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Serum metabolomics analysis of patients with chronic obstructive pulmonary disease and 'frequent exacerbator' phenotype.

ABSTRACT: Chronic obstructive pulmonary disease (COPD) exacerbations accelerate loss of lung function and increased mortality. The complex nature of COPD presents challenges in accurately predicting and understanding frequent exacerbations. The present study aimed to assess the metabolic characteristics of the frequent exacerbation of COPD (COPD‑FE) phenotype, identify potential metabolic biomarkers associated with COPD‑FE risk and evaluate the underlying pathogenic mechanisms. An internal cohort of 30 stable patients with COPD was recruited. A widely targeted metabolomics approach was used to detect and compare serum metabolite expression profiles between patients with COPD‑FE and patients with non‑frequent exacerbation of COPD (COPD‑NE). Bioinformatics analysis was used for pathway enrichment analysis of the identified metabolites. Spearman's correlation analysis assessed the associations between metabolites and clinical indicators, while receiver operating characteristic (ROC) analysis evaluated the ability of metabolites to distinguish between two groups. An external cohort of 20 patients with COPD validated findings from the internal cohort. Out of the 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's correlation analysis demonstrated associations between metabolites and clinical indicators of acute exacerbation risk. ROC analysis demonstrated that the area under the curve (AUC) values for 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) were >0.8, highlighting their discriminative capacity between the two groups. External validation results demonstrated that DG (16:0/20:5), DG (16:0/20:4), carnitine‑C18:2 and L‑2HG were significantly different between patients with COPD‑FE and those with COPD‑NE. In conclusion, the present study offers insights into early identification, mechanistic understanding and personalized management of the COPD‑FE phenotype.

SUBMITTER: Ding HZ

PROVIDER: S-EPMC11200052 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Serum metabolomics analysis of patients with chronic obstructive pulmonary disease and 'frequent exacerbator' phenotype.

Ding Huan-Zhang HZ Wang Hui H Wu Di D Zhou Fan-Chao FC Zhu Jie J Tong Jia-Bing JB Gao Ya-Ting YT Li Ze-Geng ZG

Molecular medicine reports 20240614 2

Chronic obstructive pulmonary disease (COPD) exacerbations accelerate loss of lung function and increased mortality. The complex nature of COPD presents challenges in accurately predicting and understanding frequent exacerbations. The present study aimed to assess the metabolic characteristics of the frequent exacerbation of COPD (COPD‑FE) phenotype, identify potential metabolic biomarkers associated with COPD‑FE risk and evaluate the underlying pathogenic mechanisms. An internal cohort of 30 st ...[more]

PMID: 38873983

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Project description:BackgroundChronic obstructive pulmonary disease (COPD) patients with different phenotypes show different clinical characteristics. Therefore, we conducted a meta-analysis to explore the clinical characteristics between the non-exacerbator (NE) phenotype and the frequent exacerbator with chronic bronchitis (FE-CB) phenotype among patients with COPD.MethodsCNKI, Wan fang, Chongqing VIP, China Biology Medicine disc, PubMed, Cochrane Library, and EMBASE databases were searched from the times of their inception to April 30, 2019. All studies that reported the clinical characteristics of the COPD phenotypes and which met the inclusion criteria were included. The quality assessment was analyzed by Cross-Sectional/Prevalence Study Quality recommendations. The meta-analysis was carried out using RevMan5.3.ResultsTen cross-sectional observation studies (n = 8848) were included. Compared with the NE phenotype, patients with the FE-CB phenotype showed significantly lower forced expiratory volume in 1 s percent predicted (FEV1%pred) (mean difference (MD) -8.50, 95% CI -11.36--5.65, P < 0.001, I2 = 91%), forced vital capacity percent predicted (FVC%pred) [MD - 6.69, 95% confidence interval (CI) -7.73--5.65, P < 0.001, I2 = 5%], and forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) (MD -3.76, 95% CI -4.58--2.95,P < 0.001, I2 = 0%); in contrast, Charlson comorbidity index (MD 0.47, 95% CI 0.37-0.58, P < 0.001, I2 = 0], COPD assessment test (CAT) score (MD 5.61, 95% CI 4.62-6.60, P < 0.001, I2 = 80%), the quantity of cigarettes smoked (pack-years) (MD 3.09, 95% CI 1.60-4.58, P < 0.001, I2 = 41%), exacerbations in previous year (2.65, 95% CI 2.32-2.97, P < 0.001, I2 = 91%), modified Medical British Research Council (mMRC) score (MD 0.72, 95% CI 0.63-0.82, P < 0.001, I2 = 57%), and body mass index (BMI), obstruction, dyspnea, exacerbations (BODEx) (MD 1.78, 95% CI 1.28-2.28, P < 0.001, I2 = 91%), I2 = 34%) were significantly higher in patients with FE-CB phenotype. No significant between-group difference was observed with respect to BMI (MD-0.14, 95% CI -0.70-0.42, P = 0.62, I2 = 75%).ConclusionCOPD patients with the FE-CB phenotype had worse pulmonary function and higher CAT score, mMRC scores, frequency of acute exacerbations, and the quantity of cigarettes smoked (pack-years) than those with the NE phenotype.

