Sheng Jie, Liu Jundong, Chan Kei Hang Katie
Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Department of Electrical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Front Genet. 2022 Jun 21;13:833734. doi: 10.3389/fgene.2022.833734. eCollection 2022.
Gestational diabetes mellitus (GDM), heart disease (HD) and high body mass index (BMI) are strongly related to Alzheimer's disease (AD) dementia in pregnant women. Therefore, we aimed to determine the total effects of GDM, heart disease, and high BMI on maternal AD dementia. We used data from the genome-wide association studies of European populations including more than 30,000 participants. We performed two-sample Mendelian randomization (MR) and multivariable MR (MVMR) to systematically estimate the direct effects of GDM, HD, and high BMI on maternal AD and dementia. Multiple sensitivity analyses involving classical MR approaches and expanded MR-pleiotropy residual sum and outlier analysis. In two-sample MR analysis, the inverse-variance weighted method in our study demonstrated no significant causality between GDM and maternal dementia ( = -0.006 ± 0.0026, = 0.82). This method also revealed no significant causality between high BMI and maternal dementia ( = 0.0024 ± 0.0043, = 0.57), and it was supported by the MR-Egger regression results, which showed no causal effect of high BMI on maternal Alzheimer's disease and dementia ( = 0.0027 ± 0.0096, = 0.78). The IVW method showed no significant causal relationship between maternal HD and maternal Alzheimer's disease and dementia ( = -0.05 ± 0.0042, = 0.117) and MR-Egger regression analysis gave a similar result ( = -0.12 ± 0.0060, = 0.079). In MVMR analysis, we found no significant causal relationship between GDM, high BMI, or HD and maternal Alzheimer's disease and dementia ( = 0.94, 0.82, and 0.13, respectively). Thus, the MVMR estimates were consistent with our results from the two-sample MR analysis. We confirmed that these results showed no horizontal pleiotropy and enhanced the robustness of our results through multiple sensitivity analyses. In two-sample MR analysis, we found no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. These results differed from previous observational studies showing HD is a significant predictor of dementia. MVMR analysis supported no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. Sensitivity analysis broadly increased the robustness of two-sample MR and MVMR analysis results.
妊娠期糖尿病（GDM）、心脏病（HD）和高体重指数（BMI）与孕妇患阿尔茨海默病（AD）痴呆密切相关。因此，我们旨在确定GDM、心脏病和高BMI对孕产妇AD痴呆的总体影响。我们使用了来自欧洲人群全基因组关联研究的数据，包括30000多名参与者。我们进行了两样本孟德尔随机化（MR）和多变量MR（MVMR），以系统地估计GDM、HD和高BMI对孕产妇AD和痴呆的直接影响。进行了多项敏感性分析，包括经典MR方法以及扩展的MR多效性残差和异常值分析。在两样本MR分析中，我们研究中的逆方差加权法表明GDM与孕产妇痴呆之间无显著因果关系（β = -0.006 ± 0.0026，P = 0.82）。该方法还显示高BMI与孕产妇痴呆之间无显著因果关系（β = 0.0024 ± 0.0043，P = 0.57），MR-Egger回归结果也支持这一点，该结果显示高BMI对孕产妇阿尔茨海默病和痴呆无因果效应（β = 0.0027 ± 0.0096，P = 0.78）。IVW方法显示孕产妇HD与孕产妇阿尔茨海默病和痴呆之间无显著因果关系（β = -0.05 ± 0.0042，P = 0.117），MR-Egger回归分析给出了类似结果（β = -0.12 ± 0.0060，P = 0.079）。在MVMR分析中，我们发现GDM、高BMI或HD与孕产妇阿尔茨海默病和痴呆之间无显著因果关系（P分别为0.94、0.82和0.13）。因此，MVMR估计结果与我们两样本MR分析的结果一致。我们证实这些结果无水平多效性，并通过多项敏感性分析增强了结果的稳健性。在两样本MR分析中，我们发现GDM、HD和高BMI与孕产妇AD和痴呆之间无显著因果关系。这些结果与之前的观察性研究不同，之前的研究表明HD是痴呆的重要预测因素。MVMR分析支持GDM、HD和高BMI与孕产妇AD和痴呆之间无显著因果关系。敏感性分析广泛提高了两样本MR和MVMR分析结果的稳健性。
