| Literature DB >> 27570155 |
Wei Guo1, Chunying Jiang1, Liu Yang1, Tianqi Li1, Xia Liu1, Mengxia Jin1, Kai Qu1, Huili Chen1, Xiangju Jin1, Hongyue Liu1, Haibo Zhu1, Yinghong Wang1.
Abstract
Atherosclerosis (AS) is a progressive disease that contributes to cardiovascular disease and shows a complex etiology, including genetic and environmental factors. To understand systemic metabolic changes and to identify potential biomarkers correlated with the occurrence and perpetuation of diet-induced AS, we applied 1H NMR-based metabolomics to detect the time-related metabolic profiles of plasma, urine, and liver extracts from male hamsters fed a high fat and high cholesterol (HFHC) diet. Conventional biochemical assays and histopathological examinations as well as protein expression analyses were performed to provide complementary information. We found that diet treatment caused obvious aortic lesions, lipid accumulation, and inflammatory infiltration in hamsters. Downregulation of proteins related to cholesterol metabolism, including hepatic SREBP2, LDL-R, CYP7A1, SR-BI, HMGCR, LCAT, and SOAT1 was detected, which elucidated the perturbation of cholesterol homeostasis during the HFHC diet challenge. Using "targeted analysis", we quantified 40 plasma, 80 urine, and 60 liver hydrophilic extract metabolites. Multivariate analyses of the identified metabolites elucidated sophisticated metabolic disturbances in multiple matrices, including energy homeostasis, intestinal microbiota functions, inflammation, and oxidative stress coupled with the metabolisms of cholesterol, fatty acids, saccharides, choline, amino acids, and nucleotides. For the first time, our results demonstrate a time-dependent metabolic progression of multiple biological matrices in hamsters from physiological status to early AS and further to late-stage AS, demonstrating that 1H NMR-based metabolomics is a reliable tool for early diagnosis and monitoring of the process of AS.Entities:
Keywords: NMR; atherosclerosis; hamsters; high fat and high cholesterol diet; quantitative metabolomics
Mesh:
Substances:
Year: 2016 PMID: 27570155 DOI: 10.1021/acs.jproteome.6b00179
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466