Transcriptomic Evidence of Acquired Cannabis Hypersensitivity in Cannabinoid Hyperemesis Syndrome

Cannabinoid hyperemesis syndrome (CHS) is a paradoxical and increasingly prevalent disorder characterized by recurrent vomiting in people with chronic cannabis use. Despite its growing clinical impact, the underlying mechanisms remain poorly understood. Contrary to prevailing hypotheses implicating the endogenous cannabinoid system (ECS), we found no significant changes in ECS-related transcripts. Instead, CHS was associated with marked activation of the adaptive immune system, including upregulation of B-cell related immunoglobin transcripts and altered expression of T cell, monocyte, and neutrophil-related transcripts. DEGs also suggested increased matrix degradation, and reduced adhesion and protease inhibitor transcripts, consistent with impaired gut barrier function. Digital HLA isotyping revealed increased MHC Class I expression, Class II allele restriction, and down-regulation of IgE receptor transcripts, a known response to elevated IgE levels in allergic hypersensitivity. Together, these findings suggest that CHS may represent an acquired, gut-restricted, immune-mediated hypersensitivity response to cannabis. This transcriptomic analysis provides new mechanistic insights into CHS and lays groundwork for future studies to identify biomarkers, clarify immune triggers, and develop targeted therapies. A genome-wide RNA sequencing was used to characterize transcriptomic differences and identify potential pathways involved in CHS pathogenesis. In this pilot study, whole blood RNA sequencing was performed on 7 patients with CHS and 7 matched controls. Differentially expressed genes (DEGs) were identified, annotated and analyzed by automated and manual analysis. RNA sequences were further analyzed by digital isotyping for HLA Class I and II allele usage. *************************************************************** Raw files for human/patient samples were not submitted to GEO due to concerns about submitting personally identifiable sequence data for open access. ***************************************************************