Search Results (334)

Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory infections (ALRIs) in young children, especially bronchiolitis, with significant global health and economic impact. Increasing evidence links early-life RSV infection to long-term respiratory complications, notably recurrent wheezing and asthma. This narrative review examines these associations, emphasizing predictive factors and emerging biomarkers for risk stratification. Early RSV infection can trigger persistent airway inflammation and immune dysregulation, increasing the likelihood of chronic respiratory outcomes. Risk factors include severity of the initial infection, age at exposure, genetic susceptibility, prematurity, air pollution, and tobacco smoke. Biomarkers such as cytokines and chemokines are showing promise in identifying children at higher risk, potentially guiding early interventions. RSV-related bronchiolitis may also induce airway remodeling and promote Th2/Th17-skewed immune responses, mechanisms closely linked to asthma development. Advances in molecular profiling are shedding light on these pathways, suggesting novel targets for early therapeutic strategies. Furthermore, passive immunization and maternal vaccination offer promising approaches to reducing both acute and long-term RSV-related morbidity. A deeper understanding of RSV’s prolonged impact is essential to develop targeted prevention, enhance risk prediction, and improve long-term respiratory health in children. Future studies should aim to validate biomarkers and refine immunoprophylactic strategies. Full article

Respiratory diseases represent a persistent global health challenge, underscoring the need for intelligent, accurate, and personalized diagnostic and therapeutic systems. Existing methods frequently suffer from limitations in diagnostic precision, lack of individualized treatment, and constrained adaptability to complex clinical scenarios. To address these challenges, our study introduces a modular AI-powered framework that integrates an audio-based disease classification model with simulated molecular biomarker profiles to evaluate the feasibility of future multimodal diagnostic extensions, alongside a synthetic-data-driven prescription recommendation engine. The disease classification model analyzes respiratory sound recordings and accurately distinguishes among eight clinical classes: bronchiectasis, pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma, chronic obstructive pulmonary disease (COPD), bronchiolitis, and healthy respiratory state. The proposed model achieved a classification accuracy of 99.99% on a holdout test set, including 94.2% accuracy on pediatric samples. In parallel, the prescription module provides individualized treatment recommendations comprising drug, dosage, and frequency trained on a carefully constructed synthetic dataset designed to emulate real-world prescribing logic.The model achieved over 99% accuracy in medication prediction tasks, outperforming baseline models such as those discussed in research. Minimal misclassification in the confusion matrix and strong clinician agreement on 200 prescriptions (Cohen’s $\kappa$ = 0.91 [0.87–0.94] for drug selection, 0.78 [0.74–0.81] for dosage, 0.96 [0.93–0.98] for frequency) further affirm the system’s reliability. Adjusted clinician disagreement rates were 2.7% (drug), 6.4% (dosage), and 1.5% (frequency). SHAP analysis identified age and smoking as key predictors, enhancing model explainability. Dosage accuracy was 91.3%, and most disagreements occurred in renal-impaired and pediatric cases. However, our study is presented strictly as a proof-of-concept. The use of synthetic data and the absence of access to real patient records constitute key limitations. A trialed clinical deployment was conducted under a controlled environment with a positive rate of satisfaction from experts and users, but the proposed system must undergo extensive validation with de-identified electronic medical records (EMRs) and regulatory scrutiny before it can be considered for practical application. Nonetheless, the findings offer a promising foundation for the future development of clinically viable AI-assisted respiratory care tools. Full article

Asthma, the most common chronic respiratory condition in children, involves airway inflammation, hyper-responsiveness, and frequent exacerbation that worsen the airflow and inflammation. Exosomes, extracellular vesicles carrying microRNAs (miRNAs), play a key role in cell communication alongside other types of communication and are promising markers of asthma severity. This study compares exosomal miRNA and long non-coding RNA (lncRNA) profiles in boys with asthma, focusing on differences between those with normal lung functions and those with severe airflow obstruction. This study enrolled 20 boys aged 9–18 years with asthma, split into two groups based on their lung function. Ten had normal lung function (NLF; FEV1/FVC > 0.84, FEF75% > 69% predicted), while ten had severe airflow obstruction (SAO; FEV1/FVC < 0.70, FEF75 < 50% predicted). Saliva and blood samples were collected. Exosomes were isolated, quantified, and analyzed via small RNA sequencing to identify differentially expressed (DE) miRNA and lncRNA profiles. Bioinformatic tools were then used to explore potential miRNA biomarkers linked to asthma severity. SAO subjects were more likely to exhibit allergen sensitization, higher IgE levels, and more eosinophils. We identified 27 DE miRNAs in plasma and 40 DE miRNAs in saliva. Additionally, five key miRNAs were identified in both saliva and plasma which underline important pathways such as neurotrophins, T-cell receptor, and B-cell receptor signaling. We further outlined key features and functions of miRNAs and long non-coding RNAS (lncRNAs) and their interactions in children with asthma. This study identified DE miRNAs and lncRNAs in children with SAO when compared to those with NLF. Exosomal miRNAs show strong potential as non-invasive biomarkers for personalized asthma diagnosis, treatment, and monitoring. These RNA markers may also aid in tracking disease progression and response to therapy, thereby supporting the need for future studies aimed at applications in precision medicine. Full article

