Abstract Rationale Next generation sequencing specifically 16S rRNA sequencing has facilitated more accurate microbial identification offering a more comprehensive understanding of the microbial communities that reside within the lung. Current studies report distinct microbial signatures that correlate with asthma pathophysiology, phenotype and with increasing evidence treatment response specific to inhaled corticosteroids. The study of individual microbial signatures may contribute to precision medicine approaches, identifying microbial signatures that may guide personalized therapy or serve as novel biomarkers of disease activity and progression. Methods This was a prospective observational study with a non-invasive (n = 58) and invasive arm (n = 27) recruiting patients with respiratory symptoms and a physician diagnosis of asthma. Participants were phenotyped based on clinical features, Th2 biomarkers and physiologic parameters and had biosamples (OR; oral rinse, NS; nasopharyngeal swab, SS; sputum sample, BAL; bronchoalveolar lavage) collected longitudinally. 16S rRNA sequencing was used to examine differences in microbial diversity, composition and taxonomic enrichment before and after (i) starting Nasal Corticosteroid (NCS) (ii) stopping Inhaled Corticosteroid (ICS) (iii) starting Biologic therapy. Results In those who started NCS (n = 35), sinonasal symptoms improved significantly (p = <0.01). Alpha diversity decreased while beta diversity and overall enrichment were unchanged in NS. Responders showed enrichment of Finegoldia and Anaerococcus; non-responders showed Leptotrichia . In those who stopped ICS (n = 16), asthma like symptoms improved (p = <0.01). There was no significant change in read counts, alpha or beta diversity in SS. Responders had higher Streptococcus, Lactobacillus, Prevotella, Actinomyces, while non-responders had distinct enrichment of Prevotella, Leptotrichia, Neisseria, Fusobacterium, Veillonella . In those who started a biologic (n = 6), all showed clinical response with FeNO reduction (p = 0.013) and improved FEV₁ (p = 0.041). Diversity metrics in paired OR and BAL were unchanged; taxa enriched post-biologic included Haemophilus, Streptococcus, Prevotella in OR and Prevotella, Veillonella, Porphyromonas in BAL. Conclusions In this study, we show that treatment strategies commonly used for asthma result in a significant change in the microbial micro-environment across the respiratory tract. Some of these may be associated with treatment response. Specifically, with biologic therapy, site-specific taxonomic signals identified warrant confirmation in larger studies in identifying patients more likely to respond to therapy. This abstract is funded by: Charitable Infirmary Charitable Trust

Rationale: Emerging evidence suggests that the lung microbiome plays a critical role in asthma, impacting pathophysiology, clinical presentation and treatment outcomes. This study investigates microbial profiles across asthma phenotypes and their association with treatment responses, aiming to inform personalized asthma therapies. Methods: This observational study enrolled patients from the Respiratory outpatient department at Beaumont Hospital between October 2023 and October 2024. Four in person visits were carried out over a three month period. The study population included non-asthma controls, those with Th2 inflammation without asthma and asthma (Th2 high/low). Blood, oral rinse, nasal swab and induced sputum were collected for microbiome analysis. Asthma control and comorbidity data were obtained through validated questionnaires. Spirometry and impulse oscillometry were used to assess respiratory function, while data on adherence, treatment changes, and exacerbation history were collected for comprehensive profiling. Results: Of the 58 participants, 15 were non-asthma controls, 7 were Th2 non-asthma, and 36 had asthma. Median age was 46 with a female predominance. Detailed demographic data for each subgroup available in Table 1 which outlines key characteristics such as age, gender distribution, BMI, and smoking history. There was a high prevalence of co-morbidities at enrolment specifically GERD and sino-nasal disease which are common among individuals with asthma and can significantly impact disease severity and treatment outcomes. Patients with asthma were phenotyped based on allergic status and the presence of Th2 inflammation. Comparative box plots show significant differences in respiratory function and microbial diversity across groups, highlighting potential microbiome-related drivers of asthma severity. Comparing diversity metrics there were significant microbial differences between the three groups. Conclusions: Asthma is a heterogenous condition that can present with variable and intermittent symptoms that make diagnosis challenging. A comprehensive diagnostic strategy that includes serial measurements is essential for accurate asthma diagnosis and effective management. Microbial signatures associated with three different groups of patients being referred for evaluation of asthma. These findings suggest that the microbial landscape may vary significantly based on asthma status and Th2 inflammation, potentially serving as important factors in the pathophysiology of asthma. Further research may establish the lung microbiome as a biomarker and therapeutic target in asthma, ultimately enhancing personalized treatment strategies. Table 1.

