with those requested to maintain treatment. Centre was also an important determinant regarding the likelihood of patients to follow treatment advice., Conclusions: Belonging to an ethnic minority group and multiple prior treatment adjustments were associated with not following HCP treatment advice. Patients also responded differently to HCP advice across UK specialist centres. These findings have implications for the generalisability of models of care in severe asthma and require further focused studies., Competing Interests: Conflict of interest: J. Busby has nothing to disclose. Conflict of interest: J.G. Matthews has nothing to disclose. Conflict of interest: R. Chaudhuri reports grants, personal fees for advisory board work and nonfinancial support for meeting attendance from AstraZeneca, personal fees for advisory board work from GlaxoSmithKline and Novartis, personal fees for advisory board work and nonfinancial support for meeting attendance from Chiesi, nonfinancial support for meeting attendance from Napp Pharmaceuticals, outside the submitted work. Conflict of interest: I.D. Pavord reports personal fees for lectures, advisory board honoraria, sponsorship to attend scientific meetings, and payments for organising educational events from AstraZeneca, personal fees for lectures, advisory board honoraria, and sponsorship to attend scientific meetings from Boehringer Ingelheim and GlaxoSmithKline, personal fees for lectures from Aerocrine and Chiesi, personal fees for lectures and advisory board honoraria from Almirall and Novartis, advisory board honoraria from Genentech, Regeneron, Sanofi, Circassia and Knopp, personal fees for lectures, payments for organising educational events, and sponsorship to attend scientific meetings from Teva, grants from the National Institute for Health Research, outside the submitted work. Conflict of interest: T.C. Hardman has nothing to disclose. Conflict of interest: J.R. Arron has patents “Diagnosis and treatments relating to Th2 inhibition” (US 9,684,000 B2) and “Diagnosis and treatments relating to Th2 inhibition” (US 9,995,755 B2) issued with rights assigned to Genentech, a member of the Roche group, and is an employee of Genentech, Inc. and owns stocks/options in the Roche group. Conflict of interest: P. Bradding reports grants from Genentech, other (consultancy work on behalf of the University of Leicester) from Roche and Boehringer Ingelheim, outside the submitted work. Conflict of interest: C.E. Brightling reports grants and personal fees from GlaxoSmithKline, AstraZeneca, Sanofi, Novartis, Chiesi, Genentech, Gossamer, Mologic and 4D Pharma, all paid to the institution and outside the submitted work. Conflict of interest: D.F. Choy is an employee of Genentech, Inc. and owns stocks/options in the Roche group. Conflict of interest: D.C. Cowan has nothing to disclose. Conflict of interest: R. Djukanovic reports receiving fees for lectures at symposia organised by Novartis, AstraZeneca and Teva, consultation for Teva and Novartis as member of advisory boards, and participation in a scientific discussion about asthma organised by GlaxoSmithKline; he is a co-founder and current consultant, and has shares in Synairgen, a University of Southampton spin-out company. Conflict of interest: C.E. Hanratty has nothing to disclose. Conflict of interest: T.W. Harrison reports grants, personal fees and nonfinancial support from AstraZeneca, grants and personal fees from GlaxoSmithKline, personal fees from Vectura, Synairgen and Chiesi, outside the submitted work. Conflict of interest: C.T. Holweg is an employee and stock owner of Genentech Inc., a member of the Roche Group, outside the submitted work. Conflict of interest: P.H. Howarth reports employment by GlaxoSmithKline. Conflict of interest: S.J. Fowler reports personal fees for lectures and support to attend an international conference from AstraZeneca, grants and personal fees for lectures from Boehringer Ingelheim, personal fees for lectures, participation in an advisory board, and support to attend an national conference from Chiesi, personal fees for lectures from GlaxoSmithKline, Novartis and Teva, outside the submitted work. Conflict of interest: J.L. Lordan has nothing to disclose. Conflict of interest: A.H. Mansur reports personal and institution payment for talks, advisory board meetings, sponsorship to attend conferences and education grants for service developments from GlaxoSmithKline, AstraZeneca, Novartis, Sanofi, Teva and others, outside the submitted work. Conflict of interest: A. Menzies-Gow reports grants and personal fees from AstraZeneca, personal fees from