Biomarkers For Chronic Obstructive Pulmonary Disease Research Articles

Automated evaluation of diaphragm configuration based on chest CT in COPD patients

BackgroundSevere chronic obstructive pulmonary disease (COPD) often results in hyperinflation and flattening of the diaphragm. An automated computed tomography (CT)-based tool for quantifying diaphragm configuration, a biomarker for COPD, was developed in-house and tested in a large cohort of COPD patients.MethodsWe used the LungQ platform to extract the lung-diaphragm intersection, as direct diaphragm segmentation is challenging. The tool computed the diaphragm index (surface area/projected surface area) as a measure of diaphragm configuration on inspiratory scans in a COPDGene subcohort. Visual inspection of 250 randomly selected segmentations served as a quality check. Associations between the diaphragm index, Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages, forced expiratory volume in 1 s (FEV1) % predicted, and CT-derived emphysema scores were explored using analysis of variance and Pearson correlation.ResultsThe tool yielded incomplete segmentation in 9.2% (2.4% major defect, 6.8% minor defect) of 250 randomly selected cases. In 8431 COPDGene subjects (4240 healthy; 4191 COPD), the diaphragm index was increasingly lower with higher GOLD stages (never-smoked 1.83 ± 0.16; GOLD-0 1.79 ± 0.18; GOLD-1 1.71 ± 0.15; GOLD-2: 1.67 ± 0.16; GOLD-3 1.58 ± 0.14; GOLD-4 1.54 ± 0.11) (p < 0.001). Associations were found between the diaphragm index and both FEV1% predicted (r = 0.44, p < 0.001) and emphysema score (r = −0.36, p < 0.001).ConclusionWe developed an automated tool to quantify the diaphragm configuration in chest CT. The diaphragm index was associated with COPD severity, FEV1%predicted, and emphysema score.Relevance statementDue to the hypothesized relationship between diaphragm dysfunction and diaphragm configuration in COPD patients, automatic quantification of diaphragm configuration may prove useful in evaluating treatment efficacy in terms of lung volume reduction.Key PointsSevere COPD changes diaphragm configuration to a flattened state, impeding function.An automated tool quantified diaphragm configuration on chest-CT providing a diaphragm index.The diaphragm index was correlated to COPD severity and may aid treatment assessment.Graphical

Exploring the associations between elevated plasma SP-D levels and OSCAR gene expression as potential biomarkers in patients with COPD: a cross-sectional study.

Background: Chronic obstructive pulmonary disease (COPD) imposes a substantial burden on patients and healthcare systems. Spirometry is the most widely used test to diagnose the disease; however, a surrogate marker is required to predict the disease pattern and progression. Objectives: The aim of the current study was to explore the association of elevated levels of plasma surfactant protein D (SP-D) with gene expression of osteoclast-associated receptor (OSCAR) and lung functions as potential diagnostic biomarkers of COPD. Methods: This cross-sectional study employed convenience sampling. As men compose the majority of patients in the outpatient department and with smoking being common among Pakistani men, choosing men offered a representative sample. Using a post-bronchodilator forced expiratory volume in the first second (FEV1) to a forced vital capacity (FVC) of less than 0.70 (FEV1/FVC <0.7), COPD patients were diagnosed on spirometry (n = 41). Controls were healthy individuals with FEV1/FVC >0.7 (n = 41). Plasma SP-D levels were measured using an enzyme-linked immunosorbent assay (ELISA). The gene expression of OSCAR was determined by real-time polymerase chain reaction (qPCR) and subsequently analyzed by the threshold cycle (Ct) method. Statistical Package for Social Sciences (SPSS) version 20 was used for statistical analysis. Results: The mean BMI of controls (25.66 ± 4.17kg/m2) was higher than that of cases (23.49 ± 2.94kg/m2 (p = .008)). The median age of controls was 49 years (interquartile range (IQR) 42.0-65.0years) and that of cases was 65years (IQR = 57.50-68.50). SP-D concentration was not significantly higher in COPD patients [4.96ng/mL (IQR 3.26-7.96)] as compared to controls [3.64ng/mL (IQR 2.60-8.59)] (p = .209). The forced expiratory ratio (FEV1/FVC) and FEV1 were related to gene expression of OSCAR (p = <.001). The gene expression of OSCAR was significantly related to SP-D (p = .034). A multiple regression model found FEV1 and FVC to have a significant effect on the gene expression of OSCAR (p-values <0.001 and 0.001, respectively). Conclusion: Gene expression of OSCAR was increased in COPD patients and related directly to SP-D levels and inversely to lung functions in cohort of this study, suggesting that OSCAR along with SP-D may serve as a diagnostic biomarker of COPD.

