A complex systems approach to aging biology

系统生物学 钥匙(锁) 功能(生物学) 复杂适应系统 认知科学 数据科学 透视图(图形) 弹性(材料科学) 生物 计算机科学 计算生物学 进化生物学 心理学 生态学 人工智能 热力学 物理
作者
Alan A. Cohen,Luigi Ferrucci,Tamás Fülöp,Dominique Gravel,Nan Hao,Andres Kriete,Morgan E. Levine,Lewis A. Lipsitz,Marcel G. M. Olde Rikkert,Andrew D. Rutenberg,Nicholas Stroustrup,Ravi Varadhan
出处
期刊:Nature Aging 卷期号:2 (7): 580-591 被引量:119
标识
DOI:10.1038/s43587-022-00252-6
摘要

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging. The authors discuss how adopting a complex systems perspective is a crucial step in advancing our understanding of the aging process and requires fundamental alteration of the questions being asked and the methods used to answer them.
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