Integrating Omics into Endocannabinoid Research: a Paradigm Shift Toward a System-Level Understanding of a Dynamic Biological Network

Abstract

Originally identified as the molecular machinery responsible for mediating the effects of cannabis-derived compounds, the endocannabinoid system (ECS) is now recognized as having a role in the regulation of many biological processes. Its contribution to physiological homeostasis relies on the coordinated activity of cannabinoid receptors, endogenous lipid mediators, metabolic enzymes and interconnected signaling pathways. Despite substantial advances in ECS research, several aspects of its regulation and functional relevance remain not completely understood. Many studies have traditionally focused on individual molecular components, involving either cannabinoid receptors or specific enzymes responsible for endocannabinoid metabolism. Although these approaches have provided essential mechanistic knowledge, they may not fully represent the dynamic complexity of the ECS, whose activity varies according to genetic background, metabolic state, environmental factors, cellular identity, tissue context, and disease progression. The integration of omics may provide a broader framework for investigating this complex system. Genomics, transcriptomics, proteomics, lipidomics, and metabolomics offer complementary molecular perspectives that allow the ECS to be examined beyond individual pathways and within a systems biology context. These approaches may contribute to the identification of regulatory mechanisms, molecular signatures associated with diseases, potential biomarkers, and factors influencing therapeutic response. The convergence of endocannabinoid biology and multi-omics technologies may support a more comprehensive representation of the ECS as a multidimensional and context-dependent biological network. This perspective paper discusses the current contribution of omics to the study of ECS physiology and dysfunction, together with their potential applications and the methodological and translational challenges that still need to be addressed.