Exploring the link between body physiology and cognition: the role of the brain and aging.

IF 13 Q2 GERIATRICS & GERONTOLOGY
Irina Buianova, Narun Pat
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引用次数: 0

Abstract

Epidemiological links between cognition and body physiology in aging are well established, but their strength and drivers remain unclear. Which physiological systems - from body composition to cardiovascular, pulmonary, renal, hepatic, immune, metabolic, and musculoskeletal - best predict cognition, and to what extent are cognition-body associations linked to brain variation across aging? We examined 19 physiological phenotypes alongside three neuroimaging modalities in over 30,000 UK Biobank participants. Machine learning models integrating body measures predicted cognition at r = 0.4, demonstrating a cognition-body covariation at 16%. Body composition and bone health emerged as the strongest predictors. Notably, 85.1% of cognition-body covariance overlapped with neuroimaging, especially white matter features. Moreover, 71.7% of cognition-age covariance was jointly shared with neuroimaging and physiology, and 96.8% was shared with either brain or body markers, or their overlap. Together, these findings clarify how body physiology and brain structure and function covary with cognitive aging.

探索身体生理和认知之间的联系:大脑和衰老的作用。
认知和衰老的身体生理之间的流行病学联系已经确立,但其强度和驱动因素尚不清楚。哪些生理系统——从身体组成到心血管、肺、肾、肝、免疫、代谢和肌肉骨骼——能最好地预测认知,以及认知-身体关联在多大程度上与衰老过程中的大脑变异有关?我们在30,000多名英国生物银行参与者中检查了19种生理表型和三种神经成像模式。整合身体测量的机器学习模型预测认知的r = 0.4,表明认知-身体协变为16%。身体成分和骨骼健康是最强的预测因子。值得注意的是,85.1%的认知-体协方差与神经影像学重叠,尤其是白质特征。此外,71.7%的认知-年龄协方差与神经影像学和生理学共同共享,96.8%的认知-年龄协方差与大脑或身体标记或它们的重叠共同共享。总之,这些发现阐明了身体生理和大脑结构和功能是如何随认知衰老而变化的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.90
自引率
0.00%
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