Please use this identifier to cite or link to this item: https://bura.brunel.ac.uk/handle/2438/34131
Title: Alzheimer’s disease genetics converges on microglial and neuronal dysregulation
Authors: Uffelmann, Emil
Wightman, Douglas P
Bahrami, Shahram
Shadrin, Alexey A
Fominykh, Vera
Ojima, Takafumi
Jiang, Chenyang
Benner, Christian
Moreno, Elisa
Campos, Adrian I
Thomassen, Jesper Q
Ghanbari, Mohsen
Franc, Monique
Pedersen, Nancy L
Bell, Nathaniel Y
Tesi, Niccoló
Buchanan, Adam
Engstad, Torgeir
Tung, Paul
Fladby, Tormod
Krishnamoorthy, Santhanagopalan
INDIANA-CHALASANI
Wu, Hei Man
Merritt, Victoria
Cliby, William A
Bergh, Sverre
van der Flier, Wiesje M
Wang, Rujin
Stahl, Eli A
Carey, David J
Hooli, Basavaraj
Rader, Daniel J
Mount Sinai Million Health Discoveries Program
Medbøen, Ingrid T
Hartmann, Annette M
Ritchie, Marylyn D
Weaver, JoEllen
Naseer, Nawar
Walters, G Bragi
Ahlskog, J Eric
Sirugo, Giorgio
Poindexter, Afiya
Martin, Christa L
Estonian Biobank research team
Ko, Yi-An
Dunn, Joseph
Nerz, Kyle P
Dever, Jenna
Yamaguchi, Taka
Harvey, Aidan
Linn, Sydney
Livingstone, Meghan
Vadivieso, Fred
DerOhannessian, Stephanie
VA Million Veteran Program
Bower, James H
Pereira, Naveen L
Ku, Lisa
Sherva, Richard
Tran, Teo
Stephanowski, Julia
Santos, Salma
Chalasani, Naga
Haubein, Ned
Meyer, Michelle N
PGC-ALZ
Retterer, Kyle
Holstege, Henne
Namba, Shinichi
Kudron, Elizabeth L
Wang, Xuemin
Rolston, David
Cerhan, James R
Couch, Fergus J
Olson, Janet E
Larson, Nicholas B
Hjerling-Leffler, Jens
Fredericksen, Zachary S
Cicek, Mine
Ma, Daniel J
Bundgaard, Henning
van Seumeren, Anna L
Biernacka, Joanna M
Bakkum-Gamez, Jamie N
Karpyak, Victor M
Vemuri, Prashanthi
Bryois, Julien
Rongve, Arvid
Ramanan, Vijay K
Frye, Mark A
McLaughlin, Sarah A
Ruddy, Kathryn J
Bielinski, Suzette J
Lacy, Rashawnda
Zetterberg, Henrik
Lieske, John C
Mutter, Robert W
Saykin, Andrew J
Dispenzieri, Angela
Hooten, W Michael
Boardman, Lisa A
Kennedy, Richard B
Badley, Andrew D
Krebs, Kristi
Dowdy, Sean C
Lange, Ethan M
Eckel-Passow, Jeanette E
Ullum, Henrik
Colborn, Lisa K
Madsen, Bengt O
Frei, Oleksandr
Narita, Akira
Charney, Alexander W
Danielsen, Andrew J
Harrington, Jonathan J
Kushwaha, Jennifer M
Anderson, Heather D
Lesny, Joe A
Aquilante, Christina L
Arbogast, Kelsey
Verma, Shefali S
Truelsen, Thomas
Brooks, Ian M
Burke, Elizabeth E
Casteel, Emily M
Bousiges, Olivier
Davis, Lea K
Cole, Joanne B
Serretti, Alessandro
Lin, Meng
Coughlin, Curtis R
Hendricks, Audrey E
Crawford, Jacob
Crooks, Kristy
Giegling, Ina
Culver, Erin
Fisher, Matthew J
Frye, Teresa C
George, Hunter
Gignoux, Chris R
Logue, Mark W
Zettergren, Anna
Tijms, Betty M
Svenningsson, Per
Gilliland, Elizabeth K
Greene, Casey S
Simonsen, Anja H
Skoog, Ingmar
Hearst, Emily
Martin, James L
