Deciphering the genetic landscape of Alzheimer disease (AD) is essential to define the pathophysiological pathways involved and to successfully translate genomics to potential tailored medical care. To generate the most complete knowledge of the AD genetics, we developed through the European Alzheimer Disease BioBank (EADB) consortium a discovery meta-analysis of genome-wide association studies (GWAS) based on a new large case-control study and previous GWAS (in total 39,106 clinically diagnosed cases, 46,828 proxy-AD cases and 401,577 controls) with the most promising signals followed-up in independent samples (18,063 cases and 23,207 controls). In addition to 34 known AD loci, we report here the genome-wide significant association of 31 new loci with the risk of AD. Pathway-enrichment analyses strongly indicated the involvement of gene sets related to amyloid and Tau, but also highlighted microglia, in which increased gene expression corresponds to more significant AD risk. In addition, we successfully prioritized candidate genes in the majority of our new loci, with nine being primarily expressed in microglia. Finally, we observed that a polygenic risk score generated from this new genetic landscape was strongly associated with the risk of progression from mild cognitive impairment (MCI) to dementia (4,609 MCI cases of whom 1,532 converted to dementia), independently of age and the APOE e4 allele.

Alzheimer’s disease (AD) (MIM: 104300) is a highly heritable disease with great complexity in its genetic contributors, and represents the most common form of dementia. With the gradual aging of the world’s population, leading to increased prevalence of AD, and the substantial cost of care for those afflicted, identifying the genetic causes of disease represents a critical effort in identifying therapeutic targets. Here we provide a comprehensive review of genomic studies of AD, from the earliest linkage studies identifying monogenic contributors to early-onset forms of AD to the genome-wide and rare variant association studies of recent years that are being used to characterize the mosaic of genetic contributors to late-onset AD (LOAD), and which have identified approximately ~20 genes with common variants contributing to LOAD risk. In addition, we explore studies employing alternative approaches to identify genetic contributors to AD, including studies of AD-related phenotypes and multi-variant association studies such as pathway analyses. Finally, we introduce studies of next-generation sequencing, which have recently helped identify multiple low-frequency and rare variant contributors to AD, and discuss on-going efforts with next-generation sequencing studies to develop statistically well-powered and comprehensive genomic studies of AD. Through this review, we help uncover the many insights the genetics of AD have provided into the pathways and pathophysiology of AD.

Alzheimer’s disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals—16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.

Background: With the development of next-generation sequencing technologies, it is possible to identify rare genetic variants that influence the risk of complex disorders. To date, whole exome sequencing (WES) strategies have shown that specific clusters of damaging rare variants in the TREM2, SORL1 and ABCA7 genes are associated with an increased risk of developing Alzheimers Disease (AD), reaching odds ratios comparable with the APOE-ε4 allele, the main common AD genetic risk factor. Here, we set out to identify additional AD-associated genes by an exome-wide investigation of the burden of rare damaging variants in the genomes of AD cases and cognitively healthy controls. Method: We integrated the data from 25,982 samples from the European ADES consortium and the American ADSP consortium. We developed new techniques to homogenise and analyse these data. Carriers of pathogenic variants in genes associated with Mendelian inheritance of dementia were excluded. After quality control, we used 12,652 AD cases and 8,693 controls for analysis. Genes were analysed using a burden analysis, including both non-synonymous and loss-of-function rare variants, the impact of which was prioritised using REVEL. Result: We confirmed that carrying rare protein-damaging genetic variants in TREM2, SORL1 or ABCA7 is associated with increased AD-risk. Moreover, we found that carrying rare damaging variants in the microglial ATP8B4 gene was significantly associated with AD, and we found suggestive evidence that rare variants in ADAM10, ABCA1, ORC6, B3GNT4 and SRC genes associated with increased AD risk. High-impact variants in these genes were mostly extremely rare and enriched in AD patients with earlier ages at onset. Additionally, we identified two suggestive protective associations in CBX3 and PRSS3. We are currently replicating these associations in independent datasets. Conclusion: With our newly developed homogenisation methods, we identified novel genetic determinants of AD which provide further evidence for a pivotal role of APP processing, lipid metabolism, and microglia and neuro-inflammatory processes in AD pathophysiology.