In vivo validation of late-onset Alzheimer's disease genetic risk factors

Sasner, M.; Preuss, C.; Pandey, R. S.; Uyar, A.; Garceau, D.; Kotredes, K. P.; Williams, H.; Oblak, A.; Lin, P. B.-C.; Perkins, B.; Soni, D. M.; Ingraham, C.; Gosselin, A. L.; Lamb, B. T.; Howell, G.; Carter, G. W.

doi:10.1101/2023.12.21.572849

bioRxiv · 10.1101/2023.12.21.572849

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Sasner, M.·Preuss, C.·Pandey, R. S.·Uyar, A.·Garceau, D.·Kotredes, K. P.·Williams, H.·Oblak, A.·Lin, P. B.-C.·Perkins, B.·Soni, D. M.·Ingraham, C.·Gosselin, A. L.·Lamb, B. T.·Howell, G.·Carter, G. W.

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Abstract

Structured AbstractO_ST_ABSIntroductionC_ST_ABSGenome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimers disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. MethodsCandidate 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. ResultsWe 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. DiscussionThese results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

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Sasner, M., Preuss, C., Pandey, R. S., Uyar, A., Garceau, D., Kotredes, K. P., Williams, H., Oblak, A., Lin, P. B.-C., Perkins, B., Soni, D. M., Ingraham, C., Gosselin, A. L., Lamb, B. T., Howell, G., Carter, G. W.. 2023-12-24. In vivo validation of late-onset Alzheimer's disease genetic risk factors. https://doi.org/10.1101/2023.12.21.572849

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