Search Results (165)

Background and Objectives: Alpha-1 antitrypsin deficiency (AATD) is a rare genetic condition associated with chronic respiratory diseases such as chronic obstructive pulmonary disease (COPD) and emphysema, and with liver involvement through a distinct toxic gain-of-function mechanism. Despite its clinical relevance, AATD remains underdiagnosed and exhibits marked phenotypic heterogeneity. Artificial intelligence (AI) has shown growing potential in respiratory medicine, yet its application to AATD is still limited. This systematic review synthesizes the clinical evidence on AI in AATD, primarily in the respiratory domain and, where available, in hepatic outcomes. Materials and Methods: We conducted a PRISMA-guided search (PubMed, Web of Science, IEEE Xplore) for original, peer-reviewed articles (January 2014–September 2025) applying AI to detection, classification, stratification, or prediction tasks in AATD. Results: Six studies met eligibility criteria. Supervised models (e.g., XGBoost, penalized regression, Transformer-based architectures) and one unsupervised approach were identified. Applications included screening in COPD populations, prediction of emphysema progression from CT, proteomic modeling of lung function, identification of clinical subgroups, and prediction of clinical outcomes in AATD-associated liver disease. External validation and genotype diversity remained limited across studies. Conclusions: Although AI shows promise in improving detection, prognosis, and patient stratification in AATD across both respiratory and hepatic manifestations, the current evidence remains limited. Broader, multicenter validation in genotype-diverse cohorts is required to confirm its clinical utility and support the implementation of precision medicine in AATD. Full article

Introduction: Alpha-1 antitrypsin deficiency (AATD) is a genetic condition caused by SERPINA1 variants with variable severity. Current international guidelines do not recommend augmentation therapy for intermediate AATD; nevertheless, some patients show clinically severe phenotypes in real-world practice. We aimed to evaluate, in an exploratory manner, the potential effects of augmentation therapy on exacerbations, quality of life, and lung function in this subgroup. Methods: In this multicenter retrospective study, we included 27 heterozygous patients with intermediate AATD (serum AAT 50–110 mg/dL), Chronic Obstructive Pulmonary Disease (COPD), and/or emphysema. Clinical phenotypes included emphysema-predominant disease, COPD with frequent exacerbations, and overlap with bronchiectasis/asthma; HRCT patterns were recorded. We assessed the annual number of exacerbations (moderate: steroids/antibiotics; severe: hospitalization/including pneumothorax), St. George’s Respiratory Questionnaire (SGRQ), and lung function before and after 12 months of therapy. Results: Augmentation therapy was associated with a reduction in annual exacerbations from a median (IQR) of 2 (1.5–3) to 1 (0–1) (p < 0.0001) and an improvement in SGRQ total score (58.89 ± 16.83 to 48.34 ± 21.20; p = 0.0039). The mean SGRQ change exceeded the 4-point MCID for COPD. No significant changes were observed in spirometry or Diffusing Capacity of the Lung for Carbon Monoxide (DLCO). Conclusions: These exploratory findings suggest that augmentation therapy may reduce exacerbations and improve quality of life in selected patients with intermediate AATD and COPD/emphysema. Given the retrospective design, small sample, and lack of a control group, the results should be interpreted as hypothesis-generating and warrant confirmation in prospective studies. Full article

Pulmonary hypertension (PH) with chronic obstructive pulmonary disease (COPD) is associated with poor survival with no approved therapies. We report on the response to inhaled treprostinil (iTRE) of a small retrospective cohort of PH-COPD patients with a baseline “PH-right ventricular (RV) phenotype”, defined by a RV-dependent circulatory limitation derived from a combination of echocardiographic and hemodynamic criteria. Patients were started on inhaled treprostinil with significant improvement in six-minute walk distance, NT-proBNP, and improved RV metrics by echocardiography. The preliminary findings of this cohort provide evidence for the importance of precision phenotyping of PH-COPD. Full article

