Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK; School of Psychology, Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK; National Institute for Health Research (NIHR), Nottingham Biomedical Research Centre, Queen's Medical Centre, Nottingham, UK.
Neurobiol Aging. 2022 Jun;114:1-14. doi: 10.1016/j.neurobiolaging.2022.02.005. Epub 2022 Feb 19.
Numerous studies indicate large heterogeneity in brain ageing, which can be attributed to modifiable lifestyle factors, including sleep. Inadequate sleep has been previously linked to gray (GM) and white (WM) matter changes. However, the reported findings are highly inconsistent. By contrast to previous research independently characterizing patterns of either GM or WM changes, we used here linked independent component analysis (FLICA) to examine covariation in GM, and WM in a group of older adults (n = 50). Next, we employed a novel technique to estimate the brain age delta (difference between chronological and brain age assessed using neuroimaging data) and study its associations with sleep quality and sleep fragmentation, hypothesizing that inadequate sleep accelerates brain ageing. FLICA revealed a number of multimodal components, associated with age, sleep quality, and sleep fragmentation. Subsequently, we show significant associations between brain age delta and inadequate sleep, suggesting 2 years deviation above the chronological age. Our findings indicate sensitivity of multimodal approaches and brain age delta in detecting link between inadequate sleep and accelerated brain ageing.
大量研究表明,大脑老化存在很大的异质性,这可以归因于可改变的生活方式因素,包括睡眠。先前的研究表明,睡眠不足与灰质 (GM) 和白质 (WM) 的变化有关。然而,报告的结果高度不一致。与之前分别描述 GM 或 WM 变化模式的研究不同,我们在这里使用链接独立成分分析 (FLICA) 来检查一组老年人的 GM 和 WM 的协变 (n=50)。接下来,我们采用一种新的技术来估计大脑年龄差 (使用神经影像学数据评估的与实际年龄之间的差异),并研究其与睡眠质量和睡眠碎片化的关联,假设睡眠不足会加速大脑老化。FLICA 揭示了与年龄、睡眠质量和睡眠碎片化相关的多个多模态成分。随后,我们发现大脑年龄差与睡眠不足之间存在显著关联,表明大脑年龄比实际年龄高出 2 年。我们的研究结果表明,多模态方法和大脑年龄差对检测睡眠不足与加速大脑老化之间的联系具有敏感性。