Menopause is associated with dyslipidemia and an increased risk of cardiovascular disease, the underlying mechanism of dyslipidemia is attributed to an insufficiency of estrogen. In this study, we find that estrogen mediates an atherosclerotic-protective action via estrogen receptor alpha/SREBP-1 signaling. Increased lipid accumulation and low-density lipoprotein (LDL)-uptake in HepG2 cells and THP-1 macrophages were induced by treatment of mixed hyperlipidemic serum from postmenopausal women; 17β-estradiol [estrogen (E2)] (10 nM) administration significantly improved hyperlipidemic profiles, relieved fatty-liver damage and attenuated the plaque area in the heart chamber of high-fat diet (HFD)-fed ovariectomized (OVX) ApoE–/– mice. Expression of sterol regulatory element-binding protein (SREBP)-1 mRNA of circulating leukocytes in postmenopausal women was strongly correlated to the serum E2 level. Exploration of data from the Gene Expression Profiling Interactive Analysis (GEPIA) database revealed that expression of SREBP-1 protein correlated to expression of estrogen receptor (ESR)α protein in the liver, blood and in normal tissue. Genetic overexpression/inhibition of ESRα resulted in increased/decreased SREBP-1 expression as well as attenuated/deteriorated lipid deposition in vitro. An inhibitor of the protein kinase B/mammalian target of rapamycin (AKT/mTOR) pathway, AZD8055, abolished ESRα-induced SREBP-1 expression in HepG2 cells. Moreover, E2 and statin co-treatment significantly reduced lipid accumulation in vitro and hindered the progression of atherosclerosis and fatty-liver damage in OVX ApoE–/– mice. Collectively, our results suggest that estrogen could exerted its atherosclerotic-protective action via ESRα/SREBP-1 signaling. E2 might enhance the cellular sensitivity of statins and could be used as a novel therapeutic strategy against atherosclerotic disorders in postmenopausal women.

Background: This study sought to analyze non-targeted plasma metabolites in patients with atherosclerosis (AS). Methods:The plasma of patients with AS (the patient group) and the plasma of age-matched and gendermatched healthy individuals (the control group) at the Taihe Hospital was collected. One hundred patients were included in the study (60 in the patient group and 40 in the control group). Fasting venous plasma was collected in the morning. The metabolites in the plasma were examined by liquid chromatographymass spectrometry (LC-MS). An unsupervised principal component analysis (PCA) was conducted to observe the overall distribution of each sample and the stability of the analysis process. Next, a supervised partial least squares-discriminant analysis (PLS-DA) and an orthogonal partial least squares-discriminant analysis (OPLS-DA) were conducted to examine the overall differences among the metabolic profiles of the groups and identify different metabolites in the groups. Pathway enrichment was analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.Results: In total, 1,126 different metabolites were detected in the patient and control groups. Compared to the control group, 411 species decreased, and 715 species increased in the patient group. There were 61 different metabolites with a variable weight in the projection (VIP) >1 and a P<0.05. There were 34 types of lipid metabolites, 10 types of carbon and oxygen compounds, 8 types of organic acids and derivatives, 4 types of organoheterocyclic compounds, 3 types of nitrogen-containing organic compounds, and 2 types of nucleotides and analogs. Compared to the control group, 47 species decreased, and 14 species increased in the patient group. The following 9 metabolites had the most significant differences (|log2fold change| >1; P<0.05): 2-tetradecanone, pantothenol, all-trans-13,14-dihydroretinol, linoleoyl ethanolamide, N-oleoylethanolamine, 4-methyl-2-pentenal, Cer (d18:1/14:0), chenodeoxycholic acid glycine conjugate, and 5-acetamidovalerate. The enrichment analysis results of the 61 different metabolite pathways identified 17 metabolic pathways with significant differences (P<0.05), including the choline metabolism, lipid metabolism, autophagy, amino acid metabolism, vitamin digestion, and absorption pathways.Conclusions: There are significant differences in non-targeted plasma metabolites between patients with AS and healthy individuals. The above-mentioned 9 most significantly different metabolites may be potential markers of AS.