Biomarkers For Chronic Obstructive Pulmonary Disease Research Articles

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.

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.

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.

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.

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.

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

Plasma Proteomics Study Between the Frequent Exacerbation and Infrequent Exacerbation Phenotypes of Chronic Obstructive Pulmonary Disease.

Frequent exacerbation (FE) and infrequent exacerbation (IE) are two phenotypes of chronic obstructive pulmonary disease (COPD), of which FE is associated with a higher incidence of exacerbation and a serious threat to human health. Because the pathogenesis mechanisms of FE are unclear, this study aims to identify FE-related proteins in the plasma via proteomics for use as predictive, diagnostic, and therapeutic biomarkers of COPD. A cross-sectional study was conducted in which plasma protein profiles were analyzed in COPD patients at stable stage, and differentially expressed proteins (DEPs) were screened out between the FE and IE patients. FE-related DEPs were identified using data-independent acquisition-based proteomics and bioinformatics analyses. In addition, FE-related candidates were verified by enzyme-linked immunosorbent assay. In this study, 47 DEPs were screened out between the FE and IE groups, including 20 upregulated and 27 downregulated proteins. Key biological functions (eg, neutrophil degranulation, extracellular exosome, protein homodimerization activity) and signaling pathways (eg, arginine and proline metabolism) were enriched in association with the FE phenotype. Receiver operating characteristic (ROC) analysis of the 11 combined DEPs revealed an area under the curve of 0.985 (p <0.05) for discriminating FE from IE. Moreover, correlation and ROC curve analyses indicated that creatine kinase, M-type (CKM) and fat storage-inducing transmembrane protein 1 (FITM1) might be clinically significant in patients with the FE phenotype. In addition, plasma expression levels of CKM and FITM1 were validated to be significantly decreased in the FE group compared with the IE group (CKM: p <0.01; FITM1: p <0.05). In this study, novel insights into COPD pathogenesis were provided by investigating and comparing plasma protein profiles between the FE and IE patients. CKM, FITM1, and a combinative biomarker panel may serve as useful tools for assisting in the precision diagnosis and effective treatment of the FE phenotype of COPD.

Identification and bioinformatic analysis of CircRNAs in the plasma of patients with very severe chronic obstructive pulmonary disease

BackgroundThe differential expression of circular RNAs (circRNAs) in individuals with very severe chronic obstructive pulmonary disease (COPD) and healthy individuals was screened using microarray technology. The related functions and mechanisms were analyzed using bioinformatic methods to explore the potential of target circRNAs as biomarkers of COPD and provide insights for future pathogenesis.Patients and methodsThirty patients with very severe COPD and thirty healthy controls were diagnosed at The Second People’s Hospital of Hefei from September 2021 to September 2022. The differential expression of circRNAs was compared and analyzed using a gene microarray and verified using quantitative real-time polymerase chain reaction (qRT-PCR) technology.ResultsA total of 90 upregulated and 29 downregulated circRNAs were screened in patients with very severe COPD and compared with those in healthy controls. qRT-PCR analysis showed that hsa_circ_0062683 of patients with very severe COPD was significantly upregulated, and hsa_circ_0089763 and hsa_circ_0008882 were significantly downregulated. By constructing the circRNA-miRNA interaction network, it was found that hsa-miR-612, hsa-miR-593-5p, hsa-miR-765, and hsa-miR-103a-2-5p are the miRNAs regulated by more differentially expressed circRNAs (DEcircRNAs). DEcircRNAs may participate in the development of COPD through hypoxia or regulation of various immune cells.ConclusionPlasma circRNAs may play a helpful role in the diagnosis and assessment of COPD and be valuable disease biomarkers.

Bioinformatics analysis of PLA2G7 as an immune-related biomarker in COPD by promoting expansion and suppressive functions of MDSCs

BackgroundImmune mechanism is involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, the exact immune pathogenesis still remains unclear. This study aimed to identify the immune-related biomarkers in COPD through bioinformatics analysis and its potential molecular mechanism. MethodsGSE76925 was downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened, and enrichment analysis was performed. Single sample gene enrichment analysis (ssGSEA) was conducted to score the infiltration levels of immune cells. Weighted gene co-expression network analysis (WGCNA) was applied to identify trait-related modules and to further determine the key module-related DEGs. Moreover, the correlations between the key genes and clinical parameters and infiltration levels of immune cells were analyzed. Furthermore, expression of the selected one key gene, PLA2G7, the frequency of MDSCs, and the expression of MDSCs-related immunosuppressive mediators were determined among healthy, smokers and COPD patients. Finally, effects of PLA2G7 abnormal expression on the frequency of MDSCs and the expression of MDSCs-related immunosuppressive mediators were examined. ResultsA total of 352 DEGs were observed. These DEGs were mainly related to RNA metabolism and positive regulation of organelle organization. In addition, the black module was the most correlated with COPD. Six key genes (ADAMDEC1, CCL19, CHIT1, MMP9, PLA2G7, and TM4SF19) were identified between the black module and DEGs. Serum Lp-PLA2 and mRNA levels of PLA2G7, MDSCs, and MDSCs-related immunosuppressive mediators were found to be upregulated in COPD patients compared to the controls. The expression of PLA2G7 represented positive impact on the frequency of MDSCs and the expression of MDSCs-related immunosuppressive mediators. ConclusionPLA2G7 may serve as a potential immune-related biomarker contributing to the progression of COPD by promoting expansion and suppressive functions of MDSCs.

Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review.

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease which is characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypic complexity of COPD, traditional diagnostic methods provide limited information and pose a great challenge to clinical management. In recent years, with the development of omics technologies, proteomics, metabolomics, transcriptomics, etc., have been widely used in the study of COPD, providing great help to discover new biomarkers and elucidate the complex mechanisms of COPD. In this review, we summarize the prognostic biomarkers of COPD based on proteomic studies in recent years and evaluate their association with COPD prognosis. Finally, we present the prospects and challenges of COPD prognostic-related studies. This review is expected to provide cutting-edge evidence in prognostic evaluation of clinical patients with COPD and to inform future proteomic studies on prognostic biomarkers of COPD.

Inflammation biomarkers in OSA, chronic obstructive pulmonary disease, and chronic obstructive pulmonary disease/OSA overlap syndrome.

The coexistence of obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) in a single individual, also known as overlap syndrome (OVS), is associated with higher cardiovascular risk and mortality than either OSA or COPD alone. However, the underlying mechanisms remain unclear. We hypothesized that patients with OVS have elevated systemic inflammatory biomarkers relative to patients with either disease alone, which could explain greater cardiovascular risk observed in OVS. We included 255 participants in the study, 55 with COPD alone, 100 with OSA alone, 50 with OVS, and 50 healthy controls. All participants underwent a home sleep study, spirometry, and a blood draw for high-sensitivity C-reactive protein and total blood count analysis. In a randomly selected subset of 186 participants, inflammatory protein profiling was performed using Bio-Rad Bio-Plex Pro Human Cytokine 27-Plex Assays. Biomarker level differences across groups were identified using a mixed linear model. Levels of interleukin 6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), and granulocyte colony stimulating factor (G-CSF) were higher in participants with OVS and COPD compared with healthy controls and participants with OSA. Furthermore, participants with OVS had higher circulating levels of leukocytes and neutrophils than those with COPD, OSA, and controls. COPD and OVS are associated with higher systemic inflammation relative to OSA and healthy controls. This work proposes the potential utilization of interleukin 6, granulocyte colony stimulating factor, and high-sensitivity C-reactive protein as screening biomarkers for COPD in patients with OSA. Inflammatory pathways may not fully explain the higher cardiovascular risk observed in OVS, indicating the need for further investigation. Sanchez-Azofra A, Gu W, Masso-Silva JA, etal. Inflammation biomarkers in OSA, chronic obstructive pulmonary disease, and chronic obstructive pulmonary disease/OSA overlap syndrome. J Clin Sleep Med. 2023;19(8):1447-1456.

A2M Serves as Promising Biomarker for Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) often associated with cigarette smoking. However, increasing evidence suggests that non-smoking COPD is much higher than previously thought. This study aims to identify a nonsmoking COPD biomarker and examined its value in diagnosis and prediction of acute exacerbation. A total of 35 stable COPD patients, 70 acute exacerbation chronic obstructive pulmonary disease (AECOPD) patients and 35 healthy control subjects were included. Plasma α 2 macroglobulin (A2M) and matrix metalloproteinase-9 (MMP-9) levels were measured using the enzyme-linked immunosorbent assay (ELISA) method on all participants. Their association with clinical characteristics and lung function parameters were determined by regression analysis. Receiver operating characteristic (ROC) curve was used to determine the diagnostic sensitivity and specificity. Correlation coefficients were evaluated using Pearson's correlation. Plasma A2M concentration was decreased and MMP-9 concentration, MMP-9/A2M ratio were elevated in stable COPD patients compared with control groups. And MMP-9 expression was significantly higher in AECOPD patients. A2M level was increased in AECOPD patients with infection compared with those without. In addition, there was no statistical difference in A2M levels between smokers and nonsmokers COPD or healthy control subjects. Furthermore, A2M, MMP-9 and MMP-9/A2M were correlated with forced expiratory volume in one second (FEV1)%, FEV1/ forced vital capacity (FVC), CAT and mMRC score in COPD patients, but had no correlation with fraction of exhaled nitric oxide (FeNO) and concentration of alveolar nitric oxide (CaNO). A2M is altered in peripheral blood of COPD patients and correlated with severity and infection. Moreover, there was no significant correlation between the change in A2M and smoking, FeNO and CaNO, suggesting A2M may reflect the overall rather than local inflammation in COPD patients and serve as a potential biomarker for nonsmoking COPD patients.