Background: Obstructive Sleep Apnea (OSA) leads to repetitive episodes of upper airway collapse, and subsequent airway inflammation. OSA is also associated with considerable dysbiosis in the gastro-intestinal microbiome, but the influence of OSA on the upper airway microbiome is less well established. In this study, we aimed to investigate the nasal and oral microbiome in those with and without OSA, and again following CPAP therapy. Methods: Sixty-two individuals with symptoms of OSA were recruited. Demographic and symptom data was collected, and all individuals underwent a WatchPAT sleep study. On the day of their sleep study, oral wash and nasal rinse was performed for sampling of the upper airway microbiome. 16s rRNA sequencing was preformed on all biosamples and data analysed using R. Results: Sixty-two individuals were recruited, of which 36 (58%) were female, with a mean age of 50 years and mean BMI of 35kg/units2. In this cohort and based on apnoea-hypopnea index (AHI), 43 (69%) individuals any evidence of OSA on their sleep study, of which 19 (44%) had mild disease, 6 (14%) had moderate disease and 18 (42%) had severe disease. Regarding microbial assessment, there were no significant differences in α or β-diversity between those who did or did not have OSA or even between OSA severity. However, by differential analysis, in the nasal microbiome, those with OSA were enriched with Anaerococcus, Dialister and Streptococcus. The mild OSA group was also enriched with Streptococcus, Corynebacterium and Moraxella. In addition, the severe group was enriched with Prevotella. Examining the oral microbiome, Streptococcus anginosus was enriched in OSA, with Neisseria oralis and Prevotella enriched in mild OSA and Prevotella melaninogenica enriched in severe OSA. 18 individuals returned for assessment following three months of CPAP therapy. There was no significant difference in α or β-diversity following three months of CPAP therapy. However, those adherent to CPAP therapy were enriched with Prevotella, Enterobacteriaceae and Streptococcus prior to CPAP, but not following three months of therapy, but were enriched with Alloiococcus and Moraxella linocolnii post therapy. Conclusion: OSA is associated with significant dysbiosis in both the nasal and oral microbiome, with enrichment in both pro-inflammatory and potentially pathogenic taxa. This may contribute to airway inflammation associated with OSA. Following CPAP therapy, there is a reduction in the prevalence of some of these taxa.

Background: The Apnoea-Hypopnea Index (AHI), used to categorise obstructive sleep apnea (OSA) severity is a poor predictor of symptoms or adverse cardiovascular outcomes, while hypoxic burden appears to have stronger predictive value for symptoms and adverse outcomes. In addition, OSA is associated with dysbiosis of the respiratory and gastro-intestinal microbiome, however, to date no studies have assessed the relationship between hypoxic burden and microbial signatures in the upper airway. Methods: Sixty-two individuals with symptoms of OSA were recruited. All participants had a WatchPAT sleep study, and demographic and symptom data was collected. Hypoxic burden was quantified as sleep time with oxygen saturations less than 90% (T90). For assessment of the upper airway microbiome, oral wash and nasal rinse was performed. 16s rRNA sequencing was preformed on all biospecimens and data analysed using R. Results: In this cohort, 36 (42%) were male, with an average age of 50 years and average BMI of 35kg/m2. Regarding their sleep studies, 43 (69%) had OSA. Mean oxygen saturations were 94%. Median T90 was 0.6%; 48 (77%) individuals had light hypoxia (T90 < 5%), 7 (11%) had mild hypoxia (T90 5 – 10%) and 7 (11%) had moderate to severe hypoxia (T90 >10%). Examining the nasal microbiome, there was no difference in α or β diversity, assessed by Shannon diversity and Bray Curtis Index between the hypoxic burden subgroups. Those with moderate/severe hypoxia were enriched with multiple taxa including Prevotella and Veillonella. In the oral microbiome, there was no significant difference in α diversity, but the light hypoxia group had significantly reduced β diversity compared to both the mild (p=0.04) and moderate/severe (p=0.004) subgroups. In addition, the moderate/severe hypoxia group was enriched with multiple taxa including Veillonella and Prevotella.Conclusion: Hypoxic burden is associated with a distinct microbial signature in the upper airway microbiome. Increasing hypoxia is associated with enrichment of anaerobic taxa in both the oral and nasal microbiome, including Veillonella and Prevotella.

