Alzheimer’s disease is characterized by the accumulation of cerebral beta-amyloid (Aβ) and tau pathology, which together cause progressive neurodegeneration and cognitive decline.

Our overarching goal is to better understand the mechanisms that promote the development and progression of Alzheimer’s disease in order to develop clinically applicable personalized medicine models for predicting patient-specific disease trajectories (e.g. Franzmeier et al., Alzheimers Dement, 2020). To this end, we combine multi-modal neuroimaging methods including positron-emission tomography (PET) and magnetic resonance imaging (MRI) with clinical assessments and genetics in large-scale patient data. 

A major research focus is the prediction of trans-neuronal tau pathology spread, i.e. the major driver of neurodegeneration and cognitive decline in Alzheimer’s disease. In a translational approach, we combine tau-PET imaging with MRI-based connectomics for modeling connectivity-based tau spreading patterns (e.g. Franzmeier et al., Brain, 2019; Nat Commun, 2020). We have recently established connectivity-based tau spreading models, which allow accurate prediction of future tau spreading patterns on the patient level (Franzmeier et al., Sci Adv, 2020). These prediction models have high clinical utility, as they can be utilized to determine patient-specific endpoints in tau targeting trials which can drastically enhance the sensitivity for detecting treatment effects 
(see here: https://www.alzforum.org/news/research-news/connectivity-not-proximity-predicts-tau-spread or here: https://www.alzforum.org/news/research-news/individualized-tau-pet-model-outperforms-predictive-power-braak-staging) 
In ongoing collaborative work, we are extensively validating these tau spreading models across atypical Alzheimer’s disease variants and other neurodegenerative tauopathies.