Multi-trait association studies discover pleiotropic loci between Alzheimer\u2019s disease and cardiometabolic traits

William P Bone,Scott M Damrauer,Katherine M Siewert,Derek Klarin,Marylyn D Ritchie,Anupama Jha,Themistocles L Assimes,Kyong-Mi Chang,Philip S Tsao,Benjamin F Voight

doi:10.1186/s13195-021-00773-z

William P Bone, Scott M Damrauer + Show 8 more

Open Access

https://doi.org/10.1186/s13195-021-00773-z

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Abstract

BackgroundIdentification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits.MethodsWe performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes.ResultsWe identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE, the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic.ConclusionOur results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

Highlights

Identification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets
Bivariate genome-wide association studies (GWAS) We used the summary statistics from publicly available single-trait GWAS to perform pairwise metaMANOVA bivariate GWAS between AD [17] and the following cardiometabolic traits: coronary heart disease (CHD) [18], type II diabetes (T2D) [19], systolic blood pressure (SBP) [20], diastolic blood pressure (DBP) [20], body mass index (BMI) [21], waist-hip ratio adjusted for BMI (WHRadjBMI) [22], body fat percentage (BFP) [23], total cholesterol (TC) [24], low-density lipoproteins (LDL) [24], high-density lipoproteins (HDL) [24], and triglycerides (TG) [24] (Table 1 and Additional file 1 - Supplementary Table 1; Availability of data and materials)
To identify candidate causal genes at these three loci, we performed single-tissue-expression quantitative trait loci (eQTL) colocalization analysis between the AD signal at each locus using eQTLs identified by Genotype-Tissue Expression (GTEx) (“Methods”)

Summary

Introduction

Identification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Recent methods and analysis have sought to characterize the extent of the phenomenon throughout the genome [8], quantifying pairwise genetic correlation across a battery of traits [8, 11], exploiting pleiotropy to perform causal inference in the framework of Mendelian randomization [8, 12], or statistically co-localizing association signals across two or more traits [13, 14]. These methods and publicly available GWAS summary statistics enable studies to dissect the shared genetic etiology between AD and cardiometabolic traits. Due to the epidemiological correlation between AD and cardiometabolic traits, coupled with the fact that many cardiometabolic traits are genetically correlated with one another, additional broaderscale pleiotropic studies are warranted, and recently the field has begun to do so [4, 11]

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Conclusion