Search Results (172)

Assessing autophagy may offer insights into the pathogenesis of chronic obstructive pulmonary disease (COPD). However, measuring the dynamic aspect of autophagy is challenging, and sample manipulation can cause signal fluctuations that deviate from physiological conditions. We applied an organotypic method to quantify autophagy in COPD, where it frequently demonstrates disease-related dysregulation. Blood from control and COPD participants was treated with or without chloroquine. Microtubule-associated protein 1 light chain 3B II (LC3B-II) abundance was quantified in peripheral blood mononuclear cells (PBMCs), and findings were validated by transmission electron microscopy. Our observations show that while basal LC3B-II abundance was similar between groups (p = 0.60), autophagic flux was significantly lower in the COPD cohort, suggesting disruption in the regulatory factors that direct autophagosome clearance (p = 0.004). This was supported by less frequent observations of autophagy-related vacuoles in the cytosol of COPD-derived PBMCs. Our findings indicate that the suppression of autophagy can be detected in the blood of individuals with COPD, which warrants further investigation into its contribution to extrapulmonary disease processes. Full article

Background: Atrial fibrillation (AF) is a common arrhythmia with a high incidence, and patients with chronic obstructive pulmonary disease (COPD) are at particularly high risk. However, there are currently no tools available for early risk stratification of AF in this population. Objectives: To develop and validate a neural network diagnostic model based on transthoracic echocardiography to address two clinical challenges in patients with COPD: risk stratification for AF; and detection of occult supraventricular arrhythmias (including “micro-AF”) based on 24 h ECG monitoring data. Methods: The study consisted of three consecutive stages: development of a neural network (NN) based on transthoracic echocardiography (TTE) parameters, validation of the model’s predictive ability in patients (n = 311, including 99 with COPD), and assessment of the ability to detect occult atrial arrhythmias (n=207) in patients with COPD. The model architecture consists of a fully connected multilayer perceptron (MLP) with 13 inputs, 4 hidden layers of 130 neurons each, and 2 output neurons. Training was performed on 684 TTE scans (292 without AF, 392 with AF). The echocardiographic parameters were validated on an independent test set (n = 100). Statistical analysis included pairwise and multiple comparisons, logistic regression analysis, and ROC analysis with assessment of the area under the ROC curve (AUC). The median follow-up period for study participants was 18 months. Results: The neural network demonstrated high classification metrics for AF on the test set (AUC = 0.80). A threshold value of the first output layer neuron > 0.75 allowed for the identification of a high-risk subgroup, in which the incidence of AF in patients with COPD was 14.8% versus 0% in the low-risk subgroup (p = 0.0073). Logistic regression models of the relationship between AF development and the neural network output value were statistically significant in both patients with COPD and patients without COPD (p < 0.0001). In patients with COPD without a history of AF, the neural network identified a high-risk group. In this group, 24 h ECG monitoring more frequently recorded episodes of AF, group supraventricular extrasystoles, and the combined endpoint (AF + GSE) compared to the low-risk group (55.32% vs. 17.5%; p < 0.0001). The area under the ROC curve for detecting latent AF in patients with sinus rhythm based on the neural network prediction was 0.93. Conclusions: The developed neural network model, which integrates a set of TTE parameters into a single quantitative measure of the severity of myocardial remodeling, is an effective tool for risk stratification for AF. The model may help identify COPD patients who could benefit from intensified rhythm monitoring; however, external validation is required before clinical implementation. Full article