Background: Mepolizumab is an effective treatment for severe eosinophilic asthma, leading to a depletion of blood eosinophil levels, the clinical relevance of which remains unclear. Objective: The aim of this study was to assess the relationship between mepolizumab-induced blood eosinophil reduction and clinical outcome in patients with severe eosinophilic asthma, in particular, whether the magnitude of blood eosinophil reduction was associated with clinical remission. Methods: We conducted a real-world retrospective analysis of 58 adult patients with severe eosinophilic asthma treated with mepolizumab. Clinical and respiratory functional parameters were evaluated at the start of mepolizumab treatment (T0) and after two years of treatment (T2; mean follow-up: 22.8 ± 7.5 months). Blood eosinophil counts were recorded at T0 and during the first year of treatment (T1; mean follow-up: 7.7 ± 4.1 months). Results: After two years of mepolizumab treatment, 58 severe asthmatic patients showed significant improvements in ACT score, FVC, and FEV₁ and a reduction in acute exacerbations and the use of maintenance therapies. Clinical remission was achieved in 55.1% of patients. Lower blood eosinophil counts during the first year (T1) were associated with greater improvements in lung function and fewer exacerbations. A greater relative decrease in eosinophils from baseline to T1 (ΔEOS%) was significantly associated with remission, reductions in exacerbations, and no maintenance OCS use. ΔEOS% was the only independent predictor of remission in the multivariate analysis. A ≥90% reduction predicted remission with 80% specificity (AUC = 0.726). Conclusions: Monitoring blood eosinophils after mepolizumab initiation could be a useful tool for predicting long-term response to treatment. In particular, a reduction by over 90% of peripheral blood eosinophils during the first year of mepolizumab treatment predicts clinical remission with a specificity of 80%. Considering the accessibility and the low cost of this biomarker, it may help to optimize long-term asthma management. Full article

Diagnosing and prognosing immune-mediated airway diseases, like hypersensitivity pneumonitis (HP) and sarcoidosis, is complicated due to their overlapping symptoms and the lack of definitive biomarkers. Hence, we wanted to compare bronchoalveolar lavage (BAL) cytokine and chemokine profiles from 92 patients with different immune-mediated and inflammatory airway diseases, namely, HP, sarcoidosis, non-allergic asthma, amiodarone lung, and EGPA. We also compared pulmonary function parameters, BAL’s cellularity, and lymphocyte immunophenotypes. We found significant differences across all measured lung functions (VC, VC%, FEV1, FEV1%, and Tiff%) and in the number of macrophages, lymphocytes, neutrophils, and eosinophils. Furthermore, we showed significant differences in CD4, CD8, and CD4/8 across all included ILDs and OLDs; however, no significant differences were found in CD3, CD19, NK, or NKT. We identified nine biomarkers (IL-1β, IL-6, IL-8, IL-13, VEGF, angiogenin, C4a, RANTES, and MCP-1) that significantly differ in the BAL of patients with HP and sarcoidosis and showed that RANTES and IL-6 are associated with fibrotic outcome. We have demonstrated that interstitial and obstructive lung diseases differ in cytokine and cellular lung imprint, which may, in the future, enable the determination of the disease subtype and thus the identification of targets for the treatment of individuals or subgroups within diseases. Full article

