健康衰老
成功老龄化
透视图(图形)
组学
肌萎缩
疾病
医学
心理学
生物信息学
数据科学
生物
老年学
计算机科学
病理
人工智能
解剖
作者
Nadia Alejandra Rivero-Segura,Omar Yaxmehen Bello‐Chavolla,Oscar Salvador Barrera-Vázquez,Luis Miguel Gutiérrez‐Robledo,Juan Carlos Gómez-Verján
标识
DOI:10.1016/j.arr.2020.101164
摘要
The aging process has been linked to the occurrence of chronic diseases and functional impairments, including cancer, sarcopenia, frailty, metabolic, cardiovascular, and neurodegenerative diseases. Nonetheless, aging is highly variable and heterogeneous and represents a challenge for its characterization. In this sense, intrinsic capacity (IC) stands as a novel perspective by the World Health Organization, which integrates the individual wellbeing, environment, and risk factors to understand aging. However, there is a lack of quantitative and qualitative attributes to define it objectively. Therefore, in this review we attempt to summarize the most relevant and promising biomarkers described in clinical studies at date over different molecular levels, including epigenomics, transcriptomics, proteomics, metabolomics, and the microbiome. To aid gerontologists, geriatricians, and biomedical researchers to understand the aging process through the IC. Aging biomarkers reflect the physiological state of individuals and the underlying mechanisms related to homeostatic changes throughout an individual lifespan; they demonstrated that aging could be measured independently of time (that may explain its heterogeneity) and to be helpful to predict age-related syndromes and mortality. In summary, we highlight the areas of opportunity and gaps of knowledge that must be addressed to fully integrate biomedical findings into clinically useful tools and interventions.
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