Lu Alicia, Than Stephanie, Beare Richard, La Hood Alexandra, Collyer Taya Annabelle, Srikanth Velandai, Moran Chris
Peninsula Clinical School, School of Translational Medicine, Monash University, Frankston, VIC, Australia.
Department of Geriatric Medicine, Peninsula Health, Mornington, VIC, Australia.
Front Dement. 2024 Sep 23;3:1456716. doi: 10.3389/frdem.2024.1456716. eCollection 2024.
Low skeletal muscle volume may increase dementia risk through mechanisms affecting brain structure. However, it is unclear whether this relationship exists outside of sarcopenia and/or varies by other factors. We aimed to study the interplay between skeletal muscle volume and factors, such as age, sex, and body mass index (BMI), in explaining brain structure at midlife in a cohort without sarcopenia.
We used abdominal and brain magnetic resonance imaging (MRI) data from a population-based cohort enrolled in the UK Biobank. The following measures were derived: thigh fat-free muscle volume (FFMV), total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), total hippocampal volume (THV), and white matter hyperintensity volume (WMHV). Participants below sex-based grip strength thresholds suggesting probable sarcopenia were excluded. Linear regression analysis was used to study the interaction or mediation effects of age, sex, and BMI on the associations between FFMV and brain volumes.
Data were available for 20,353 participants (median age 64 years, 53% female). We found interactions between thigh FFMV, BMI, and age (all < 0.05). Greater thigh FFMV was associated with better brain volumes in those aged <64 years with normal (TBV: β = 2.0 ml/L, = 0.004; GMV: β = 0.8 ml/L, = 0.04; WMV: β = 1.1 ml/L, = 0.006; WMHV: β = -0.2 ml/L, = 3.7 × 10) or low BMI (TBV: β = 21.2 ml/L, = 0.003; WMV: β = 13.3 ml/L, = 0.002, WMHV: β = -1.1 ml/L, = 0.04).
Greater thigh muscle volume correlates with better brain volumes at midlife in people without sarcopenia, but this relationship weakens with greater age and BMI. Further study is required to investigate the underlying mechanisms to understand which components of body composition are potentially modifiable risk factors for dementia.
低骨骼肌量可能通过影响脑结构的机制增加痴呆风险。然而，尚不清楚这种关系在肌少症之外是否存在和/或是否因其他因素而异。我们旨在研究骨骼肌量与年龄、性别和体重指数（BMI）等因素之间的相互作用，以解释无肌少症队列中年期的脑结构。
我们使用了英国生物银行中一个基于人群队列的腹部和脑部磁共振成像（MRI）数据。得出了以下测量值：大腿无脂肪肌肉量（FFMV）、全脑体积（TBV）、灰质体积（GMV）、白质体积（WMV）、海马总体积（THV）和白质高信号体积（WMHV）。排除基于性别握力阈值提示可能存在肌少症的参与者。采用线性回归分析来研究年龄、性别和BMI对FFMV与脑体积之间关联的交互作用或中介作用。
共有20353名参与者的数据可用（中位年龄64岁，53%为女性）。我们发现大腿FFMV、BMI和年龄之间存在交互作用（均P<0.05）。在年龄<64岁且BMI正常（TBV：β=2.0 ml/L，P=0.004；GMV：β=0.8 ml/L，P=0.04；WMV：β=1.1 ml/L，P=0.006；WMHV：β=-0.2 ml/L，P=3.7×10⁻⁴）或BMI较低（TBV：β=21.2 ml/L，P=0.003；WMV：β=13.3 ml/L，P=0.002，WMHV：β=-1.1 ml/L，P=0.04）的人群中，大腿FFMV越大与脑体积越好相关。
在无肌少症的人群中，中年时大腿肌肉量越大与脑体积越好相关，但这种关系会随着年龄和BMI的增加而减弱。需要进一步研究以探究潜在机制，从而了解身体成分的哪些组成部分可能是痴呆的可改变危险因素。