Asthma places a significant burden at individual and societal levels, but there remains no gold-standard objective test for asthma diagnosis or asthma severity risk prediction. MicroRNAs (miRNAs) are short non-coding RNA sequences that are attracting interest as biological signatures of health and disease status. We sought to construct serum miRNA panels that could serve as potential biomarkers to aid in the diagnosis of asthma and predict asthma severity. Thirty-five asthma-related miRNAs were screened in the serum of three patient groups (never-asthma, mild-asthma, and severe-asthma; n = 50/group) drawn from two well-characterised cohorts. miRCURY LNA technology was used, followed by GeneGlobe analysis. The associations of miRNA expression with clinical outcomes of interest and diagnostic value of the proposed miRNA panels were assessed. We identified an asthma diagnosis panel comprising upregulated miR-223-3p, miR-191-5p, and miR-197-3p (area under curve (AUC) = 0.813, sensitivity 76% and specificity 72%). Compared with mild-asthma individuals, we also identified an asthma severity risk panel comprising upregulated miR-223-3p plus downregulated miR-30a-5p, miR-660-5p, and miR-125b-5p (AUC = 0.759, sensitivity 78%, specificity 64%). Individual miRNAs showed associations with worse clinical asthma severity and impaired quality of life. miRNA panels with high sensitivity and specificity offer potential as biomarkers for asthma diagnosis and asthma severity. Full article

Asthma represents a heterogeneous disorder characterized by a dynamic balance between pro-inflammatory and anti-inflammatory forces, with allergic sensitization contributing substantially to airway hyperresponsiveness and remodeling. Central to its pathogenesis are cytokines such as IL-4, IL-5, IL-13, IL-17, and IL-33, which drive recruitment of eosinophils, neutrophils, and other effector cells, thereby precipitating episodic exacerbations in response to viral and environmental triggers. Conventional biomarkers, including blood and sputum eosinophil counts, IgE levels, and fractional exhaled nitric oxide, facilitate phenotypic classification and guide the emerging biologic era. Monoclonal antibodies targeting IgE (omalizumab) and IL-5 (mepolizumab, benralizumab, reslizumab, depemokimab) have demonstrated the ability to reduce exacerbation frequency and improve lung function, with newer agents such as depemokimab offering extended dosing intervals. Itepekimab, an anti-IL-33 antibody, effectively engages its target and mitigates tissue eosinophilia, while CM310-stapokibart, tralokinumab, and lebrikizumab inhibit IL-4/IL-13 signaling with variable efficacy depending on patient biomarkers. Comparative analyses of these biologics, encompassing affinity, dosing regimens, and trial outcomes, underscore the imperative of personalized therapy to optimize disease control in severe asthma. Full article

Asthma is a highly heterogeneous respiratory disease that, in its severe forms, is characterized by persistent symptoms, frequent exacerbations, and a significant impact on patients’ quality of life. Despite high-dose inhaled corticosteroids and long-acting bronchodilators, a subset of patients remains uncontrolled, necessitating advanced therapeutic strategies. The advent of biologic therapies has revolutionized the management of severe asthma, offering targeted interventions based on the underlying inflammatory endotypes, primarily T2-high and T2-low. However, selecting the most appropriate biologic remains challenging due to overlapping phenotypic features and the limited availability of validated biomarkers. This narrative review explores the clinical utility of key biomarkers, including blood eosinophils, fractional exhaled nitric oxide (FeNO), periostin, and total and specific IgE, in guiding biologic therapy. All the information provided is based on an extensive literature search conducted on PubMed. We also examine the clinical characteristics and comorbidities that influence therapeutic choices. Furthermore, we present a practical decision-making platform, including a clinical table matching phenotypes with biologic agents, such as omalizumab, mepolizumab, benralizumab, dupilumab, and tezepelumab. By integrating biomarker analysis with clinical assessment, based on current guidelines and our extensive real-life experience, we aim to offer a logical framework to help clinicians select the most suitable biologic treatment for patients with uncontrolled severe asthma. Future research should focus on identifying novel biomarkers, refining patient stratification, and evaluating long-term outcomes to further advance precision medicine in the management of severe asthma. Full article

