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Abstract

Bipolar disorder (BD) is a heritable mental illness with complex etiology. We performed a genome-wide association study (GWAS) of 41,917 BD cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. BD risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating eQTL data implicated 15 genes robustly linked to BD via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of BD subtypes indicated high but imperfect genetic correlation between BD type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of BD, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

02 /Specification & Classification

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In-depth summary

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Claude Opus 5.5 · max effort · 8 Nov 2026 · from the full text of version 2 (27 Mar 2021) · CC BY 4.0

Meta-analysis of 41,917 European-ancestry bipolar disorder cases versus 371,549 controls yields 64 risk loci (33 novel), neuronal and synaptic gene enrichment, and 15 eQTL-prioritized genes.

Twin and family studies put bipolar disorder (BD) heritability at 60-85%, but the prior Psychiatric Genomics Consortium GWAS (PGC2; 29,764 cases, 169,118 controls) found 30 loci, explaining only a fraction of genetic risk and leaving mechanisms unknown. With a 1.5-fold larger effective sample, this third PGC analysis more than doubles locus discovery and links risk to neuronal cell types, drug targets, expression-mediated genes and subtype differences.

Key results

  1. ShownThe meta-analysis detected 64 independent genome-wide significant loci, 33 new for BD; the major histocompatibility complex (MHC) signal, significant for the first time, is led by a variant outside classical HLA and C4 genes, and GWAS inflation mostly reflected polygenicity, not stratification.

    P < 5E-08 in 57 cohorts (effective N = 101,962); 28/30 PGC2 loci replicated; liability SNP-heritability 18.6% (SE=0.008, 2% prevalence); genomic inflation λGC 1.38 but attenuation ratio 0.06 (SE=0.02); 17 loci shared with schizophrenia and seven with major depression GWAS; MHC lead SNP rs13195402 is a BTN2A1 missense variant; imputed C4 alleles were not associated with BD. · GWAS results; MHC locus; Discussion

  2. ShownBD signal concentrated in synaptic signaling gene sets, in genes specifically expressed by excitatory and inhibitory neurons of cortex and hippocampus, and in targets of psycholeptic, calcium channel blocker, antiepileptic and anesthetic drugs.

    MAGMA: 161 of 19,576 genes and 4 synaptic gene sets (of 11,858) significant; enrichment for neuron-specific genes (mouse cortical/subcortical; human hippocampal pyramidal neurons, prefrontal/hippocampal interneurons; 5% FDR); mibefradil and nisoldipine target sets significant among 893 drug sets; four of 63 Anatomical Therapeutic Chemical drug classes enriched. · Enrichment analyses; Enrichment analyses; Discussion

  3. SuggestedIntegrating brain and blood expression quantitative trait locus (eQTL) data prioritized 15 genes whose BD association is consistent with mediation through expression, including druggable HTR6, MCHR1, DCLK3 and FURIN; many are not the nearest gene to the lead variant.

    FUSION TWAS with PsychENCODE weights (1,321 brain samples): 77 genes in 40 regions; FOCUS posterior inclusion probability (PIP) > 0.9 for 22 genes, > 0.7 for 32; 15 of those 32 significant in SMR (PsychENCODE or eQTLGen, 31,684 blood samples) and passing HEIDI; DCLK3 lies 87 kb upstream of top-locus gene TRANK1; HTR6/MCHR1 top eQTLs act oppositely in brain and blood. · eQTL integrative analyses; eQTL integrative analysis; Discussion

  4. ShownBD overlaps extensively with schizophrenia and major depression at the variant level, while its subtypes diverge: BD I shows higher SNP-heritability and closer genetic ties to schizophrenia, BD II to major depression, and their correlation falls short of 1.

    Genetic correlation (rg) 0.68 with schizophrenia (SCZ), 0.44 with major depression (MD); MiXeR: ~8.6 k BD-influencing variants, 97% shared with MD and 96% with SCZ, sign concordance 80% vs 69% (SCZ vs MD); BD I 44 loci, BD II one locus; liability SNP-heritability 20.9% vs 11.6%; BD I-BD II rg 0.85 (P=1.6E-03 vs 1); SCZ rg 0.66 vs 0.54, MD rg 0.34 vs 0.66 (BD I vs BD II). · Genetic architecture of BD and other traits; BD subtypes; Discussion

  5. ShownEuropean polygenic risk scores (PRS), built by leaving each target cohort out of discovery, explained modest liability-scale variance; full meta-analysis PRS explained less in East Asian and admixed African American samples, rising with European discovery size; authors deem PRS not yet clinically useful.

    European weighted mean liability R^2 4.57% (GWAS P threshold < 0.1, 2% prevalence; ~4% for PGC2-based PRS), weighted AUC 65%; top vs middle decile OR 3.5 (95% CI 1.7-7.3), vs lowest decile OR 9.3 (95% CI 1.7-49.3); R^2 up to 2.3% and 1.9% (two East Asian samples) vs 1.2% and 0.4% (two admixed African American samples). · Polygenic risk scoring; Polygenic risk scoring; Discussion; Introduction

Methods, data and reproducibility

Per-cohort logistic-regression GWAS on imputed genotypes were meta-analyzed (fixed-effects, inverse-variance), followed by LD score regression heritability/genetic correlation, MAGMA gene, cell-type and drug-target enrichment, TWAS/SMR eQTL integration, C4 imputation, leave-one-out PRS, MiXeR overlap models, GSMR Mendelian randomization and subtype GWAS.