Rational: Post-COVID syndrome is a common complication of SARS-CoV-2 infection, affecting up to 73% individuals. The cause of this syndrome remains unknown. Acute SARS-CoV-2 infection itself has been shown to cause significant dysbiosis of both the respiratory and gastro-intestinal microbiome. Furthermore, post-COVID syndrome has also been shown to be associated with dysbiosis of the gastro-intestinal microbiome. Little is known about the effect of post-COVID syndrome on the respiratory microbiome. Methods: Patients with post-COVID syndrome were recruited from the Post-COVID clinic, and controls from the sleep clinic. All patients had basic demographic data collected, and history of their COVID-disease, followed by an oral wash and nasal lavage. 16s rRNA gene sequencing was performed bio-specimens and data analysed using R. Results: Forty-two individuals with post-COVID syndrome, and 20 controls were recruited. Of the controls, 6 had never contracted SARS-CoV-2 and 14 had a history of SARS-CoV-2 infection but did not develop post-COVID syndrome. In the entire cohort, 36 (58%) were female, with a mean age of 50 years. In the cohort with post-COVID syndrome, 19 (45%) were female, with a mean age of 53 years and were recruited a mean of 18 months post their initial infection. Regarding COVID disease severity, 20 (48%) had severe disease, 8 (19%) had moderate disease and 14 (33%) had mild disease. In the nasal microbiome, those with post-COVID syndrome had significantly reduced α-diversity (p=0.03), and differing β-diversity (p=0.02), when compared to those who had never contracted SARS-CoV-2. These differences were not seen in the oral wash samples. Individuals with post-COVID syndrome were enriched with Moraxella, Streptococcus, Anaerococcus, Staphylococcus, Corynebacterium and Haemophilus influenzae in the nasal microbiome. Their oral microbiome was enriched with Prevotella melaninogenica, Rothia mucilaginosa, Veillonella parvula, Actinobacillus and Leptotrichia. Conclusion: Post-COVID syndrome is associated with significant disruption of the upper airway microbiome up to 18 months following initial infection. Compared to un-infected controls, those with post-COVID syndrome have lower α-diversity and differing β-diversity in their nasal microbiome. In addition, there is evidence of enrichment of inflammatory and potentially pathogenic taxa in both the nasal and oral microbiome

Rationale In asthma, corticosteroids suppress T2 inflammation, but adherence to these medications varies over time and between people. Objective: The influence of corticosteroids on individual patient T2 biomarker status and asthma features and outcomes was assessed. Methods T2 biomarkers, serum cytokines, lung function were measured 6 times over 32 weeks in 200 patients who participated in a randomised trial (NCT02307669). Inhaled corticosteroid (ICS) exposure was assessed using data from digitally-enabled inhalers, oral corticosteroid (OCS) use was obtained from dispensing records and the data combined to give the cumulative exposure. Results The lowest corticosteroid exposure was in persistently T2 high patients (n=48, 24%). They had lower, more variable lung function and increased Th-2, Th-1 and Th-17 cytokines. In contrast persistently T2 low patients (n=40,20%) had normal lung function, low between-visit FEV1 and diurnal PEF variance, cytokine levels similar to healthy controls, and a high symptom burden explained by co-existing conditions. T2 low status was independently associated with both higher ICS (OR 1.03 per change in mg FP received/month [95% CI 1.00 – 1.05], p=0.011) and OCS exposure, OR 1.44/course of OCS [95% CI 1.07 – 1.96], p=0.018.). Cumulative corticosteroid exposure >5mg prednisolone equivalent/day occurred in 132 (66%) patients, of whom 53 (40%) had no exacerbation. Of the 112 who had 1 exacerbation, 32 (28%) had a low corticosteroid exposure (3.6mg prednisolone equivalent/day). Conclusion. An individual's T2 biomarker status reflects disease activity and corticosteroid use. Concurrent measurement of corticosteroid exposure and lung function over time provides a direct assessment of two important asthma risks.

