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. 2022 Jul 22:16:880105.
doi: 10.3389/fnins.2022.880105. eCollection 2022.

Assessing the Association Between Lead Pollution and Risk of Alzheimer's Disease by Integrating Multigenomics

Chunying Li  1   2 , Yuwei Zhang  1 , Jiandong Liang  3 , Changyan Wu  3 , Xiao Zou  1
Affiliations

Assessing the Association Between Lead Pollution and Risk of Alzheimer's Disease by Integrating Multigenomics

Chunying Li et al. Front Neurosci. .

Abstract

Alzheimer's disease (AD) is a life-threatening neurodegenerative disease of the elderly. In recent observations, exposure to heavy metals environmental may increase the risk of AD. However, there are few studies on the causal relationship between heavy metal exposure and AD. In this study, we integrated two large-scale summaries of AD genome-wide association study (GWAS) datasets and a blood lead level GWAS dataset and performed the two-sample Mendelian randomization analysis to assess the causality of blood lead level and AD risk. The results showed that there is a significantly positive causality between blood lead level and AD risk both in the inverse-variance weighted (IVW) model and the weighted median estimator (WME) model. An independent additional verification also reached a consistent conclusion. These findings further confirm the conclusions of previous studies and improve the understanding of the relationship between AD pathogenesis and the toxicity of lead in environmental pollution.

Keywords: Alzheimer’s disease; Mendelian randomization; blood lead; heavy metal pollution; multigenomics.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The Mendelian randomization (MR) analysis for the causality of blood lead level and Alzheimer’s disease (AD) risk. (A) The forest plot represents the causal effect of blood lead level on AD using the Wald ratio. The Mendelian randomization using singly each SNP and all SNPs by the WME and IVW models are shown in it. (B) The method comparison plot shows the SNP effects on AD against SNP effects on blood lead levels in the WME and IVW models. Each method has a different line, and the slope of the line represents the causal association. Panels (C,D) show the forest plot of causal effect and the method comparison plot of WME and IVW models for the EFO_0000249 dataset, respectively.
FIGURE 2
FIGURE 2
The heterogeneity test and sensitivity analysis of the Mendelian randomization analysis. (A) Funnel plot to assess heterogeneity. Asymmetry and large spread suggest a high heterogeneity. (B) The forest plot of leave-one-out sensitivity analysis shows if an association is being disproportionately influenced by a single SNP. Each black point represents the Mendelian randomization analysis excluding that particular SNP. Panels (C,D) show the results of the heterogeneity test and leave-one-out sensitivity analysis for the EFO_0000249 dataset, respectively.
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