Giannos Panagiotis, Prokopidis Konstantinos, Forbes Scott C, Celoch Kamil, Candow Darren G, Tartar Jaime L
Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, South Kensington, London SW7 2AZ, UK.
Society of Meta-Research and Biomedical Innovation, London W12 0BZ, UK.
Brain Sci. 2022 Jun 24;12(7):825. doi: 10.3390/brainsci12070825.
Sleep deprivation leads to the deterioration in the physiological functioning of the brain, cognitive decline, and many neurodegenerative diseases, all of which progress with advancing age. Sleep insufficiency and impairments in cognitive function are characterized by progressive neuronal losses in the cerebral cortex. In this study, we analyze gene expression profiles following sleep-deprived murine models and circadian matched controls to identify genes that might underlie cortical homeostasis in response to sleep deprivation. Screening of the literature resulted in three murine () gene expression datasets (GSE6514, GSE78215, and GSE33491) that included cortical tissue biopsies from mice that are sleep deprived for 6 h ( = 15) and from circadian controls that are left undisturbed ( = 15). Cortical differentially expressed genes are used to construct a network of encoded proteins that are ranked based on their interactome according to 11 topological algorithms. The analysis revealed three genes-NFKBIA, EZR, and SGK1-which exhibited the highest multi-algorithmic topological significance. These genes are strong markers of increased brain inflammation, cytoskeletal aberrations, and glucocorticoid resistance, changes that imply aging-like transcriptional responses during sleep deprivation in the murine cortex. Their potential role as candidate markers of local homeostatic response to sleep loss in the murine cortex warrants further experimental validation.
睡眠剥夺会导致大脑生理功能恶化、认知能力下降以及许多神经退行性疾病,所有这些都会随着年龄的增长而加重。睡眠不足和认知功能障碍的特征是大脑皮层中神经元逐渐丧失。在本研究中,我们分析了睡眠剥夺小鼠模型和昼夜节律匹配对照组后的基因表达谱,以确定可能是响应睡眠剥夺的皮层稳态基础的基因。对文献的筛选得到了三个小鼠基因表达数据集(GSE6514、GSE78215和GSE33491),其中包括来自睡眠剥夺6小时的小鼠(n = 15)和未受干扰的昼夜节律对照组(n = 15)的皮层组织活检样本。利用皮层差异表达基因构建编码蛋白质网络,根据11种拓扑算法,基于其相互作用组对这些蛋白质进行排序。分析揭示了三个基因——NFKBIA、EZR和SGK1——它们表现出最高的多算法拓扑显著性。这些基因是大脑炎症增加、细胞骨架畸变和糖皮质激素抵抗的强标志物,这些变化意味着小鼠皮层在睡眠剥夺期间出现类似衰老的转录反应。它们作为小鼠皮层对睡眠丧失的局部稳态反应候选标志物的潜在作用值得进一步的实验验证。