Retrograde Endocannabinoid Signaling Shows Robust Enrichment in Bipolar Disorder: Insights from Standardized Pathway Analyses

Background and Rationale: Bipolar disorder is among the most heritable psychiatric conditions, yet its polygenic architecture is far from fully accounted for by models that foreground synaptic pruning and calcium signaling. The endocannabinoid system, which plays a well-documented role in modulating synaptic plasticity, stress reactivity, and affective stability, has received comparatively little attention as a source of independent genetic liability. This study set out to test whether standardized endocannabinoid signaling pathways contribute to bipolar disorder risk in their own right. Methods: The analysis drew on summary statistics from the largest published European-ancestry genome-wide association study of bipolar disorder (O'Connell et al., 2025; effective sample approximately 137,097, after exclusion of UK Biobank and 23andMe participants). Three publicly curated endocannabinoid gene sets were obtained from the Molecular Signatures Database: the Gene Ontology Biological Process Cannabinoid Signaling Pathway (9 genes), the WikiPathways Cannabinoid Receptor Signaling set (29 genes), and the KEGG Retrograde Endocannabinoid Signaling pathway (148 genes). These were benchmarked against a negative control comprising housekeeping genes (182 genes) and a positive control of monoaminergic system genes (101 genes). Partial overlap between sets was retained so as not to distort their biological meaning. Three complementary post-GWAS approaches were applied: competitive gene-set enrichment testing through MAGMA version 1.10, using a window of 35 kilobases upstream and 10 kilobases downstream; partitioned linkage disequilibrium score regression for heritability enrichment, with annotations extended 10 kilobases in each direction and one-tailed testing against a European 1000 Genomes linkage disequilibrium reference; and transcriptome-wide association analysis via S-PrediXcan, employing GTEx version 8 MASHR prediction models across eight brain tissues, with tibial artery included as a peripheral control. Results: The KEGG and WikiPathways endocannabinoid sets showed consistent enrichment across all three analytic frameworks. In the MAGMA analysis, both survived Bonferroni correction for five tests (KEGG, p = .003; WikiPathways, p = .035). Partitioned linkage disequilibrium score regression yielded the strongest heritability enrichment for the KEGG set (1.61-fold after linkage disequilibrium adjustment; one-tailed p = 1.79 times 10 to the negative third), with the WikiPathways set following at 1.13-fold. In the S-PrediXcan analysis, absolute Z-score distributions were notably elevated for both pathways (WikiPathways, 1.61-fold enrichment, p = 2.48 times 10 to the negative sixth; KEGG, 1.25-fold, p = 2.99 times 10 to the negative fifth). DAGLA, encoding the principal synthetic enzyme for the endocannabinoid 2-arachidonoylglycerol, was implicated repeatedly, including through significantly lower predicted expression in the frontal cortex (Brodmann area 9). The monoaminergic positive control and the smaller Gene Ontology set performed in line with expectations or were likely underpowered, while housekeeping genes showed only modest baseline enrichment. Conclusions and Implications: Taken together, these convergent results point to polygenic variation within core endocannabinoid signaling machinery as a contributor to bipolar disorder susceptibility that is not reducible to previously emphasised synaptic or calcium-dependent pathways. The findings sharpen mechanistic accounts of bipolar disorder and lay a biological groundwork for future stratified clinical trials of non-intoxicating endocannabinoid modulators, such as cannabidiol, particularly among individuals whose risk profiles are shaped by endocannabinoid-related polygenic scores. Realising the translational potential of these observations will require larger multi-ancestry investigations that incorporate single-cell transcriptomic and lipidomic data.