Background: Pre-Chronic Obstructive Pulmonary Disease (pre-COPD) and Preserved Ratio Impaired Spirometry (PRISm) phenotypes represent important components of the early obstructive lung disease spectrum, characterized by respiratory symptoms and structural lung abnormalities prior to the development of overt airflow limitation. Emphysema is considered one of the major structural phenotypes underlying airway disease and the COPD spectrum. Although cigarette smoking is the best recognized risk factor for these conditions, non-tobacco exposures may also contribute to early structural lung changes. In this study, we evaluated the radiological features, pulmonary function parameters, and dyspnea severity of CT-detected emphysema in symptomatic patients classified as having pre-COPD or PRISm, with particular attention paid to the potential influence of smoking status on disease characteristics. Methods: In this retrospective, single-center study, symptomatic patients aged 20–50 years classified as having pre-COPD or PRISm and in whom emphysema was detected on high-resolution computed tomography (HRCT) were evaluated. Only symptomatic patients who underwent HRCT for clinical indications and in whom emphysema was identified were included. Demographic characteristics, emphysema type and quantitative emphysema severity, pulmonary function parameters, and Modified Medical Research Council (mMRC) dyspnea scores were analyzed. The PRISm and pre-COPD groups were compared in terms of clinical and symptomatic characteristics. In addition, smoking-related clinical and radiological characteristics were also evaluated. Results: A total of 232 patients were included in the study. The median age was 43 years (38–48), and 84.1% of the participants were male. Among the study population, 68.5% were classified in the pre-COPD group and 31.5% in the PRISm group. The most frequently identified emphysema patterns were paraseptal (44.4%) and centrilobular (40.5%). The median total lung emphysema area was 18% (13–22). A weak negative correlation was observed between the degree of emphysema and FEV₁ (r = −0.185; p = 0.005), whereas a weak positive correlation was found between emphysema extent and the mMRC dyspnea score (r = 0.214; p = 0.001). Dyspnea severity was significantly higher in the PRISm group compared with the pre-COPD group (p < 0.001). In the smoking-status subgroup analysis, ever-smokers demonstrated significantly greater dyspnea severity and lower FEV₁ values, whereas never-smokers had a significantly higher proportion of emphysema extent > 18% (all p < 0.05). Conclusions: Radiologically detected emphysema in symptomatic patients without airflow limitation was associated with statistically significant but weak alterations in pulmonary function and dyspnea burden. Dyspnea severity was significantly higher in the PRISm phenotype. In a smoking-status subgroup analysis, ever-smokers had significantly greater dyspnea severity, whereas never-smokers showed a significantly higher proportion of extensive emphysema (>18%), despite similar functional impairment across groups. These findings underscore the importance of non-tobacco exposures in the development of emphysema within pre-obstructive spirometric phenotypes. Multicenter prospective studies incorporating healthy controls and systematic exposure documentation are needed to confirm these observations. Full article

Background: Industrial activities may contribute to airway diseases, particularly chronic obstructive pulmonary disease (COPD) and asthma, which are major respiratory health problems with geographically variable prevalence. The objective of this study was to assess the prevalence of COPD and asthma and to examine factors associated with impaired pulmonary function among workers and residents of the Navanakorn Industrial Zone, Thailand. Methods: A cross-sectional study was performed from September 2025 to January 2026 among adults aged ≥18 years who were employed in or residing within the Navanakorn Industrial Zone. Data collected included demographic characteristics, comorbidities, respiratory symptoms, chest radiographic findings, and spirometric parameters, including forced vital capacity (FVC), forced expiratory volume in one second (FEV₁), and bronchodilator responsiveness (BDR). COPD was defined as the presence of respiratory symptoms in conjunction with at least one risk factor and a post-bronchodilator FEV₁/FVC < 70%. Asthma was defined by the presence of respiratory symptoms with a positive BDR. Results: Among the 373 participants (65.4% female; mean age 55.0 ± 13.6 years), the prevalence of COPD and asthma was 4.3% and 5.4%, respectively. Abnormal chest radiographic findings were present in 8.6%, while abnormal pulmonary function was identified in 30.8%. Lung function abnormalities included airway obstruction (12.9%), restrictive patterns (9.7%), mixed defects (2.1%), and small airway disease (6.2%). A positive BDR was detected in 2.4% of participants. Multivariable logistic regression analysis demonstrated older age, male sex, a history of asthma, and the presence of chest tightness as independent predictors of abnormal lung function. Conclusions: COPD and asthma were prevalent among individuals working or living in the industrial zone, and abnormal pulmonary function—particularly obstructive defects—was common. Older age, male sex, a history of asthma, and respiratory symptoms were associated with a greater risk of lung function impairment, underscoring the importance of targeted surveillance and preventive strategies in industrial environments. Full article