Project description:To investigate the difference of clinical characteristics between chronic obstructive pulmonary disease (COPD) patients with the frequent exacerbators with chronic bronchitis (FE-CB) phenotype and those with the asthma-COPD overlap syndrome (ACO) phenotype.We searched CNKI, Wan Fang, Chongqing VIP, China Biology Medicine disc, PubMed, Cochrane Library, and EMBASE databases for studies published as of April 30, 2019. All studies that investigated COPD patients with the FE-CB and ACO phenotypes and which qualified the inclusion criteria were included. Cross-sectional/prevalence study quality recommendations were used to measure methodological quality. RevMan5.3 software was used for meta-analysis.Ten studies (combined n = 4568) qualified the inclusion criteria. The FE-CB phenotype of COPD was associated with significantly lower forced vital capacity percent predicted (mean difference [MD] -9.05, 95% confidence interval [CI] [-12.00, -6.10], P < .001, I = 66%), forced expiratory volume in 1 second (FEV1) (MD -407.18, 95% CI [-438.63, -375.72], P < .001, I = 33%), forced expiratory volume in 1 second percent predicted (MD -9.71, 95% CI [-12.79, -6.63], P < .001, I = 87%), FEV1/forced vital capacity (MD -5.4, 95% CI [-6.49, -4.30], P < .001, I = 0%), and body mass index (BMI) (MD -0.81, 95% CI [-1.18, -0.45], P < .001, I = 44%) as compared to the ACO phenotype. However, FE-CB phenotype was associated with higher quantity of cigarettes smoked (pack-years) (MD 6.45, 95% CI [1.82, 11.09], P < .001, I = 73%), COPD assessment test score (CAT) (MD 4.04, 95% CI [3.46, 4.61], P < .001, I = 0%), mMRC score (MD 0.54, 95% CI [0.46, 0.62], P < .001, I = 34%), exacerbations in previous year (1.34, 95% CI [0.98, 1.71], P < .001, I = 68%), and BMI, obstruction, dyspnea, exacerbations (BODEx) (MD 1.59, 95% CI [1.00, 2.18], P < .001, I = 86%) as compared to the ACO phenotype.Compared with the ACO phenotype, COPD patients with the FE-CB phenotype had poorer pulmonary function, lower BMI, and higher CAT score, quantity of cigarettes smoked (pack-years), exacerbations in previous year, mMRC score, and BODEx.This study is an analysis of published literature, which belongs to the second study. Therefore, this study does not require the approval of the ethics committee. The findings will be disseminated through a peer-reviewed journal publication or conference presentation.

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.

Project description:PurposeChronic obstructive pulmonary disease (COPD) is a heterogeneous disease with high morbidity and mortality rates. This study used proteomic profiling of serum to identify the differentially expressed proteins in COPD patients compared with healthy controls, to expand the knowledge of COPD pathogenesis and to ascertain potential new targets for diagnosis and treatment of COPD.MethodsSerum samples were collected from 56 participants (COPD group n = 28; Healthy Control group n = 28). A data-independent acquisition quantitative proteomics approach was used to identify differentially expressed proteins (DEPs) between the two groups. Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment, and protein-protein interaction analyses of DEPs were conducted to identify their relevant biological processes, cellular components, and related pathways. We used a parallel reaction monitoring (PRM)-based targeted quantitative proteomics approach to validate those findings.ResultsOf 8484 peptides identified by searching the UniProtKB/Swiss-Prot knowledgebase, 867 proteins were quantifiable, of which 20 were upregulated and 35 were downregulated in the COPD group. GO functional annotation indicated that the subcellular localization of most DEPs was extracellular. The top three molecular functions of the DEPs were signaling receptor binding, antigen binding, and immunoglobulin receptor binding. The most relevant biological process was immune response. The transforming growth factor-β signaling pathway, Staphylococcus aureus infection, and hematopoietic cell lineage were the top three pathways identified in the KEGG pathway functional enrichment. Our PRM analyses confirmed the identification of 11 DEPs identified in our data-independent acquisition analyses, 8 DEPs were upregulated and 3 DEPs were downregulated.ConclusionThis study using data-independent acquisition analyses with PRM confirmation of findings identified 11 DEPs in the serum of patients with COPD. These DEPs are potential diagnostic or prognostic biomarkers or may be future targets for the treatment of COPD.

Dataset Information

Serum metabolomics analysis of patients with chronic obstructive pulmonary disease and 'frequent exacerbator' phenotype.

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Serum metabolomics analysis of patients with chronic obstructive pulmonary disease and 'frequent exacerbator' phenotype.

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