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A single dose of the gamma-secretase inhibitor semagacestat alters the cerebrospinal fluid peptidome in humans

Artikel i vetenskaplig tidskrift
Författare Mikko Hölttä
R. A. Dean
E. Siemers
K. G. Mawuenyega
W. Sigurdson
P. C. May
D. M. Holtzman
Erik Portelius
Henrik Zetterberg
R. J. Bateman
Kaj Blennow
Johan Gobom
Publicerad i Alzheimers Research & Therapy
Volym 8
Nummer/häfte 11
ISSN 1758-9193
Publiceringsår 2016
Publicerad vid Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi
Språk en
Länkar dx.doi.org/10.1186/s13195-016-0178-...
Ämnesord alzheimers-disease, amyloid hypothesis, beta-like, therapeutics, biomarkers, proteomics, proteins, marker, trials, Neurosciences & Neurology
Ämneskategorier Neurovetenskaper, Neurologi

Sammanfattning

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 gamma-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 gamma-secretase substrates per se, but that are regulated in a gamma-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 PXD003075.

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