Brain : a journal of neurology
Published

The landscape of autosomal-dominant Alzheimer's disease: global distribution and age of onset

Authors

Haiyan Liu, Thomas W Marsh, Xinyu Shi, Alan E Renton, Kevin M Bowling, Ellen Ziegemeier, Guoqiao Wang, Yuchen Cao, Alisha Aristel, Jessie Li, Alexa Dickson, Richard J Perrin, Alison M Goate, Victoria Fernández, Gregory S Day, Michelle Doering, Alisha Daniels, Brian A Gordon, Tammie L S Benzinger, Jason Hassenstab, Laura Ibanez, Charlene Supnet-Bell, Chengjie Xiong, Ricardo Allegri, Sarah B Berman, Nick C Fox, Natalie Ryan, Edward D Huey, Jonathan Vöglein, James M Noble, Jee Hoon Roh, Mathias Jucker, Christoph Laske, Takeshi Ikeuchi, Raquel Sanchez-Valle, Peter R Schofield, Patricio Chrem Mendez, Jasmeer P Chhatwal, Martin Farlow, Jae-Hong Lee, Allan I Levey, Johannes Levin, Francisco Lopera, Ralph Martins, Yoshiki Niimi, Pedro Rosa-Neto, John C Morris, Randall J Bateman, Celeste M Karch, Carlos Cruchaga, Eric McDade, Jorge J Llibre-Guerra
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Abstract

Brain. 2025 Feb 4:awaf038. doi: 10.1093/brain/awaf038. Online ahead of print.

ABSTRACT

We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer's disease (ADAD). A total of 550 variants in the APP, PSEN1, and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on ACMG-AMP criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature, and public databases. Symptomatic age at onset (AAO) data was estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity, and AAO. Importantly, 226 variants meet eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrate the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study (DIAN-OBS). This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria.

PMID:39903689 | DOI:10.1093/brain/awaf038