University of Sydney, Charles Perkins Centre, Camperdown, New South Wales, 2006, Australia.
University of Sydney, School of Life and Environmental Science, Camperdown, New South Wales, 2006, Australia.
BMC Biol. 2022 Sep 1;20(1):196. doi: 10.1186/s12915-022-01395-z.
Little is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process.
Ageing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don't deviate too much from norms ('homeostatic plateaus'). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space.
Using multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.
关于人类饮食模式的正常变化如何影响衰老过程,我们知之甚少。迄今为止,大多数分析这个问题的方法都使用了一种单维范式,只关注单一营养素对单一结果的影响。也许,我们理解这个问题的能力受到了阻碍,因为营养和衰老的生理学都是高度复杂和多维的,涉及到大量的功能相互作用。在这里,我们将营养的多维几何框架应用于来自 1560 名老年人的四年随访生物衰老数据,以大规模评估营养素摄入与衰老过程的关联。
通过整合血液生物标志物来量化衰老和与年龄相关的内稳态丧失(生理失调)。使用营养的几何框架来模拟饮食的影响,应用于宏量营养素和 19 种微量营养素/营养素亚类。我们观察到了四种广泛的模式:(1)营养素摄入的最佳水平取决于所使用的衰老指标。高蛋白摄入改善/降低了一些衰老参数,而高碳水化合物水平则改善/降低了其他参数;(2)存在非线性关系,中间水平的营养素对许多结果都表现良好(即反对简单的更多/更少更好的观点);(3)对于不太偏离正常水平的营养素摄入模式有广泛的耐受性(即稳态平台)。(4)一种营养素的最佳水平通常取决于另一种营养素的水平(例如,维生素 E 和维生素 C)。更简单的线性/单变量分析方法不足以捕捉到这些关联。我们提出了一个交互式工具来探索高维营养空间中的结果。
使用多维建模技术来测试营养摄入对老年人群生理失调的影响,我们确定了与最小生物衰老相关的特定营养素的关键模式。我们的方法为未来的研究提供了探索营养-衰老全景的路线图。