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Plenary 1: SEARCHING FOR GENES INFLUENCING SUCCESSFUL BRAIN AGING

机译:全体会议1:寻找影响成功脑老化的基因

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Population projections suggest for the first time in humanhistory that there will be more individuals over the age of 65 years than below the age of 14 years by 2050. Indeed, the percentage of Americans over the age of 65 years is expected to increase from 13% in 2010 to over 20% in 2040. Thus, there is considerable interest in delineating the biological mechanisms that influence age-related changes to facilitate successful aging. As the brain appears to play a pivotal role in aging biology, one promising strategy is to define measures of brain structure and function that index concomitant aging outcomes. However, the biological bases of successful brain aging are poorly understood and there is considerable debate whether aging is intrinsically 'programmed' or incidental to cumulative environmental exposure. Yet, genes likely regulate both the developmental program and the robustness to environmental exposure, suggesting a role for genetic variation in brain aging. To establish phenotypes for gene discovery projects focused on brain aging, we utilized a quantitative gene-by-environment interaction analysis, where age is treated as an environmental factor, in a large cohort of randomly selected pedigrees (n = 1,129 subjects, age range 18-83 years). We found a heritable basis for neurocognitive and gray-matter deterioration as a function of age. In contrast, increasing white-matter incoherence with age appears to be non-genetic. Here we present linkage analyses, using phenotypes identified via the gene x age (G x A) interaction approach, to localize chromosomal regions involved in brain again. Results of these analyses suggest novel quantitative trait loci influencing successful brain aging.
机译:人口预测建议在人类核查中第一次建议,在2050年的14岁以下将有更多的人比低于14岁。实际上,65岁以上的美国人的百分比预计将从13%增加增加2010年在2040年以上20%以上。因此,划定影响年龄相关变化的生物机制有相当大的兴趣,以促进成功的老化。随着大脑在老化生物学中发挥关键作用,一个有希望的策略是确定脑结构的措施和指标伴随老化结果的功能。然而,成功脑老化的生物基础知之甚少,无论老龄化是否有着重要的争论,无论是内在的“编程”或涉及累积环境暴露的偶然。然而,基因可能会调节发展方案和环境暴露的稳健性,表明脑老化遗传变异的作用。为了建立专注于脑老化的基因发现项目的表型,我们利用了定量基因 - 常相互作用分析,其中年龄被视为环境因素,在大型随机选择的章程中(n = 1,129个受试者,年龄范围18 -83岁)。我们为年龄的函数发现了神经认知和灰度恶化的遗传依据。相比之下,随着年龄的增长似乎增加了不相互性的非遗传。在这里,我们呈现联动分析,使用通过基因X年龄(G X A)相互作用方法的表型,以便再次定位脑部涉及脑中​​的染色体区域。这些分析的结果表明了影响成功脑老化的新型定量特质基因座。

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