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Serum metabolic alterations in peritoneal dialysis patients with excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambul...

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Detalles Bibliográficos
Autores principales: Chen, Wei, Xu, Ying, Li, Zheng-Hao, Si, Ya-Chen, Wang, Hai-Yan, Bian, Xiao-Lu, Li, Lu, Guo, Zhi-Yong, Lai, Xue-Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116928/
https://www.ncbi.nlm.nih.gov/pubmed/37051665
http://dx.doi.org/10.1080/0886022X.2023.2190815
Descripción
Sumario:Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS–metabolite–target network and the protein–protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.