Untargeted metabolomic profiling identifies Alzheimer’s disease-specific signatures in serum and faeces impacted by tetrahydroxy stilbene glycoside through UPLC-Q-TOF/MS

Abstract

Listen

Translate article

BackgroundsAmyloid beta (Aβ) accumulates within cells in the brains of Alzheimer's disease (AD) patients, especially in the aged. Increased Aβ production would promote abnormalities. However, relative metabolic mechanisms of AD are not fully elucidated yet. Tetrahydroxy stilbene glycoside (TSG) is the main active constituent of the traditional Chinese medicine, Polygonum multiflorum. Herein, we intended to identify the pharmacological effects of TSG on the serum and fecal metabolites in APP/PS1 mice. MethodsWe described current dynamic metabolic form changes in serum and excrement samples of AD model mice by mass spectrometry-based untargeted metabolomic assays and metagenomic sequencing. We quantified proteins from mouse serum and feces, respectively. ResultsBy untargeted metabolomics of plasma, the total count of metabolites confirmed by positive ion mode was 216 and negative mode was 190. The total metabolite identification quantity was 457. The total number of metabolites confirmed by positive ion mode was 296 and negative mode was 227 in feces. Sequences between wild-type and APP/PS1 groups were divided into the same OTU as 703 while between APP/PS1 and TSG 120 groups were 652. Compared to WT, APP/PS1 mice showed obvious regulation of metabolism related pathways, especially in amino acid and lipid. TSG changed the metabolic substance ratio of lipids, oxygen compounds and nitrogen compounds in both blood and feces, respectively. Lipids are closely related to the formation and clearance of Aβ. ConclusionsIn brief, urea cycle and the ABC transporters were highly related to Aβ and AD progression, at least in current AD mouse model at 5-month with TSG treatment. Alistipes and Prevotella were also closely related to TSG. We present a total framework of TSG effects in AD mouse serum and feces in order to better understand the biologically metabolites related to disease pathology and the progression in the state of prodromal and preclinical stages.