Late-onset Alzheimer’s (late-AD) is a complex neurodegenerative condition with abnormalities in toxic protein accumulation, vascularization, inflammation, neuronal activity and cerebral atrophy. In keeping with the tenets of Personalized Medicine, treatments should be tailored to individual therapeutic needs as opposed to treating all patients with the same approach. In Neurodegeneration, unfortunately, we currently do not have appropriate methods to tailor interventions at the personalized level.
In this project, we propose to extensively validate a new integrative neuroimaging and cognitive/clinical framework for characterizing and predicting individual treatment response. For this, data from three recently concluded clinical trials in late-AD (1292 participants) will be used for testing the framework’s clinical applicability. Specifically, individual biological fingerprints/signatures from baseline imaging data will be used to predict and explain treatment-specific positive and negative effects. Furthermore, the (dis)advantages of performing personalized rather than group-level analyses when evaluating therapeutic treatments will be deeply analyzed. The proposed analyses may well represent a turning point towards individually-tailored selection of treatments in neurodegeneration, biologically-guided patient enrollment in clinical trials, and better understanding of pharmaceutic results. In addition, motivated for the current lack of open-access tools for precision medicine in neurology, all resulting methods will be made available to the international community.