Background/Objectives: Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory lung disease characterized by irreversible airway obstruction. This study aims to investigate the associations between COPD and its phenotypes with polymorphic variants of the IREB2 and CHRNA5 genes in the Kazakhstan population. Methods: A case–control study was conducted involving 265 COPD patients and 267 controls. Genotyping of the IREB2 polymorphisms rs13180 and rs2568494, as well as CHRNA5 rs16969968 polymorphism, was performed using real-time polymerase chain reactions (Real-Time PCRs). Results: A higher frequency of the AA genotype of the IREB2 rs2568494 polymorphism was identified in COPD patients with moderate to very severe airflow obstruction (Chronic Obstructive Lung Disease (GOLD) stages II, III, and IV), with an odds ratio of 0.69 (95% CI = 0.23–2.10; Padj = 0.03). The IREB2 rs13180 polymorphism was significantly more frequent or prevalent in smokers and showed a correlation with FEV₁ (forced expiratory volume in one second) (β = 7.79, SE = 2.98, p = 0.01) and FEV₁/ FVC (forced vital capacity) (β = 9.51, SE = 2.95, p = 0.002). Additionally, the CC genotype of this polymorphism was associated with clinical manifestations of COVID-19 in COPD patients (χ²= 3,95, df = 2, p = 0.05). Conclusions: Our study identified a significant association between the IREB2 rs2568494 polymorphism and an increased risk of severe COPD. The IREB2 rs13180 polymorphism was linked to smoking behavior, as well as key lung function indicators, suggesting its potential role in disease progression and lung damage. Furthermore, the CC genotype of the IREB2 rs13180 polymorphism was associated with clinical manifestations of COVID-19 in COPD patients, indicating a potential impact of this genetic variant on susceptibility to viral infections in this population. Full article

Human rhinovirus (RV) is the most frequent cause of the common cold, as well as severe exacerbations of chronic obstructive pulmonary disease (COPD) and asthma. Currently, there are no effective and accurate diagnostic tools or antiviral therapies. MicroRNAs (miRNAs) are small, non-coding sections of RNA involved in the regulation of gene expression and have been shown to be associated with different pathologies. However, the precise role of miRNAs in RV infection is not yet well established. Also, no unified computational framework exists to specifically link miRNA expression with functional gene targets during RV infection. This study aimed to first analyse the impact of RV16 on miRNA expression across the viral life cycle to identify a small panel with altered expression. We then developed a novel bioinformatics pipeline that integrated time-resolved miRNA profiling with multi-database gene-phenotype mapping to identify diagnostic biomarkers and their regulatory networks. Our in-house Python-based tool, combining mirDIP, miRDB and VarElect APIs, predicted seven genes (EZH2, RARG, PTPN13, OLFML3, STAG2, SMARCA2 and CD40LG) implicated in antiviral responses and specifically targeted by RV16 and regulated by our miRNAs. This method therefore offers a scalable approach to interrogate miRNA-gene interactions for viral infections, with potential applications in rapid diagnostics and therapeutic target discovery. Full article

Alpha-1 antitrypsin deficiency (AATD) represents a paradigmatic genetic disorder with well-characterized hepatic manifestations but relatively underexplored pulmonary implications. While liver involvement has been extensively reviewed, the underlying mechanisms of lung disease progression remain poorly understood, particularly regarding immunological pathways and inflammatory processes. The pathophysiology involves defective alpha-1 antitrypsin (AAT) production, including AAT variants that induce neutrophil elastase activity, causing progressive alveolar destruction and sustained inflammation, leading to emphysema, as one of the main components of chronic obstructive pulmonary disease (COPD). AATD and smoking represent major risk factors for COPD, the third leading cause of death worldwide at present. In AATD patients, neutrophils, which constitute the majority of circulating leukocytes, become dysregulated. Under normal conditions, cells perform essential functions, including phagocytosis and neutrophil extracellular trap formation (NETosis); in AATD, however, they accumulate excessively in alveolar spaces due to impaired elastase control. The accumulation of Z-AAT polymers within epithelial cells creates a pathological cycle, acting as chemoattractants that sustain pro-inflammatory responses and contribute to chronic obstructive pulmonary disease development. In addition, monocytes, representing a smaller fraction of leukocytes, migrate to inflammatory sites and differentiate into macrophages while secreting AAT with anti-inflammatory properties. However, in PiZZ patients, this protective mechanism fails, as polymer accumulation within cells reduces both AAT secretion and the number of protective human leukocyte antigen(HLA)-DR-monocyte subsets. In particular, macrophages demonstrate remarkable plasticity, switching between pro-inflammatory M1 (classically activated macrophages) and tissue-repairing M2 (alternatively activated macrophages) phenotypes based on environmental cues. In AATD, this adaptive capability becomes compromised due to intracellular polymer accumulation, leading to impaired phagocytic function and dysregulated cytokine production and ultimately perpetuating chronic inflammation and progressive tissue damage. Recent advances in induced pluripotent stem cell (iPSC) technology have facilitated alveolar epithelial cell (AEC) generation, in addition to the correction of AATD mutations through gene editing systems. Despite the limitations of AAT correction, iPSC-derived organoid models harboring AATD mutations can deliver important insights into disease pathophysiology, while gene editing approaches help demonstrate causality between specific mutations and observed phenotypes. Therefore, in this review, we investigated recent studies that can serve as tools for gene editing and drug development based on recently developed iPSC-related technologies to understand the pathogenesis of AATD. Full article

