Integration of Alzheimer\u2019s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes

Gloriia Novikova,Jaroslav Bendl,Edsel M Abud,Panos Roussos,Julia Tcw,Anastasia G Efthymiou,Ke Hao,Edoardo Marcora,Haoxiang Cheng,Manav Kapoor,Yunlong Liu,Alison M Goate,Yiyuan Liu,John F Fullard,Wayne W Poon,Steven X Chen,Johan Lm Björkegren

doi:10.1038/s41467-021-21823-y

Abstract

Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility.

Highlights

Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis
A study comparing two mouse strains reported that genetic variants in Mafb, Smad[3], and Usf[1] binding sites affected PU.[1] binding in microglia, suggesting that these transcription factors (TFs) could be binding partners of PU.[1] in microglia[21]. These results show that AD risk alleles are enriched in active enhancers of monocytes, macrophages, and microglia, and nominate shared and cell-type specific TFs that likely regulate the activity of these regulatory elements
In this study we report an integration of AD GWAS with epigenomic and transcriptomic datasets from myeloid cells to nominate candidate causal variants, regulatory elements, genes and pathways and inform a mechanistic understanding of AD genetics and pathobiology for the formulation of novel therapeutic hypotheses (Supplementary Figure 7)

Summary

Introduction

Genome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Given the selective enrichment of AD risk alleles in myeloid active enhancers, we sought to link the activity of myeloid enhancers that contain AD risk variants to target gene expression regulation and AD risk modification To accomplish this we use two complementary approaches. We map myeloid active enhancers that contain AD risk alleles (AD risk enhancers) to their target genes by integrating chromatin interactions (promoter-capture Hi–C) and eQTL datasets from monocytes and macrophages This approach allows us to nominate candidate causal genes in eleven genomewide significant and five suggestive AD risk loci, including TP53INP1, APBB3, RABEP1, and SPPL2A. We further fine-map AD risk enhancers to identify candidate functional variants that likely affect TF binding and regulate gene expression in seven loci, and validate one of these variants in the MS4A locus in human induced pluripotent stem cell (hiPSC)-derived microglia and brain

Methods

Results

Conclusion