Neurodegenerative diseases are characterized by deposition of abnormal protein aggregates in the brain in predictable spatial and temporal patterns. This selective vulnerability to pathology, which encompasses vulnerabilities of cell types, regions, and brain networks, is a fundamental feature of disease that is not yet understood. Mouse models of human disease are required for preclinical investigations into molecular and cellular mechanisms underlying vulnerability and resilience. Yet, little data exists on how well aligned commonly used models are with the brain-wide human spatiotemporal vulnerability maps. To address this gap and more deeply characterize existing models, we built a high-throughput whole brain imaging and informatics pipeline to systematically quantify spatiotemporal patterns of disease-relevant pathologies in mice. Using whole brain clearing, antibody labeling, and lightsheet imaging, we have quantified tyrosine hydroxylase levels in a mouse model of Parkinson’s Disease with nigrostriatal degeneration and show the utility of 3D imaging to identify disease-relevant regional vulnerabilities.
