Obstructive sleep apnea (OSA) is a highly prevalent sleep-related breathing disorder, primarily characterized by recurrent episodes of upper airway obstruction during sleep. Individuals affected by OSA are at increased risk for a variety of adverse health outcomes, particularly neurocognitive impairments and cardiovascular complications, highlighting the clinical significance of this condition. A defining feature of OSA is intermittent hypoxemia, which contributes to the excessive production of reactive oxygen species (ROS) and the subsequent development of oxidative stress. The primary objective of this narrative review was to comprehensively investigate the intricate mechanisms of oxidative stress and elucidate their complex interplay in the development and progression of OSAS. Subsequently, we examined the current literature to identify the most promising biomarkers and pharmacological treatments related to OSA and oxidative stress. We found that biomarkers of oxidative stress have shown potential in assessing disease severity and tracking individual responses to therapy. However, none have yet to be incorporated into standard clinical practice. Continuous positive airway pressure (CPAP) is the gold standard treatment for OSA. Nevertheless, antioxidant therapy has emerged as a potential adjunctive approach that may help address residual dysfunctions not fully resolved by CPAP alone. Both the use of oxidative stress biomarkers and antioxidant-based therapies require further validation through robust clinical studies before they can be routinely implemented in clinical settings.

Asthma is a prevalent chronic condition, affecting an estimated 260 million people worldwide, according to the 2021 Global Burden of Disease Study. This condition significantly impacts individuals of all ages. One notable finding is that asthma prevalence among adults was higher in females than males. Recent evidence suggests that these disparities in asthma prevalence and outcomes are likely due to complex interactions among hormonal, anatomical, and environmental factors, coupled with societal and behavioral influences. The interchangeable use of the terms “sex” and “gender” in the scientific literature is frequently inconsistent. Biological sex is defined by anatomical and physiological characteristics determined by genetics; “gender”, on the other hand, is a more complex construct and a universally accepted definition is still lacking. This lack of clarity, coupled with potential knowledge gaps, misunderstandings, or the inherent difficulty in differentiating sex- and gender-related effects, often leads to the terms being poorly defined or used interchangeably. Such imprecise usage hinders accurate data interpretation and research progress. This paper provides a perspective review synthesizing current knowledge regarding the influence of sex and gender on asthma, specifically focusing on their impact on disease pathogenesis, clinical presentation, severity, and management strategies.

Asthma has traditionally been viewed as a single disease, but recent research reveals its clinical and molecular complexity. This perspective highlights the need to shift from a traditional, uniform treatment paradigm to one that embraces the heterogeneity of asthma across individuals. Each patient presents a unique clinical story shaped by a complex interplay of genetic predispositions, developmental programming during critical early-life windows, the influence of sex and hormones, and lifelong environmental exposures. Asthma comprises multiple subtypes with distinct clinical and biological features. Furthermore, lifestyle factors such as obesity and smoking, along with highly prevalent comorbidities like allergic rhinitis and gastroesophageal reflux disease, significantly modify the disease’s course and response to treatment. This article explores how classifying the disease into clinical phenotypes (observable characteristics) and molecular endotypes (underlying mechanisms)—particularly the distinction between T2-high and T2-low inflammation—provides a crucial framework for managing this complexity. The application of this framework, guided by biomarkers, has enabled the development of targeted biologic therapies that can transform care for specific patient subgroups. Despite these advances, significant challenges remain. The pathophysiology of certain subgroups, particularly non-T2 asthma, remains poorly defined, and there is an urgent need for reliable predictive biomarkers to guide therapy and monitor outcomes. It is our opinion that future studies must adopt a systems-biology strategy, with a multi-omics approach that constructs a comprehensive molecular profile of each patient. This integrative methodology will require the use of advanced computational methods, including machine learning and artificial intelligence, to decipher the complex pathways linking genetic and environmental inputs to clinical disease. In conclusion, this article argues for a more personalized understanding of asthma, urging clinicians and researchers to consider each patient’s unique clinical presentation.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with multiple clinical and inflammatory phenotypes. The coexistence of bronchiectasis, known as bronchiectasis–COPD overlap (BCO), identifies a subgroup with increased morbidity and mortality. Non-invasive breath analysis using electronic noses (e-noses) has shown promise in identifying disease-specific volatile organic compound (VOC) patterns (“breathprints”). Our aim was to evaluate the ability of an e-nose to differentiate between COPD and BCO patients, and to assess its utility in detecting inflammatory endotypes (neutrophilic vs. eosinophilic). In a monocentric, prospective, real-life study, 98 patients were enrolled over nine months. Forty-two patients had radiologically confirmed BCO, while fifty-six had COPD without bronchiectasis. Exhaled breath samples were analyzed using the Cyranose 320 e-nose. Principal component analysis (PCA) and discriminant analysis were used to identify group-specific breathprints and inflammatory profiles. PCA revealed significant breathprint differences between BCO and COPD (p = 0.021). Discriminant analysis yielded an overall accuracy of 69.6% (AUC 0.768, p = 0.037). The highest classification performance (76.8%) was achieved when distinguishing eosinophilic COPD from neutrophilic BCO. These findings suggest distinct inflammatory profiles that may be captured non-invasively. E-nose technology holds potential for the non-invasive endotyping of COPD, especially in identifying neutrophilic BCO as a unique inflammatory entity. Breathomics may support early, personalized treatment strategies.

