Molecular Interactions of SARS-CoV-2 in Lung Tissue of Patients with Chronic Obstructive Pulmonary Disease.
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ABSTRACT:
SUBMITTER: Agusti A
PROVIDER: S-EPMC8641835 | biostudies-literature | 2021 Nov
REPOSITORIES: biostudies-literature
Publications
Molecular Interactions of SARS-CoV-2 in Lung Tissue of Patients with Chronic Obstructive Pulmonary Disease.
Agusti Alvar A Sibila Oriol O Casas-Recasens Sandra S Mendoza Nuria N Perea Lidia L Lopez-Giraldo Alejandra A Faner Rosa R
Annals of the American Thoracic Society 20211101 11
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Project description:RationaleBased on surface brushings and bronchoalveolar lavage fluid, Hilty and coworkers demonstrated microbiomes in the human lung characteristic of asthma and chronic obstructive pulmonary disease (COPD), which have now been confirmed by others.ObjectivesTo extend these findings to human lung tissue samples.MethodsDNA from lung tissue samples was obtained from nonsmokers (n = 8); smokers without COPD (n = 8); patients with very severe COPD (Global Initiative for COPD [GOLD] 4) (n = 8); and patients with cystic fibrosis (CF) (n = 8). The latter served as a positive control, with sterile water as a negative control. All bacterial community analyses were based on polymerase chain reaction amplifying 16S rRNA gene fragments. Total bacterial populations were measured by quantitative polymerase chain reaction and bacterial community composition was assessed by terminal restriction fragment length polymorphism analysis and pyrotag sequencing.Measurement and main resultsTotal bacterial populations within lung tissue were small (20-1,252 bacterial cells per 1,000 human cells) but greater in all four sample groups versus the negative control group (P < 0.001). Terminal restriction fragment length polymorphism analysis and sequencing distinguished three distinct bacterial community compositions: one common to the nonsmoker and smoker groups, a second to the GOLD 4 group, and the third to the CF-positive control group. Pyrotag sequencing identified greater than 1,400 unique bacterial sequences and showed an increase in the Firmicutes phylum in GOLD 4 patients versus all other groups (P < 0.003) attributable to an increase in the Lactobacillus genus (P < 0.0007).ConclusionsThere is a detectable bacterial community within human lung tissue that changes in patients with very severe COPD.
| S-EPMC3359894 | biostudies-literature
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:Diaphragm muscles in Chronic Obstructive Pulmonary Disease (COPD) patients undergo an adaptive fast to slow transformation that includes cellular adaptations. This project studies the signaling mechanisms responsible for this transformation. Keywords: other
2003-07-16 | GSE475 | GEO
Project description:Background Chronic obstructive pulmonary disease (COPD) is a common chronic lung disease and its incidence is steadily increasing. COPD patients and mouse models of COPD share some similarities in lung pathology and physiology. We performed this study to explore the potential metabolic pathways involved in the pathogenesis of COPD and to discover the COPD-associated biomarkers. Furthermore, we aimed to examine how much the mouse model of COPD was similar and different to human COPD in terms of the altered metabolites and pathways. Methods Twenty human lung tissue samples (ten COPD and ten controls) and twelve mice lung tissue samples (six COPD and six controls) were analyzed by targeted HM350 metabolomics, and multivariate and pathway analysis were performed by Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results The counts of many metabolites such as amino acids, carbohydrates and carnitines were changed in both COPD patients and mice compared to controls, respectively. While lipid metabolism was changed only in COPD mice. After KEGG analysis, we found these altered metabolites involved in COPD through aging, apoptosis, oxidative stress and inflammation pathways. Conclusions The expressions of metabolites changed in both COPD patients and cigarette smoke exposed (CS-exposed) mice. And there were also some differences between COPD patients and mouse models due to the differences between species. Our study suggested the dysregulation in amino acid metabolism, energy production pathway and perhaps lipid metabolism may be significantly related to the pathogenesis of COPD.
