Sasner, MichaelPreuss, ChristophPandey, Ravi S.Uyar, AsliGarceau, DylanKotredes, Kevin P.Williams, HarrietOblak, Adrian L.Lin, Peter Bor-ChianPerkins, BridgetSoni, DishaIngraham, CindyLee-Gosselin, AudreyLamb, Bruce T.Howell, Gareth R.Carter, Gregory W.2024-05-222024-05-222023-12-24Sasner M, Preuss C, Pandey RS, et al. In vivo validation of late-onset Alzheimer's disease genetic risk factors. Preprint. bioRxiv. 2023;2023.12.21.572849. Published 2023 Dec 24. doi:10.1101/2023.12.21.572849https://hdl.handle.net/1805/40932Introduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. Results: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. Discussion: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.en-USAttribution 4.0 InternationalAPOE4Abca7Alzheimer’s diseaseAnimal modelsMthfrPlcg2PreclinicalTranscriptomic analysisTrem2Article