Bayesian colocalization of psychiatric disorder GWAS signals with molecular quantitative trait loci highlights histone involvement and neuroimmune dysregulation in pathogenesis.

Bayesian colocalization of psychiatric disorder GWAS signals with molecular quantitative trait loci highlights histone involvement and neuroimmune dysregulation in pathogenesis.

Publication date: Oct 01, 2026

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

Concepts Keywords
Autism Spectrum Disorder
Bayes Theorem
Bipolar Disorder
Bipolar disorder
Colocalization
GABAergic neurotransmission
Genome-Wide Association Study
Histone
Histones
Histones
Humans
Major Depressive Disorder
Major depressive disorder
Mental Disorders
Neuroimmunomodulation
Quantitative Trait Loci
Schizophrenia
Schizophrenia

Semantics

Type Source Name
disease MESH psychiatric disorder
disease MESH autism spectrum disorder
disease MESH bipolar disorder
disease MESH major depressive disorder
disease MESH schizophrenia
disease MESH included
disease MESH Attention Deficit Disorder with Hyperactivity
disease MESH Genetic Predisposition to Disease

Original Article

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