Aging biomarkers and the brain.

Aging biomarkers and the brain.
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DOI:
10.1016/j.semcdb.2021.01.003
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发表时间:
2021-08
影响因子:
7.3
通讯作者:
Levine ME
Levine ME
中科院分区:
生物学2区
文献类型:
--
作者:
Higgins-Chen AT;Thrush KL;Levine ME

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量化生物衰老对于理解为什么衰老是发病率和死亡率的主要驱动因素以及评估对抗病理性衰老的新疗法至关重要。在过去的十年中,使用各种数据类型和建模技术开发了许多与大脑衰老相关的生物标志物。衰老涉及许多相互关联的过程,因此需要许多互补的生物标志物,每一个都捕捉衰老生物学的不同部分。在这里,我们提出了一个层次框架,强调这些生物标志物是如何相互关联的,以及潜在的生物过程。我们回顾了在脑衰老的背景下研究最多的测量方法:表观遗传时钟、蛋白质组时钟和神经成像年龄预测因子。许多研究将这些生物标志物与认知、心理健康、大脑结构和衰老过程中的病理联系起来。我们还深入研究了解释这些生物标志物的挑战和复杂性,并提出了进一步创新的领域。最终,需要对这些生物标志物有一个强有力的机制理解,以有效地干预衰老过程,预防和治疗与年龄相关的疾病。
Quantifying biological aging is critical for understanding why aging is the primary driver of morbidity and mortality and for assessing novel therapies to counter pathological aging. In the past decade, many biomarkers relevant to brain aging have been developed using various data types and modeling techniques. Aging involves numerous interconnected processes, and thus many complementary biomarkers are needed, each capturing a different slice of aging biology. Here we present a hierarchical framework highlighting how these biomarkers are related to each other and the underlying biological processes. We review those measures most studied in the context of brain aging: epigenetic clocks, proteomic clocks, and neuroimaging age predictors. Many studies have linked these biomarkers to cognition, mental health, brain structure, and pathology during aging. We also delve into the challenges and complexities in interpreting these biomarkers and suggest areas for further innovation. Ultimately, a robust mechanistic understanding of these biomarkers will be needed to effectively intervene in the aging process to prevent and treat age-related disease.
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发表时间: 1997-05-01
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发表时间: 2020-10-20
期刊: Aging
影响因子: --
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