Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
University of Minnesota, Minneapolis, MN, USA.
Geroscience. 2021 Feb;43(1):395-408. doi: 10.1007/s11357-021-00325-1. Epub 2021 Feb 5.
Measures of biological age and its components have been shown to provide important information about individual health and prospective change in health as there is clear value in being able to assess whether someone is experiencing accelerated or decelerated aging. However, how to best assess biological age remains a question. We compare prediction of health outcomes using existing summary measures of biological age with a measure created by adding novel biomarkers related to aging to measures based on more conventional clinical chemistry and exam measures. We also compare the explanatory power of summary biological age measures compared to the individual biomarkers used to construct the measures. To accomplish this, we examine how well biological age, phenotypic age, and expanded biological age and five sets of individual biomarkers explain variability in four major health outcomes linked to aging in a large, nationally representative cohort of older Americans. We conclude that different summary measures of accelerated aging do better at explaining different health outcomes, and that chronological age has greater explanatory power for both cognitive dysfunction and mortality than the summary measures. In addition, we find that there is reduction in the variance explained in health outcomes when indicators are combined into summary measures, and that combining clinical indicators with more novel markers related to aging does best at explaining health outcomes. Finally, it is hard to define a set of assays that parsimoniously explains the greatest amount of variance across the range of health outcomes studied here. All of the individual markers considered were related to at least one of the health outcomes.
生物年龄及其组成部分的测量方法已经证明可以提供有关个体健康和健康未来变化的重要信息,因为能够评估某人是否经历加速或减速衰老具有明显的价值。然而,如何最好地评估生物年龄仍然是一个问题。我们将使用现有的生物年龄综合测量方法来预测健康结果,并将其与通过添加与衰老相关的新型生物标志物来创建的测量方法进行比较,这些标志物是基于更传统的临床化学和检查测量方法的。我们还比较了综合生物年龄测量方法与用于构建这些方法的个体生物标志物的解释能力。为了实现这一目标,我们研究了生物年龄、表型年龄和扩展生物年龄以及五组个体生物标志物在多大程度上可以解释与衰老相关的四个主要健康结果的变异性,这些结果是在美国一个大型的、具有全国代表性的老年人群体中进行的。我们的结论是,不同的加速衰老综合测量方法在解释不同的健康结果方面表现更好,而且与综合测量方法相比,年龄对认知功能障碍和死亡率的解释能力更强。此外,我们发现,当指标组合成综合指标时,健康结果的解释方差会减少,并且将临床指标与更多与衰老相关的新型标志物相结合可以更好地解释健康结果。最后,很难定义一组检测方法能够简洁地解释这里研究的健康结果范围内的最大方差。考虑的所有个体标志物都与至少一种健康结果有关。