| S-EPMC10267913 | biostudies-literature
Project description:BACKGROUND:Oral taxa are often found in the chronic obstructive pulmonary disease (COPD) lung microbiota, but it is not clear if this is due to a physiologic process such as aspiration or experimental contamination at the time of specimen collection. METHODS:Microbiota samples were obtained from nine subjects with mild or moderate COPD by swabbing lung tissue and upper airway sites during lung lobectomy. Lung specimens were not contaminated with upper airway taxa since they were obtained surgically. The microbiota were analyzed with 16S rRNA gene qPCR and 16S rRNA gene hypervariable region 3 (V3) sequencing. Data analyses were performed using QIIME, SourceTracker, and R. RESULTS:Streptococcus was the most common genus in the oral, bronchial, and lung tissue samples, and multiple other taxa were present in both the upper and lower airways. Each subject's own bronchial and lung tissue microbiota were more similar to each other than were the bronchial and lung tissue microbiota of two different subjects (permutation test, p = 0.0139), indicating more within-subject similarity than between-subject similarity at these two lung sites. Principal coordinate analysis of all subject samples revealed clustering by anatomic sampling site (PERMANOVA, p = 0.001), but not by subject. SourceTracker analysis found that the sources of the lung tissue microbiota were 21.1% (mean) oral microbiota, 8.7% nasal microbiota, and 70.1% unknown. An analysis using the neutral theory of community ecology revealed that the lung tissue microbiota closely reflects the bronchial, oral, and nasal microbiota (immigration parameter estimates 0.69, 0.62, and 0.74, respectively), with some evidence of ecologic drift occurring in the lung tissue. CONCLUSION:This is the first study to evaluate the mild-moderate COPD lung tissue microbiota without potential for upper airway contamination of the lung samples. In our small study of subjects with COPD, we found oral and nasal bacteria in the lung tissue microbiota, confirming that aspiration is a source of the COPD lung microbiota.
| S-EPMC5759273 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer suggesting that the COPD stroma contains factors supporting tumorigenesis. Since cancer initiation is complex we used a multi-omic approach to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumor and adjacent non-malignant tissue) and those with COPD without lung cancer for proteomic and mRNA (cytoplasmic and polyribosomal) profiling. We used the joint and individual variation explained (JIVE) method to integrate and analysis across the three datasets. JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples. Predictive variables that associated with the tumor, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas, predictive variables associated with adjacent tissue compared to controls was represented at the translatomic level. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed extracellular matrix (ECM) and PI3K-Akt signaling pathways as important signals in the pre-malignant stroma. COPD stroma adjacent to lung cancer is unique and differs from non-malignant COPD tissue and is distinguished by the extracellular matrix and PI3K-Akt signaling pathways.
2018-10-05 | GSE106899 | GEO
Project description:BackgroundChronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are characterized by shared exposures and clinical features, but distinct genetic and pathologic features exist. These features have not been well-studied using large-scale gene expression datasets. We hypothesized that there are divergent gene, pathway, and cellular signatures between COPD and IPF.MethodsWe performed RNA-sequencing on lung tissues from individuals with IPF (n = 231) and COPD (n = 377) compared to control (n = 267), defined as individuals with normal spirometry. We grouped the overlapping differential expression gene sets based on direction of expression and examined the resultant sets for genes of interest, pathway enrichment, and cell composition. Using gene set variation analysis, we validated the overlap group gene sets in independent COPD and IPF data sets.ResultsWe found 5010 genes differentially expressed between COPD and control, and 11,454 genes differentially expressed between IPF and control (1% false discovery rate). 3846 genes overlapped between IPF and COPD. Several pathways were enriched for genes upregulated in COPD and downregulated in IPF; however, no pathways were enriched for genes downregulated in COPD and upregulated in IPF. There were many myeloid cell genes with increased expression in COPD but decreased in IPF. We found that the genes upregulated in COPD but downregulated in IPF were associated with lower lung function in the independent validation cohorts.ConclusionsWe identified a divergent gene expression signature between COPD and IPF, with increased expression in COPD and decreased in IPF. This signature is associated with worse lung function in both COPD and IPF.
