Background: In Alzheimer’s disease, beta-amyloid peptides in the brain aggregate into toxic oligomers and
plaques, a process which is associated with neuronal degeneration, memory loss, and cognitive decline. One
therapeutic strategy is to decrease the production of potentially toxic beta-amyloid species by the use of inhibitors
or modulators of the enzymes that produce beta-amyloid from amyloid precursor protein (APP). The failures of
several such drug candidates by lack of effect or undesired side-effects underscore the importance to monitor the
drug effects in the brain on a molecular level. Here we evaluate if peptidomic analysis in cerebrospinal fluid (CSF)
can be used for this purpose.
Methods: Fifteen human healthy volunteers, divided into three groups, received a single dose of placebo or either
140 mg or 280 mg of the γ-secretase inhibitor semagacestat (LY450139). Endogenous peptides in CSF, sampled
prior to administration of the drug and at six subsequent time points, were analyzed by liquid chromatography
coupled to mass spectrometry, using isobaric labeling based on the tandem mass tag approach for relative
quantification.
Results: Out of 302 reproducibly detected peptides, 11 were affected by the treatment. Among these, one was
derived from APP and one from amyloid precursor-like protein 1. Nine peptides were derived from proteins that
may not be γ-secretase substrates per se, but that are regulated in a γ-secretase-dependent manner.
Conclusions: These results indicate that a CSF peptidomic approach may be a valuable tool both to verify target
engagement and to identify other pharmacodynamic effects of the drug. Data are available via ProteomeXchange
with identifier PXD00307
