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Mendelian randomization highlights significant difference and genetic heterogeneity in clinically diagnosed Alzheimer's disease GWAS and self-report proxy phenotype GWAX.

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机构： [1]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China [2]School of Life Science and Technology, Harbin Institute of Technology, Harbin 150080, China [3]Department of Pathology, The Afli‑ated Hospital of Weifang Medical University, Weifang 261053, China [4]Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100069, China [5]Department of Anesthesiology, The Afliated Hospital of Weifang Medical University, Weifang 261053, China [6]Chi‑nese Institute for Brain Research, Beijing, China [7]State Key Laboratory of Medi‑cal Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China [8]Key Laboratory of Cerebral Microcircula‑tion in Universities of Shandong, Department of Neurology, Second Afliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China [9]Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China

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Until now, Mendelian randomization (MR) studies have investigated the causal association of risk factors with Alzheimer's disease (AD) using large-scale AD genome-wide association studies (GWAS), GWAS by proxy (GWAX), and meta-analyses of GWAS and GWAX (GWAS+GWAX) datasets. However, it currently remains unclear about the consistency of MR estimates across these GWAS, GWAX, and GWAS+GWAX datasets.Here, we first selected 162 independent educational attainment genetic variants as the potential instrumental variables (N = 405,072). We then selected one AD GWAS dataset (N = 63,926), two AD GWAX datasets (N = 314,278 and 408,942), and three GWAS+GWAX datasets (N = 388,324, 455,258, and 472,868). Finally, we conducted a MR analysis to evaluate the impact of educational attainment on AD risk across these datasets. Meanwhile, we tested the genetic heterogeneity of educational attainment genetic variants across these datasets.In AD GWAS dataset, MR analysis showed that each SD increase in years of schooling (about 3.6 years) was significantly associated with 29% reduced AD risk (OR=0.71, 95% CI: 0.60-0.84, and P=1.02E-04). In AD GWAX dataset, MR analysis highlighted that each SD increase in years of schooling significantly increased 84% AD risk (OR=1.84, 95% CI: 1.59-2.13, and P=4.66E-16). Meanwhile, MR analysis suggested the ambiguous findings in AD GWAS+GWAX datasets. Heterogeneity test indicated evidence of genetic heterogeneity in AD GWAS and GWAX datasets.We highlighted significant difference and genetic heterogeneity in clinically diagnosed AD GWAS and self-report proxy phenotype GWAX. Our MR findings are consistent with recent findings in AD genetic variants. Hence, the GWAX and GWAS+GWAX findings and MR findings from GWAX and GWAS+GWAX should be carefully interpreted and warrant further investigation using the AD GWAS dataset.© 2022. The Author(s).

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出版当年[2021]版：

大类 | 2 区医学

小类 | 2 区临床神经病学 2 区神经科学

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大类 | 1 区

医学

小类 | 1 区临床神经病学 1 区神经科学

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出版当年[2020]版：

Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES

最新[2023]版：

Q1 CLINICAL NEUROLOGY Q1 NEUROSCIENCES

影响因子： 8 最新[2023版] 8.3 最新五年平均 6.982 出版当年[2020版] 8.076 出版当年五年平均 6.116 出版前一年[2019版] 8.831 出版后一年[2021版]

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第一作者机构： [1]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China

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通讯机构： [4]Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 100069, China [6]Chi‑nese Institute for Brain Research, Beijing, China [8]Key Laboratory of Cerebral Microcircula‑tion in Universities of Shandong, Department of Neurology, Second Afliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian 271000, Shandong, China [9]Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China

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