Exhaled breath analysis for the discrimination of asthma and chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) and asthma are the most common chronic respiratory diseases. In middle-aged and elderly patients, it is difficult to distinguish between COPD and asthma based on clinical symptoms and pulmonary function examinations in clinical practice. Thus, an accurate and reliable inspection method is required. In this study, we aimed to identify breath biomarkers and evaluate the accuracy of breathomics-based methods for discriminating between COPD and asthma. In this multi-center cross-sectional study, exhaled breath samples were collected from 89 patients with COPD and 73 with asthma and detected on a high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform from 20 October 2022, to 20 May 2023, in four hospitals. Data analysis was performed from 15 June 2023 to 16 August 2023. The sensitivity, specificity, and accuracy were calculated to assess the overall performance of the volatile organic component (VOC)-based COPD and asthma discrimination models. Potential VOC markers related to COPD and asthma were also analyzed. The age of all participants ranged from to 18–86 years, and 54 (33.3%) were men. The age [median (minimum, maximum)] of COPD and asthma participants were 66.0 (46.0, 86.0), and 44.0 (17.0, 80.0). The male and female ratio of COPD and asthma participants were 14/75 and 40/33, respectively. Based on breathomics feature selection, ten VOCs were identified as COPD and asthma discrimination biomarkers via breath testing. The joint panel of these ten VOCs achieved an area under the curve of 0.843, sensitivity of 75.9%, specificity of 87.5%, and accuracy of 80.0% in COPD and asthma discrimination. Furthermore, the VOCs detected in the breath samples were closely related to the clinical characteristics of COPD and asthma. The VOC-based COPD and asthma discrimination model showed good accuracy, providing a new strategy for clinical diagnosis. Breathomics-based methods may play an important role in the diagnosis of COPD and asthma.

Exploring Molecular Mechanisms and Biomarkers in COPD: An Overview of Current Advancements and Perspectives.

Chronic obstructive pulmonary disease (COPD) plays a significant role in global morbidity and mortality rates, typified by progressive airflow restriction and lingering respiratory symptoms. Recent explorations in molecular biology have illuminated the complex mechanisms underpinning COPD pathogenesis, providing critical insights into disease progression, exacerbations, and potential therapeutic interventions. This review delivers a thorough examination of the latest progress in molecular research related to COPD, involving fundamental molecular pathways, biomarkers, therapeutic targets, and cutting-edge technologies. Key areas of focus include the roles of inflammation, oxidative stress, and protease-antiprotease imbalances, alongside genetic and epigenetic factors contributing to COPD susceptibility and heterogeneity. Additionally, advancements in omics technologies-such as genomics, transcriptomics, proteomics, and metabolomics-offer new avenues for comprehensive molecular profiling, aiding in the discovery of novel biomarkers and therapeutic targets. Comprehending the molecular foundation of COPD carries substantial potential for the creation of tailored treatment strategies and the enhancement of patient outcomes. By integrating molecular insights into clinical practice, there is a promising pathway towards personalized medicine approaches that can improve the diagnosis, treatment, and overall management of COPD, ultimately reducing its global burden.

The relevance of eosinophils in chronic obstructive pulmonary disease: inflammation, microbiome, and clinical outcomes

Abstract Chronic obstructive pulmonary disease is caused by the inhalation of noxious particles such as cigarette smoke. The pathophysiological features include airway inflammation, alveolar destruction, and poorly reversible airflow obstruction. A subgroup of patients with chronic obstructive pulmonary disease has higher blood eosinophil counts, associated with an increased response to inhaled corticosteroids and increased biomarkers of pulmonary type 2 inflammation. Emerging evidence shows that patients with chronic obstructive pulmonary disease with increased pulmonary eosinophil counts have an altered airway microbiome. Higher blood eosinophil counts are also associated with increased lung function decline, implicating type 2 inflammation in progressive pathophysiology in chronic obstructive pulmonary disease. We provide a narrative review of the role of eosinophils and type 2 inflammation in the pathophysiology of chronic obstructive pulmonary disease, encompassing the lung microbiome, pharmacological targeting of type 2 pathways in chronic obstructive pulmonary disease, and the clinical use of blood eosinophil count as a chronic obstructive pulmonary disease biomarker.

