State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China; email:
Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
Annu Rev Biomed Data Sci. 2023 Aug 10;6:129-152. doi: 10.1146/annurev-biodatasci-020722-120642. Epub 2023 Apr 26.
Organismal aging exhibits wide-ranging hallmarks in divergent cell types across tissues, organs, and systems. The advancement of single-cell technologies and generation of rich datasets have afforded the scientific community the opportunity to decode these hallmarks of aging at an unprecedented scope and resolution. In this review, we describe the technological advancements and bioinformatic methodologies enabling data interpretation at the cellular level. Then, we outline the application of such technologies for decoding aging hallmarks and potential intervention targets and summarize common themes and context-specific molecular features in representative organ systems across the body. Finally, we provide a brief summary of available databases relevant for aging research and present an outlook on the opportunities in this emerging field.
生物体的衰老在不同组织、器官和系统的不同细胞类型中表现出广泛的特征。单细胞技术的进步和丰富数据集的产生,使科学界有机会以前所未有的范围和分辨率来解码这些衰老特征。在这篇综述中,我们描述了使细胞水平数据解释成为可能的技术进步和生物信息学方法。然后,我们概述了这些技术在解码衰老特征和潜在干预靶点中的应用,并总结了在身体代表性器官系统中常见的主题和特定于背景的分子特征。最后,我们简要总结了与衰老研究相关的可用数据库,并展望了这个新兴领域的机遇。