Introduction It is estimated that between 5–10% of asthma patients have severe disease. Eosinophilic asthma represents the majority of severe asthma cases, and many of these patients require commencement of anti-eosinophilic biologics. Eosinophils are believed to play a pivotal role in the host defence against parasite infections and thus prescribers of anti-IL5/5R biologics are cautioned against their use in patients with known or untreated helminth infections. There remains global ambiguity surrounding if, when and how, patients should be screened. To ensure appropriate identification of patients at risk, a comprehensive screening protocol based on patient travel history and exposure was introduced at our institution in collaboration with Infectious disease colleagues. Methods A retrospective review of all protocol directed parasite screens performed from January 2019 up to January 2023 in adult severe asthma patients who met NICE criteria for commencement of an anti-IL5/5R biologic, was completed. Based on each patient's exposure and travel history, targeted stool smear testing and/or serum enzyme-linked immunosorbent assays (ELISA) were used to detect parasitic antibodies. Results A total of 479 patients were screened for parasite infection. 26 patients (5.4%) had a positive result and of these, 16 (61.5%) were for Schistosoma and 10 (38.5%) for Strongyloides. Table 1 stratifies the characteristics of these patients. No patient had a positive stool smear, or positive result for Toxocara or Filaria antibodies. All positive antibody results were discussed within a join respiratory and infectious disease MDT, with appropriate treatment administered prior to the first dose of anti-il5/5R biologic. Conclusions Within a targeted screening population of at-risk, severe eosinophilic asthma patients, just under 1 in 20 patients had a positive parasite screen. To date, this is the largest reported cohort of severe asthmatics to have undergone pre-anti-IL5/5R screening in the literature, which serves to help inform global clinical practice and risk assessments.

Background: Adrenal insufficiency (AI) is present in over 60% of oral corticosteroid (OCS) dependant severe asthma patients receiving asthma biologic therapy. Assessment for AI often requires measurement of serum cortisol levels before, at 30 mins and at 60 mins after parenteral tetracosactide; a Short Synacthen Test (SST). At present, there is no literature to support an optimal approach to SST performance in asthma biologic patients. Aims: To evaluate the implications on AI diagnosis and management by comparing 30 min with 60min SST serum cortisol levels in this specific population. Methods: SST results from severe asthma patients on high dose ICS and 5mg PO prednisolone, receiving any asthma biologic at a specialist asthma centre between 2017 and 2020, were retrospectively reviewed. AI diagnoses based on 30 min and 60 min samples were compared. Results: Of the 89 results analysed (Table 1), 17 patients (19.1%) had an insufficient SST response (cortisol < 450 nmol/L) at 30 minutes but a normal response (cortisol > 450 nmol/L) at 60 minutes. No patients had normal 30 min with abnormal 60 min serum cortisol results. Conclusions: Measurement of baseline and 60 min serum cortisol levels alone were sufficiently able to identify all patients with AI; avoiding the need for an additional 30 min cortisol blood test. Reliance on the 30 min cortisol sample alone could led to an overdiagnosis of AI and prolonged exposure to OCS.

Introduction and objectivesAnti-IL5 therapies act by reducing blood and tissue eosinophils and are indicated in the management of patients with severe refractory eosinophilic Asthma. Eosinophils are important mediators in the host defence of parasitic infection. Prescribing guidelines recommend treatment of pre-existing parasitic infection prior to initiation of therapy. However, such infections are often chronic and asymptomatic and there is no clear guidance on who to screen and what to screen for. In addition, awaiting treatment by a specialist team can delay commencement of asthma therapy. We sought to review our current practice and to develop a comprehensive protocol to guide screening and treatment of occult parasitic infection in patients selected to receive anti-IL5 therapy.MethodsA retrospective study of 219 severe asthma patients prescribed anti-IL5 therapy was performed to identify the prevalence of occult parasitic infection in this cohort. Anti-IL5 clinical trial protocols and infectious disease literature was also studied. Using these data, a protocol for parasite screening was developed.ResultsFifty-six patients (26%) had parasite screening carried out based on travel outside of Europe or North America. Seven of the patients screened (12.5%) had a positive test. Each patient was screened for an average of 5 different parasites (total number of tests=303), however positive tests were for Strongyloides (n=3) or Schistosoma (n=4) only. A protocol which provides guidance for targeted screening for parasite infection and which includes comprehensive risk assessment and travel history was developed. Implementation of this protocol could reduce the number and costs of tests performed by 80% whilst maintaining the positive detection rate. The protocol incorporates additional guidance on how to manage and treat occult parasite infection when detected.ConclusionsDespite being recommended prior to initiation of anti-IL5 therapy, there is no clear guidance on screening for parasitic infections in this cohort, which can lead to inadequate screening or unnecessary tests being performed. We have developed a protocol to streamline this process to ensure the right tests are performed for the right patient first time.