Salman Siddiqui

1 1.1 Background: Many longitudinal omics studies contain only a small number of repeated measurements collected before, during, or after an intervention. Existing approaches, including mixed-effects models and generalized additive models, estimate temporal effects but do not generally provide a discrete representation of trajectory topology that can be queried directly across experimental groups. 1.2 Methods: We developed LongOmicsTraj, an open-source R package for topology-based representation and querying of short longitudinal omics trajectories. The framework encodes the direction of change between adjacent visits as up , down , or flat , with the ordered sequence defining an Ordinal Trajectory State (OTS). LongOmicsTraj operates downstream of trajectory estimation and can therefore be applied to empirical summaries or model-derived visit-level estimates, including those from linear mixed-effects models, generalized additive models, and polynomial regression, following a maSigPro-style time-course formulation [1]. OTS labels provide a common representation for topology-based querying, cross-group comparison, and evaluation of higher-level representations such as trajectory clusters. We evaluated the framework using controlled simulations and bronchial biopsy transcriptomic data from the GLUCOLD corticosteroid intervention study (GEO accession GSE36221 ), measured at baseline, 6 months, and 30 months. The biological analysis compared continued inhaled corticosteroid (ICS) treatment, ICS withdrawal after 6 months, and placebo. 1.3 Results: In simulations, LongOmicsTraj recovered predefined stable, monotonic, transient, rebound, and oscillatory trajectories with high accuracy when longitudinal signal was sufficiently clear, with performance declining under high-noise conditions and depending partly on the upstream estimator. In GLUCOLD, comparator-aware topology queries reduced 20,358 measured transcripts to 168 genes showing a corticosteroid response that was maintained during continued treatment, reversed following withdrawal, and was not reproduced under placebo. The selected genes included established corticosteroid-response genes and were enriched for immune-cell migration, chemotaxis, cell adhesion, and extracellular-matrix organisation. Topology-aware evaluation of FlexMix trajectory clusters additionally revealed substantial within-cluster temporal heterogeneity, with topology purities of approximately 46–60%. 1.4 Conclusions: LongOmicsTraj provides a compact, directly queryable representation of temporal direction and order in short longitudinal omics studies. It complements existing longitudinal estimation and clustering methods by making trajectory structure explicit, enabling structured cross-group queries and quantification of temporal heterogeneity within trajectory clusters.

Background: Spirometry with bronchodilator response (BDR) testing is the first-line test for asthma in international guidelines; however, it has been shown to have suboptimal sensitivity for asthma diagnosis and detecting small airways dysfunction. Oscillometry with BDR may identify bronchodilator response in patients with no significant BDR by spirometry. The aims of the present study were to determine whether oscillometry identifies additional BDR in the Assessment of Small Airways Involvement in Asthma (ATLANTIS) study asthma cohort compared to spirometry ( ClinicalTrials.gov identifier NCT02123667 ), and to characterise phenotypic differences between BDR groups. Methods: Baseline data from 518 adults with objectively confirmed asthma enrolled in ATLANTIS were analysed. Differences in clinical, biomarker and physiological characteristics were assessed between BDR groups. A subset with computed tomography (CT) imaging (208 out of 518) and nasal RNA-sequencing data (236 out of 518) underwent CT biomarker and differential gene expression analysis to investigate differences in airway morphology and pathways underlying a small airways bronchodilator responsive phenotype. Results: Oscillometry detected significant bronchodilator response in an additional 11% of participants not identified by spirometry, although spirometry identified more responders overall. Spirometry-positive BDR-only cases (group 1) had greater airway obstruction and exhaled nitric oxide fraction (pversus group 1 and reduced luminal area and greater gas trapping on CT imaging (p<0.05). Interpretation: Oscillometry identified additional bronchodilator-responsive participants beyond spirometry, indicating complementary physiological information. Distinct BDR patterns were associated with differing inflammatory, physiological and structural features, suggesting distinct asthma phenotypes.

Background: Transcriptomic analysis of bronchial brushes reveals asthma‐associated gene signatures but is limited by the invasiveness of bronchoscopy. Based on the “united airways” hypothesis, we evaluated whether and to what extent nasal brushes reflect asthma‐associated transcriptomic changes in the lower airways. Methods: In the ARMS study, we included 26 asthma patients and 28 healthy controls, all fully clinically characterized. Nasal and bronchial brushes were collected for RNA sequencing. We used edgeR and WGCNA to identify asthma‐associated genes and modules in bronchial brushes. We assessed their expression patterns in ARMS nasal brushes and validated the findings in the independent ATLANTIS study ( n = 427). Results: We identified 51 asthma‐associated genes in the lower airways, of which 40 were up‐regulated and 11 were down‐regulated in asthma compared to healthy controls. Seven of the 40 up‐regulated genes were also up‐regulated in ARMS nasal brushes and validated in ATLANTIS: CLCA1, FETUB, CST1, NTRK2, CDH26, TPSAB1, and DHX35. WGCNA revealed two modules that were consistently elevated in asthma across bronchial and nasal brushes in ARMS and confirmed in ATLANTIS. One module represents IL‐13 related inflammation, whereas the other represents mast cell activity. Conclusion: The asthma‐associated gene signatures of the lower and upper airways show a limited but biologically coherent overlap, with seven genes and two gene modules consistently elevated in asthma. The shared gene signatures reflect two separate components of type 2 inflammation: IL‐13 related inflammation and mast cell activity. Selected nasal gene signatures offer a non‐invasive tool to identify asthma endotypes with distinct molecular mechanisms driving underlying disease biology.