Alam, Shaiful
Verma, Anurag
Kaufmann, Scott H
Aagaard, Bitten
Li, Qingqin S
Ariannejad, Maryam
Berkovich, Yael
Boutros, Paul
Broudy, Michael
Corbett, Anne
Bui, Alex
Chang, Tim
Brumpton, Ben M
Kripke, Colleen Morse
Djurovic, Srdjan
Denny, Chris
Pasaniuc, Bogdan
Dry, Sarah
Duntugan, Albert
Hauger, Richard
Geschwind, Dan
Haas, Roni
Illiev, Lora
Jain, Ankur
Lajonchere, Clara
Lichtwarck, Bjørn
Risman, Marjorie
Knapskog, Anne-Brita
den Braber, Anouk
Saltvedt, Ingvild
Magyar, Clara
Martinez, Danielle
Mohammed, Ghouse
Naeim, Arash
Zhang, Rui
Nelson, Stan
Kirsebom, Bjørn-Eivind
Zeng, Jian
Judy, Renae
Visscher, Peter M
Glaser, Gretchen E
Sando, Sigrid B
Rektorova, Irena
O’Reilly, Paul F
Mahajan, Anubha
Ferreira, Manuel
Okada, Yukinori
Creese, Byron
van der Lee, Sven J
Ostrowski, Sisse R
Harris, Peter C
Frikke-Schmidt, Ruth
Stefansson, Hreinn
van Harten, Argonde C
Yang, Ping
Gaziano, J Michael
Heilbron, Karl
Minois-Genin, Emmanuel
Reynolds, Chandra A
Andreassen, Ole A
Posthuma, Danielle
LifeLines Cohort Study
Wollack, Colin
DBDS Genomic consortium
Regeneron Genetics Center
Penn Medicine Biobank
GHS–RGC DiscovEHR collaboration
Mayo Clinic-RGC Project Generation
Haavik, Jan
Luo, Jiao
Vachon, Celine M
Colorado Center for Personalized Medicine–RGC Collaboration
Harder, Arvid
Kern, Silke
Lin, Tian
UCLA–RGC ATLAS collaboration
Hägg, Sara
Karlsson, Ida K
Johnson, Randi K
Schwantes-An, Tae-Hwi Linus
Antwi, Samuel O
Erikstrup, Christian
Mikkelsen, Christina
Ballard, Clive
Aarsland, Dag
Thordardottir, Steinunn
Shigemizu, Daichi
Rujescu, Dan
Snaedal, Jon
Jones, Shelby
Gudbjartsson, Daniel
Eyjolfsdottir, Helga
Aakhus, Eivind
Sørensen, Erik
Oberg, Ann L
Stordal, Eystein
Duits, Flora H
Wolters, Frank J
Blanc, Frederic
Biessels, Geert Jan
Kao, Dave
Phung, Tanya N
Werge, Thomas
Damrauer, Scott
Selbæk, Geir
Bråthen, Geir
Tamiya, Gen
Waldemar, Gunhild
Rabe, Kari G
Seelaar, Harro
Vijverberg, Everard GB
Knortz, Gabrielle A
Sealock, Julia M
Patel, Yash
Schipper, Marijn
Bradford, Yuki
Blennow, Kaj
Nordengen, Kaja
Persson, Karin
Scheffler, Katja
Matsuda, Koichi
Ozaki, Kouichi
Lehto, Kelli
Pihlstrøm, Lasse
Athanasiu, Lavinia
Hansen, Thomas F
Petruse, Antonia
Dudek, Scott
Pålhaugen, Lene
Pedersen, Ole B
Hulsman, Marc
Waern, Margda
Averina, Maria
Koffenberger, Danielle
Wettergreen, Marianne
Moksnes, Marta R
Huisman, Martijn
Yamamoto, Masayuki
Toft, Mathias
Drivas, Theodore
Spellman, Paul
Panizzon, Matthew S
Kyosaka, Tomoki
Goode, Ellen L
Visser, Pieter J
Topholm Bruun, Mie
Issue Date: 28-Oct-2026
Publisher: Springer Nature
Citation: Uffelmann, E. et al. on behalf of PGC-ALZ et al. (2026) 'Alzheimer’s disease genetics converges on microglial and neuronal dysregulation', Nature, 0(ahead of print), pp. 1–28. doi: 10.1038/s41586-026-11206-y.
