Metabotyping of docosahexaenoic acid - treated Alzheimer's disease cell model.

Abstract

BACKGROUND: Despite the significant amount of work being carried out to investigate the therapeutic potential of docosahexaenoic acid (DHA) in Alzheimer's disease (AD), the mechanism by which DHA affects amyloid-β precursor protein (AβPP)-induced metabolic changes has not been studied. OBJECTIVE: To elucidate the metabolic phenotypes (metabotypes) associated with DHA therapy via metabonomic profiling of an AD cell model using gas chromatography time-of-flight mass spectrometry (GC/TOFMS). METHODS: The lysate and supernatant samples of CHO-wt and CHO-AβPP695 cells treated with DHA and vehicle control were collected and prepared for GC/TOFMS metabonomics profiling. The metabolic profiles were analyzed by multivariate data analysis techniques using SIMCA-P+ software. RESULTS: Both principal component analysis and subsequent partial least squares discriminant analysis revealed distinct metabolites associated with the DHA-treated and control groups. A list of statistically significant marker metabolites that characterized the metabotypes associated with DHA treatment was further identified. Increased levels of succinic acid, citric acid, malic acid and glycine and decreased levels of zymosterol, cholestadiene and arachidonic acid correlated with DHA treatment effect. DHA levels were also found to be increased upon treatment. CONCLUSION: Our study shows that DHA plays a role in mitigating AβPP-induced impairment in energy metabolism and inflammation by acting on tricarboxylic acid cycle, cholesterol biosynthesis pathway and fatty acid metabolism. The perturbations of these metabolic pathways by DHA in CHO-wt and CHO-AβPP695 cells shed further mechanistic insights on its neuroprotective actions.