Background: Asthma remission is a feasible treatment goal. However, remission definitions vary, and predictive biomarkers remain underexplored. Methods: We conducted a post hoc analysis of ATLANTIS (NCT02123667), a multinational prospective study including 684 adult asthmatics. Remission was defined by 3‐component (3C) and 4‐component (4C) criteria. 3C remission included: (1) ACQ‐6 < 1.5, (2) no maintenance oral corticosteroids, (3) no exacerbations. An absolute decline < 10% in pre‐bronchodilator FEV ₁ % predicted, was added for the 4C definition. Multivariate logistic regression identified remission predictors. A novel Low Disease Activity (LDA) score was developed using factor analysis of five clinical variables (ACQ‐6, FeNO, BEC, and FEV ₁ ) including an innovative small airways dysfunction questionnaire tool (SADT). Nasal transcriptomics were analysed for differential gene expression and pathway enrichment and were replicated in U‐BIOPRED (NCT01976767) using sputum transcriptomics. U‐BIOPRED was included only to study omics replication of remission pathways identified in ATLANTIS. Findings: Remission occurred in 48% (3C) and 45% (4C) of patients. Predictors included male sex, better lung function, fewer previous exacerbations, and higher SADT (fewer small airways symptoms). LDA identified milder disease and was associated with remission [OR 3C 4.43 (2.80, 7.10) and 4C 3.46 (2.23, 5.43)], improved QoL [OR 2.07 (1.65, 2.60)], and fewer future exacerbations [OR 0.43 (0.22, 0.85)]. Transcriptomic analyses revealed remission‐associated upregulation of interleukin 4/13 signalling and downregulation of coagulation pathways, in both ATLANTIS and U‐BIOPRED. Interpretation: SAD was associated with reduced asthma remission. A novel LDA tool demonstrated clinical utility in stratifying prospective asthma risk. Key immunologic and haemostatic pathways may underpin remission, offering potential targets for future intervention.

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare and potentially life‐threatening systemic, inflammatory disease with multi‐organ manifestations, variable presentation and complex pathology. Multiple interconnected immunological pathways are implicated in EGPA pathology, including a type‐2 immune response driving predominantly eosinophilic inflammation, B‐cell mediated autoimmunity, neutrophil activation, and the generation of pathogenic anti‐neutrophil cytoplasmic antibodies, all of which can contribute to tissue/organ damage. High‐dose glucocorticoids are the mainstay treatment for EGPA, but over the past two decades the development of biologic treatments targeting interleukin (IL)‐5, eosinophils and B‐cells has revitalized the treatment landscape. Mepolizumab, a humanized monoclonal antibody that specifically targets IL‐5, and benralizumab, which targets the IL‐5 receptor (IL‐5Rα), are both approved for the treatment of patients with non‐severe relapsing or refractory EGPA. In Phase III trials, these biologics have demonstrated favorable safety profiles and efficacy, with treatment leading to remission induction, remission maintenance, and oral glucocorticoid sparing benefits. However, as understanding of the full complexity of EGPA pathogenesis improves, new treatment targets are emerging. Consequently, understanding key pathogenic mechanisms at the patient level, enabling a more tailored treatment approach, is an important goal for future research.

