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A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease

Research output: Contribution to journalArticlepeer-review

23andMe Research Team, Douglas P Wightman, Iris E Jansen, Jeanne E Savage, Alexey A Shadrin, Shahram Bahrami, Dominic Holland, Arvid Rongve, Sigrid Børte, Bendik S Winsvold, Ole Kristian Drange, Amy E Martinsen, Anne Heidi Skogholt, Cristen Willer, Geir Bråthen, Ingunn Bosnes, Jonas Bille Nielsen, Lars G Fritsche, Laurent F Thomas, Linda M Pedersen & 31 more Maiken E Gabrielsen, Marianne Bakke Johnsen, Tore Wergeland Meisingset, Wei Zhou, Petroula Proitsi, Angela Hodges, Richard Dobson, Latha Velayudhan, Julia M Sealock, Lea K Davis, Nancy L Pedersen, Chandra A Reynolds, Ida K Karlsson, Sigurdur Magnusson, Hreinn Stefansson, Steinunn Thordardottir, Palmi V Jonsson, Jon Snaedal, Anna Zettergren, Ingmar Skoog, Silke Kern, Margda Waern, Henrik Zetterberg, Kaj Blennow, Eystein Stordal, Kristian Hveem, John-Anker Zwart, Lavinia Athanasiu, Per Selnes, Ingvild Saltvedt, Dag Aarsland

Original languageEnglish
Pages (from-to)1276-1282
Number of pages7
JournalNature Genetics
Issue number9
Early online date7 Sep 2021
Accepted/In press16 Jul 2021
E-pub ahead of print7 Sep 2021
PublishedSep 2021

Bibliographical note

Funding Information: We thank all the participants included in this study, including the participants from Finngen, GR@CE, IGAP, UKB, DemGene, TwinGene, STSA, the Gothenburg H70 Birth Cohort Studies and Clinical AD from Sweden, ANMerge, BioVU, 23andMe, HUNT, and deCODE. We thank the research participants from 23andMe who made this study possible. We thank the participants of the Norwegian Dementia Genetics Network (DemGene). This work was supported by BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (grant no. 024.004.012). This work was supported by the Research Council of Norway (RCN: 248980, 248778, 223273), Norwegian Regional Health Authorities, Norwegian Health Association (22731, EU JPND: PMI-AD RCN 311993); and National Institutes of Health, National Institute on Aging R01 AG08724, R01 AG17561, R01 AG028555 and R01 AG060470. We thank the International Genomics of Alzheimer’s Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients and their families. The iSelect chips were funded by the French National Foundation on Alzheimer’s disease and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD/PERADES was supported by the Medical Research Council (grant no. 503480), Alzheimer’s Research UK (grant no. 503176), the Wellcome Trust (grant no. 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) (grant nos. 01GI0102, 01GI0711, 01GI0420). CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants U01 AG032984, U24 AG021886, U01 AG016976 and the Alzheimer’s Association grant ADGC–10–196728. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors


Late-onset Alzheimer's disease is a prevalent age-related polygenic disease that accounts for 50-70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer's disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer's disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer's disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer's disease to identify further genetic variants that contribute to Alzheimer's pathology.

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