UNASSIGNED: Initiated by the Severe Asthma Network Italy (SANI), this study aims to explore asthma patients\' perceptions of disease severity, differentiating between mild and severe asthma. The objective is to identify factors influencing tailored treatment strategies for varying disease severities and to provide insights into asthma care in Italy.
UNASSIGNED: Conducted between November 2020 and January 2021, a survey using Computer-Assisted Personal Interviewing (CAPI) collected data from 308 Italian adults, representing the population. A 25 item multiple choice questionnaire covered asthma diagnosis, symptoms, treatment approaches, associated conditions, and quality of life.
UNASSIGNED: Among participants, 83.8% reported having mild asthma, while 16.2% had severe asthma. Severe asthma patients had longer disease durations, more severe symptoms, frequent exacerbations, and higher hospital/ER visits. Although treatment adherence and symptom profiles generally aligned with international guidelines for self reported severe asthma, 22% of self identified mild asthmatics experienced severe respiratory symptoms. Oral corticosteroid (OCS) use was observed in 50% of severe cases and 22% of mild cases. Adherence was higher in severe asthma patients (76%) versus mild asthma patients (28%). Both groups experienced comorbidities, with 96% of severe asthmatics and 72% of mild asthmatics reporting impaired quality of life.
UNASSIGNED: This study highlights the disparity between clinical categorization and patient perceptions of asthma severity. The prevalence of self reported severe asthma exceeds literature data. The burden of mild asthma remains significant, with treatment approaches not fully aligned, particularly regarding disproportionate OCS use. Addressing this gap requires enhancing patient education, improving diagnostic practices, and promoting adherence.

BACKGROUND: Dupilumab has been shown to be an effective treatment in moderate-to-severe atopic dermatitis (AD) and severe asthma (SA). However, comparative real-world analyses of adverse events (AE), particularly dupilumab-associated ocular surface disease (DAOSD), are lacking.
OBJECTIVE: This is the first real-world study to provide insight into the prevalence of AEs associated with dupilumab in AD compared with SA. Secondary objectives were to assess the prevalence, onset and therapeutic strategies of DAOSD and evaluate dupilumab discontinuation rates.
METHODS: Data from two daily practice registries including AD and SA patients receiving dupilumab treatment were analyzed. Adverse events, including DAOSD, were evaluated.
RESULTS: In total, 322 AD and 148 SA patients were included. Headaches (23.6%), injection site reactions (10.1%), and influenza-like symptoms (13.5%) were more prevalent in SA patients. Interestingly, ocular AEs were significantly more prevalent in AD patients (62.1%, p < 0.001), including conjunctivitis (17.1%, p = 0.004). 88% AD and 47% SA patients with ocular AEs received one or more ophthalmic treatment(s). Additionally, 20% of AD and 17.6% of SA patients discontinued dupilumab treatment due to ocular AEs, while only 65% of these AD and none of these SA patients were referred to an ophthalmologist.
CONCLUSIONS: The higher incidence of DAOSD in AD patients compared with SA patients in this real-world study highlights the importance of physician awareness, especially when prescribing dupilumab to AD patients. Conversely, the findings of this study help alleviate potential concerns about ocular AEs in patients with SA who do not have comorbid AD. Furthermore, the effective management of most ocular AEs with ophthalmic treatments suggests favorable tolerability of dupilumab in daily practice, and multidisciplinary collaboration is essential to proactively manage ocular AEs before discontinuing dupilumab.

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BACKGROUND: Asthma is a heterogeneous, inflammatory disease with several phenotypes and endotypes. Severe asthmatics often exhibit mixed granulocytosis with reduced corticosteroid sensitivity. Bronchom is a newly developed Ayurvedic prescription medicine, indicated for the treatment of obstructive airway disorders. The purpose of the present study was to evaluate the in-vivo efficacy of Bronchom in mouse model of mixed granulocytic asthma with steroidal recalcitrance.
METHODS: High-performance thin layer chromatography (HPTLC) and Ultra-high performance liquid chromatography (UHPLC) were employed to identify and quantitate the phytometabolites present in Bronchom. The preclinical effectiveness of Bronchom was assessed in house dust mite (HDM) and Complete Freund\'s adjuvant (CFA)-induced mixed granulocytic asthma model in mice. High dose of dexamethasone was tested parallelly. Specific-pathogen-free C57BL/6 mice were immunized with HDM and CFA and nineteen days later, they were intranasally challenged with HDM for four consecutive days. Then the mice were challenged with nebulized methacholine to evaluate airway hyperresponsiveness (AHR). Inflammatory cell influx was enumerated in the bronchoalveolar lavage fluid (BALF) followed by lung histology. Additionally, the concentrations of Th2 and pro-inflammatory cytokines was assessed in the BALF by multiplexed immune assay. The mRNA expression of pro-inflammatory cytokines and Mucin 5AC (MUC5AC) was also evaluated in the lung.
RESULTS: HPTLC fingerprinting and UHPLC quantification of Bronchom revealed the presence of bioactive phytometabolites, namely, rosmarinic acid, gallic acid, methyl gallate, piperine, eugenol and glycyrrhizin. Bronchom effectively reduced AHR driven by HDM-CFA and the influx of total leukocytes, eosinophils and neutrophils in the BALF. In addition, Bronchom inhibited the infiltration of inflammatory cells in the lung as well as goblet cell metaplasia. Further, it also suppressed the elevated levels of Th2 cytokines and pro-inflammatory cytokines in the BALF. Similarly, Bronchom also regulated the mRNA expression of pro-inflammatory cytokines as well as MUC5AC in mice lungs. Reduced effectiveness of a high dose of the steroid, dexamethasone was observed in the model.
CONCLUSIONS: We have demonstrated for the first time the robust pharmacological effects of an herbo-mineral medicine in an animal model of mixed granulocytic asthma induced by HDM and CFA. The outcomes suggest the potential utility of Bronchom in severe asthmatics with a mixed granulocytic phenotype.

