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人类长寿的情境遗传学:JACC 焦点研讨会

The Contextualized Genetics of Human Longevity: JACC Focus Seminar.

机构信息

Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy; Department of Applied Mathematics, Institute of Information Technology, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod-National Research University, Nizhny Novgorod, Russia.

Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.

出版信息

J Am Coll Cardiol. 2020 Mar 3;75(8):968-979. doi: 10.1016/j.jacc.2019.12.032.

DOI:10.1016/j.jacc.2019.12.032
PMID:32130932
Abstract

The genetics of human longevity has long been studied, and in this regard, centenarians represent a very informative model. Centenarians are characterized by 2 main features: 1) the capability to avoid or postpone the major age-related diseases; and 2) a high level of heterogeneity of their phenotype. The first suggests that longevity and resistance to diseases are mediated by shared mechanisms, the latter that many strategies can be used to become long lived, likely as a result of variable genome-environment interactions. The authors suggest that the complexity of genome-environment interactions must be considered within an evolutionary and ecological perspective and that the concept of "risk allele" is highly context dependent, changing with age, time, and geography. Genes involved in both longevity and cardiovascular diseases, taken as a paradigmatic example of age-related diseases, as well as other emerging topics in genetics of longevity, such as micro-ribonucleic acid (miRNA) genetics, polygenic risk scores, environmental pollutants, and somatic mutations are discussed.

摘要

人类长寿的遗传学研究由来已久,在这方面,百岁老人是一个非常有价值的模型。百岁老人有两个主要特征:1)能够避免或延缓与年龄相关的主要疾病;2)表型高度异质性。第一个特征表明,长寿和对疾病的抵抗力是由共同的机制介导的,后者表明可以使用许多策略来实现长寿,这可能是由于基因组-环境相互作用的变化。作者认为,必须从进化和生态的角度考虑基因组-环境相互作用的复杂性,并且“风险等位基因”的概念高度依赖于上下文,会随着年龄、时间和地理位置的变化而变化。本文以与年龄相关的疾病(如心血管疾病)为例,讨论了与长寿和心血管疾病相关的基因,以及长寿遗传学中的其他新兴主题,如 micro-ribonucleic acid (miRNA) genetics、多基因风险评分、环境污染物和体细胞突变。

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