Shared Genetic Foundations of Schizophrenia & Bipolar Disorder
Large-scale GWAS reveal a deeply overlapping polygenic landscape — thousands of common variants each exerting small additive effects across both conditions.
~270Genome-wide significant loci in schizophrenia (PGC3, 2022)
~64Genome-wide significant loci in bipolar disorder (PGC BPD3, 2021)
rg ≈ 0.70Genetic correlation between SCZ and BPD
>100KCommon SNPs contribute meaningfully to polygenic risk scores
Genetic Overlap Architecture
Genetic Correlation & Representative Effect Sizes
LD-score regression rg SCZ ↔ BPD
Top locus odds ratios
CACNA1COR 1.15
ANK3OR 1.18
MHC / HLA regionOR 1.22
NRXN1OR 1.12
GRIN2AOR 1.10
Most common variants have small individual effects (OR 1.05–1.25). Polygenicity arises from their large number acting additively.
Schematic Manhattan Profile — Key Chromosomal Regions
Multivariate genomic SEM, fine-mapping, and functional annotation refine shared causal variants. PRS explain ~4–9% of liability variance in held-out samples.
Horizon
Ancestrally diverse biobanks and single-cell genomics aim to resolve cell-type-specific mechanisms and improve global transferability of polygenic scores.
Sources: PGC SCZ3 (Trubetskoy et al., Nature 2022) · PGC BPD3 (Mullins et al., Nature Genetics 2021) · Cross-Disorder Group (Anttila et al., Science 2018; Lee et al., Nature Genetics 2019) h² = twin-based heritability · SNP h² = common-variant narrow-sense heritability · rg = genetic correlation · OR = odds ratio · GWS = genome-wide significant (p < 5×10⁻⁸) · CNV = copy number variant