Department of Nephrology, Shanghai Changhai Hospital, Shanghai, P.R. China.
Institute of Neuroscience and Key Laboratory of Molecular Neurobiology of Military of Education, Naval Medical University, Shanghai, P.R. China.
Ren Fail. 2023 Dec;45(1):2190815. doi: 10.1080/0886022X.2023.2190815.
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.
白天过度嗜睡(EDS)与终末期肾病患者的生活质量和全因死亡率有关。本研究旨在确定生物标志物并揭示腹膜透析(PD)患者 EDS 的潜在机制。根据爱泼沃斯嗜睡量表(ESS),将 48 名非糖尿病持续非卧床腹膜透析患者分为 EDS 组和非 EDS 组。采用超高效液相色谱-四极杆飞行时间质谱联用仪(UHPLC-Q-TOF/MS)鉴定差异代谢物。将 27 名(男/女,15/12;年龄,60.1±16.2 岁)ESS≥10 的 PD 患者分配到 EDS 组,而 21 名(男/女,13/8;年龄,57.9±10.1 岁)ESS<10 的 PD 患者定义为非 EDS 组。通过 UHPLC-Q-TOF/MS,发现两组之间有 39 种代谢物存在显著差异,其中 9 种与疾病严重程度有良好的相关性,并进一步分为氨基酸、脂质和有机酸代谢。总共发现了 103 个差异代谢物和 EDS 的重叠靶蛋白。然后,构建了 EDS-代谢物-靶标网络和蛋白质-蛋白质相互作用网络。代谢组学方法与网络药理学的结合为 PD 患者 EDS 的早期诊断和机制提供了新的见解。