• Zhe Wang, Lei Meng, Liang Shen, and Hong-Fang Ji.
• Institute of Biomedical Research, Shandong University of Technology, Zibo, Shandong, China; Shandong Provincial Research Center for Bioinformatic Engineering and Technique, Zibo Key Laboratory of New Drug Development of Neurodegenerative Diseases, School of Life Sciences, Shandong University of Technology, Zibo, Shandong, China.
• Neurobiol. Aging. 2020 Jul 1; 91: 167.e11-167.e19.

AbstractWith the steadily increasing prevalence of Alzheimer's disease (AD) and great difficulties encountered for AD drug development presently, much interest has been devoted to identifying modifiable risk factors to lower the risk of AD, while the causal associations between risk factors and AD remain inconclusive. The present study conducted a comprehensive evaluation of the causal associations between risk factors and AD development by taking the recent advancements of Mendelian randomization (MR). Inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode were used for complementary calculation. A total of 45 risk factors and corresponding studies were covered in the study. This two-sample MR (2SMR) analysis provided a suggestive association between genetically predicted higher years of schooling and reduced risks of AD, and each standard deviation (3.71 years) increased in years of schooling was associated with a 41% reduction in the risk of AD (IVW, OR: 0.59, 95% CI: 0.45-0.77). At the same time, it was genetically predicted that urate might be a risk factor in AD, and it was found that each standard deviation increase in urate levels (1.33 mg/dL) was associated with a 0.09-fold increase in the risk of AD (IVW, OR: 1.09, 95% CI: 1.01-1.18). To summarize, the 2SMR analysis indicated a suggestive association between genetically predicted higher years of schooling and reduced risks of AD, and between genetically predicted higher urate levels and increased risks of AD. The findings provide useful clues to help combat AD and warrants future studies.Copyright © 2020 Elsevier Inc. All rights reserved.

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