HTR2B as a novel biomarker of chronic obstructive pulmonary disease with lung squamous cell carcinoma

Chronic obstructive pulmonary disease (COPD) is often associated with lung squamous cell carcinoma (LUSC), which has the same etiology (smoking, inflammation, oxidative stress, microenvironmental changes, and genetics). Smoking, inflammation, and airway remodeling are the most important and classical mechanisms of COPD comorbidity in LUSC patients. Cancer can occur during repeated airway damage and repair (airway remodeling). Changes in the inflammatory and immune microenvironments, which can cause malignant transformation of some cells, are currently being revealed in both LUSC and COPD patients. We obtained the GSE76925 dataset from the Gene Expression Omnibus database. Screening for possible COPD biomarkers was performed using the LASSO regression model and a random forest classifier. The compositional patterns of the immune cell fraction in COPD patients were determined using CIBERSORT. HTR2B expression was analyzed using validation datasets (GSE47460, GSE106986, and GSE1650). HTR2B expression in COPD cell models was determined via real-time quantitative PCR. Epithelial–mesenchymal transition (EMT) marker expression levels were determined after knocking down or overexpressing HTR2B. HTR2B function and mechanism in LUSC were analyzed with the Kaplan‒Meier plotter database. HTR2B expression was inhibited to detect changes in LUSC cell proliferation. A total of 1082 differentially expressed genes (DEGs) were identified in the GSE76925 dataset (371 genes were significantly upregulated, and 711 genes were significantly downregulated). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were mainly enriched in the p53 signaling and β-alanine metabolism pathways. Gene Ontology enrichment analysis indicated that the DEGs were largely related to transcription initiation from the RNA polymerase I promoter and to the regulation of mononuclear cell proliferation. The LASSO regression model and random forest classifier results revealed that HTR2B, DPYS, FRY, and CD19 were key COPD genes. Immune cell infiltration analysis indicated that these genes were closely associated with immune cells. Analysis of the validation sets suggested that HTR2B was upregulated in COPD patients. HTR2B was significantly upregulated in COPD cell models, and its upregulation was associated with increased EMT marker expression. Compared with that in bronchial epithelial cells, HTR2B expression was upregulated in LUSC cells, and inhibiting HTR2B expression led to the inhibition of LUSC cell proliferation. In conclusions, HTR2B might be a new biomarker and therapeutic target in COPD patients with LUSC.

The role of serum chloride ion in the prognosis of COPD

BackgroundAs exacerbations of chronic obstructive pulmonary disease (COPD) are one of the leading causes of hospitalization and are associated with significant mortality, it is particularly important to accurately assess the risk of exacerbations in COPD. Most of the current clinical biomarkers are related to inflammation and few consider how ion levels affect COPD. Chloride ion, the second most abundant serum electrolyte, has been shown to be associated with poor prognoses in several diseases, but their relationship with COPD remains unclear. MethodsIn total, 105 patients with acute exacerbations of COPD were recruited. Data on clinical characteristics, lung function, blood count, blood biochemistry, relevant scales including the Clinical COPD Questionnaire (CCQ), BODE (BMI, airflow obstruction, dyspnea, exercise capacity) index and the St. George's Respiratory Questionnaire (SGRQ) were collected from all patients for statistical analysis. ResultThere were significant differences in lung function indicators and disease severity in the low chloride ion subgroup compared with the high chloride ion subgroup. On multiple logistic regression analysis, chloride ion was an independent factor affecting lung function in COPD patients (OR=0.808, 95% CI: 0.708 - 0.922, p=0.002). The sensitivity of chloride ion in predicting COPD severity was 78%, the specificity was 63%, and the area under the curve was 0.734 (p<0.001). Subgroup analysis showed that chloride ion was a stronger predictor in male and smoking patients. ConclusionsChloride ion was a novel prognostic biomarker for COPD, and low levels of chloride ion were independently associated with exacerbations in COPD patients.

Proteomic Blood Profiles Obtained by Totally Blind Biological Clustering in Stable and Exacerbated COPD Patients.

