Lipid associated polygenic enrichment in Alzheimer’s disease

Abstract

Cardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimer's disease (AD) pathogenesis. Beyond the ε 4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), lowdensity (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimer's risk.

Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

“…SMC4 is known to inhibit cellular senescence in replicating cells [61,62]. Additional eQTL colocalization results for IEAA include CD46, a regulator of the complement system and T-cell function [63,64], and the lipid transporter gene ATP8B4, which contains variants that have been reported in relation to centenarian status in Italians and Alzheimer's disease [65,66].…”

“…We did not limit our analysis to any particular phenotype class amongst the Mendelian disease genes but looked for enrichment of any disease processes found to be strongly linked to genes in the GWAS loci. MendelVar analysis was run using intervals based on ±0.5 Mbp window around the lead SNPs using the 1000 Genomes EUR population as LD reference [66]. Inside MendelVar, INRICH was run in "target" enrichment mode, with the target gene set filter set at minimum 5 (-i option) and maximum of 20000 (-j option), and minimum observed threshold of 2 (-z option) [77].…”

Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits

“…To performed a locus discovery analysis we performed a bivariate GWAS between AD and each cardiometabolic trait (Table S4). To identify loci that were both pleiotropic and novel, we required the bivariate GWAS lead SNP had r 2 < 0.2 in 1kG EUR and was greater than 500 KB away from all known single-trait associated loci for AD or the cardiometabolic trait being tested, as well as any loci from previous pleiotropic GWAS between the two traits 4,35 . Additionally, each locus needed to have at least a nominal single trait association with both traits, so we required an AD P-value < 5x10 -3 and a cardiometabolic trait P-value < 5x10 -3 ( Figure 1).…”

“…Studies have consistently found a positive epidemiological correlation between Alzheimer's disease (AD) and cardiometabolic traits, yet the biological mechanisms behind this correlation is not well understood [1][2][3][4] . A leading hypothesis is that this correlation is due to shared genetic influence, or pleiotropy, between AD and cardiometabolic traits 4 . By identifying pleiotropic loci between these traits, we can (i) identify new therapeutic targets or opportunities for drug repurposing, (ii) predict potential side effects, and (iii) better understand the etiology of these complex traits.…”

“…These methods and publicly available GWAS summary statistics enable studies to dissect the shared genetic etiology between AD and cardiometabolic traits 8,12 . 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 broader-scale pleiotropic studies are warranted, and recently the field has begun to do so 4,16 . Statistical methods for detecting pleiotropy use the definition of a single locus associated with two or more traits, and these methods are generally intended to detect loci that have a single genetic variant underlying the shared heritability at the locus.…”