UNASSIGNED: There are no validated decision-making algorithms concerning severe asthma (SA) management. Future risks are crucial factors and can be derived from SA trajectories.
UNASSIGNED: The future severe asthma-decision trees should revisit current knowledge and gaps. A focused literature search has been conducted.
UNASSIGNED: Asthma severity is currently defined a priori, thereby precluding a role for early interventions aiming to prevent outcomes such as exacerbations (systemic corticosteroids exposure) and lung function decline. Asthma \'at-risk\' might represent the ultimate paradigm but merits longitudinal studies considering modern interventions. Real exacerbations, severe airway hyperresponsiveness, excessive T2-related biomarkers, noxious environments and patient behaviors, harms of OCS and high-doses inhaled corticosteroids (ICS), and low adherence-to-effectiveness ratios of ICS-containing inhalers are predictors of future risks. New tools such as imaging, genetic, and epigenetic signatures should be used. Logical and numerical artificial intelligence may be used to generate a consistent risk score. A pragmatic definition of response to treatments will allow development of a validated and applicable algorithm. Biologics have the best potential to minimize the risks, but cost remains an issue. We propose a simplified six-step algorithm for decision-making that is ultimately aiming to achieve asthma remission.

UNASSIGNED: Children with severe asthma suffer from recurrent symptoms and impaired quality of life despite advanced treatment. Underlying causes of severe asthma are not completely understood, although genetic mechanisms are known to be important.
UNASSIGNED: The aim of this study was to identify gene regulatory enhancers in leukocytes, to describe the role of these enhancers in regulating genes related to severe and mild asthma in children, and to identify known asthma-related SNPs situated in proximity to enhancers.
UNASSIGNED: Gene enhancers were identified and expression of enhancers and genes were measured by Cap Analysis Gene Expression (CAGE) data from peripheral blood leukocytes from children with severe asthma (n = 13), mild asthma (n = 15), and age-matched controls (n = 9).
UNASSIGNED: From a comprehensive set of 8,289 identified enhancers, we further defined a robust sub-set of the high-confidence and most highly expressed 4,738 enhancers. Known single nucleotide polymorphisms, SNPs, related to asthma coincided with enhancers in general as well as with specific enhancer-gene interactions. Blocks of enhancer clusters were associated with genes including TGF-beta, PPAR and IL-11 signaling as well as genes related to vitamin A and D metabolism. A signature of 91 enhancers distinguished between children with severe and mild asthma as well as controls.
UNASSIGNED: Gene regulatory enhancers were identified in leukocytes with potential roles related to severe and mild asthma in children. Enhancers hosting known SNPs give the opportunity to formulate mechanistic hypotheses about the functions of these SNPs.

BACKGROUND: The burden of asthma remains steady with no decline observed in the past few decades. Obesity prevalence has been steadily increasing with a rate of 41.9% in the United States between 2017-2020. Obesity is an inflammatory chronic condition that may partially contribute to the burden and severity of asthma. This study aimed to examine whether the association between obesity and asthma varies with the categories of obesity (class I, II, and III) and persistent asthma (mild, moderate, and severe asthma). We hypothesized that subjects with elevated body mass index (BMI) are more likely to be diagnosed with persistent asthma than subjects without obesity with asthma.
METHODS: As a retrospective and cross-sectional study, this study used a total of 1,977 records of subjects with asthma (age ≥ 19 y) hospitalized in Nevada between 2016-2021. BMI and persistent asthma were evaluated as the main exposure and outcome of interest. Logistic regression was used to estimate the magnitude of the association between obesity and persistent asthma.
RESULTS: Among the selected subject records, subjects with obesity were more likely to be diagnosed with persistent asthma compared to subjects without obesity (odds ratio 1.50 [CI 1.10-2.05]). Subgroup analyses revealed that subjects with class III obesity (BMI ≥ 40) were more likely than subjects without obesity to be diagnosed with mild persistent asthma (odds ratio 2.21 [CI 1.18-4.16]) and severe persistent asthma (odds ratio 1.74 [CI 1.12-2.70]).
CONCLUSIONS: Obesity was identified as a risk factor for persistent asthma, particularly class III obesity. This in turn increases the potential for greater health care utilization and economic burden. Public health and clinical interventions are necessary among those with comorbid asthma and obesity.