Background: Distinguishing chronic obstructive pulmonary disease (COPD) from asthma–COPD overlap (ACO) remains challenging due to shared clinical and inflammatory features. Interleukin-13 (IL-13) is implicated in airway inflammation and remodeling and may represent a potential treatable trait. This study aimed to evaluate whether serum IL-13 could differentiate between COPD and ACO or define ACO subtypes and to explore its relationship with clinical and phenotype parameters. Materials and Methods: We conducted a cross-sectional bicentric study in 215 COPD and ACO patients recruited from outpatient clinics. The study measured blood IL-13 levels in COPD vs. ACO patients, across five ACO subtypes, and evaluated IL-13’s ability to predict ACO. Additionally, correlations were explored among endotype (IL-13) and different phenotype traits (e.g., fractional exhaled nitric oxide (FeNO), sputum eosinophilia, serum total immunoglobulin E (tIgE) levels, blood eosinophilia, and neutrophilia) and clinical outcomes (annualized exacerbation rate, symptom scores, and pulmonary function parameters). Results: No significant differences in IL-13 levels were found between COPD and ACO patients or among ACO subtypes. IL-13 did not predict ACO occurrence. We observed a weak correlation between IL-13 and tIgE levels in the entire cohort. Additionally, there was a weak correlation between IL-13 and FeNO in patients with eosinophil counts exceeding 300 cells/μL, as well as between IL-13 and age in the COPD cohort. No correlation was found between IL-13 and other phenotypic features or clinical outcomes in the overall cohort, including within both COPD and ACO groups. Conclusions: IL-13 cannot differentiate between COPD and ACO or ACO’s subtypes. Full article

Background: Delayed diagnosis of Chronic Obstructive Pulmonary Disease (COPD) in primary care is common and contributes to preventable morbidity. A deeper understanding of pre-diagnostic patterns is needed to develop targeted detection strategies. We aimed to characterize diagnostic delay and missed diagnostic opportunities (MDOs) and identify high-risk clinical profiles. Methods: We conducted a retrospective cohort study of 167 patients newly diagnosed with COPD in primary care centers in Madrid, Spain. Healthcare utilization in the 12 months preceding diagnosis was analyzed. Multivariable logistic regression was used to identify predictors of MDOs, and K-means clustering was used to identify patient phenotypes. Results: Diagnostic delay (>30 days) was present in 45.5% of patients, and MDOs in 47.3%. MDO-positive patients had significantly worse lung function (mean FEV₁: 1577 vs. 1898 mL, p = 0.008), greater symptom burden (CAT score ≥ 10: 79.7% vs. 59.1%, p = 0.003), and more frequent pre-diagnostic exacerbations (mean: 1.24 vs. 0.71, p = 0.032). After multivariable adjustment, diagnostic delay remained a powerful independent predictor of MDOs (OR 10.25, 95% CI 4.39–24.88; p < 0.001). Cluster analysis identified three distinct clinical phenotypes: ‘Paucisymptomatic–Preserved’, ‘Frequent Attenders/High-Risk’, and ‘Silent Decliners’. Conclusions: The pre-diagnostic period in COPD is a dynamic window of detectable, and potentially preventable, clinical deterioration driven by diagnostic inertia. The identification of distinct patient phenotypes suggests that a proactive, stratified, and personalized approach, rather than a one-size-fits-all strategy, is required to improve early diagnosis in primary care. Full article