Asthma is a chronic and heterogeneous inflammatory airway disease with diverse clinical endotypes and limited curative treatment options. Recent systems biology analyses identified four potential molecular triggers—AKT1, MAPK13, STAT1, and TLR4—as candidate regulators of asthma-associated signaling pathways. This study aimed to validate the expression of these four proteins and their downstream signaling elements in peripheral blood mononuclear cells (PBMCs) from patients with allergic asthma (AA), nonallergic asthma (NA), and healthy controls (HC), to explore their potential as biomarkers or therapeutic targets. For that, PBMC samples were collected from 45 AA patients, 17 NA patients, and 15 HC subjects. Gene and protein expression of AKT1, MAPK13, STAT1, and TLR4 were quantified using RT-qPCR and Western blotting. Expression patterns were compared across groups and stratified by asthma severity. Correlations with clinical parameters (FEV1, FVC, FeNO, IgE, eosinophil counts) and treatment regimens were also assessed. All four target genes showed significantly reduced expression in asthma patients compared to controls (p < 0.001), with the most marked downregulation in NA patients. At the protein level, MAPK13 and TLR4 showed significant differential expression. Stratification by severity revealed a stepwise reduction in gene expression in AA patients, correlating with disease severity, whereas NA patients showed uniformly low expression regardless of severity. Multiple pathway-related genes, including RELA, SMAD3, NFATC1, and ALOX5, were also downregulated, particularly in NA patients. Notably, differential correlations were observed between gene expression and lung function parameters in AA vs. NA groups. In conclusion, this study supports the potential involvement of AKT1, MAPK13, STAT1, and TLR4 in asthma pathogenesis and highlights differences between allergic and nonallergic asthma at the molecular level. These proteins and their associated pathways may serve as future targets for biomarker development or endotype-specific therapies. Further studies in larger and more diverse cohorts, including functional validation, are warranted. Full article

Background/Objectives: Recurring infections in children with allergies pose significant clinical challenges, with these conditions often exacerbating each other through complex immunological interactions. This narrative review examines the connection between recurring infections and allergic conditions in pediatric patients, focusing on how immune system dysfunction influences infection susceptibility in respiratory allergies. Methods: A comprehensive literature search across PubMed, Web of Science, and SciELO databases was conducted from January 2014 to May 2024. Studies involving children and adolescents up to 18 years old with diagnosed respiratory allergies were included, while reviews, opinion pieces, case reports, and studies not addressing immune–infection interactions were excluded. Results: Analysis reveals significant immune dysfunction in allergic children, affecting both innate and adaptive immunity components. Children with allergic rhinitis and asthma demonstrate decreased interferon-gamma production, increasing vulnerability to viral infections (particularly rhinovirus) and bacterial infections such as Mycoplasma pneumoniae. Rhinovirus represents the most common pathogen, present in 75% of asthma exacerbations. Atopic children exhibit markedly higher bacterial infection rates, with 27.1% showing Mycoplasma pneumoniae involvement versus 4.9% in non-atopic children. Conclusions: Recurring infections in allergic pediatric patients result from significant immune dysfunction involving altered cytokine production and immune cell function. These complex interactions highlight the need for targeted therapeutic approaches that enhance immune responses and reduce infection risks. Future research should focus on identifying specific biomarkers and immune mechanisms for developing more effective interventions. Full article

During the early stages of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, concerns arose regarding the susceptibility of asthmatic children, one of the most common chronic conditions in childhood and a major cause of hospitalization in pediatric settings. Unexpectedly, evidences showed milder clinical courses and fewer asthma exacerbations in these patients, even if cases of critical and fatal infection, often related to specific clinical features of the patient, are not negligible. In this regard, obesity is considered not only an important comorbidity in patients with difficult-to-treat asthma but also a risk factor for more severe forms of COVID-19. These observations are of even greater concern in the context of an increase in childhood obesity that began even before the SARS-CoV-2 pandemic and has continued also as a consequence of it. Given asthma’s heterogeneity, especially in children, an endotype-based approach is crucial. This is possible through a detailed analysis of the complex metabolic pathways that correlate asthma, COVID-19 infection and obesity thanks to new high-through-put technologies, especially metabolomics, which with minimally invasive sampling, including on exhaled breath condensate (EBC), can provide precise and unbiased evidence in support of existing endotypes, making it possible to identify not only the most vulnerable individuals and thus risk stratification through specific biomarkers, but also new molecular and therapeutic targets. This review explores asthma endotypes by highlighting their shared immunometabolic pathways with COVID-19. Findings suggest that metabolomics could enable more accurate risk stratification and guide personalized interventions during viral pandemics, especially in the presence of relevant comorbidities such as obesity. Full article

