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英国生物库中体成分模式与心血管疾病和神经退行性疾病风险的关系。

Association Between Body Composition Patterns, Cardiovascular Disease, and Risk of Neurodegenerative Disease in the UK Biobank.

机构信息

From the West China Hospital of Sichuan University (S.X., S.W., Y.Y., J.H., H.Y., Y.Q., Y.Z., J.Z., H.S.), Chengdu, China; and Karolinska Institutet (F.F.), Solna, Sweden.

出版信息

Neurology. 2024 Aug 27;103(4):e209659. doi: 10.1212/WNL.0000000000209659. Epub 2024 Jul 24.

Abstract

BACKGROUND AND OBJECTIVES

Accumulating evidence connects diverse components of body composition (e.g., fat, muscle, and bone) to neurodegenerative disease risk, yet their interplay remains underexplored. This study examines the associations between patterns of body composition and the risk of neurodegenerative diseases, exploring the mediating role of cardiovascular diseases (CVDs).

METHODS

This retrospective analysis used data from the UK Biobank, a prospective community-based cohort study. We included participants free of neurodegenerative diseases and with requisite body composition measurements at recruitment, who were followed from 5 years after recruitment until April 1, 2023, to identify incident neurodegenerative diseases. We assessed the associations between different components and major patterns of body composition (identified by principal component analysis) with the risk of neurodegenerative diseases, using multivariable Cox models. Analyses were stratified by disease susceptibility, indexed by polygenetic risk scores for Alzheimer and Parkinson diseases, genotype, and family history of neurodegenerative diseases. Furthermore, we performed mediation analysis to estimate the contribution of CVDs to these associations. In addition, in a subcohort of 40,790 participants, we examined the relationship between body composition patterns and brain aging biomarkers (i.e., brain atrophy and cerebral small vessel disease).

RESULTS

Among 412,691 participants (mean age 56.0 years, 55.1% female), 8,224 new cases of neurodegenerative diseases were identified over an average follow-up of 9.1 years. Patterns identified as "fat-to-lean mass," "muscle strength," "bone density," and "leg-dominant fat distribution" were associated with a lower rate of neurodegenerative diseases (hazard ratio [HR] = 0.74-0.94) while "central obesity" and "arm-dominant fat distribution" patterns were associated with a higher rate (HR = 1.13-1.18). Stratification analysis yielded comparable risk estimates across different susceptibility groups. Notably, 10.7%-35.3% of the observed associations were mediated by CVDs, particularly cerebrovascular diseases. The subcohort analysis of brain aging biomarkers corroborated the findings for "central obesity," "muscle strength," and "arm-dominant fat distribution" patterns.

DISCUSSION

Our analyses demonstrated robust associations of body composition patterns featured by "central obesity," "muscle strength," and "arm-dominant fat distribution" with both neurodegenerative diseases and brain aging, which were partially mediated by CVDs. These findings underscore the potential of improving body composition and early CVD management in mitigating risk of neurodegenerative diseases.

摘要

背景与目的

越来越多的证据表明,身体成分的不同组成部分(如脂肪、肌肉和骨骼)与神经退行性疾病的风险有关,但它们之间的相互作用仍未得到充分探索。本研究旨在探讨身体成分模式与神经退行性疾病风险之间的关联,并探讨心血管疾病(CVDs)的中介作用。

方法

本回顾性分析使用了英国生物银行(UK Biobank)的数据,这是一项前瞻性的社区为基础的队列研究。我们纳入了在招募时无神经退行性疾病且有必要的身体成分测量值的参与者,并在招募后 5 年开始随访,直至 2023 年 4 月 1 日,以确定新发神经退行性疾病。我们使用多变量 Cox 模型评估了不同成分和主要身体成分模式(通过主成分分析确定)与神经退行性疾病风险之间的关联。分析按阿尔茨海默病和帕金森病的多基因风险评分、基因型和神经退行性疾病家族史等疾病易感性进行分层。此外,我们进行了中介分析,以估计 CVDs 对这些关联的贡献。此外,在一个包含 40790 名参与者的亚队列中,我们研究了身体成分模式与大脑老化生物标志物(即脑萎缩和脑小血管疾病)之间的关系。

结果

在 412691 名参与者(平均年龄 56.0 岁,55.1%为女性)中,平均随访 9.1 年后,有 8224 例新发神经退行性疾病。被确定为“脂肪与瘦体重”、“肌肉力量”、“骨密度”和“腿部主导性脂肪分布”的模式与较低的神经退行性疾病发生率相关(风险比 [HR] = 0.74-0.94),而“中心性肥胖”和“手臂主导性脂肪分布”模式与较高的发生率相关(HR = 1.13-1.18)。分层分析在不同的易感组中得出了类似的风险估计值。值得注意的是,观察到的关联中有 10.7%-35.3%是通过 CVDs 介导的,特别是脑血管疾病。大脑老化生物标志物的亚队列分析证实了“中心性肥胖”、“肌肉力量”和“手臂主导性脂肪分布”模式的发现。

讨论

我们的分析表明,以“中心性肥胖”、“肌肉力量”和“手臂主导性脂肪分布”为特征的身体成分模式与神经退行性疾病和大脑老化均有显著关联,部分通过 CVDs 介导。这些发现强调了改善身体成分和早期 CVD 管理以降低神经退行性疾病风险的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/02b7/11314951/e14bd747698e/WNL-2023-007357f1.jpg

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