Bayesian colocalization of psychiatric disorder GWAS signals with molecular quantitative trait loci highlights...

Genome-wide association studies (GWAS) have revolutionized our understanding of the genetic architecture of psychiatric disorders. However, the interpretation of these findings remains challenging, as most risk loci reside in non-coding regions, obscuring the underlying molecular mechanisms. To elucidate the functional consequences of psychiatric risk variants, we implemented a multi-omics Bayesian colocalization framework using transcript, protein and metabolite levels for attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder (BIP), major depressive disorder (MDD), and schizophrenia (SCZ). Sixty-five SCZ, BIP, and MDD GWAS signals colocalized with immune cell-type-specific expression quantitative trait loci (eQTL), targeting 70 genes. Notably, they included 17 histone-encoding genes colocalized from five GWAS signals. These signals subsequently colocalized with protein QTL (pQTL), targeting 310 proteins enriched in various immune-related pathways (P < 5.99 × 10^⁻12). Further colocalization with metabolite QTL (metabQTL) revealed 23 metabolites, highlighting GABAergic neurotransmission, norepinephrine metabolism, and androgenic neurosteroid pathways. Considering critical histone function as damage-associated molecular patterns, variability in histone expression might have contributed to neuroimmune mechanisms and thus the pathogenesis of the psychiatric disorders. This study underscores the role of common nucleotide variants regulating histone genes in neuroimmune mechanisms contributing to SCZ, BIP, and MDD. These findings enhance our understanding of underlying molecular targets in their pathophysiology, with a potential strategy of precision psychiatry.