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Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Schwartzentruber, Jeremy  ORCID logo  https://orcid.org/0000-0002-6183-2092
Cooper, Sarah 
Liu, Jimmy Z 
Barrio-Hernandez, Inigo  ORCID logo  https://orcid.org/0000-0002-5686-0451
Bello, Erica 

Abstract

Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.

Description

Keywords

Adaptor Proteins, Signal Transducing, Alzheimer Disease, Chromosome Mapping, Cytoskeletal Proteins, Gene Expression, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Microglia, Oncogene Proteins, Polymorphism, Single Nucleotide, Protein Interaction Maps, Quantitative Trait Loci, Risk Factors, Tetraspanins

Journal Title

Nat Genet

Conference Name

Journal ISSN

1061-4036
1546-1718

Volume Title

53

Publisher

Springer Science and Business Media LLC

Rights

All rights reserved
Sponsorship
MULTIPLE SCLEROSIS SOCIETY (50)
Wellcome Trust (203151/Z/16/Z)
Multiple Sclerosis Society (50)
Medical Research Council (MC_PC_17230)
This work was funded by Open Targets (OTAR037). We thank Jeff Barrett for guidance during initiation of the project, and Kaur Alasoo for early access to the eQTL catalogue. We thank Agustín Ruiz for support in using summary results from the Gr@ace study. We acknowledge the participants and investigators of FinnGen study. RJMF is supported by grants from the UK Multiple Sclerosis Society (MS 50), the Adelson Medical Research Foundation, and a core support grant from Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute (203151/Z/16/Z). AY is supported by a Wellcome Trust PhD for Clinicians fellowship