Asthma, chronic obstructive pulmonary disease (COPD), and acute respiratory distress syndrome (ARDS) are the major lung inflammatory complications affecting the global population. Exposure to allergens, infections, smoking, and environmental pollutants could cause persistent oxidative stress and dysregulated immune responses, leading to lung inflammatory complications. Increased oxidative stress can lead to lipid peroxidation and the formation of toxic lipid aldehydes. One of the major lipid aldehydes formed during lipid peroxidation is 4-hydroxy-2-nonenal (4-HNE). 4-HNE is well known to covalently modify proteins, nucleic acids, and lipids, thus modifying cellular signaling pathways and inflammatory cascades. Increased levels of 4-HNE have been identified in lung tissues, bronchoalveolar lavage (BAL) fluid, and the serum of patients with inflammatory lung conditions. Further, 4-HNE contributes to airway remodeling, mitochondrial dysfunction, and modulation of inflammatory responses in the lung epithelial cells. Recent studies also indicate the potential role of 4-HNE as an important mediator and a potential biomarker of various human disease progression, including the diagnosis and monitoring of lung inflammatory diseases. In this narrative review, we discuss current evidence on the pathological role of 4-HNE, its potential as a biomarker, and its importance for early detection and for potential therapeutic strategies in lung inflammatory complications. Full article

Background: Tuberculosis (TB) remains a major global health threat, particularly in low- and middle-income countries, with TB infection (TBI) serving as the primary source of TB disease. While HIV infection has long been recognised as a major risk factor for TB progression, the rise of Non-Communicable Diseases (NCDs), which may exert immunosuppressive effects, further compounded by their treatment, contributes to increased TB susceptibility. This scoping review synthesises evidence from systematic reviews on medical and behavioural risk factors for TBI progression to TB disease, for both asymptomatic and symptomatic disease. Methods: A preliminary literature search was conducted on 11 January 2025, in PUBMED using the keywords “tuberculosis,” “asymptomatic or subclinical tuberculosis” “risk factors,” and “systematic review” followed by targeted reviews on the identified medical and behavioural risk factors for TB infection progression to TB disease. Results: A total of 25 systematic reviews were included. Medical risk factors for progression from TB infection to TB disease included diabetes mellitus (DM), chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), undernutrition (including iron and vitamin D deficiency), cancer—particularly haematological malignancies—and immunosuppressive therapies (TNF-α inhibitors and glucocorticoids). Iron and vitamin D deficiency, particularly severe deficiency, is linked to increased TB risk, especially among people living with HIV. Behavioural risk factors, including tobacco, drug, and alcohol use, were also highlighted. Geographic variations in TB prevalence, diagnostic practices, and healthcare systems contributed to differences in risk estimates across reviews. No systematic reviews were identified that examined risk factors for asymptomatic TB. Conclusions: The convergence of TB with NCDs, compounded by immunosuppressive therapies, poses a public health challenge in high TB burden settings. Effective TB prevention requires targeted screening, along with enhanced management of these NCDs. Nutritional support, particularly screening and treatment of anaemia and vitamin D deficiency, may benefit individuals with TBI, comorbid NCDs, and HIV. A multidisciplinary approach, integrating behavioural interventions and tailored prevention strategies, is essential to achieving WHO’s End TB targets. Addressing the evidence gap on risk factors for asymptomatic TB is also critical to improve early detection and interrupt transmission. Full article

Field-effect transistor (FET) biosensors using graphene have become one of the most promising biosensing platforms for the early diagnosis of diseases with features such as high sensitivity, label-free detection and application compatibility with point-of-care systems. Herein, we critically discuss recent advances in graphene FET (GFET) biosensor development toward clinically relevant biomarkers associated with representative diseases including cancer, neurodegenerative disease, infectious disease, and inflammatory conditions. Recent progress was reviewed to evaluate GFET architectures, surface functionalization methods, and detection quality. The biomarkers explored were clusterin in Alzheimer’s disease, thrombin in coagulopathy, estrogen receptor α (ER-α) in breast cancer, Carcinoembryonic antigen in lung cancer, microRNAs for malignant tumors, exosomes derived from HepG2 for the hepatocellular carcinoma (HCC) cell line, interleukin-6 (IL-6) for chronic obstructive pulmonary disease (COPD), Polyclonal antibodies and antigens (P24) for HIV and prostate-specific antigen for prostate cancer. The developed devices demonstrate ultralow detection limits at femtomolar to attomolar concentrations with the aid of designed antibodies, aptamers and nanomaterials. Herein, this review presents the sensing mechanisms and biomedical application of various GFET platforms, focusing on their emerging potential as next-generation platforms for rapid, non-invasive and point-of-care diagnostics. Full article

