Alzheimer disease (AD) is the most common neurodegenerative disorder and affects >40 million patients worldwide. To date, no effective AD treatment or prevention is possible. A key drug target is BACE1, which cleaves the amyloid precursor protein (APP), thereby catalyzing the first step in the generation of Aß, the key pathogenic peptide in AD. Different inhibitors of the protease BACE1 (also referred to as ß-secretase) have been tested in phase 3 clinical trials, but all of the trials have been discontinued either due to adverse effects or due to lack of efficacy. Based on work in mice, the side effects are believed to be mechanism-based (and not off-target) due to simultaneous cleavage inhibition of other BACE1 substrates with fundamental functions in neurobiology.The overarching aim of this joint project is to enable personalized dosing of BACE inhibitors for AD prevention and treatment of early AD stages and thus make BACE inhibitors safer and more effective. Particularly, the hypothesis, that the occurrence of side effects upon BACE inhibitor treatment correlates with the extent of cleavage inhibition of selected BACE1 substrates, will be tested. Thus, the intradisciplinary team working on CLINSPECT-M`s workpackage 2 aims to develop new mass spectrometry based diagnostic assays suited for a future personalized dosing of BACE inhibitors and thereby prevention or control of undesired side effects.

A team of experts in the field of mass spectrometry-based proteomics around Prof. Stefan Lichtenthaler (Chair for Neuroproteomics, Technical University of Munich) optimize and apply a Data Independent Acquisition (DIA) approach to perform discovery proteomics experiments on CSF samples form AD patients treated with BACE inhibitor or placebo and healthy controls from completed clinical trials. Identified significant hits will be correlated with clinical parameters, that are compiled, analyzed and processed by a team of clinicians with special expertise on neurodegenerative diseases around Prof. Johannes Levin (Department of Neurology, LMU University Hospital). The team is further supported by bioinformaticians around Prof. Jan Baumbach (Chair of Computational Systems Biology, University of Hamburg), who will develop and apply statistical and bioinformatic methods needed to analyze and correlate proteomic and clinical data.