Although Chronic Obstructive Pulmonary Disease (COPD) is highly prevalent, it is often underdiagnosed. One of the main characteristics of this heterogeneous disease is the presence of periods of acute clinical impairment (exacerbations). Obtaining blood biomarkers for either COPD as a chronic entity or its exacerbations (AECOPD) will be particularly useful for the clinical management of patients. However, most of the earlier studies have been characterized by potential biases derived from pre-existing hypotheses in one or more of their analysis steps: some studies have only targeted molecules already suggested by pre-existing knowledge, and others had initially carried out a blind search but later compared the detected biomarkers among well-predefined clinical groups. We hypothesized that a clinically blind cluster analysis on the results of a non-hypothesis-driven wide proteomic search would determine an unbiased grouping of patients, potentially reflecting their endotypes and/or clinical characteristics. To check this hypothesis, we included the plasma samples from 24 clinically stable COPD patients, 10 additional patients with AECOPD, and 10 healthy controls. The samples were analyzed through label-free liquid chromatography/tandem mass spectrometry. Subsequently, the Scikit-learn machine learning module and K-means were used for clustering the individuals based solely on their proteomic profiles. The obtained clusters were confronted with clinical groups only at the end of the entire procedure. Although our clusters were unable to differentiate stable COPD patients from healthy individuals, they segregated those patients with AECOPD from the patients in stable conditions (sensitivity 80%, specificity 79%, and global accuracy, 79.4%). Moreover, the proteins involved in the blind grouping process to identify AECOPD were associated with five biological processes: inflammation, humoral immune response, blood coagulation, modulation of lipid metabolism, and complement system pathways. Even though the present results merit an external validation, our results suggest that the present blinded approach may be useful to segregate AECOPD from stability in both the clinical setting and trials, favoring more personalized medicine and clinical research.

Study of inflammatory biomarkers in Chronic obstructive pulmonary disease (COPD) and their association with comorbidities

Background Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory condition associated with systemic inflammation and various comorbidities, significantly impacting patients’ health outcomes. This study investigates the relationships between inflammatory biomarkers in COPD and their associations with comorbidities. By focusing on specific biomarkers such as C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-ALFA), and fibrinogen, we seek to find the complex interplay between systemic inflammation, COPD severity, and the prevalence of comorbidities. This research is critical for advancing our understanding of the systemic manifestations of COPD and informing targeted interventions for improved patient management. Methods This cross-sectional observational study will be conducted at AVBRH, a tertiary care hospital in central India, over two years (August 2022 to August 2024). A sample size of 90 COPD patients will be randomly selected based on inclusion and exclusion criteria. Diagnostic tests will be performed, including pulmonary function tests, chest X-rays, and biomarker assessments. Statistical analyses, encompassing chi-square tests, Pearson’s correlation coefficient, and logistic regression, will explore associations between inflammatory biomarkers, COPD severity, and comorbidities. The study design ensures rigorous data collection and adherence to ethical standards, with SPSS 27.0 utilized for statistical analyses. Expected Outcome Anticipated outcomes include a comprehensive understanding of how inflammatory biomarkers correlate with the severity of COPD and their associations with comorbidities. We expect to identify specific biomarkers that may serve as indicators of increased risk for certain comorbid conditions. The findings will contribute valuable insights into the systemic nature of COPD and inform healthcare strategies tailored to mitigate comorbidity-related risks in COPD patients. This research has the potential to enhance clinical decision-making, guide personalized treatment plans, and ultimately improve the overall management of individuals living with COPD.

Promising Intestinal Microbiota Associated with Clinical Characteristics of COPD Through Integrated Bioinformatics Analysis.

Chronic obstructive pulmonary disease (COPD), an incurable chronic respiratory disease, has become a major public health problem. The relationship between the composition of intestinal microbiota and the important clinical factors affecting COPD remains unclear. This study aimed to identify specific intestinal microbiota with high clinical diagnostic value for COPD. The fecal microbiota of patients with COPD and healthy individuals were analyzed by 16S rDNA sequencing. Random forest classification was performed to analyze the different intestinal microbiota. Spearman correlation was conducted to analyze the correlation between different intestinal microbiota and clinical characteristics. A microbiota-disease network diagram was constructed using the gut MDisorder database to identify the possible pathogenesis of intestinal microorganisms affecting COPD, screen for potential treatment, and guide future research. No significant difference in biodiversity was shown between the two groups but significant differences in microbial community structure. Fifteen genera of bacteria with large abundance differences were identified, including Bacteroides, Prevotella, Lachnospira, and Parabacteroides. Among them, the relative abundance of Lachnospira and Coprococcus was negatively related to the smoking index and positively related to lung function results. By contrast, the relative abundance of Parabacteroides was positively correlated with the smoking index and negatively correlated with lung function findings. Random forest classification showed that Lachnospira was the genus most capable of distinguishing between patients with COPD and healthy individuals suggesting it may be a potential biomarker of COPD. A Lachnospira disease network diagram suggested that Lachnospira decreased in some diseases, such as asthma, diabetes mellitus, and coronavirus disease 2019 (COVID-19), and increased in other diseases, such as irritable bowel syndrome, hypertension, and bovine lichen. The dominant intestinal microbiota with significant differences is related to the clinical characteristics of COPD, and the Lachnospira has the potential value to identify COPD.