| S-EPMC9026726 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) is one of the underlying conditions in adults of any age that place them at risk for developing severe illnesses associated with COVID-19. To determine whether SARS-CoV-2's cellular tropism plays a critical role in severe pathophysiology in the lung, we investigated its host cell entry receptor distribution in the bronchial airway epithelium of healthy adults and high-risk adults (those with COPD). We found that SARS-CoV-2 preferentially infects goblet cells in the bronchial airway epithelium, as mostly goblet cells harbor the entry receptor angiotensin-converting enzyme 2 (ACE2) and its cofactor transmembrane serine protease 2 (TMPRSS2). We also found that SARS-CoV-2 replication was substantially increased in the COPD bronchial airway epithelium, likely due to COPD-associated goblet cell hyperplasia. Likewise, SARS-CoV and Middle East respiratory syndrome (MERS-CoV) infection increased disease pathophysiology (e.g., syncytium formation) in the COPD bronchial airway epithelium. Our results reveal that goblet cells play a critical role in SARS-CoV-2-induced pathophysiology in the lung. IMPORTANCE SARS-CoV-2 or COVID-19's first case was discovered in December 2019 in Wuhan, China, and by March 2020 it was declared a pandemic by the WHO. It has been shown that various underlying conditions can increase the chance of having severe COVID-19. COPD, which is the third leading cause of death worldwide, is one of the conditions listed by the CDC which can increase the chance of severe COVID-19. The present study uses a healthy and COPD-derived bronchial airway epithelial model to study the COVID-19 and host factors which could explain the reason for COPD patients developing severe infection due to COVID-19.
| S-EPMC9430117 | biostudies-literature
Project description:Investigation of whole genome gene expression level changes of the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10, compared to the normal people and stable COPD patients. A five chip study using total RNA recovered from Peripheral Blood Mononuclear Cell of Peripheral Blood.Evaluating the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10 after the hospital admission, to compared with healthy controls or patients with stable COPD. Slides were scanned at 5 μm/pixel resolution using an Axon GenePix 4000B scanner (Molecular Devices Corporation) piloted by GenePix Pro 6.0 software (Axon). Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and Gene level (*_RMA.calls) files were generated after normalization.
2014-08-14 | E-GEOD-60399 | biostudies-arrayexpress
Project description:BackgroundChronic obstructive pulmonary disease (COPD) is a highly morbid and heterogenous disease. While COPD is defined by spirometry, many COPD characteristics are seen in cigarette smokers with normal spirometry. The extent to which COPD and COPD heterogeneity is captured in omics of lung tissue is not known.MethodsWe clustered gene expression and methylation data in 78 lung tissue samples from former smokers with normal lung function or severe COPD. We applied two integrative omics clustering methods: (1) Similarity Network Fusion (SNF) and (2) Entropy-Based Consensus Clustering (ECC).ResultsSNF clusters were not significantly different by the percentage of COPD cases (48.8% vs. 68.6%, p = 0.13), though were different according to median forced expiratory volume in one second (FEV1) % predicted (82 vs. 31, p = 0.017). In contrast, the ECC clusters showed stronger evidence of separation by COPD case status (48.2% vs. 81.8%, p = 0.013) and similar stratification by median FEV1% predicted (82 vs. 30.5, p = 0.0059). ECC clusters using both gene expression and methylation were identical to the ECC clustering solution generated using methylation data alone. Both methods selected clusters with differentially expressed transcripts enriched for interleukin signaling and immunoregulatory interactions between lymphoid and non-lymphoid cells.ConclusionsUnsupervised clustering analysis from integrated gene expression and methylation data in lung tissue resulted in clusters with modest concordance with COPD, though were enriched in pathways potentially contributing to COPD-related pathology and heterogeneity.
| S-EPMC10091624 | biostudies-literature