Background: Exacerbations of chronic obstructive pulmonary disease (COPD) are a leading cause of morbidity, mortality, and healthcare burden worldwide. Early detection and timely intervention remain important challenges in COPD management, given the unpredictable nature of acute deterioration and limitations of traditional spirometry-based risk assessment. Methods: This narrative review synthesizes artificial intelligence (AI)-driven approaches for predicting and detecting chronic obstructive pulmonary disease (COPD) exacerbations across electronic health records, wearable sensors, imaging, environmental data, and patient-reported outcomes, emphasizing novel discoveries and emerging relationships rather than predictive performance. Results: Three major discoveries have been made. First, measurable physiological and behavioral deterioration may precede symptom recognition by approximately 7–14 days, thereby establishing a potential intervention window for anticipatory care. Second, machine learning (ML) models integrating pollutant exposure, medication adherence, and clinical characteristics have identified phenotypes with differential environmental sensitivity, including unexpected exposure–adherence interactions. Third, deep neural network analysis of full spirometry curves has revealed structural phenotypes beyond traditional Forced Expiratory Volume (FEV₁)-based measures and novel imaging biomarkers. The predictive performance ranges from the Area Under the Curve (AUC) 0.72–0.95, with a pooled meta-analytic AUC of approximately 0.77. Conclusions: AI has uncovered hidden patterns in the progression of COPD, supporting a shift from reactive to anticipatory management. Translation to routine care requires prospective validation, improved interpretability, workflow integration, and generalizability and equity. Full article

Objective: Emphysema is an important chronic obstructive pulmonary disease (COPD) phenotype characterized by the destruction of air spaces distal to the terminal bronchiole. Aiming to detect potential emphysema biomarkers and to assess the systemic effects of emphysema in blood plasma, we conducted a small cross-sectional shotgun proteomics study. Methods: This study included N = 40 participants divided into four subgroups (N = 10 per group): patients with emphysema and COPD (CE), patients with COPD but without emphysema (CN), healthy smokers (HS) and healthy never-smokers (HN). The participants were sampled non-probabilistically to be similar in terms of age, sex and comorbidities. Participants’ blood plasma was analyzed using liquid chromatography–mass spectrometry. Bioinformatic analysis included detection of differentially expressed proteins (DEPs) and overrepresentation analysis (ORA). Results: Across all groups, a total of 994 proteins were identified, with NADP-dependent malic enzyme (NADP-ME; encoded by ME1) being the only DEP in the CE vs. CN contrast. Proteins such as BMP1, ADAMTSL-2, -4 and IGFBP4, -5, 6 were identified to be upregulated in CE vs. HN. Fibulin-1, -3 and several immunoglobulin components were identified to be downregulated in the CE vs. HN contrast. ORA revealed several enriched processes, including serine-type endopeptidase activity, insulin-like growth factor I and II binding, and signaling receptor binding. Conclusion: We propose NADP-ME, an important enzyme of intermediary metabolism and redox homeostasis, as a potential biomarker candidate of emphysema. Notably, NADP-ME is also implicated in anoikis resistance. Additionally, changes in the expression levels of BMP1, ADAMTSL-2 and -4, and fibulin suggest potential major systemic effects of extracellular matrix perturbation. As all data was derived from LC-MS analysis, these findings need to be further evaluated with complementary methods. Full article

Chronic obstructive pulmonary disease (COPD) is a major contributor to global respiratory morbidity and exhibits substantial sex- and gender-related differences in incidence, phenotype, pathophysiology, and outcomes across the life course. Historically regarded as a predominantly male disease due to higher smoking rates, COPD is now increasingly recognized among women, reflecting changing exposure patterns and enhanced diagnostic attention. Moreover, evidence indicates that women may be more biologically susceptible to the harmful effects of tobacco smoke and often develop COPD at younger ages. Clinical manifestations also differ, with women more frequently reporting dyspnea, anxiety, and depression, whereas men may exhibit more cough and sputum production. Imaging studies suggest that airway-predominant disease is more common in women, while men are more likely to demonstrate emphysema-predominant patterns. Furthermore, women face an increased risk of exacerbation, yet they are more likely to experience underdiagnosis or misdiagnosis. Treatment responses and comorbidity patterns also show sex- and gender-related variations. Despite these differences, most clinical guidelines and therapeutic strategies do not differentiate by sex and gender, highlighting a gap in personalized COPD management. Overall, growing evidence underscores the importance of incorporating sex and gender as biological and sociocultural variables in COPD research, diagnosis, and treatment. Recognizing sex/gender-specific risk profiles, symptom patterns, and disease phenotypes may improve early detection and enable more targeted, effective interventions. This narrative synthesis, derived from a meticulous search in PubMed and the critical selection of 74 articles from the 448 identified originally, integrates evidence from guideline statements, registry studies, mechanistic and preclinical research, imaging and physiology investigations, systematic reviews, and randomized controlled trials that report sex- and gender-disaggregated data. Full article

