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Serum Metabolomics Analysis Revealed Metabolic Pathways Related to AECOPD Complicated with Anxiety and Depression
Jing Ye1,2, Ping Li1,2, Pengcheng Liu1,2
1Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, People's Republic of China.
Background:
Anxiety and depression are two of the most common comorbidities of COPD, which can directly lead to the number of acute exacerbations and hospitalizations of COPD patients and reduce their quality of life. At present, there are many studies on anxiety and depression in stable COPD, but few studies on anxiety and depression in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients.
Objective:
We aim to explore the changes of serum metabolomics in AECOPD complicated with anxiety and depression and to provide some clues for further understanding its pathogenesis.
Methods:
This is an observational high-throughput experimental study based on retrospective data extraction. Twenty-one AECOPD with anxiety and depressive patients and 17 healthy controls (HCs) were retrospectively enrolled in the Second Affiliated Hospital of Anhui Medical University. Hamilton anxiety scale (HAMA) and Hamilton depression scale (HAMD) for anxiety and depression were used to assess the patients with AECOPD. Untargeted metabolomics analysis was carried out to investigate different molecules in the serum of all participants. General information of all participants, baseline data and clinical measurement data of AECOPD patients were collected. Statistical analysis and bioinformatics analysis were performed to reveal different metabolites and perturbed metabolic pathways.
Results:
A total of 724 metabolites in positive ionization mode and 555 metabolites in negative ionization mode were different in AECOPD patients with anxiety and depression. The 1,279 serum metabolites could be divided into 77 categories. Based on multivariate and univariate analysis, 74 metabolites were detected in positive ionization mode, and 60 metabolites were detected in negative ionization as differential metabolites. The 134 metabolites were enriched in 18 pathways, including biosynthesis of unsaturated fatty acids, aldosterone synthesis and secretion, protein digestion and absorption, ovarian steroidogenesis, long-term depression, retrograde endocannabinoid signaling, and so on.
Conclusion:
This work highlights the key metabolites and metabolic pathways disturbed in AECOPD patients with anxiety and depression. These findings support the use of metabolomics to understand the pathogenic mechanisms involved in AECOPD patients with anxiety and depression.