Neutrophil-to-Lymphocyte Ratio and Blood Eosinophil Levels As Inflammatory Indicators in Smoker and Non-smoker Young Adult Patients With Chronic Obstructive Pulmonary Disease at a Tertiary Care Hospital.

Background Inflammatory markers are elevated in chronic obstructive pulmonary disease (COPD) and can be quantified to detect severity, prognosis, mortality risk, and response to treatment. However, the estimation costs are high. The blood neutrophil-to-lymphocyte ratio (NLR) and eosinophil levels are emerging as biomarkers in COPD, yet there is a paucity of data. Aim and objectives This study was designed to elucidate the roles of the NLRand eosinophil levels in smokers and non-smokers with stable COPD male subjects, correlating them with lung functions. Materials and methods A prospective observational clinical study was conducted from January to June 2023, after receiving approval from the Institutional Ethics Committee, on 73 COPD patients aged 30-60 years who gave voluntary informed consent. Complete blood counts and spirometry were performed. Patients with a forced expiratory volume in one second(FEV1) % predicted <70% and an FEV1/forced vital capacity (FVC) % <70% based on the pulmonary function test (MIR Spirolab) were included. They were further divided into mild (n=10), moderate (n=27), severe (n=26), and very severe (n=10) categories as per the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. Subjects were also categorized into smoker (n=45) and non-smoker (n=28) groups. The complete blood count was analyzed using an automated analyzer (Beckman Coulter). Analysis was also carried out with an NLR of more or less than three. A P-value of less than 0.05 was considered significant. Results Smokers constituted 61.65% (n=45) of the subjects, and non-smokers 38.35% (n=28). Among smokers, 17.78% had very severe airflow obstruction. In all COPD subjects (n=73), lymphocytes, eosinophils, and lung functions were lower in the group where the NLR was greater than three. NLR in smokers (3.52±1.43) was higher than in non-smokers (3.39±0.94). In non-smokers (n=28), blood eosinophils and lymphocytes were elevated. In smokers (n=45), blood neutrophils, monocytes, and basophils were increased. Smokers showed a non-significant increase in RBC, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH). Neutrophils, monocytes, eosinophils, and NLR increased with disease severity. NLR negatively correlated with FEV1 (r=-0.350, p=0.034) and positively with pack-years (r=0.546, p<0.001) in smokers. NLR negatively correlated with eosinophils, FVC, FEV1/FVC, and FEV1 % predicted. In all COPD subjects (n=73), NLR negatively correlated with blood eosinophils (r=-0.184, p=0.12), BMI, and lung functions. Conclusion NLR is elevated in COPD subjects and can serve as a marker of inflammation and a predictor of the risk and severity of airflow limitation. NLR correlates both positively and negatively with pack-years and lung functions, respectively.

Clonal Hematopoiesis of Indeterminate Potential Is Associated with Current Smoking Status and History of Exacerbation in Patients with Chronic Obstructive Pulmonary Disease.

There is limited data regarding the clinical outcomes of clonal hematopoiesis of indeterminate potential (CHIP) in patients with chronic obstructive pulmonary disease (COPD). This study aimed to evaluate the clinical significance of CHIP as a COPD biomarker. This retrospective study was conducted on patients with COPD who were enrolled prospectively in the Seoul National University Hospital Airway Registry from January 2013 to December 2019 and underwent pulmonary function and blood tests. We evaluated the CHIP score according to smoking status and severity of airflow obstruction. We analyzed next-generation sequencing data to detect CHIP in 125 patients with COPD. Current smokers had a higher prevalence of CHIP in combination of DNMT3A, TET2, and PPM1D (DTP), DNA methyltransferase 3 alpha (DNMT3A), and protein phosphatase, Mg2+/Mn2+ dependent 1D (PPM1D) genes than in never- or ex-smokers. CHIP of DTP and DNMT3A genes was significantly associated with current smokers (adjusted odds ratio [aOR], 2.80; 95% confidence interval [CI], 1.01 to 7.79) (aOR, 4.03; 95% CI, 1.09 to 14.0). Patients with moderate-to-severe airflow obstruction had a higher prevalence of CHIP in most of the explored genes than those with mild obstruction, although the difference was not statistically significant. CHIP in ASXL transcriptional regulator 1 (ASXL1) genes was significantly associated with history of mild, severe, and total acute exacerbation. Given that CHIP in specific genes was significantly associated with current smoking status and acute exacerbation, CHIP can be considered as a candidate biomarker for COPD patients.