Background: Coronary artery disease (CAD) commonly coexists with chronic obstructive pulmonary disease (COPD), but may be under-recognised, since symptoms such as dyspnoea and chest discomfort are often attributed to lung disease. We hypothesised that coronary artery disease is highly prevalent in patients with COPD, even in the absence of typical angina symptoms. Methods: This study aimed to detect CAD in patients with COPD. We conducted a single-centre observational study, including 76 patients with no known previous cardiovascular events. To detect ischaemic heart disease, three methods were used, according to standard clinical indications: coronary angiography, coronary CT, and calcium score analysis on chest CT. The findings were categorised according to lesion severity and vessel involvement. Results: A substantial proportion of patients with COPD harboured previously undiagnosed atherosclerotic coronary disease (78%). However, most detected disease was non-obstructive atherosclerosis (56%), whereas severe stenosis was present in approximately one-third of patients (32%). Single-vessel disease accounted for 37% of cases, while the remaining patients exhibited multi-vessel involvement. Nevertheless, only a small proportion of patients had typical angina symptoms (11.8%), and the most frequent complaint was effort dyspnoea (50%). Patients not receiving inhaled corticosteroid therapy were more likely to have extensive coronary artery disease (χ² (6)= 14.228, p = 0.027). Conclusions: These findings support our hypothesis that atherosclerotic coronary disease is often under-recognised in patients with COPD. ICS-containing therapy appeared to be associated with less extensive coronary artery involvement; however, this observation should be interpreted cautiously. Full article

Lung diseases are among the leading causes of death worldwide. Nowadays, to detect lung diseases, a specialist uses auscultation to make a diagnosis. Newer auscultation devices based on stethoscopes allow these sounds to be recorded for later analysis. However, the diagnosis process is time-consuming and relies on medical expertise to generate an accurate diagnosis. For these reasons, automated and objective diagnostic systems are crucial for the early detection of lung diseases and preventing them from worsening. In this study, a computer-aided diagnostic system that integrates the Radial Short-Time Fourier Transform (RSTFT) with a Convolutional Neural Network (CNN) enhanced by attention mechanisms is presented. The RSTFT is employed to convert lung sound recordings from a public dataset into angular frequency representations, which are used as input to the CNN. The network automatically extracts discriminative features and classifies the recordings into five categories: Chronic Obstructive Pulmonary Disease (COPD), bronchiectasis, pneumonia, asthma, and healthy lungs. Experimental results demonstrate that the proposed method outperforms several state-of-the-art approaches in terms of accuracy, precision, recall, and F1-score. These findings indicate that the proposed RSTFT–CNN framework provides an effective and reliable solution for the automated diagnosis of lung diseases, offering valuable support for clinical decision-making and early intervention. Full article

Background/Objectives: This study aimed to use cluster analysis of healthcare utilization patterns to identify distinct clinical phenotypes in patients with comorbid chronic obstructive pulmonary disease (COPD) and atrial fibrillation (AF) and to assess their associations with demographic characteristics and clinical outcomes. Methods: A retrospective cohort study was conducted using data from 1247 patients with COPD and AF extracted from a regional medical information system (Lipetsk Region, period 2021–2025). The k-means algorithm was used to cluster patients based on the average number of medical encounters per three-character ICD-10 categories. Groups were compared using descriptive and analytical statistical methods with correction for multiple comparisons. Results: The k-means algorithm identified three distinct clusters (phenotypes), which differed significantly in demographics, comorbidity structure, and mortality. Cluster 1 (“High-frequency utilization phenotype”, 25.3%): characterized by high utilization for acute respiratory infections, metabolic, and urological diseases; demonstrated the lowest mortality (10.1%). Cluster 2 (“Cerebrovascular Phenotype”, 32.3%): characterized by chronic cerebrovascular pathology and its sequelae (codes I67, I69); had intermediate mortality (20.8%). Cluster 3 (“Low-frequency utilization phenotype”, 42.4%): distinguished by minimal utilization for “outpatient” reasons alongside the highest mortality (31.1%) and a high proportion of deaths from respiratory failure. Analysis within the deceased patient subgroup confirmed the persistence of specific utilization patterns for each phenotype right up until the fatal outcome. Conclusions: Cluster analysis of real-world clinical practice data identified three discrete phenotypes of patients with comorbid COPD and AF, which have fundamentally different clinical–behavioral trajectories and prognoses. These findings justify the need for differentiated organizational approaches, particularly the development of proactive strategies for the active detection and engagement in follow-up care of patients with the low-frequency utilization phenotype, which is associated with the worst outcomes. Full article

