Single-nucleus transcriptomic profiling of human lung tissue in chronic obstructive pulmonary disease (COPD)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE310058 | GEO | 2025/11/17
REPOSITORIES: GEO
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Project description:Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease with complex pathological features and largely unknown etiologies. Identification and validation of biomarkers for this disease could facilitate earlier diagnosis, appreciation of disease subtypes and/or determination of response to therapeutic intervention. To identify gene expression markers for COPD, we performed genome-wide expression profiling of lung tissue from 56 subjects using the Affymetrix U133 Plus 2.0 array. Lung function measurements from these subjects ranged from normal, un-obstructed to severely obstructed. Analysis of differential expression between cases (FEV1<70%, FEV1/FVC<0.7) and controls (FEV1>80%, FEV1/FVC>0.7) identified a set of 65 probe sets representing discrete markers associated with COPD. Correlation of gene expression with quantitative measures of airflow obstruction (FEV1 or FEV1/FVC) identified a set of 220 probe sets. A total of 31 probe sets were identified that showed evidence of significant correlation with quantitative traits and differential expression between cases and controls. Keywords: Disease state marker
2008-05-31 | GSE8581 | GEO
Project description:COPD is a common and disabling lung disease for which very few therapeutic options are currently available. We reasoned that global gene expression profiling of COPD lungs could reveal previously unidentified disease pathways for potential therapeutic interventions. Forty-eight human lung samples were obtained from lungs or lobes resected for small peripheral lung lesions (5 non-smokers, 21 GOLD 0, 9 GOLD 1, 10 GOLD 2 and 3 GOLD 3 patients). mRNA from the specimens was profiled using Agilent’s Functional ID v2.0 array which contains 23,720 sequences. Quantitative morphometric analysis of the specimens revealed that the samples contained a variable proportion of airways, blood vessels and parenchyma. Incorporating these data into a model relating gene expression to % predicted forced expiratory flow between 25 and 75% of forced expiratory volume (FEF 25-75 % P) revealed a signature gene set of 203 transcripts. Genes involved in extracellular matrix synthesis/degradation, oxidative stress and cell proliferation were among the up-regulated genes whereas genes which participate in nicotine metabolism, elastic fiber homeostasis and anti-inflammatory response were down-regulated. Immunohistochemistry confirmed expression of urokinase (PLAU), urokinanse receptor (PLAUR) and thrombospondin (THBS1) by alveolar macrophages and small airway epithelial cells. Genes in this pathway have been shown to be involved in transforming growth factor beta-1 (TGF?1) and matrix metalloproteinase (MMP) activation and are subject to inhibition by serpin E2. Interestingly, both TGF?1 and serpin E2 have been identified as candidate genes in COPD genetic linkage and association studies. The results thus provide a possible link between these two powerful approaches to identify potential therapeutic targets. (255 words) Forty-eight human lung samples were obtained from lungs or lobes resected for small peripheral lung lesions (5 non-smokers, 21 GOLD 0, 9 GOLD 1, 10 GOLD 2 and 3 GOLD 3 patients). mRNA from the specimens was profiled using Agilent’s Functional ID v2.0 array which contains 23,720 sequences. Quantitative morphometric analysis of the specimens revealed that the samples contained a variable proportion of airways, blood vessels and parenchyma. Incorporating these data into a model relating gene expression to % predicted forced expiratory flow between 25 and 75% of forced expiratory volume (FEF 25-75 % P) revealed a signature gene set of 203 transcripts.
2007-11-09 | E-GEOD-8500 | biostudies-arrayexpress
Project description:Rationale: Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease lacking disease modifying treatment. The role of CXCL12/CXCR4 axis has been demonstrated in acute exacerbation of COPD. The interest of study early COPD has been recently pointed out. Objectives: To study the role of the CXCL12/CXCR4 axis in both human and mouse model of early COPD. Methods: Blood and lung tissue were obtained from both COPD patients and mice exposed to cigarette smoke (CS) for 10 weeks and intranasal instillations of polyinosinic–polycytidylic acid (poly(I:C)) to mimic exacerbations for 5 weeks. Measurements and Main Results: Exposed mice presented mild airway obstruction, peri-bronchial fibrosis and right heart remodeling. The level of CXCR4 expressing cells was increased in the blood of exposed mice, as well as in the blood of patients with mild COPD. Lung CXCL12 expression was higher both in exposed mice and COPD patients. The densities of fibrocytes expressing CXCR4 were increased in the blood and in the bronchial submucosa of exposed mice. Conditional inactivation of CXCR4 at adult stage as well as pharmacological inhibition of CXCR4 with plerixafor injections improved lung function and inflammation and protected against CS and poly-(I:C)-induced airway and cardiac remodeling. CXCR4-/- and plerixafor-treated mice also had reduced levels of CXCR4-expressing circulating cells and a lower density of peri-bronchial fibrocytes. Conclusions: We demonstrated that targeting CXCR4 has beneficial effects in an animal model of early COPD, and provide a framework to translate preclinical findings to clinical settings within a drug repurposing approach.
