Document Type
Article
Publication Date
7-1-2024
Original Citation
Sasner M,
Preuss C,
Pandey R,
Uyar A,
Garceau D,
Kotredes K,
Jackson HM,
Oblak A,
Lin P,
Perkins B,
Soni D,
Ingraham C,
Lee-Gosselin A,
Lamb B,
Howell G,
Carter GW.
In vivo validation of late-onset Alzheimer's disease genetic risk factors. Alzheimers Dement. 2024;20(7):4970-84.
Keywords
JGM, JMG, SS1, Alzheimer Disease, Animals, Mice, Humans, Risk Factors, Mice, Transgenic, Disease Models, Animal, Genetic Predisposition to Disease, Genome-Wide Association Study, Male, Brain, Female
JAX Source
Alzheimers Dement. 2024;20(7):4970-84.
ISSN
1552-5279
PMID
38687251
DOI
https://doi.org/10.1002/alz.13840
Grant
Data collection was supported through funding by National Institute on Aging (NIA) grants P30AG10161 (ROS), R01AG15819 (ROSMAP; genomics and RNAseq), R01AG17917 (MAP), R01AG36836 (RNAseq), the Illinois Department of Public Health (ROSMAP), and the Translational Genomics Research Insti- tute (genomic). Data collection was supported through funding by NIA grants P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949, National Institute of Neurological Disor- ders and Stroke (NINDS) grant R01 NS080820, CurePSP Foundation, and support from Mayo Foundation. The Brain and Body Donation Program was supported by the NINDS (U24 NS072026 National Brain and Tissue Resource for Parkinson’s Disease and Related Disorders), the NIA (P30 AG19610 Arizona Alzheimer’s Disease Core Center), the Arizona Department of Health Services (contract 211002, Ari- zona Alzheimer’s Research Center), the Arizona Biomedical Research Commission (contracts 4001, 0011, 05-901 and 1001 to the Arizona Parkinson’s Disease Consortium), and the Michael J. Fox Foundation for Parkinson’s Research. The IU/JAX/PITT MODEL-AD Center was supported through funding by NIA grant U54AG054345.
Abstract
INTRODUCTION: 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 APOE ε4/ε4 and Trem2*R47H. The 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.
HIGHLIGHTS: A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.