Plasma Metabolomics and Lipidomics Reveal Perturbed Metabolites in Different Disease Stages of Chronic Obstructive Pulmonary Disease
Authors Zhou J, Li Q, Liu C, Pang R, Yin Y
Received 2 September 2019
Accepted for publication 10 January 2020
Published 9 March 2020 Volume 2020:15 Pages 553—565
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Chunxue Bai
Juntuo Zhou,1,* Qiuyu Li,2,* Chengyang Liu,3 Ruifang Pang,1 Yuxin Yin3
1Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Beijing, People’s Republic of China; 3Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Beijing Key Laboratory of Tumor Systems Biology, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing 100191, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yuxin Yin
Department of Pathology, School of Basic Medical Sciences, Beijing Key Laboratory of Tumor Systems Biology, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing 100191, People’s Republic of China
Background: Chronic obstructive pulmonary disease (COPD) is a common disease characterized by persistent respiratory symptoms and airflow restriction. It is usually manifested as airway and/or alveolar abnormalities caused by significant exposure to harmful particulates or gases.
Objective: We aim to explore plasma metabolomic changes in the acute exacerbation stage of COPD (AECOPD) and stable stage of COPD (Stable COPD) to identify potential biomarkers for diagnosis or prognosis in clinical practice.
Methods: Untargeted metabolomics and lipidomics analyses were performed to investigate dysregulated molecules in blood plasma of AECOPD patients (n=48) and Stable COPD (n=48), and a cohort of healthy people were included as a control group (n=48). Statistical analysis and bioinformatics analysis were performed to reveal dysregulated metabolites and perturbed metabolic pathways. SVM-based multivariate ROC analysis was used for candidate biomarker screening.
Results: A total of 142 metabolites and 688 lipids were dysregulated in COPD patients. Pathway enrichment analysis showed that several metabolic pathways were perturbed after COPD onset. Several biomarker panels were proposed for diagnosis of COPD vs healthy control and AECOPD vs Stable COPD with AUC greater than 0.9.
Conclusion: Numerous plasma metabolites and several metabolic pathways were detected relevant to COPD disease onset or progression. These metabolites may be considered as candidate biomarkers for diagnosis or prognosis of COPD. The perturbed pathways involved in COPD provide clues for further pathological mechanism studies of COPD.
Keywords: metabolomics, lipidomics, COPD, biomarker
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