Patient-centered Transcriptomic and Multimodal Neuroimaging Determinants of Clinical Progression, Physical Activity and Treatment Needs in Parkinson Disease

Parkinson disease is a complex and multifactorial disorder, but how its biological and clinical complexity emerge from molecular to macroscopic brain interactions remains poorly understood. Here, we use a personalized multiscale generative brain model to characterize direct spatiotemporal links between genes and multimodal neuroimaging-derived biological factors in PD. We identified a set of genes modulating PD-associated longitudinal changes in dopamine transporter level, neuronal activity, dendrite density and tissue atrophy. Inter-individual heterogeneity in the gene-mediated biological mechanisms is associated with five distinct configurations of PD motor and non-motor symptoms. Although characterized by distinctive biological pathways, all the symptom configurations are associated with cell cycle processes. Notably, the protein-protein interaction networks underlying these configurations revealed distinct hub genes including MYC, CCNA2, CCDK1, SRC, STAT3 and PSMD4. We also uncovered the biological mechanisms associated with physical activities performance in PD, and observed that leisure and work activities are principally related to neurotypical cholesterol homeostasis and inflammatory response processes, respectively. Finally, patient-tailored in silico gene perturbations revealed a set of putative disease-modifying drugs with potential to effectively treat PD, most of which are associated with dopamine reuptake and anti-inflammation. Our study constitutes the first self-contained multiscale approach providing comprehensive insights into the complex multifactorial pathogenesis of PD, unravelling key biological modulators of physical and clinical deterioration, and serving as a blueprint for optimum drug selection at personalized level.