Mapping the genetic landscape across 14 psychiatric disorders

Abstract

Psychiatric disorders display high levels of comorbidity and genetic overlap1,2, challenging current diagnostic boundaries. For disorders for which diagnostic separation has been most debated, such as schizophrenia and bipolar disorder3, genomic methods have revealed that the majority of genetic signal is shared4. While over a hundred pleiotropic loci have been identified by recent cross-disorder analyses5, the full scope of shared and disorder-specific genetic influences remains poorly defined. Here we addressed this gap by triangulating across a suite of cutting-edge statistical and functional genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders (1,056,201 cases). Using genetic association data from common variants, we identified and characterized five underlying genomic factors that explained the majority of the genetic variance of the individual disorders (around 66% on average) and were associated with 238 pleiotropic loci. The two factors defined by (1) Schizophrenia and bipolar disorders (SB factor); and (2) major depression, PTSD and anxiety (Internalizing factor) showed high levels of polygenic overlap6 and local genetic correlation and very few disorder-specific loci. The genetic signal shared across all 14 disorders was enriched for broad biological processes (for example, transcriptional regulation), while more specific pathways were shared at the level of the individual factors. The shared genetic signal across the SB factor was substantially enriched in genes expressed in excitatory neurons, whereas the Internalizing factor was associated with oligodendrocyte biology. These observations may inform a more neurobiologically valid psychiatric nosology and implicate targets for therapeutic development designed to treat commonly occurring comorbid presentations. Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

The authors' abstract, as published at the source. Nature, 2025 · DOI ↗