Title

Sesame Oil And An Aqueous Extract Derived From Sesame Oil Enhance Regression Of Preexisting Atherosclerotic Lesions In Low-Density Lipoprotein Receptor Knockout Mice

Keywords

cholesterol; inflammation; lipid metabolism; regression

Abstract

Diet and exercise are recommended both as a prophylactic and as a therapeutic approach for patients with established coronary artery disease. We previously reported that sesame oil (SESO) and its aqueous extract (SOAE) showed antiatherosclerotic and anti-inflammatory properties. We also observed that genes involved in reverse cholesterol transport (RCT) might be activated. In this study, we tested whether post-treatment with SESO or SOAE would reduce preexisting atherosclerosis by enhancing RCT. Female low-density lipoprotein receptor knockout (LDL-R-/-) mice were fed an atherogenic diet for 3 months, followed by post-treatment with either control or SESO or SOAE for 1 month. Plasma lipids and atherosclerotic lesions were quantified at the end of the study. RNA was extracted from the aortic tissues and used for real-time polymerase chain reaction analysis. SESO and SOAE post-treatment significantly reduced atherosclerotic lesions in LDL-R-/- mice compared to controls. No significant change in plasma cholesterol, triglyceride, or LDL cholesterol levels was observed. Aortic gene analysis showed that the SESO/SOAE post-treatment reduced inflammatory gene expression and induced genes involved in cholesterol metabolism and RCT. This is the first study that demonstrates that post-treatment with SESO and SOAE could be an effective treatment for preexisting atherosclerosis and inflammation. The study also may suggest that reducing inflammation might be conducive to an accelerated regression of lesions.

Publication Date

7-1-2018

Publication Title

Journal of Medicinal Food

Volume

21

Issue

7

Number of Pages

641-646

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1089/jmf.2018.0032

Socpus ID

85050291762 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85050291762

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