Idiopathic pulmonary fibrosis (IPF) and autoimmune usual interstitial pneumonia (aUIP) share overlapping clinico-radiological features, complicating differential diagnosis. Electronic nose (eNose) technology characterizes exhaled breath profiles (“breathprints”) and may offer a non-invasive diagnostic approach in fibrotic interstitial lung diseases. To evaluate whether eNose breathprint analysis can discriminate between IPF and aUIP. In this cross-sectional study of 60 patients (34 IPF, 26 aUIP), breathprints were analyzed using principal component analysis (PCA, retaining eigenvalues > 1). Group differences were assessed via independent t-tests. Linear discriminant analysis (LDA) with leave-one-out cross-validation evaluated the discriminatory performance of PC combinations. PCA identified four principal components, with PC1 explaining 96% of the total variance. PC1 scores were significantly higher in aUIP compared to IPF (mean difference −0.53; 95% CI −1.04 to −0.02; p = 0.04); PC2-PC4 showed no significant differences (p > 0.3). LDA utilizing PC1 and PC3 achieved a cross-validated classification accuracy of 73.3% (95% CI 60.7–84.4, p < 0.05). eNose-derived breathprints showed preliminary discriminatory potential between IPF and autoimmune UIP, supporting further validation of this non-invasive adjunctive approach. Breathomics represents a promising non-invasive adjunctive tool for phenotyping fibrotic interstitial lung diseases, though larger validation studies integrating clinical and biological data are warranted.

Background/Objective: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommends using the COPD Assessment Test (CAT) and the modified Medical Research Council (mMRC) scale for symptom assessment. However, discordant results between these tools are common and may affect clinical phenotyping and treatment decisions. This study aims to identify clinical, functional, and radiological characteristics associated with discordant CAT and mMRC scores in COPD and assess the stability of this classification over time. Methods: We retrospectively analyzed 222 COPD patients classified into GOLD A, B, E, or a newly defined discordant group (GOLD_D), characterized by CAT ≥ 10 with mMRC < 2 or CAT < 10 with mMRC ≥ 2. Clinical, functional, laboratory, and imaging data were collected. Logistic regression identified predictors of GOLD classification. GOLD group changes were assessed at follow-up. Results: At baseline, 12.8% of patients belonged to the GOLD_D group. Compared to GOLD A and B, these patients had lower occupational exposure and higher rates of chest HRCT findings such as consolidations and centrilobular nodules. Regression models confirmed these features and identified FEV1 and FVC as independent predictors. GOLD classification showed notable variability during follow-up. Conclusions: Patients with discordant CAT-mMRC scores display distinct clinical and radiologic traits not captured by standard GOLD categories. These results underscore the limitations of relying solely on symptom scores and support a more comprehensive, trait-based approach to COPD assessment and management.