In view of great difficulties in the pathogenesis analysis of Alzheimer’s disease (AD) presently, profiling the modifiable risk factors is crucial for early detection and intervention of AD. However, the causal associations among them have yet to be identified, and the effective integration and application of these data also remain considerable challenges due to the lack of efficient collection and analysis procedures. To address this issue, we performed comprehensive analyses by two-sample Mendelian randomization (2SMR) and established the AlzRiskMR database (https://github.com/SDBMC/RiskFactors2AD). Four 2SMR analysis methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, were used for the complementary calculation to test the reliability of the results. The database currently comprises 1870 sets of data of Genome-Wide Association Studies (GWAS) from the MR-Base and NHGRI-EBI GWAS Catalog database. AlzRiskMR database not only estimates causal associations between modifiable risk factors and AD but also offers a useful and timely resource for early intervention of AD development incidence.

中文翻译：

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AlzRiskMR 数据库：暴露因素对阿尔茨海默病影响的在线数据库。

鉴于目前阿尔茨海默病 (AD) 的发病机制分析存在很大困难，分析可改变的危险因素对于 AD 的早期检测和干预至关重要。然而，它们之间的因果关系尚未确定，由于缺乏有效的收集和分析程序，这些数据的有效整合和应用也仍然是相当大的挑战。为了解决这个问题，我们通过双样本孟德尔随机化（2SMR）进行了综合分析，并建立了 AlzRiskMR 数据库（https://github.com/SDBMC/RiskFactors2AD）。采用逆方差加权（IVW）、MR-Egger、加权中位数和加权模式四种2SMR分析方法进行互补计算，以检验结果的可靠性。该数据库目前包含来自 MR-Base 和 NHGRI-EBI GWAS Catalog 数据库的 1870 组全基因组关联研究 (GWAS) 数据。AlzRiskMR 数据库不仅可以估计可修改的风险因素与 AD 之间的因果关系，而且还为 AD 发生率的早期干预提供了有用和及时的资源。