Background: It is estimated that around 5% of people with asthma have severe asthma. Severe asthma typically presents with poor symptom control, impaired lung function and asthma exacerbations, despite regular inhaled steroids and additional controller medications. In the BEyond Allergic Th2-Severe Asthma clinical trials programme, we worked with severe asthma specialist centres in the United Kingdom to identify patients who experienced frequent asthma attacks (two or more per year), who were potentially eligible for stratified asthma treatments. Objectives: There are currently two recognised subtypes of severe asthma which can be characterised by their level of eosinophils (a type of white blood cells). In the BEyond Allergic Th2-Severe Asthma clinical trial programme, we aimed to test whether a simple, once-daily oral antibiotic (doxycycline) can reduce asthma attacks in individuals with lower levels of eosinophils in peripheral blood (T2-Low arm: < 300 cells/µl). We also aimed to test whether a simple twice-daily oral drug (dexpramipexole) can reduce asthma attacks in individuals with high levels of eosinophils in peripheral blood (T2-High arm : ≥ 300 cells/µl). The trial was established using a master protocol and platform trial design with study protocols for the T2-High and T2-Low cohorts. Study outcomes: The trial platform was successfully set up during the COVID-19 pandemic and opened across 13 sites in the United Kingdom for recruitment between August 2021 and September 2022, following a 12-month trial pause due to the pandemic. Several changes to the trial protocol were made to make the protocol easier to deliver due to pandemic restrictions. Due to capacity issues at National Health Service trusts in the United Kingdom following the pandemic, the trial was delayed in opening sites by approximately 4 months. Shortly after all sites were opened, a decision was made with the Trial Steering Committee and funders to close the dexpramipexole (T2-High) arm of the trial (October 2022), as the drug had moved on to definitive and confirmatory phase III trials. Recruitment into the doxycycline trial progressed slowly, largely in part due to challenges in finding people with asthma who had the required number of asthma attacks to be eligible, as attack rates in the United Kingdom fell during the pandemic. Furthermore, the trial was recruiting exclusively from severe asthma centres in the United Kingdom and did not have the funding required to change the recruitment model to include screening within primary care also. As a result of these factors, a decision was made by the sponsor of the trial to close the trial (April 2023), in line with National Institute for Health and Care Research post pandemic reset policy. Limitations and future work: While no scientific conclusions can be drawn from this trial, following the pandemic a formal review of commercial clinical trials was commissioned by the government (Lord O’Shaughnessy review), with several recommendations to enhance clinical trial delivery in the United Kingdom. Many of the recommendations are applicable to non-commercial asthma trials. Furthermore, pivotal phase III trials of dexpramipexole are currently well underway. We would advocate the development of a Respiratory Clinical Trials Accelerator Platform for airways disease trials in the United Kingdom to support academic trials. Funding: This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation programme as award number 16/71/05.

Chan R, et al. Allergy Asthma Immunol Res. 2026 Jan;18(1):19-38. https://doi.org/10.4168/aair.2026.18.1.19

Asthma represents a profoundly heterogeneous syndrome underpinned by multiple, distinct and overlapping immunopathological mechanisms. Nevertheless, prevailing management algorithms continue to adopt a largely uniform, stepwise approach in which pharmacotherapy is intensified only after clinical deterioration or recurrent exacerbations. Although the advent of targeted biologic agents has improved outcomes in severe asthma, the realisation of precision medicine – therapeutic selection directed by individual disease mechanisms – remains elusive. This is primarily attributable to the limited availability of validated biomarkers capable of defining endotypes and accurately predicting therapeutic responsiveness. Existing indicators of type-2 (T2) inflammation, including blood eosinophil counts, fractional exhaled nitric oxide, and serum Immunoglobulin E, provide only partial discrimination between T2 subtypes and are insufficient to guide the choice of specific T2-targeted biologics. Furthermore, robust non-T2 biomarkers are notably lacking. This review provides a critical appraisal of current biomarker paradigms and examines emerging molecular and cellular candidates with potential to enable precise endotyping. Integration of such biomarkers into early disease assessment offers the prospect of delivering truly individualised therapy, ensuring that appropriate treatment is instituted for the right patient at the optimal time.

Background: Previous cluster analyses have identified subgroups of asthma. However, only a few studies included parameters of small airways dysfunction (SAD), or gene expression profiles reflecting underlying disease mechanisms. We aimed to identify clinically distinct asthma phenotypes, beyond GINA asthma severity, using available data from the ATLANTIS study which focused on identifying the prevalence of SAD in asthma and its role in asthma control, exacerbations and quality of life. Methods: The ATLANTIS study included 773 asthma patients (mean age 44 years, 58% female, 76% never‐smoker, GINA 1–5). Subjects were extensively characterized, including symptoms, parameters of large and small airways dysfunction, blood and sputum differential cell counts, and genome‐wide gene expression profiling from nasal brushes. Clusters were generated using the Self‐Organizing Map–Ward's method. Results: Four distinct clusters were identified: A ( N = 62; 8%) characterized by the most frequent exacerbations, lower post‐bronchodilator FEV ₁ % predicted, more small airways dysfunction, higher sputum and blood eosinophils, and high expression of asthma‐related genes. B ( N = 206; 27%) consisting of atopic patients with early‐onset asthma, uncontrolled symptoms, and normal lung function and bronchial hyperresponsiveness, along with a high expression of asthma‐related genes in the nasal epithelium. C ( N = 277; 36%), predominantly male former smokers, with well‐controlled asthma, mild obstructive lung disease, and relatively high neutrophil levels. D ( N = 228; 29%), with normal lung function and low blood and sputum eosinophils. Conclusions: Four distinct clusters were identified, where the presence of SAD was associated with high type‐2 inflammation, lower lung function, and frequent exacerbations. SAD may be a marker of poorly controlled asthma and should be considered as an important clinical trait.