Han Si, Lelieveldt Tom, Sturkenboom Miriam, Biessels Geert Jan, Ahmadizar Fariba
Department of Data Science and Biostatistics, Julius Global Health, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands.
Department of Biomedical Science, University College Utrecht, Utrecht University, 3508 TC Utrecht, The Netherlands.
Biomedicines. 2025 Apr 30;13(5):1095. doi: 10.3390/biomedicines13051095.
: Type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD) are significant global health issues. Epidemiological studies suggest T2DM increases AD risk, though confounding factors and reverse causality complicate this association. This study aims to clarify the causal relationship between T2DM and AD through a systematic review and meta-analysis of Mendelian randomization (MR) studies and a new two-sample MR analysis. : A literature search across major databases was conducted through May 2024 to identify MR studies linking T2DM and AD. Fixed/random-effect models provided pooled odds ratios (ORs) with 95% confidence intervals (CIs), and heterogeneity was assessed with the I statistic. For our MR analysis, we pooled genetic variants from selected studies and analyzed AD outcomes using IGAP, EADB, and UKB databases. Multiple MR methods, including inverse variance weighted (IVW) and pleiotropy-robust approaches, were applied for validation. : Of 271 articles, 8 MR studies were included (sample sizes: 68,905 to 788,989), all from European ancestry. Our meta-analysis found no significant causal link between T2DM and AD (OR = 1.02, 95% CI: 1.00-1.04) with moderate heterogeneity (I = 31.3%). Similarly, our MR analysis using 512 SNPs as instrumental variables showed no significant associations in IGAP, EADB, or UKB data, which is consistent across sensitivity analyses. : This meta-MR and MR analysis revealed no significant causal association between T2DM and AD, indicating that genetic predisposition to T2DM does not appear to causally influence AD risk, though modifiable clinical or environmental aspects of T2DM may still contribute to neurodegenerative processes. Further research should explore other mechanisms linking these conditions.
2型糖尿病（T2DM）和阿尔茨海默病（AD）是重大的全球健康问题。流行病学研究表明T2DM会增加AD风险，尽管混杂因素和反向因果关系使这种关联变得复杂。本研究旨在通过对孟德尔随机化（MR）研究的系统评价和荟萃分析以及一项新的两样本MR分析，阐明T2DM与AD之间的因果关系。
通过检索截至2024年5月的主要数据库来查找将T2DM与AD联系起来的MR研究。固定/随机效应模型提供了具有95%置信区间（CI）的合并优势比（OR），并使用I统计量评估异质性。对于我们的MR分析，我们汇总了所选研究中的基因变异，并使用IGAP、EADB和UKB数据库分析AD结局。应用了多种MR方法，包括逆方差加权（IVW）和多效性稳健方法进行验证。
在271篇文章中，纳入了8项MR研究（样本量：68,905至788,989），所有研究对象均为欧洲血统。我们的荟萃分析发现T2DM与AD之间没有显著的因果联系（OR = 1.02, 95% CI: 1.00 - 1.04），异质性中等（I = 31.3%）。同样，我们使用512个单核苷酸多态性（SNP）作为工具变量的MR分析在IGAP、EADB或UKB数据中均未显示出显著关联，这在敏感性分析中是一致的。
这项荟萃MR和MR分析表明T2DM与AD之间没有显著的因果关联，这表明T2DM的遗传易感性似乎不会因果性地影响AD风险，尽管T2DM可改变的临床或环境因素可能仍会导致神经退行性变过程。进一步的研究应探索将这些疾病联系起来的其他机制。
