Multi‐Omics analysis identifies that different genetic perturbations affect various molecular mechanisms underlying Alzheimer's Disease (AD) in an age‐dependent manner

We have characterized in vivo signatures of three genetic candidates for late-onset Alzheimer's disease (LOAD), identifying alterations in specific LOAD-related pathways for each variant. Our study highlights that assembling multi-omics measurements reveals interrelated pathway alterations in Alzheimer's Disease (AD) and enables the identification of biomarker combinations that may inform clinical practice. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.