Dataset Information

Proteomic signatures in chronic obstructive pulmonary disease emphysematous phenotype

ABSTRACT: Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease. Emphysematous phenotype is a type of most common and critical phenotype, which is characterized by progressive lung destruction and poor prognosis. However, the underlying mechanism of this structural damage has not been completely elucidated. A total of 12 patients with COPD emphysematous phenotype (COPD-E) and 9 patients with COPD non-emphysematous phenotype (COPD-NE) were enrolled to determine differences in differential abundant protein (DAP) expression between both groups. Quantitative tandem mass tag-based proteomics was performed on lung tissue samples of all patients.

ORGANISM(S): Homo Sapiens

SUBMITTER: Li Zhao

PROVIDER: PXD023900 | iProX | Sun Jan 31 00:00:00 GMT 2021

REPOSITORIES: iProX

ACCESS DATA

Publications

Identification of Proteomic Signatures in Chronic Obstructive Pulmonary Disease Emphysematous Phenotype.

Bai Shuang S Ye Rui R Wang Cuihong C Sun Pengbo P Wang Di D Yue Yong Y Wang Huiying H Wu Si S Yu Miao M Xi Shuhua S Zhao Li L

Frontiers in molecular biosciences 20210701

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease. Emphysematous phenotype is the most common and critical phenotype, which is characterized by progressive lung destruction and poor prognosis. However, the underlying mechanism of this structural damage has not been completely elucidated. A total of 12 patients with COPD emphysematous phenotype (COPD-E) and nine patients with COPD non-emphysematous phenotype (COPD-NE) were enrolled to determine differences in differen ...[more]

PMID: 34277700

Similar Datasets

Project description:BACKGROUND: Chronic obstructive pulmonary disease (COPD) exacerbations significantly contribute to morbidity and mortality. The complex nature of COPD presents challenges in accurately predicting and understanding frequent exacerbations.OBJECTIVE: This study aimed to investigate the metabolic characteristics of frequent exacerbation of COPD (COPD-FE) phenotype, identify potential metabolic biomarkers associated with COPD-FE risk and explore underlying pathogenic mechanisms.METHODS: An internal cohort of 30 stable COPD patients was recruited. A widely targeted metabolomics approach was employed to detect and compare serum metabolite expressions between patients with COPD-FE and non-frequent exacerbations (COPD-NE). Subsequently, bioinformatics analysis was utilized for pathway enrichment of the identified metabolites; Spearman correlation analysis explored associations between metabolites and clinical indicators, and receiver operating characteristic (ROC) analysis assessed the predictive performance of identified metabolites. An external cohort of 20 patients with COPD validated findings from the internal cohort.RESULTS: Out of 484 detected metabolites, 25 exhibited significant differences between COPD-FE and COPD-NE. Metabolomic analysis revealed differences in lipid, energy, amino acid and immunity pathways. Spearman correlation analysis showed associations between metabolites and clinical indicators of acute exacerbation risk. ROC analysis revealed that D-fructose 1,6-bisphosphate (AUC=0.871), arginine (AUC=0.836), L-2-Hydroxyglutarate (L-2HG, AUC=0.849), Diacylglycerol (DG)(16:0/20:5) (AUC=0.827), DG(16:0/20:4) (AUC=0.818) and carnitine-C18:2 (AUC=0.804) had area under the curve (AUC) values above 0.8, highlighting their superior discriminative capacity between the two groups. External validation results showed that DG(16:0/20:5), DG(16:0/20:4), carnitine-C18:2 and L-2HG were significantly different between COPD-FE patients and COPD-NE patients (p-value<0.05).CONCLUSION: This study offers insights into early identification, mechanistic understanding and personalized management of COPD-FE phenotype.

Dataset Information

Proteomic signatures in chronic obstructive pulmonary disease emphysematous phenotype

Publications

Identification of Proteomic Signatures in Chronic Obstructive Pulmonary Disease Emphysematous Phenotype.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets