Foodomics reveals anti-obesity properties of cannabinoids from hemp oil

Scope: Molecular networking (MN) analysis intends to provide chemical insight of untargeted mass spectrometry (MS) data to the user’s underlying biological questions. Foodomics is the study of chemical compounds in food using advanced omics methods. In this study, we developed an MS-MN-based foodomics approach to investigate the composition and anti-obesity activity of cannabinoids in hemp oil.

Methods and results: A total of 16 cannabinoids were determined in optimized microwave pretreatment of hemp oil using the developed approach. Untargeted metabolomics analysis revealed that cannabinoid extract (CE) and its major constituent (cannabidiol, CBD), could alleviate high glucose-induced increases in lipids and carbohydrates, and decreases in amino acid and nucleic acid. Moreover, CE and CBD were also found to suppress the expression levels of mdt-15, sbp-1, fat-5, fat-6, fat-7, daf-2, and elevate the expression level of daf-1,daf-7, daf-16, sod-3, gst-4, lipl-4, resulting in the decrease of lipid synthesis and the enhance of kinetism. Canonical correspondence analysis (CCA) uncovered strong associations between specific metabolic alterations and gene expression levels.

Conclusion: These findings from this exploratory study offered a new insight into the roles of cannabinoids in the treatment of obesity and related complications. This article is protected by copyright. All rights reserved.