Li Panlong, Zhu Xirui, Huang Chun, Tian Shan, Li Yuna, Qiao Yuan, Liu Min, Su Jingjing, Tian Dandan
School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
IBRO Neurosci Rep. 2025 Jan 5;18:148-157. doi: 10.1016/j.ibneur.2025.01.001. eCollection 2025 Jun.
To investigate the impact of obesity on brain structure and cognition using large neuroimaging and genetic data.
Associations between body mass index (BMI), gray matter volume (GMV), whiter matter hyper-intensities (WMH), and fluid intelligence score (FIS) were estimated in 30283 participants from the UK Biobank. Longitudinal data analysis was conducted. Genome-wide association studies were applied to explore the genetic loci associations among BMI, GMV, WMH, and FIS. Mendelian Randomization analyses were applied to further estimate the effects of obesity on changes in the brain and cognition.
The observational analysis revealed that BMI was negatively associated with GMV (r = -0.15, p < 1 10) and positively associated with WMH (r = 0.08, p < 1 10). The change in BMI was negatively associated with the change in GMV (r = -0.04, p < 5 10). Genetic overlap was observed among BMI, GMV, and FIS at SBK1 (rs2726032), SGF29 (rs17707300), TUFM (rs3088215), AKAP6 (rs1051695), IL27 (rs4788084), and SPI1 (rs3740689 and rs935914). The MR analysis provided evidence that higher BMI was associated with lower GMV (β=-1119.12, p = 5.77 ×10), higher WMH (β=42.76, p = 6.37 ×10), and lower FIS (β=-0.081, p = 1.92 ×10).
The phenotypic and genetic association between obesity and aging brain and cognitive decline suggested that weight control could be a promising strategy for slowing the aging brain.
利用大型神经影像学和基因数据研究肥胖对脑结构和认知的影响。
在英国生物银行的30283名参与者中估计体重指数（BMI）、灰质体积（GMV）、白质高信号（WMH）和流体智力得分（FIS）之间的关联。进行纵向数据分析。应用全基因组关联研究来探索BMI、GMV、WMH和FIS之间的基因座关联。应用孟德尔随机化分析进一步估计肥胖对大脑和认知变化的影响。
观察性分析显示，BMI与GMV呈负相关（r = -0.15，p < 1×10），与WMH呈正相关（r = 0.08，p < 1×10）。BMI的变化与GMV的变化呈负相关（r = -0.04，p < 5×10）。在SBK1（rs2726032）、SGF29（rs17707300）、TUFM（rs3088215）、AKAP6（rs1051695）、IL27（rs4788084）和SPI1（rs3740689和rs935914）处观察到BMI、GMV和FIS之间存在基因重叠。孟德尔随机化分析提供的证据表明，较高的BMI与较低的GMV（β = -1119.12，p = 5.77×10）、较高的WMH（β = 42.76，p = 6.37×10）和较低的FIS（β = -0.081，p = 1.92×10）相关。
肥胖与衰老大脑及认知衰退之间的表型和基因关联表明，控制体重可能是延缓大脑衰老的一种有前景的策略。