New markers in chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD), a global healthcare and socioeconomic burden, is a multifaceted respiratory disorder that results in substantial decline in health status and life quality. Acute exacerbations of the disease contribute significantly to increased morbidity and mortality. Consequently, the identification of reliable and effective biomarkers for rapid diagnosis, prediction, and prognosis of exacerbations is imperative. In addition, biomarkers play a crucial role in monitoring responses to therapeutic interventions and exploring innovative treatment strategies. Although established markers such as CRP, fibrinogen and neutrophil count are routinely used, a universal marker is lacking. Fortunately, an increasing number of studies based on next generation analytics have explored potential biomarkers in COPD. Here we review those advances and the need for standardized validation studies in the appropriate clinical setting.

Pyroptosis-Related Genes as Diagnostic Markers in Chronic Obstructive Pulmonary Disease and Its Correlation with Immune Infiltration.

Chronic obstructive pulmonary disease (COPD) stands as a predominant cause of global morbidity and mortality. This study aims to elucidate the relationship between pyroptosis-related genes (PRGs) and COPD diagnosis in the context of immune infiltration, ultimately proposing a PRG-based diagnostic model for predicting COPD outcomes. Clinical data and PRGs of COPD patients were sourced from the GEO database. The "ConsensusClusterPlus" package was employed to generate molecular subtypes derived from PRGs that were identified through differential expression analysis and LASSO Cox analysis. A diagnostic signature including eight genes (CASP4, CASP5, ELANE, GPX4, NLRP1, GSDME, NOD1and IL18) was also constructed. Immune cell infiltration calculated by the ESTIMATE score, Stroma scores and Immune scores were also compared on the basis of pyroptosis-related molecular subtypes and the risk signature. We finally used qRT - PCR to detect the expression levels of eight genes in COPD patient and normal. The diagnostic model, anchored on eight PRGs, underwent validation with an independent experimental cohort. The area under the receiver operating characteristic (ROC) curves (AUC) for the diagnostic model showcased values of 0.809, 0.765, and 0.956 for the GSE76925, GSE8545, and GSE5058 datasets, respectively. Distinct expression patterns and clinical attributes of PRGs were observed between the comparative groups, with functional analysis underscoring a disparity in immune-related functions between them. In this study, we developed a potential as diagnostic biomarkers for COPD and have a significant role in modulating the immune response. Such insights pave the way for novel diagnostic and therapeutic strategies for COPD.

Key role of activated platelets in the enhanced adhesion of circulating leucocyte-platelet aggregates to the dysfunctional endothelium in early-stage COPD.

Chronic obstructive pulmonary disease (COPD), usually caused by long-term tobacco smoking, is independently associated with systemic inflammation. However, little is known about the systemic inflammatory status of patients with early-stage COPD (classified as GOLD 1) and long-term smokers with normal lung function (LF). Here, we characterised the early changes in the associated inflammatory state in patients with GOLD 1 and in long-term smokers with normal LF. Fresh blood samples from 27 patients with GOLD 1, 27 long-term smokers and 14 non-smokers were analysed. Ex vivo blood analysis revealed greater leucocyte-platelet adhesion to TNFα-stimulated pulmonary endothelium in patients with GOLD 1 than in smokers and non-smokers. In addition, platelet reactivity (platelet count and activation, and fibrinogen levels) and the frequency of leucocyte-platelet aggregates were higher in the GOLD 1 group than in the other groups. Some of these findings correlated with the severity of lung dysfunction, while platelet hyperactivity correlated positively with leucocyte-platelet adhesion. The GOLD 1 group also had a higher Th17/Treg ratio and higher circulating levels of IL-17C and C-reactive protein than the other groups. However, long-term smokers also had higher leucocyte counts and activation, and higher plasma levels of TNFα and IL-6 than non-smokers. Our data suggest that the altered inflammatory parameters in long-term smokers may represent early biomarkers of COPD. Accordingly, peripheral immune monitoring based on the above parameters may be useful to prevent disease progression in long-term smokers with normal LF and early COPD.