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. Full article

The study examined the association between body composition and beverage consumption and the risk of asthma and chronic obstructive pulmonary disease (COPD) and explored the single nucleotide polymorphisms (SNPs) involved in these associations by leveraging summary statistics from genome-wide association studies (GWAS) in nonoverlapping populations. The IEU OpenGWAS project was sourced for exposure datasets: body mass index, body fat percentage, fat-free mass, total body water mass, alcohol intake frequency, and coffee intake, and selected health outcome datasets: asthma and chronic obstructive pulmonary disease. Datasets were assessed and filtered using R, followed by a two-sample Mendelian randomization analysis. The MR Egger, weighted median, inverse variance weighted, simple mode, and weighted mode methods were used to examine the association between exposures and outcomes. Heterogeneity and pleiotropy analyses were used to evaluate the reliability of results. Additionally, SNPnexus was used to ascertain SNPs linked to established phenotypes, while SNP annotation was obtained from the Ensembl BioMart database via the biomaRt package. Genes belonging to overlapping groups were visualized using ComplexHeatmap. Higher body fat percentage (OR = 1.72, 95% CI: 1.23–2.41, p = 0.002), increased BMI (OR = 1.56, CI: 1.23–1.20, p = 2.53 × 10⁻⁴), and more frequent alcohol intake (OR = 1.34, CI: 1.08–1.68, p = 0.009) were associated with elevated COPD risk. Asthma risk was similarly increased with higher body fat percentage (OR = 1.60, CI: 1.23–2.21, p = 0.001), BMI (OR = 1.54, CI: 1.29–1.84, p = 2.23 × 10⁻⁶), fat-free mass (OR = 1.21, CI: 1.02–1.44, p = 0.032), and alcohol intake frequency (OR = 1.19, CI: 1.01–1.40, p = 0.039). Total body water mass and coffee intake were not associated with asthma and COPD. SNP annotation revealed that some genetic variants that influenced the association of the exposure variables with asthma and COPD were missense variants in several genes, including the evolutionarily highly conserved gene, SLC39A8 (rs13107325; C/A/T allele), and POC5 (rs2307111; T/A/C allele), as well as intronic variants in FTO (rs56094641; A/G/T allele) and NRXN3 (rs10146997; A/G allele). The discovery of the missense variants rs13107325 and rs2307111 in SLC39A8 and POC5, respectively, in addition to other intronic and synonymous SNPs suggests that these SNPs may have some roles in the development or progression of asthma and COPD. This may contribute to the identification of molecular signatures or biomarkers that forecast the risk, development, or therapeutic response of chronic lung diseases in persons with metabolic dysregulation, including obesity. Full article

Background/Objectives: Lung cancer remains a major cause of cancer-related mortality, with regional differences in incidence and patient characteristics. This study aimed to verify and quantify a perceived dramatic increase in lung cancer cases at a Romanian center, identify distinct patient phenotypes using unsupervised machine learning, and characterize contributing factors, including demographic shifts, changes in the healthcare system, and geographic patterns. Methods: A comprehensive retrospective analysis of 4206 lung cancer patients admitted between 2013 and 2024 was conducted, with detailed molecular characterization of 398 patients from 2023 to 2024. Temporal trends were analyzed using statistical methods, while k-means clustering on 761 clinical features identified patient phenotypes. The geographic distribution, smoking patterns, respiratory comorbidities, and demographic factors were systematically characterized across the identified clusters. Results: We confirmed an 80.5% increase in lung cancer admissions between pre-pandemic (2013–2020) and post-pandemic (2022–2024) periods, exceeding the 51.1% increase in total hospital admissions and aligning with national Romanian trends. Five distinct patient clusters emerged: elderly never-smokers (28.9%) with the highest metastatic rates (44.3%), heavy-smoking males (27.4%), active smokers with comprehensive molecular testing (31.7%), young mixed-gender cohort (7.3%) with balanced demographics, and extreme heavy smokers (4.8%) concentrated in rural areas (52.6%) with severe comorbidity burden. Clusters demonstrated significant differences in age (p < 0.001), smoking intensity (p < 0.001), geographic distribution (p < 0.001), as well as molecular characteristics. COPD prevalence was exceptionally high (44.8–78.9%) across clusters, while COVID-19 history remained low (3.4–8.3%), suggesting a limited direct association between the pandemic and cancer. Conclusions: This study presents the first comprehensive machine learning-based stratification of lung cancer patients in Romania, confirming genuine epidemiological increases beyond healthcare system artifacts. The identification of five clinically meaningful phenotypes—particularly rural extreme smokers and age-stratified never-smokers—demonstrates the value of unsupervised clustering for regional healthcare planning. These findings establish frameworks for targeted screening programs, personalized treatment approaches, and resource allocation strategies tailored to specific high-risk populations while highlighting the potential of artificial intelligence in identifying actionable clinical patterns for the implementation of precision medicine. Full article

Chronic obstructive pulmonary disease (COPD) is an escalating global health burden, with a disproportionate impact on low- and middle-income countries (LMICs). Although tobacco smoking is a well-established risk factor, emerging evidence highlights the significant role of non-smoking exposure in driving the prevalence of COPD in these regions. This narrative review synthesizes current data on key non-smoking contributors, including household air pollution, ambient urban pollution, occupational exposure, early-life respiratory insults, chronic infections, and socioeconomic adversity. These risk factors are associated with distinct COPD phenotypes, often marked by increased airway inflammation, reduced emphysema, and variable airflow limitation. Such presentations are particularly common among women and younger populations in LMICs. However, diagnostic and therapeutic challenges persist, owing to limited disease awareness, under-resourced health systems, restricted access to essential medications, and financial constraints impacting adherence. Despite the proven effectiveness of non-pharmacological measures and public health interventions, their implementation remains inadequate because of infrastructural and funding limitations. Bridging these gaps requires region-specific clinical guidelines, improved diagnostic infrastructure, expanded access to affordable treatment, and culturally sensitive interventions. Future priorities include identifying robust biomarkers, refining disease definitions to accommodate non-smoking phenotypes, and advancing implementation science to improve interventions. A coordinated, context-aware global response is essential to reduce the growing burden of COPD in LMICs and to ensure equitable respiratory health outcomes. Full article

