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Chronic Obstructive Pulmonary Disease (COPD) patient microbiome

ABSTRACT: Chronic Obstructive Pulmonary Disease (COPD) patient microbiome

PROVIDER: PRJEB46960 | ENA |

REPOSITORIES: ENA

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Chronic obstructive pulmonary disease (COPD)

Project description:Chronic obstructive pulmonary disease (COPD) Metagenome

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Chronic obstructive pulmonary disease

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2003-07-16 | GSE475 | GEO

Plasma proteomics enable differentiation of lung adenocarcinoma from chronic obstructive pulmonary disease (COPD)

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

The site and nature of terminal bronchiolar destruction in chronic obstructive pulmonary disease (COPD).

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Association of sputum microbiome with exacerbations, patient subgroups and host response in chronic obstructive pulmonary disease

Project description:Little is known about the lung microbiome dynamics and host-microbiome interactions in relation to chronic obstructive pulmonary disease (COPD) exacerbations and in patient subgroups based on smoking status and disease severity. Here we performed a 16S ribosomal RNA survey on sputum microbiome from 16 healthy and 43 COPD subjects. For COPD subjects, a longitudinal sampling was performed from stable state to exacerbations, at two and six weeks post-exacerbations and at six months from first stable visit. Host sputum transcriptome were characterized for a subset of COPD patient samples.

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Human Chronic Obstructive Pulmonary Disorder (COPD) Biomarker

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

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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.

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Transcription profiling of human diaphragm Chronic Obstructive Pulmonary Disease (COPD) patients vs. controls to study diaphragm muscle fast to slow adaptive transformation.

2007-10-25 | E-GEOD-475 | biostudies-arrayexpress

A preliminary study on the screening and mechanism of miRNA as a biomarker for patients with different progressive chronic obstructive pulmonary disease (COPD)

Project description:In this study, a high-throughput sequencing technology was used to screen the differentially expressed miRNA in the patients with "fast" and "slow" progression of chronic obstructive pulmonary disease (COPD). Moreover, the possible mechanism, affecting the progression of COPD, was preliminarily analyzed based on the target genes of candidate miRNAs.

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trancription profiling by array of human pulmonary and circulating CD8 cells in COPD

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