Background and Objectives: The 2023 GOLD report introduced seven etiological categories, known as etiotypes, to better reflect the heterogeneity of chronic obstructive pulmonary disease (COPD). However, the clinical, functional, radiological, and psychosocial characteristics associated with these etiologies remain insufficiently defined. This study aimed to explore the differences among GOLD 2023 etiotypes in a stable COPD cohort. Materials and Methods: This prospective, observational, cross-sectional study included 315 stable outpatients with COPD from a tertiary clinic between June and July 2025. Etiological classification was based on predefined criteria, including genetic predisposition, impaired lung development, exposure-related mechanisms, infection-related mechanisms, and asthma-like characteristics. Patients were evaluated using clinical instruments (mMRC and CAT), psychological assessments (LCQ, BDI, BAI, and CAFS), pulmonary function tests, and thoracic CT scans. Results: COPD due to environmental exposure (COPD-E) was the most common type (98.7%), followed by infection-related (COPD-I, 13.3%), asthma-related (COPD-A, 9.8%), and combined forms (COPD-D and COPD-G, each 2.5%). Participants with COPD-A were younger (median 54 vs. 66 years; p < 0.001), reported less tobacco exposure (36 vs. 50 pack-years; p < 0.001), and showed less CT-detected emphysema (31.6% vs. 78.3%; p < 0.001). COPD-G exhibited more severe airflow obstruction (FEV₁ 25.5% predicted; p < 0.001), higher symptom burden (CAT score 21 vs. 6; p < 0.001), and lower oxygen saturation (p = 0.001). Eosinophil counts and psychosocial measures did not significantly differ by etiology. Conclusions: The GOLD 2023 COPD etiotypes demonstrated distinct clinical and functional profiles, reflecting diverse underlying mechanisms of the disease. Recognizing these etiological differences can help clinicians tailor diagnostic evaluations, guide individualized treatment strategies, and ultimately improve patient outcomes. Understanding disease etiology remains a cornerstone for accurate diagnosis, personalized management and optimized therapeutic decisions in COPD. Full article

Bronchopulmonary dysplasia (BPD) is a chronic lung condition in preterm infants characterized by impaired alveolar development, disrupted vascular growth, and persistent inflammation. These alterations, which often arise from early exposure to mechanical ventilation, oxygen toxicity, and infection, can lead to long-term structural and functional deficits in the developing lung. In adulthood, chronic obstructive pulmonary disease (COPD) represents a major cause of morbidity and mortality and is defined by progressive airflow obstruction, reduced respiratory capacity, and chronic inflammatory responses. Although traditionally considered a disease of adult smokers, growing evidence suggests that early-life respiratory insults play a key role in shaping long-term lung health. Recent studies reveal a biologically plausible link between BPD and later COPD, indicating that premature birth, impaired lung growth, and early inflammatory injury may predispose individuals to earlier or more severe COPD development. This review explores the shared molecular pathways connecting these conditions, focusing on overlapping inflammatory biomarkers such as IL1B, IL6, IL8, TNF, TGFB, and VEGF, which collectively reflect persistent dysregulation of immune and repair mechanisms. Additionally, common genetic variants, including SERPINA1 and HHIP, may contribute to susceptibility across the lifespan. Emerging biomarkers—such as PRMT7, cathelicidin/LL-37, CRISPLD2, and GDF15—offer further insight into disease progression. Identifying these shared markers may ultimately improve early detection and help clinicians pinpoint infants with BPD who face an elevated risk of developing COPD later in life. Full article