Severe asthma is a syndromic label assigned to patients based on clinical parameters, yet there are diverse underlying molecular endotypes in severe asthma pathobiology. Immunophenotyping of asthma biospecimens commonly includes a mixture of granulocytes and lymphocytes. Recently, a subset of severe asthma patients was defined as non-type 2 with neutrophil-enriched inflammation associated with increased Th17 CD4+ T cells and IL-17 levels. Here, we used an allergen-driven mouse model of increased IL-17 and mixed granulocyte lung inflammation to determine the impact of upstream regulation by an Anticalin protein that specifically binds IL-23. Airway administration of the IL-23 binding Anticalin protein (AcIL-23) decreased lung neutrophils, eosinophils, macrophages, and lymphocytes, IL-17+ CD4 T cells, mucous cell metaplasia and methacholine-induced airway hyperresponsiveness. Selective targeting of IL-23 with a monoclonal antibody (IL-23p19) (αIL-23) also decreased macrophages, IL-17+ CD4 T cells and airway hyperresponsiveness. In contrast, a monoclonal antibody against IL-17A (αIL-17A) had no significant effect on airway hyperresponsiveness, but did decrease lung neutrophils, macrophages, and IL-17+ CD4 T cells. Targeting the IL-23 pathway did not significantly change IL-5+ or IL-13+ CD4 T cells. Together, these data indicate that airway AcIL-23 mirrored the activity of systemic anti-IL-23 antibody to decrease airway hyperresponsiveness in addition to mixed granulocytic inflammation, and that these protective actions were broader than blocking only IL-17A or IL-5, which selectively decreased airway neutrophils and eosinophils, respectively.

BACKGROUND: Asthma is a heterogeneous disorder. This study aimed to identify changes in gene expression and molecular mechanisms associated with moderate to severe asthma.
METHODS: Differentially expressed genes (DEGs) were analyzed in GSE69683 dataset among moderate asthma and its controls as well as between severe asthma and moderate asthma. Key module genes were identified via co-expression analysis, and the molecular mechanism of the module genes was explored through enrichment analysis and gene set enrichment analysis (GSEA). GSE89809 was used to verify the characteristic genes related to moderate and severe asthma.
RESULTS: Accordingly, 2540 DEGs were present between moderate asthma and the control group, while 6781 DEGs existed between severe asthma and moderate asthma. These genes were identified into 14 co-expression modules. Module 7 had the highest positive correlation with severe asthma and was recognized to be a key module by STEM. Enrichment analysis demonstrated that the module genes were mainly involved in oxidative stress-related signaling pathways. The expression of HSPA1A, PIK3CG and PIK3R6 was associated with moderate asthma, while MAPK13 and MMP9 were associated with severe asthma. The AUC values were verified by GSE89809. Additionally, 322 drugs were predicted to target five genes.
CONCLUSIONS: These results identified characteristic genes related to moderate and severe asthma and their corresponding molecular mechanisms, providing a basis for future research.

UNASSIGNED: The individualized PREdiction of DIsease Control using digital sensor Technology (iPREDICT) program was developed for asthma management using digital technology. Devices were integrated into daily lives of patients to establish a predictive model of asthma control by measuring changes from baseline health status with minimal device burden.
UNASSIGNED: To establish baseline disease characteristics of the study participants, detect changes from baseline associated with asthma events, and evaluate algorithms capable of identifying triggers and predicting asthma control changes from baseline data. Patient experience and compliance with the devices were also explored.
UNASSIGNED: This was a multicenter, observational, 24-week, proof-of-concept study conducted in the United States.
UNASSIGNED: Patients (⩾12 years) with severe, uncontrolled asthma engaged with a spirometer, vital sign monitor, sleep monitor, connected inhaler devices, and two mobile applications with embedded patient-reported outcome (PRO) questionnaires. Prospective data were linked to data from electronic health records and transmitted to a secure platform to develop predictive algorithms. The primary endpoint was an asthma event: symptom worsening logged by patients (PRO); peak expiratory flow (PEF) < 65% or forced expiratory volume in 1 s < 80%; increased short-acting β2-agonist (SABA) use (>8 puffs/24 h or >4 puffs/day/48 h). For each endpoint, predictive models were constructed at population, subgroup, and individual levels.
UNASSIGNED: Overall, 108 patients were selected: 66 (61.1%) completed and 42 (38.9%) were excluded for failure to respond/missing data. Predictive accuracy depended on endpoint selection. Population-level models achieved low accuracy in predicting endpoints such as PEF < 65%. Subgroups related to specific allergies, asthma triggers, asthma types, and exacerbation treatments demonstrated high accuracy, with the most accurate, predictive endpoint being >4 SABA puffs/day/48 h. Individual models, constructed for patients with high endpoint overlap, exhibited significant predictive accuracy, especially for PEF < 65% and >4 SABA puffs/day/48 h.
UNASSIGNED: This multidimensional dataset enabled population-, subgroup-, and individual-level analyses, providing proof-of-concept evidence for development of predictive models of fluctuating asthma control.