House dust mites (HDMs) are a major source of indoor allergens, significantly contributing to allergic rhinitis, asthma and atopic dermatitis. This review examines the epidemiology, microbiological classification and pathophysiology of HDM allergy, highlighting key allergens such as Der p 1, Der p 2 and Der p 23. Furthermore, we discuss the pivotal role of allergen-specific immunotherapy (AIT), the only disease-modifying treatment for immunoglobulin (Ig)-E disease. Recent studies have identified predictive biomarkers for allergen-specific immunotherapy (AIT) efficacy, including the specific IgE to total IgE (sIgE/tIgE) ratio and regulatory follicular T cell profiles, supporting a more personalized approach to therapy. Additionally, emerging immunotherapy strategies, such as recombinant allergens and peptide-based formulations, aim to improve safety and clinical outcomes. As HDM allergy prevalence rises globally, further research into optimizing diagnostics and treatment strategies remains crucial for enhancing patient care. Full article

Recent advancements in spatial transcriptomics (ST) have revolutionized our understanding of the lung’s cellular organization and pathological alterations. By preserving the spatial distribution of gene expression, ST reveals localized immune niches, stromal–epithelial interactions, and disease-associated transcriptional “hotspots” that cannot be captured by conventional sequencing methods alone. In lung cancer, ST-based investigations have delineated distinct tumor microenvironments between tumor cores and invasive fronts, revealing prognostically significant gene signatures and identifying subpopulations with differential responses to immunotherapy and chemotherapy. Similarly, in chronic obstructive pulmonary disease, asthma, and idiopathic pulmonary fibrosis, ST has mapped the ecosystem, including immune cells, inflammatory mediators, and fibroblast subtypes, of discrete regions within diseased lung tissue, offering mechanistic insights into disease progression and tissue remodeling. In addition, a more recent ST study provides spatial information for where drugs act within tissues. This review highlights the emerging role of spatial transcriptomics in respiratory research, demonstrating its potential to refine disease classification, elucidate mechanisms of therapeutic resistance, and inform spatially guided personalized interventions in respiratory diseases. Full article

Lipids play important roles in maintaining pulmonary structure, performing physiological functions and controlling the immune status of the lung. There is increasing evidence that lipid metabolism and immune activity are closely linked and that dysfunction in lipid metabolism contributes to the development and progression of chronic respiratory diseases such as COPD and asthma. These diseases are characterized by metabolic and immune dysregulation, with lipid mediators playing a key role in both the development and resolution of inflammation. In this regard, lipid metabolic pathways are attracting increasing attention as promising targets for biomarker detection and therapeutic intervention. Full article

Background: Asthma is a chronic inflammatory airway disease in which oxidative stress and antioxidant imbalance play a critical role in disease progression and therapeutic response. This study aimed to evaluate oxidative stress and antioxidant status in relation to asthma control levels. Methods: A total of 106 patients admitted to the Clinical Hospital of Pulmonary Diseases, Iași, between March and May 2024 were included in this study. Patients were classified into three groups based on asthma control: well-controlled (AB-TCG), partially controlled (AB-PCG), and uncontrolled asthma (AB-UCG). Demographic, biochemical, and hematological parameters were assessed, with attention to oxidative stress markers and antioxidant defenses. Results: The study population was predominantly female (75%), with a mean age ranging from 50.75 to 64.38 years, and the majority residing in rural areas (73–75%). The AB-UCG group showed significantly elevated inflammatory markers, including a white blood cell count of 9.33 × 10³/µL (p = 0.005) and eosinophil percentage of 4.20% (p = 0.03), compared with the other groups. This group also exhibited an unfavorable lipid profile, with increased total cholesterol (207.40 mg/dL) and triglyceride levels (157.21 mg/dL). Oxidative stress was notably higher in the AB-UCG group, as indicated by elevated malondialdehyde (MDA) levels (2.86 mmol/L) versus 2.35 mmol/L in the AB-PCG group (p < 0.005), along with decreased serum uric acid (4.64 mg/dL) and reduced glutathione (GSH) levels (275.41 µmol/L), leading to a lower GSH/GSSG ratio. Environmental exposures, including tobacco smoke and occupational chemicals, were associated with exacerbated oxidative imbalance. Conclusions: The findings highlight the critical involvement of oxidative stress and compromised antioxidant defenses in poorly controlled asthma. Biomarkers such as MDA, white blood cell count, eosinophil percentage, and the GSH/GSSG ratio may act as valuable tools for personalized asthma management and therapeutic monitoring. Full article