Abstract
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.
Original language | English |
---|---|
Pages (from-to) | 1276-1282 |
Number of pages | 7 |
Journal | Nature Genetics |
Volume | 53 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Sept 2021 |
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In: Nature Genetics, Vol. 53, No. 9, 01.09.2021, p. 1276-1282.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease
AU - 23andMe Research Team
AU - Wightman, Douglas P.
AU - Jansen, Iris E.
AU - Savage, Jeanne E.
AU - Shadrin, Alexey A.
AU - Bahrami, Shahram
AU - Holland, Dominic
AU - Rongve, Arvid
AU - Børte, Sigrid
AU - Winsvold, Bendik S.
AU - Drange, Ole Kristian
AU - Martinsen, Amy E.
AU - Skogholt, Anne Heidi
AU - Willer, Cristen
AU - Bråthen, Geir
AU - Bosnes, Ingunn
AU - Nielsen, Jonas Bille
AU - Fritsche, Lars G.
AU - Thomas, Laurent F.
AU - Pedersen, Linda M.
AU - Gabrielsen, Maiken E.
AU - Johnsen, Marianne Bakke
AU - Meisingset, Tore Wergeland
AU - Zhou, Wei
AU - Proitsi, Petroula
AU - Hodges, Angela
AU - Dobson, Richard
AU - Velayudhan, Latha
AU - Agee, Michelle
AU - Aslibekyan, Stella
AU - Babalola, Elizabeth
AU - Bell, Robert K.
AU - Bielenberg, Jessica
AU - Bryc, Katarzyna
AU - Bullis, Emily
AU - Cameron, Briana
AU - Coker, Daniella
AU - Partida, Gabriel Cuellar
AU - Dhamija, Devika
AU - Das, Sayantan
AU - Elson, Sarah L.
AU - Filshtein, Teresa
AU - Fletez-Brant, Kipper
AU - Fontanillas, Pierre
AU - Freyman, Will
AU - Gandhi, Pooja M.
AU - Hicks, Barry
AU - Hinds, David A.
AU - Huber, Karen E.
AU - Jewett, Ethan M.
AU - Posthuma, Danielle
AU - Jiang, Yunxuan
N1 - 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.
PY - 2021/9/1
Y1 - 2021/9/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85114746630&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85114746630&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/s41588-021-00921-z
DO - https://doi.org/10.1038/s41588-021-00921-z
M3 - Article
C2 - 34493870
SN - 1061-4036
VL - 53
SP - 1276
EP - 1282
JO - Nature Genetics
JF - Nature Genetics
IS - 9
ER -