2025-05-12 | PXD040105 | Pride
Project description:Background: Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD, thus the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Methods: Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Results: Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, Random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. Conclusion: We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.
2022-10-17 | PXD035120 | Pride
Project description:Chronic obstructive pulmonary disease (COPD) Metagenome
| PRJNA647843 | ENA
Project description:COPD is a common and disabling lung disease for which very few therapeutic options are currently available. We reasoned that global gene expression profiling of COPD lungs could reveal previously unidentified disease pathways for potential therapeutic interventions. Forty-eight human lung samples were obtained from lungs or lobes resected for small peripheral lung lesions (5 non-smokers, 21 GOLD 0, 9 GOLD 1, 10 GOLD 2 and 3 GOLD 3 patients). mRNA from the specimens was profiled using Agilent’s Functional ID v2.0 array which contains 23,720 sequences. Quantitative morphometric analysis of the specimens revealed that the samples contained a variable proportion of airways, blood vessels and parenchyma. Incorporating these data into a model relating gene expression to % predicted forced expiratory flow between 25 and 75% of forced expiratory volume (FEF 25-75 % P) revealed a signature gene set of 203 transcripts. Genes involved in extracellular matrix synthesis/degradation, oxidative stress and cell proliferation were among the up-regulated genes whereas genes which participate in nicotine metabolism, elastic fiber homeostasis and anti-inflammatory response were down-regulated. Immunohistochemistry confirmed expression of urokinase (PLAU), urokinanse receptor (PLAUR) and thrombospondin (THBS1) by alveolar macrophages and small airway epithelial cells. Genes in this pathway have been shown to be involved in transforming growth factor beta-1 (TGFβ1) and matrix metalloproteinase (MMP) activation and are subject to inhibition by serpin E2. Interestingly, both TGFβ1 and serpin E2 have been identified as candidate genes in COPD genetic linkage and association studies. The results thus provide a possible link between these two powerful approaches to identify potential therapeutic targets. (255 words) Keywords: Pulmonary emphysema, phenotype, transcriptional analysis, cigarette smoking
2007-11-10 | GSE8500 | GEO
Project description:Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease typified by not fully reversible and often progressive airflow obstruction, along with persistent respiratory symptoms. This gap is due to lack of animal models that more closely mimic human COPD are needed to bridge translational gaps. Commonly used mice model produces primarily emphysematous disease and do not develop features pathognomonic for chronic bronchitis. Suggesting the potential for additional molecular insights to be obtained from animal models that exhibit COPD with features of chronic bronchitis and emphysema, as in humans. We sought to identify whether our ferret model of COPD captures unique genetic signatures in comparison to mouse models that can help improve understanding of the molecular pathogenesis of COPD and promote the development of new and effective therapies.
2022-10-19 | GSE193749 | GEO
Project description:Chronic Obstructive Pulmonary Disease (COPD) patient microbiome
| PRJEB46960 | ENA
Project description:Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have utilized individual proteins or pre-selected protein panels measured in blood samples. To identify COPD protein biomarkers by applying comprehensive mass spectrometry proteomics in lung tissue samples. We utilized mass spectrometry proteomic approaches to identify protein biomarkers from 152 lung tissue samples representing COPD cases and controls.
2022-01-07 | PXD024124 | Pride
Project description:Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood cells is a useful way to study disease pathobiology and may help elucidate biomarkers and molecular mechanisms of disease. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, some cell types and some indication. Accurate enumeration of the many component cell types that make up peripheral whole blood can be costly, however, and may further complicate the sample collection process. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform. We present a freely-available, and open-source, multiresponse Gaussian model capable of accurately inferring the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles. The model was developed on a cohort of patients with chronic obstructive pulmonary disease (COPD) and tested in chronic heart failure patients.
2016-05-25 | GSE77344 | GEO