Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

Abstract

Background: Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

Methods: A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

Results: Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

Conclusions: This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

Keywords: ALZHEIMER'S DISEASE; COGNITION; GENETICS; MEDICINE.

Figure 1

Overview of this study. First, we identified druggable genes. Second, a two-sample MR was conducted to estimate the causal effects of blood and brain druggable eQTLs on AD. We then performed colocalisation analyses to verify the robustness of the expressions’ IVs, and a repeat and validation study was conducted. Third, we aimed to identify AD biomarkers with GWAS data available. Subsequently, we evaluated the causal relationship of prior expressions on AD biomarkers to explore possible mechanisms. Finally, we assessed the potential side effects of targeting the prior druggable gene products for AD treatment via a phenome-wide MR. AD, Alzheimer’s disease; CSF, cerebrospinal fluid; DGIdb, Drug–Gene Interaction Database; eQTL, expression quantitative trait locus; FA, fractional anisotropy; FDR, false discovery rate; GWAS, genome-wide association study; IV, instrumental variable; MD, mean diffusivity; MR, Mendelian randomisation; TSS, transcriptional start site.

Figure 2

MR and colocalisation analysis results in the discovery phase. (A) Forest plot for MR results between brain eQTL and AD. (B) FDR and value of colocalisation analysis for significant MR result genes. (C) Forest plot for the MR result between blood eQTL and AD. The fluorescent background and bold font (A,C) indicate that these genes are significant in both tissues. The left ring (B) represents genes in the brain, and the right ring represents genes in the blood. AD, Alzheimer’s disease; eQTL, expression quantitative trait locus; FDR, false discovery rate; MR, Mendelian randomisation.

Figure 3

Manhattan plot for phenome-wide MR results of blood EPHX2, SERPINB1 and SIGLEC11. Note: ordinate representation of the p value in phenome-wide MR results. A dot represents a disease trait, and different colours represent the MR result of different expressions. EPHX2, epoxide hydrolase 2; MR, Mendelian randomisation.