Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Alzheimer Disease Genetics Consortium (ADGC),, Brian W Kunkle, Benjamin Grenier-Boley, Rebecca Sims, Joshua C Bis, Vincent Damotte, Adam C Naj, Anne Boland, Maria Vronskaya, Sven J van der Lee, Alexandre Amlie-Wolf, Céline Bellenguez, Aura Frizatti, Vincent Chouraki, Eden R Martin, Kristel Sleegers, Nandini Badarinarayan, Johanna Jakobsdottir, Kara L Hamilton-Nelson, Sonia Moreno-GrauRobert Olaso, Rachel Raybould, Yuning Chen, Amanda B Kuzma, Mikko Hiltunen, Taniesha Morgan, Shahzad Ahmad, Badri N Vardarajan, Jacques Epelbaum, Per Hoffmann, Merce Boada, Gary W Beecham, Jean-Guillaume Garnier, Denise Harold, Annette L Fitzpatrick, Otto Valladares, Marie-Laure Moutet, Amy Gerrish, Albert V Smith, Liming Qu, Delphine Bacq, Nicola Denning, Xueqiu Jian, Yi Zhao, Maria Del Zompo, Nick C Fox, Seung-Hoan Choi, Sebastiaan Engelborghs, Nathalie Fievet, Li Ma, Christine Van Broeckhoven

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1902 Citations (Scopus)

Abstract

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Original languageEnglish
Pages (from-to)414-430
Number of pages17
JournalNature Genetics
Volume51
Issue number3
DOIs
Publication statusPublished - Mar 2019

Keywords

  • Alzheimer disease
  • LOAD
  • dementia
  • genetics

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