Department of Pharmacology, College of Basic Medical Sciences, Jilin University, 126 Xinmin Street, Changchun 130012, China.
School of Nursing, Jilin University, 965 Xinjiang Street, Changchun 130012, China.
Int J Mol Sci. 2023 Aug 31;24(17):13531. doi: 10.3390/ijms241713531.
Currently studies on the correlation between obesity and Alzheimer's disease (AD) are still unclear. In addition, few indicators have been used to evaluate obesity, which has failed to comprehen-sively study the correlations between body fat mass, body fat distribution, and AD. Thus, this study innovatively utilized bioinformatics and Mendelian randomization (MR) to explore the key targets of obesity-induced AD, and investigate the causal associations between different types of obesity and key targets. The common targets of obesity and AD were screened using the GeneCards database, and functional and pathway annotations were carried out, thereby revealing the key target. MR analysis was conducted between body anthropometric indexes of obesity and the key target using an IVW model. Bioinformatics analysis revealed Apolipoprotein E (APOE) as the key target of obesity-induced AD. MR results showed that body mass index (BMI) had a negative causal association with APOE2, while body fat percentage (BFP) and trunk fat percentage (TFP) had no significant causal association with APOE2; BMI, BFP, and TFP had a negative causal association with APOE3, and none had any significant causal association with APOE4. In conclusion, there is a correlation between obesity and AD, which is mainly due to the polymorphism of the APOE gene rather than adipose tissue distribution. APOE3 carriers may be more susceptible to obesity, while the risk of AD caused by APOE2 and APOE4 may not be induced by obesity. This study sheds new light on current disputes. At the same time, it is suggested to regulate the body fat mass of APOE3 carriers in the early stage, and to reduce the risk of AD.
目前肥胖症与阿尔茨海默病(AD)之间的相关性研究仍不明确。此外,评估肥胖的指标较少,无法全面研究体脂量、体脂分布与 AD 之间的相关性。因此,本研究创新性地采用了生物信息学和孟德尔随机化(MR)方法来探讨肥胖导致 AD 的关键靶点,并研究不同类型肥胖与关键靶点之间的因果关系。使用 GeneCards 数据库筛选肥胖症和 AD 的共同靶点,并进行功能和通路注释,从而揭示关键靶点。采用 IVW 模型对肥胖症体测指标与关键靶点之间进行 MR 分析。生物信息学分析表明载脂蛋白 E(APOE)是肥胖导致 AD 的关键靶点。MR 结果表明,体质指数(BMI)与 APOE2 呈负相关,而体脂肪百分比(BFP)和躯干脂肪百分比(TFP)与 APOE2 无显著的因果关联;BMI、BFP 和 TFP 与 APOE3 呈负相关,与 APOE4 均无显著的因果关联。综上所述,肥胖与 AD 之间存在相关性,这主要归因于 APOE 基因的多态性,而不是脂肪组织分布。APOE3 携带者可能更容易受到肥胖的影响,而 APOE2 和 APOE4 引起的 AD 风险可能不是由肥胖引起的。本研究为当前的争议提供了新的视角。同时,建议在早期调节 APOE3 携带者的体脂肪量,降低 AD 风险。