RESEARCH ARTICLE Integrated transcriptomic and neuroimaging brain model decodes biological mechanisms in aging and Alzheimer’s disease Quadri Adewale1,2,3, Ahmed F Khan1,2,3, Felix Carbonell4, Yasser Iturria-Medina1,2,3*, Alzheimer’s Disease Neuroimaging Initiative† 1Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Canada; 2McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada; 3Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Canada; *For correspondence: 4Biospective Inc, Montreal, Canada
[email protected] †Data used in preparation of this article were partly obtained from the Alzheimer’s Disease Abstract Both healthy aging and Alzheimer’s disease (AD) are characterized by concurrent Neuroimaging Initiative (ADNI) alterations in several biological factors. However, generative brain models of aging and AD are database (adni.loni.usc.edu). As limited in incorporating the measures of these biological factors at different spatial resolutions. such, the investigators within the Here, we propose a personalized bottom-up spatiotemporal brain model that accounts for the ADNI contributed to the design direct interplay between hundreds of RNA transcripts and multiple macroscopic neuroimaging and implementation of ADNI modalities (PET, MRI). In normal elderly and AD participants, the model identifies top genes and/or provided data but did not modulating tau and amyloid-b burdens, vascular flow, glucose metabolism, functional activity, and participate in analysis or writing atrophy to drive cognitive decline. The results also revealed that AD and healthy aging share of this report. A complete listing specific biological mechanisms, even though AD is a separate entity with considerably more altered of ADNI investigators can be pathways.