Molecular Mechanisms and the Interplay of Important Chronic Obstructive Pulmonary Disease Biomarkers Reveals Novel Therapeutic Targets.

Chronic Obstructive Pulmonary Disease (COPD) is a progressive, age-dependent, and unmet chronic inflammatory disease of the peripheral airways, leading to difficulty in exhalation. Several biomarkers have been tested in general towards the resolution for a long time, but no apparent success was achieved. Ongoing therapies of COPD have only symptomatic relief but no cure. Reactive oxygen species (ROS) are highly reactive species which include oxygen radicals and nonradical derivatives, and are the prominent players in COPD. They are produced as natural byproducts of cellular metabolism, but their levels can vary due to exposure to indoor air pollution, occupational pollution, and environmental pollutants such as cigarette smoke. In COPD, the lungs are continuously exposed to high levels of ROS thus leading to oxidative stress. ROS can cause damage to cells, proteins, lipids, and DNA which further contributes to the chronic inflammation in COPD and exacerbates the disease condition. Excessive ROS production can overwhelm cellular antioxidant systems and act as signaling molecules that regulate cellular processes, including antioxidant defense mechanisms involving glutathione and sirtuins which further leads to cellular apoptosis, cellular senescence, inflammation, and sarcopenia. In this review paper, we focused on COPD from different perspectives including potential markers and different cellular processes such as apoptosis, cellular senescence, inflammation, sirtuins, and sarcopenia, and tried to connect the dots between them so that novel therapeutic strategies to evaluate and target the possible underlying mechanisms in COPD could be explored.

Knockdown of GNL3L Alleviates the Progression of COPD Through Inhibiting the ATM/p53 Pathway.

Chronic obstructive pulmonary disease (COPD) is a persistent chronic bronchitis disease, and its potential biomarkers have not been fully expounded. This study aims to explore the role of Guanine nucleotide binding protein like-3-like (GNL3L) in COPD induced by cigarette smoking (CS) in vivo. Two microarray datasets of COPD were selected to screen differentially expressed genes (DEGs). A protein-protein interaction network was constructed to find hub genes. The COPD model was conducted using CS/LPS-induced mouse and cigarette smoke extract induced human bronchial epithelial cells. The pathological changes of lung tissue in mice were observed by hematoxylin-eosin staining and mean linear intercept. Cell viability was measured by CCK8 assay. Oxidative stress-related indicators, inflammatory factors, and ATM/p53 related-proteins were assessed using ELISA and Western blot. In this study, there were 110 common DEGs identified from the two datasets (GSE5058 and GSE38974). The key gene GNL3L was the optimal indicator to distinguish between samples with COPD and healthy controls. Through the in vivo and in vitro experiments, GNL3L knockdown significantly improved the pathological features of CS/LPS-induced COPD mice, promoted cell viability, inhibited inflammation (IL-1β, IL-8, and TNF-α), oxidative stress (MDA, SOD, and CAT), and ATM/p53 related-proteins (ATM, p53, and p21). GNL3L is a novel biomarker of COPD, and knockdown of GNL3L participates in the progression of COPD by inhibiting ATM/p53 pathway.

Screening of Lipid Metabolism-Related Genes as Diagnostic Indicators in Chronic Obstructive Pulmonary Disease.

It has been observed that local and systemic disorders of lipid metabolism occur during the development of chronic obstructive pulmonary disease (COPD), but no specific mechanism has yet been identified. The mRNA microarray dataset GSE76925 of COPD patients was downloaded from the Gene Expression Omnibus database and screened for differentially expressed genes (DEGs). Lipid metabolism-related genes (LMRGs) were extracted from the Kyoto Encyclopedia of Genes and Genomes database and Molecular Signature Database. The DEGs were intersected with LMRGs to obtain differentially expressed lipid metabolism-related genes (DeLMRGs). GO enrichment analysis and KEGG pathway analysis were performed on DeLMRGs, and protein-protein interaction networks were constructed and screened to identify hub genes. The GSE8581 validation set and further ELISA experiments were used to validate key DeLMRG expression. Differential analysis of dataset GSE76925 identified 587 DEGs, of which 62 genes were up-regulated and 525 were down-regulated. Taking the intersection of 587 DEGs with 1102 LMRGs, 20 DeLMRGs were obtained, including 1 up-regulated gene and 19 down-regulated genes. 10 hub genes were screened by cytohubba plugin, including 9 down-regulated genes PLA2G4A, HPGDS, LEP, PTGES3, LEPR, PLA2G2D, MED21, SPTLC1 and BCHE, as well as the only up-regulated gene PLA2G7. Validation of the identified 10 DeLMRGs using the validation set GSE8581 revealed that BCHE and PLA2G7 expression levels differed between the two groups. We further constructed the ceRNA network of BCHE and PLA2G7. Cell experiments also showed that PLA2G7 expression was up-regulated and BCHE expression was down-regulated in CSE-treated RAW264.7 and THP-1 cells. Based on a comprehensive bioinformatic analysis of lipid metabolism genes, we identified BCHE and PLA2G7 as potentially significant biomarkers of COPD. These biomarkers may represent promising targets for COPD diagnosis and treatment.

