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. 2021 Jan:97:18-27.
doi: 10.1016/j.neurobiolaging.2020.09.019. Epub 2020 Oct 1.

Mendelian randomization integrating GWAS and mQTL data identified novel pleiotropic DNA methylation loci for neuropathology of Alzheimer's disease

Di Liu  1 , Youxin Wang  1 , Huiquan Jing  1 , Qun Meng  2 , Jingyun Yang  3
Affiliations

Mendelian randomization integrating GWAS and mQTL data identified novel pleiotropic DNA methylation loci for neuropathology of Alzheimer's disease

Di Liu et al. Neurobiol Aging. 2021 Jan.

Abstract

The pathogenesis of Alzheimer's disease (AD) remains largely unclear. Exploring the genetic/epigenetic loci showing pleiotropic association with the neuropathologies of AD may greatly enhance understanding of the mechanisms underlying the development of AD. In this study, using data from the Religious Orders Study and the Rush Memory and Aging Project, we undertook a Mendelian randomization approach integrating genome-wide association studies (GWASs) and DNA methylation quantitative trait locus data to explore pleiotropic epigenetic loci for AD neuropathologies, including amyloid-β (Aβ) load and tau-containing neurofibrillary tangle density. We performed GWASs of DNA methylation in brain tissues from 592 participants and mapped 60,595 cis-SNP-CpG pairs after correction for multiple testing. By linking cis-DNA methylation quantitative trait locus with GWAS results for Aβ load and tau tangles, we identified 47 CpGs showing pleiotropic association with Aβ load by the Mendelian randomization analysis. We then used gene expression data from 537 individuals and performed quantitative trait methylation analysis. We found that 18 of the 47 CpGs were in cis associated with 25 mRNAs/genes, comprising 41 unique CpG-mRNA/gene pairs. Our findings shed light on the role of DNA methylation in the pathogenesis of Aβ.

Keywords: Alzheimer's disease; DNA methylation; Mendelian randomization; Neuropathology; Quantitative trait loci; Quantitative trait methylation.

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Conflict of interest statement

Disclosure

The authors have no conflict of interest to report.

Figures

Figure 1.
Figure 1.. The flow chart of bioinformatical/statistical analysis.
ROS, Religious Orders Study; MAP, Rush Memory and Aging Project; SNP, single-nucleotide polymorphism; mQTL, DNA methylation quantitative trait loci; FDR, false discovery rate; MR, Mendelian randomization.
Figure 2.
Figure 2.. Chicago plot for the association between cis-mQTLs and DNA methylation.
We identified a total of 370,257,499 cis- mQTL SNPs at P < 0.05 using the R package “MatrixEQTL”. In the plot, we only kept the cis- mQTL SNP having the smallest P-value for a CpG in the cases of multiple SNPs associated with the same CpG. Each point represents the association of a cis- mQTL SNP. The horizontal coordinate represents the location of a CpG within the chromosome, and the vertical coordinate is –log10 (P-value) if the association is positive and log10 (P-value) if the association is negative. The dashed line corresponds to the significance level using Bonferroni correction (1.35×10−10).
Figure 3.
Figure 3.. Forest plot for the estimated MR effects and 95% confidence intervals for the casual associations of CpGs with Aβ load.
Analyses were performed using the R package “MendelianRandomization”, and multiple testings were adjusted using false discovery rate. MR, Mendelian randomization; CI, confidence interval
Figure 4.
Figure 4.. Functional enrichment and gene concept network analysis.
A) Enriched GO terms based on genes harboring the identified CpGs; B) Concept network analysis of the genes harboring the identified CpGs; C) Enriched GO terms based on cis-associated genes; and D) Concept network analysis of the cis associated genes. GO, gene ontology
See this image and copyright information in PMC

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