Novartis, GlaxoSmithKline, Sanofi and Vectura, personal fees and nonfinancial support from Teva and Boehringer Ingelheim, outside the submitted work. Conflict of interest: R.M. Niven has received lecture fees, advisory board activity and been supported to attend international meetings/conferences in the last 5 years by the following companies: AstraZeneca, Boehringer, Boston Scientific, Chiesi, Napp, Novartis and Teva. None of these have any relevance to the manuscript; R.M. Niven owns no shares or stocks and is not personally or in any family way connected to any pharmaceutical companies. Conflict of interest: D.S. Robinson has nothing to disclose. Conflict of interest: S.M. Walker has nothing to disclose. Conflict of interest: A. Woodcock reports personal fees for lectures from GlaxoSmithKline, personal fees for lectures and consultancy from Novartis, personal fees for consultancy from Chiesi, other (chairing research projects) from Reacta Biotech, Axalbion and Medicines Evaluation Unit, outside the submitted work. Conflict of interest: L.G. Heaney reports other (sponsorship for meeting attendance) from AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline and Napp Pharmaceutical, personal fees for lectures and advisory board work from Novartis, Hoffman la Roche/Genentech Inc., Sanofi, GlaxoSmithKline, AstraZeneca, Teva, Theravance and Circassia, grants from Medimmune, Novartis UK, Roche/Genentech Inc., and GlaxoSmithKline, and is academic lead for the Medical Research Council Stratified Medicine UK Consortium in severe asthma, which involves industrial partnerships with Amgen, Genentech/Hoffman la Roche, AstraZeneca, Medimmune, GlaxoSmithKline, Aerocrine and Vitalograph, outside the submitted work., (Copyright ©The authors 2022.)

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 at 12 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., Funding: This study was funded, in part, by the Medical Research Council UK., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Patients with difficult-to-control asthma consume 50-60% of healthcare costs attributed to asthma and cost approximately five-times more than patients with mild stable disease. Recent evidence demonstrates that not all patients with asthma have a typical type 2 (T2)-driven eosinophilic inflammation. These asthmatics have been called 'T2-low asthma' and have a minimal response to corticosteroid therapy. Adjustment of corticosteroid treatment using sputum eosinophil counts from induced sputum has demonstrated reduced severe exacerbation rates and optimized corticosteroid dose. However, it has been challenging to move induced sputum into the clinical setting. There is therefore a need to examine novel algorithms to target appropriate levels of corticosteroid treatment in difficult asthma, particularly in T2-low asthmatics. This study examines whether a composite non-invasive biomarker algorithm predicts exacerbation risk in patients with asthma on high-dose inhaled corticosteroids (ICS) (± long-acting beta agonist) treatment, and evaluates the utility of this composite score to facilitate personalized biomarker-specific titration of corticosteroid therapy., Methods/design: Patients recruited to this pragmatic, multi-centre, single-blinded randomised controlled trial are randomly allocated into either a biomarker controlled treatment advisory algorithm or usual care group in a ratio of 4:1. The primary outcome measure is the proportion of patients with any reduction in ICS or oral corticosteroid dose from baseline to week 48. Secondary outcomes include the rate of protocol-defined severe exacerbations per patient per year, time to first severe exacerbation from randomisation, dose of inhaled steroid at the end of the study, cumulative dose of inhaled corticosteroid during the study, proportion of patients on oral corticosteroids at the end of the study, proportion of patients who decline to progress to oral corticosteroids despite composite biomarker score of 2, frequency of hospital admission for asthma, change in the 7-item Asthma Control Questionnaire (ACQ-7), Asthma Quality of Life Questionnaire (AQLQ), forced expiratory volume in 1 s (FEV1), exhaled nitric oxide, blood eosinophil count, and periostin levels from baseline to week 48. Blood will also be taken for whole blood gene expression; serum, plasma, and urine will be stored for validation of additional biomarkers., Discussion: Multi-centre trials present numerous logistical issues that have been addressed to ensure minimal bias and robustness of study conduct., Trial Registration: ClinicalTrials.gov, NCT02717689 . Registered on 16 March 2016.