Department of Core Facility of Basic Medical Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Appl Biochem Biotechnol. 2024 Apr;196(4):1992-2011. doi: 10.1007/s12010-023-04666-9. Epub 2023 Jul 17.
It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.
普遍认为,昼夜节律紊乱会对健康造成短期或长期的不良影响。虽然之前的许多研究都集中在探索分子机制上,但还没有一种快速、方便、非侵入性的方法来揭示昼夜节律紊乱对健康的影响。在这里,我们采用了一种基于高分辨率质谱的无依赖数据采集(DIA)定量尿蛋白质组学方法,以探索在睡眠剥夺后,尿液是否可以揭示昼夜节律紊乱对健康的影响。睡眠剥夺后,与常规睡眠相比,受试者的收缩压和舒张压均显著升高。定量了 2000 多种蛋白质,它们包含了全身各个器官的特异性蛋白质。与睡眠剥夺后,共获得 177 个显著上调蛋白和 68 个显著下调蛋白。这些差异表达蛋白(DEPs)与多个器官和途径有关,反映了睡眠剥夺的广泛影响。此外,机器学习确定了一组五个 DEPs(CD300A、SCAMP3、TXN2、EFEMP1 和 MYH11),可以有效地区分昼夜节律紊乱。总之,我们的研究结果验证了尿蛋白质组在预测和诊断昼夜节律紊乱引起的变化方面的价值。