Background: Chronic Obstructive Pulmonary Disease (COPD) exhibits some phenotypic differences between patients with biomass smoke inhalation (COPD-B) and tobacco smoking (COPD-T). COPD-B is characterized by less emphysema but more airway disease and vascular pulmonary remodeling, which are related to mast cells in lung tissues in COPD-T. Our objective was to describe the differences between the number of mast cells in COPD-B and COPD-T patients. Methods: A cross-sectional study was conducted on lung tissue resections for suspected cancer obtained between 2014 and 2021 from patients with documented COPD due to wood smoke or tobacco exposure. Histological samples were analyzed for mast cell count, CD34+ expression, and structural changes in lung tissue and pulmonary circulation. Results: A total of 20 histological samples were analyzed, with significant differences found in mast cell count [median 8 (p25-75, 5–11) vs. 2 (p75-25, 0–6), p = 0.016] and severe peribronchiolar fibrosis (60% vs. 10%, p = 0.04) between COPD-B and COPD-T patients. A positive correlation [Spearman rho = 0.879 (95% CI 0.71–0.96), p < 0.001] was observed between mast cell count and a gradual increase in pulmonary artery diameter. Conclusions: These preliminary findings suggest histological differences and the presence of mast cells between COPD-B and COPD-T, which should be confirmed in a larger number of samples and patients. Full article

Background/Objective: Obesity is a documented risk factor for impaired pulmonary function and abnormal oxyhaemoglobin levels during sleep. This functional impairment becomes more significant when there are additional respiratory pathologies, such as obstructive sleep apnea (OSA) and/or chronic obstructive pulmonary disease (COPD). Overnight pulse oximetry may offer an effective evaluation of nocturnal oxyhaemoglobin levels/waveform patterns. We evaluated the correlation between obesity, overnight pulse oximetry (parameters, waveform patterns) and pulmonary function in patients diagnosed with moderate–severe OSA and normal oxyhaemoglobin saturation levels during waking hours. We also compared the overnight oxyhaemoglobin saturation levels between patients with OSA alone and those with associated COPD. Methods: This was a retrospective, transversal, non-interventional study on consecutive patients with moderate–severe OSA diagnosed using overnight cardiorespiratory polygraphy over a period of 18 months. After analyzing the study population’s characteristics, the patients were divided into two subgroups: one consisting of patients with OSA alone (Group A), and the second with coexisting OSA and COPD (Group B). Results: Seventy-six patients were included in the study, and 18% were diagnosed with COPD. A higher body mass index (BMI) correlated with a higher number of ≥3% SpO₂ drops/h (ODI3) and percentage of time with oxyhaemoglobin saturation < 90% (t90) and a lower average nocturnal oxyhaemoglobin saturation (avgSpO₂). ODI3 correlated negatively with avgSpO₂ and positively with t90. After eliminating BMI as a confounding factor, lower values of forced expiratory volume in the first second (FEV1) were associated with lower avgSpO₂ and higher t90. FEV1 did not corelate with ODI3. After dividing the study population into the two subgroups, patients from Group B had a tendency towards lower average nocturnal SpO₂ levels compared to Group A. Conclusions: Different phenotypes/patterns of nocturnal hypoxemia can be identified using quantitative and qualitative analyses of overnight pulse oximetry: repetitive, consecutive obstructive respiratory events with a characteristic intermittent (saw-tooth) hypoxemia pattern and alveolar hypoventilation, resulting in a continuous (plateau) hypoxemia pattern. According to our findings, nocturnal hypoxemia is more important at lower FEV1 values (correlating with lower avgSpO₂/higher t90, but not with ODI3). The presence of a continuous hypoxemia pattern in patients with OSA may suggest that pulmonary function tests should be performed in order to differentiate patients with alveolar hypoventilation secondary to obesity (restrictive syndrome) from those with associated COPD (obstructive syndrome). This can have an impact on the management of the case and the therapeutic approach (positive pressure therapy with/without supplemental oxygen). Full article