  • 57 European-ancestry BD case-control cohorts (Europe, North America, Australia); 52 with individual-level data, five external (iPSYCH, deCODE, Estonian Biobank, HUNT, UK Biobank) · human · n = 41,917 cases; 371,549 controls (effective N = 101,962) · dbGaP phs001254.v1.p1 (PGC bundle; subset of cohorts)
  • BD I and BD II subtype GWAS meta-analyses (55 and 31 cohorts); subtypes in biobank cohorts assigned via ICD codes · human · n = BD I 25,060/449,978; BD II 6,781/364,075 (cases/controls)
  • Non-European PRS target samples: Japanese, Korean and two admixed African American BD cohorts (GAIN-AA, AA-GPC) · human · n = 5,847 cases; 65,588 controls
  • C4 structural-allele imputation in 47 PGC cohorts using a 2,530-haplotype reference built from 1,265 whole-genome-sequenced Genomic Psychiatry cohort individuals · human · n = 32,749 cases; 53,370 controls
  • PsychENCODE brain expression weights (FUSION TWAS) and brain eQTL summary statistics (SMR) · human · n = 1,321 brain samples
  • eQTLGen Consortium whole-blood cis-eQTL summary statistics used for SMR · human · n = 31,684 blood samples
  • Expression references for enrichment: brain single-cell RNA-seq from five adult human and mouse studies (e.g., Zeisel, Saunders) and GTEx V8 tissues · human and mouse · n = five scRNA-seq studies; 54 GTEx tissue types; 16,472 genes
  • LD Hub GWAS (255 published diseases/traits, 514 UK Biobank phenotypes) for genetic correlation; GWAS of BD-linked traits (e.g., smoking, sleep, alcohol, education) for MR · human · n = 255 + 514 traits (rg); 10 traits (MR)
Methods & tools
RICOPILI pipeline (version 2018_Nov_23.001) for QC, imputation and association, PLINK v1.90 (per-cohort logistic regression, clumping and PRS scoring), Eagle v2.3.5 and Minimac3 imputation to the HRC reference panel v1.0, METAL (version 2011-03-25) inverse-variance fixed-effects meta-analysis, LD Score regression (LDSC) and LD Hub, MAGMA v1.08 in FUMA v1.3.6a (gene, gene-set, tissue, cell-type and drug-set tests), FUSION transcriptome-wide association (TWAS; vOct 1, 2019) and FOCUS v0.6.10 fine-mapping, SMR v1.03 (summary-data-based Mendelian randomization) with HEIDI test, Beagle v4.1 for C4 structural-allele imputation, MiXeR v1.3 univariate and bivariate causal mixture models, GSMR (GCTA v1.93.1f beta), TwoSampleMR (IVW, MR-Egger) and MR-PRESSO, DGIdb v.2, Ki DB, MSigDB V7.0 and GTEx V8 reference resources
Software & environment
RICOPILI 2018_Nov_23.001; PLINK v1.90; EIGENSTRAT v6.1.4; Eagle v2.3.5 + Minimac3 (HRC v1.0); METAL 2011-03-25; MAGMA v1.08/FUMA v1.3.6a; FUSION vOct 1, 2019; FOCUS v0.6.10; SMR v1.03; Beagle v4.1; MiXeR v1.3; GCTA v1.93.1f beta; bedtools v2.29.2
Reproducibility gaps
Individual-level data require a collaborative analysis proposal to the PGC BD Working Group; five external cohorts shared only summary statistics; code statement cites third-party tools, with no study-specific pipeline repository.
Limitations (6)
  • Authors note current BD PRS cannot sort people into clinically meaningful risk groups: a top-decile OR of 3.5 versus the middle decile equates to only about 7% absolute lifetime risk, so PRS have no present clinical use. · stated by the authors
  • Discovery used European-ancestry samples only; PRS explained about 2% of variance in East Asian samples and much less in admixed African American samples (attributed to allele-frequency and LD differences), and authors call for larger non-European studies. · stated by the authors
  • Case heterogeneity is a stated concern: biobank cases (ICD codes or self-report) may be milder or more varied, per-wave SNP-heritability ranged from 24.6% (PGC1) to 11.9% (external studies), and BD heterogeneity may explain fewer loci than in a similar-sized schizophrenia GWAS. · stated by the authors
  • Authors treat Mendelian randomization as exploratory: the smoking-initiation effect on BD (OR 1.49) and bidirectional links with alcohol use, sleep duration, education and mood instability are not settled causal claims; cigarettes-per-day results disagreed across MR methods. · stated by the authors
  • None of the 15 eQTL-prioritized genes is functionally tested; SMR/HEIDI cannot separate causal mediation from pleiotropy, and opposite brain versus blood eQTL directions for HTR6 and MCHR1 leave the risk-raising direction of expression unclear. · noted in this summary
  • Subtype contrasts may partly reflect power and phenotyping: BD II had a much smaller effective N (22,560 vs 64,802 for BD I), limiting locus discovery, and ICD-code subtype assignment in biobanks could misclassify cases and bias heritability and rg comparisons. · noted in this summary

Who should read:Read this if you need PGC3 bipolar disorder loci, summary statistics, eQTL-prioritized candidate genes, drug-target enrichment or cross-disorder genetic overlap to seed functional, PRS or MR follow-up work.

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