Identification of circRNA-associated ceRNA networks in peripheral blood mononuclear cells as potential biomarkers for chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD), which is a common respiratory disorder with high morbidity and mortality globally, has a complex pathogenesis that is not fully understood. Some circular RNAs (circRNAs) have been recognized to serve as miRNA sponges for regulating target RNA transcripts during the processes of human diseases. In this study, we aimed to investigate novel circRNA-associated biomarkers for COPD,245 differentially expressed circRNAs were identified, including 111 upregulated and 134 downregulated circRNAs. These candidate circRNAs were enriched in inflammation-associated pathways (such as mTOR, B-cell receptor, and NF-κB signaling pathways) via Gene Ontologyand Kyoto Encyclopedia of Genes and Genomes enrichment analyses. A combination of two circRNAs (upregulated hsa_circ_0067209 and downregulated hsa_circ_0000673) demonstrated good diagnostic value (area under the receiver operating characteristiccurve(AUC)= 0.866) for COPD byreceiver operating characteristic curve(ROC)analysis and qRT-PCR validation. Subsequently, hsa-miR-8082 and hsa-miR-1248 were identified as targets for hsa_circ_0067209 and hsa_circ_0000673, respectively, via bioinformatics analysis and a dual-luciferase reporter assay, and the combination of these two miRNAs displayed better diagnosis potential for COPD (AUC = 0.967)than each other. Evaluation of COPD-related mRNA profiles revealed that the upregulated genes ABRand TRPM6were predicted downstream targetsfor hsa_circ_0067209/hsa-miR-8082, whereas the downregulated gene RORCwas a predicted downstream target for hsa_circ_0000673/hsa-miR-1248. In summary, hsa_circ_0067209 and hsa_circ_0000673 have potential as novel diagnostic biomarkers of COPD. In addition, competing endogenous RNA networks of hsa_circ_0067209/hsa-miR-8082/ABR/TRPM6 and hsa_circ_0000673/hsa-miR- &#160;1248/RORC may play critical regulation roles for COPD pathogenesis.</p>.

Identification of potential phytochemical inhibitors for the proven six chronic obstructive pulmonary disease biomarkers – A molecular dynamics study

COPD is a multifactorial lung disease causing breathing difficulties in individuals and is becoming a major health concern worldwide. The unclear pathogenic mechanism and high mortality rate urge the development of drugs against this disease. In this study, around six COPD biomarkers identified from the preceding research through integrated gene expression analysis were taken as COPD target proteins. A total of 3307 phytocompounds were included in the COPD phytocompound library from 59 therapeutic plant sources. Furthermore, a crucial three-step virtual screening process (Absorption, Distribution, Metabolism, and Excretion, respiratory nontoxicity, less harmful and nontoxic compound category) was implemented to filter the potential drug-like phytocompounds. As a result, 160 phytocompounds were filtered with desired Absorption, Distribution, Metabolism, Excretion and Toxicity properties. The filtered 160 phytocompounds were docked against six COPD target proteins and the best-docked complexes were identified through visual inspection based on six unique parameters in SeeSAR. Furthermore, the best docked complexes were subjected to molecular dynamics simulation studies to assess the stability and conformational changes of the complexes. The presence of few amino acid residues within the crucial active, allosteric and catalytic sites of the six target proteins were revealed from the binding interaction types and major residual fluctuations from molecular docking and dynamic simulation studies respectively. This is indicative of the potential inhibitory activity of phytocompounds against the COPD biomarkers. Here we report the identified phytocompounds as a promising lead molecule for the six COPD biomarkers through in silico analysis opening new avenues in COPD pathogenesis and treatments. Communicated by Ramaswamy H. Sarma