Reverting Metabolic Dysfunction in Cortex and Cerebellum of APP/PS1 Mice, a Model for Alzheimer's Disease by Pioglitazone, a Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) Agonist.

Identification of molecular mechanisms underlying early-stage Alzheimer's disease (AD) is important for the development of new therapies against and diagnosis of AD. In this study, gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics approach was employed to investigate the metabolic profiles in plasma and brain tissues harvested from 5-month-old APP/PS1 transgenic mice and their wildtype counterparts. Since different brain regions were expected to have their own distinct metabolic signals, four different brain regions, namely cortex, hippocampus, midbrain and cerebellum tissues, were dissected and had their metabolic profiles studied separately.

Influence of drug transporters and stereoselectivity on the brain penetration of pioglitazone as a potential medicine against Alzheimer's disease.

Pioglitazone is currently undergoing clinical trials for treatment of Alzheimer's disease (AD). However, poor brain penetration remains an obstacle to development of the drug for such intended clinical uses. In this study, we demonstrate that the inhibition of P-glycoprotein (P-gp) significantly increases brain penetration of pioglitazone, whereas inhibition of breast cancer resistance protein (BCRP) has little effect.

Metabolic profiling of CHO-AβPP695 cells revealed mitochondrial dysfunction prior to amyloid-β pathology and potential therapeutic effects of both PPARγ and PPARα Agonisms for Alzheimer's disease.

In this study, we performed gas chromatography time-of-flight mass spectrometry (GC-TOFMS)-based extracellular metabolic profiling on AβPP-transfected CHO cells (CHO-AβPP695) and its wildtype. Orthogonal partial least squares discriminant analysis (OPLS-DA) was then used to identify discriminant metabolites, which gave clues on the effects of AβPP transgene on cellular processes. To confirm the hypotheses generated based on the metabolic data, we performed biochemical assays to gather further evidence to support our findings.