Gout and the risk of Alzheimer′s disease: A Mendelian randomization study

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Abstract

Objective: This study aimed to examine whether gout is causally associated with Alzheimer's disease. Methods: I used the publicly available summary statistics datasets of three genome-wide association studies (GWASs) on gout as the exposure dataset and meta-analysis results of four GWAS datasets consisting of 17 008 cases with Alzheimer's disease and 37 154 controls of European descent as the outcome dataset. The data were subjected to 2-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Results: I selected seven independent single nucleotide polymorphisms (SNPs) from gout GWASs as instrumental variables (IVs) to improve inference. These SNPs were located at MAP3K11 (rs10791821), SLC2A9 (rs11722228, rs734553), GCKR (rs1260326), ABCG2 (rs2231142, rs2728125), and CNIH-2 (rs4073582). The IVW data did not support a causal association between gout and Alzheimer's disease (β = 0.013, standard error [SE] = 0.017, P = 0.445). The MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.002, P = 0.654); it also revealed no causal association between gout and Alzheimer's disease (β = −0.013, SE = 0.076, P = 0.870). The weighted median approach yielded similar results (β = 0.004, SE = 0.022, P = 0.846). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants, and the results of “leave-one-out” analysis demonstrated that no single SNP drove the IVW estimate. Conclusions: The MR analysis results did not support a causal association between gout and Alzheimer's disease.

Original languageEnglish
JournalInternational Journal of Rheumatic Diseases
DOIs
Publication statusPublished - 2019 Jan 1

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Gout
Random Allocation
Alzheimer Disease
Mendelian Randomization Analysis
Genome-Wide Association Study
Single Nucleotide Polymorphism
Meta-Analysis
Datasets

Keywords

  • Alzheimer′s disease
  • gout
  • Mendelian randomization

ASJC Scopus subject areas

  • Rheumatology

Cite this

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title = "Gout and the risk of Alzheimer′s disease: A Mendelian randomization study",
abstract = "Objective: This study aimed to examine whether gout is causally associated with Alzheimer's disease. Methods: I used the publicly available summary statistics datasets of three genome-wide association studies (GWASs) on gout as the exposure dataset and meta-analysis results of four GWAS datasets consisting of 17 008 cases with Alzheimer's disease and 37 154 controls of European descent as the outcome dataset. The data were subjected to 2-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Results: I selected seven independent single nucleotide polymorphisms (SNPs) from gout GWASs as instrumental variables (IVs) to improve inference. These SNPs were located at MAP3K11 (rs10791821), SLC2A9 (rs11722228, rs734553), GCKR (rs1260326), ABCG2 (rs2231142, rs2728125), and CNIH-2 (rs4073582). The IVW data did not support a causal association between gout and Alzheimer's disease (β = 0.013, standard error [SE] = 0.017, P = 0.445). The MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.002, P = 0.654); it also revealed no causal association between gout and Alzheimer's disease (β = −0.013, SE = 0.076, P = 0.870). The weighted median approach yielded similar results (β = 0.004, SE = 0.022, P = 0.846). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants, and the results of “leave-one-out” analysis demonstrated that no single SNP drove the IVW estimate. Conclusions: The MR analysis results did not support a causal association between gout and Alzheimer's disease.",
keywords = "Alzheimer′s disease, gout, Mendelian randomization",
author = "Lee, {Young Ho}",
year = "2019",
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doi = "10.1111/1756-185X.13548",
language = "English",
journal = "International Journal of Rheumatic Diseases",
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T1 - Gout and the risk of Alzheimer′s disease

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AU - Lee, Young Ho

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N2 - Objective: This study aimed to examine whether gout is causally associated with Alzheimer's disease. Methods: I used the publicly available summary statistics datasets of three genome-wide association studies (GWASs) on gout as the exposure dataset and meta-analysis results of four GWAS datasets consisting of 17 008 cases with Alzheimer's disease and 37 154 controls of European descent as the outcome dataset. The data were subjected to 2-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Results: I selected seven independent single nucleotide polymorphisms (SNPs) from gout GWASs as instrumental variables (IVs) to improve inference. These SNPs were located at MAP3K11 (rs10791821), SLC2A9 (rs11722228, rs734553), GCKR (rs1260326), ABCG2 (rs2231142, rs2728125), and CNIH-2 (rs4073582). The IVW data did not support a causal association between gout and Alzheimer's disease (β = 0.013, standard error [SE] = 0.017, P = 0.445). The MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.002, P = 0.654); it also revealed no causal association between gout and Alzheimer's disease (β = −0.013, SE = 0.076, P = 0.870). The weighted median approach yielded similar results (β = 0.004, SE = 0.022, P = 0.846). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants, and the results of “leave-one-out” analysis demonstrated that no single SNP drove the IVW estimate. Conclusions: The MR analysis results did not support a causal association between gout and Alzheimer's disease.

AB - Objective: This study aimed to examine whether gout is causally associated with Alzheimer's disease. Methods: I used the publicly available summary statistics datasets of three genome-wide association studies (GWASs) on gout as the exposure dataset and meta-analysis results of four GWAS datasets consisting of 17 008 cases with Alzheimer's disease and 37 154 controls of European descent as the outcome dataset. The data were subjected to 2-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Results: I selected seven independent single nucleotide polymorphisms (SNPs) from gout GWASs as instrumental variables (IVs) to improve inference. These SNPs were located at MAP3K11 (rs10791821), SLC2A9 (rs11722228, rs734553), GCKR (rs1260326), ABCG2 (rs2231142, rs2728125), and CNIH-2 (rs4073582). The IVW data did not support a causal association between gout and Alzheimer's disease (β = 0.013, standard error [SE] = 0.017, P = 0.445). The MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.002, P = 0.654); it also revealed no causal association between gout and Alzheimer's disease (β = −0.013, SE = 0.076, P = 0.870). The weighted median approach yielded similar results (β = 0.004, SE = 0.022, P = 0.846). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants, and the results of “leave-one-out” analysis demonstrated that no single SNP drove the IVW estimate. Conclusions: The MR analysis results did not support a causal association between gout and Alzheimer's disease.

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