当年龄不仅仅是一个数字:神经退行性疾病中大脑衰老的加速

Elena Doering, Merle C. Hoenig, James H. Cole, Alexander Drzezga
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摘要

大脑老化的特点是在不同的水平上有害的过程,包括细胞/分子和结构/功能的变化。许多这些过程可以通过现代神经成像程序在体内进行评估,允许以不同的方式量化脑年龄。大脑年龄可以通过合适的机器学习策略来测量。一个人测量到的大脑年龄和实际年龄之间的偏差(两个方向)被称为大脑年龄差距(BAG)。尽管这些方法定义的脑年龄通常与一个人的实际年龄有关,但这种关系并不总是平行的,个体之间也可能存在显著差异。重要的是,尽管神经退行性疾病并不等同于加速大脑衰老,但它们可能会引起与老年人相似的大脑变化,这可以通过大脑年龄模型来捕捉。相反,健康的大脑衰老可能涉及抵抗或延迟大脑神经退行性病理的发作。这篇继续教育文章阐述了如何计算BAG,并探讨了BAG是如何从不同的神经成像模式中衍生出来的,为与年龄相关的神经退行性疾病的表型提供了独特的见解。来自t1加权MRI的结构袋有望作为监测神经退行性疾病进展的表型生物标志物,特别是在阿尔茨海默病中。此外,分子成像的代谢袋和分子袋,功能性MRI的功能性袋,弥散性MRI的微结构袋,虽然研究较少,但每种都可以为特定的大脑衰老过程及其与健康衰老的偏差提供不同的视角。我们认为,当基于适当的模式时,BAG估计可能对疾病监测有用,并提供有关治疗干预影响的有趣见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When Age Is More Than a Number: Acceleration of Brain Aging in Neurodegenerative Diseases

Aging of the brain is characterized by deleterious processes at various levels including cellular/molecular and structural/functional changes. Many of these processes can be assessed in vivo by means of modern neuroimaging procedures, allowing the quantification of brain age in different modalities. Brain age can be measured by suitable machine learning strategies. The deviation (in both directions) between a person’s measured brain age and chronologic age is referred to as the brain age gap (BAG). Although brain age, as defined by these methods, generally is related to the chronologic age of a person, this relationship is not always parallel and can also vary significantly between individuals. Importantly, whereas neurodegenerative disorders are not equivalent to accelerated brain aging, they may induce brain changes that resemble those of older adults, which can be captured by brain age models. Inversely, healthy brain aging may involve a resistance or delay of the onset of neurodegenerative pathologies in the brain. This continuing education article elaborates how the BAG can be computed and explores how BAGs, derived from diverse neuroimaging modalities, offer unique insights into the phenotypes of age-related neurodegenerative diseases. Structural BAGs from T1-weighted MRI have shown promise as phenotypic biomarkers for monitoring neurodegenerative disease progression especially in Alzheimer disease. Additionally, metabolic and molecular BAGs from molecular imaging, functional BAGs from functional MRI, and microstructural BAGs from diffusion MRI, although researched considerably less, each may provide distinct perspectives on particular brain aging processes and their deviations from healthy aging. We suggest that BAG estimation, when based on the appropriate modality, could potentially be useful for disease monitoring and offer interesting insights concerning the impact of therapeutic interventions.

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