Abstract: Alzheimer's disease (AD) is the most common cause of dementia, with global case numbers projected to reach 153 million in 20501. AD is highly heritable, with twin-based heritability estimates of 60-80%2. Although 1,200 causal loci are predicted to exist for AD3, approximately 80 loci have been associated with AD in two recent studies4,5. Low single-nucleotide polymorphism (SNP)-based heritability estimates have prompted the suggestion that little further common-variant risk remains to be found6. Here we analysed data from 109,479 cases, 74,141 proxy cases, 2,131,799 controls and 499,708 proxy controls from diverse ancestries, identifying 118 loci in a multi-ancestry analysis and 9 additional loci in ancestry-specific analyses, 48 of which are new. We identified new AD risk genes, prioritized potential drug targets, and found that genes upregulated in microglia and downregulated in neurons in cases compared with controls were enriched for AD-associated genetic risk. Moreover, we improved polygenic prediction and estimated a SNP heritability of 16%, nearly threefold higher than previous estimates. Together, our findings show that the common-variant contribution to AD has been substantially underestimated, and reveal new molecular and cellular mechanisms as well as specific targets for future drug development research.
Description: Data availability: Summary statistics are available for download (https://cncr.nl/research/summary_statistics/). This includes the multi-ancestry meta-analysis and ancestry-specific meta-analyses (EUR, AFR, EAS, AMR and SAS), each additionally stratified by sex (male, female) and by phenotype definition (case–control, proxy), as well as X chromosome summary statistics, versions excluding the UKB and a meta-analysis restricted to cohorts not included in previous AD GWAS. All summary statistics exclude data from the 23andMe Research Institute. The majority of individual-level genotype and phenotype data analysed in this study cannot be made publicly available, as they are governed by the consent, data protection and data transfer agreements of the contributing cohorts. Access to individual-level data must be requested directly from each cohort; details for each cohort are provided in the Supplementary Methods. This study used the following publicly available resources: DGIdb v5.0 (https://dgidb.org/); FUMA v1.8.3 (https://fuma.ctglab.nl/); the GWAS Catalog (https://www.ebi.ac.uk/gwas/efotraits/MONDO_0004975, accessed 7 October 2024); MSigDB v2024.1.Hs (https://www.gsea-msigdb.org/gsea/msigdb); SynGO v20231201 (https://www.syngoportal.org/); the BaselineLD model v2.2; 1000 Genomes Project phase 3; HapMap3 and pan-UKB linkage disequilibrium scores (https://pan-dev.ukbb.broadinstitute.org/); and Ensembl BioMart. Cell-type expression data were obtained from Siletti et al.106, the Allen Human Brain Atlas, GSE168408 and PsychENCODE; differential expression data from Nakatsuka et al.37; and microglial state gene sets from Sun et al.110. Summary statistics for amyotrophic lateral sclerosis and Parkinson’s disease were obtained from van Rheenen et al.82 and Nalls et al.26, respectively. UKB data were accessed under application nos. 16406 and 18177. Forest plots for each locus are available on Zenodo9 (https://doi.org/10.5281/zenodo.22791372).
Code availability: Analysis code can be downloaded on GitHub (https://github.com/euffelmann/paper-pgc_alzheimers) and Zenodo9 (https://doi.org/10.5281/zenodo.22791372).
Supplementary information is available online at: https://www.nature.com/articles/s41586-026-11206-y#Sec34 .
URI: https://bura.brunel.ac.uk/handle/2438/34131
DOI: https://doi.org/10.1038/s41586-026-11206-y
ISSN: 0028-0836
Appears in Collections:Department of Psychology Research Papers *

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