Characterizing serum metabolic alterations of Alzheimer's disease and intervention of Shengmai-San by ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry

Abstract

Alzheimer's disease (AD) is a chronic and multi-factor-induced neurodegenerative disorder. The development of a single-target treatment strategy for AD has not been successful. Shengmai-San (SMS), a traditional Chinese medicine containing multi-active components, has been reported to be effective for treating AD. However, the mechanism of SMS is still unclear, and as a multicomponent combination therapy, there is a lack of appropriate evaluation. Thereby, metabolomics was applied to investigate the multi-target intervention of SMS by monitoring the fold changes of metabolites in serum. An AD model was successfully replicated by treating rats with oral aluminum chloride (AlCl₃) and an intraperitoneal injection of D-galactose (D-gal) for 105 days. The intervention group was treated with SMS during the whole modeling process. The results of classical experiments showed that SMS could alleviate Aβ_1–40 deposition, protect neurons in the CA3 region of the hippocampus and improve spatial learning and memory impairment compared with the model group. Based on these curative effects, a metabolomics study was implemented using the UPLC-Q/TOF-MS method. A heatmap of AD-associated metabolites (P < 0.05) was set up to target the most relevant metabolic network and to evaluate the comprehensive effects of SMS. Based on this AD-associated metabolic network, the total regulation-of-metabolites’ coverage rate of SMS was 51.35% and the gross metabolites’ recovery proportion was 72.32%. Lipid peroxidation was the main mechanism of SMS intervention in AD, including inhibition of the generation of linoleic acid hydroperoxides, such as 13-HPODE, 9-HPODE and 9-OxoODE.