与老年科学相关的动物模型:生物标志物和生物老化测量的当前趋势和未来展望。

Alessandro Bartolomucci, Alice E Kane, Lauren Gaydosh, Maria Razzoli, Brianah M McCoy, Dan Ehninger, Brian H Chen, Susan E Howlett, Noah Snyder-Mackler
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引用次数: 0

摘要

几个世纪以来,衰老被认为是不可避免和不可改变的。老年科学提供了一个概念框架,将人们的注意力转移到一种新的观点上,即认为衰老是一个活跃的生物过程,个人的生物年龄是一个可改变的实体。在确定生物标志物和测量生物年龄方面已经取得了重大进展,但老年科学方面的知识缺口仍然很多。衰老动物模型是这一视角的重点,它讨论了如何优化实验设计,为生物年龄的转化相关测量指标和生物标志物的开发提供信息并加以完善。我们向该领域提出了一些建议,包括:设计纵向研究,通过重复多层次的行为/社会/分子测定对受试者进行深入的表型分析;需要考虑与所研究物种相关的社会行为变量;最后,评估发病年龄、病变严重程度和死亡年龄的重要性。我们重点介绍了利用机器学习方法整合生物标志物和功能损伤测量的方法,这些方法旨在估算生物年龄以及预测未来的健康衰退和死亡率。我们预计,衰老动物模型的进步不仅对未来的转化地球科学至关重要,而且对医学的下一个篇章也至关重要。
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Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging.

For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.

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