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Cross-ancestry genetic architecture reveals shared biological pathways of major psychiatric disorders

Molecular Psychiatry (2026)Cite this article

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Abstract

Psychiatric disorders, including bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), share substantial genetic overlap. We conducted a cross-ancestry multivariate genome-wide association study (GWAS) integrating European and East Asian populations to uncover shared genetic underpinnings. Our analyses identified 403 loci associated with shared polygenic liability to psychiatric disorders, including 88 novel regions. Cross-ancestry fine-mapping highlighted robust shared signals, notably at VRK2 (rs7596038), consistently significant across ancestries. Gene prioritization revealed 90 high-confidence candidate genes enriched in neurodevelopmental pathways. Single-nucleus RNA sequencing implicated excitatory neurons and astrocytes as key cellular contexts, emphasizing NCAM1–FGFR1 and NEGR1–NEGR1 signaling pathways. Mendelian randomization analyses provided causal evidence linking shared genetic liability to structural brain alterations, particularly in regions crucial for emotion and cognition. Polygenic risk scores derived from shared genetic liability substantially enhanced predictive accuracy for BD and SCZ, demonstrating strong trans-ancestry validity. These results advance understanding of shared genetic architecture in psychiatric disorders, highlighting potential therapeutic targets and emphasizing the critical importance of diverse ancestry studies in precision psychiatry.

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Fig. 1: Workflow.
Fig. 2: Polygenic overlaps between distinct psychiatric disorders.
Fig. 3: Cross-ancestry multivariate GWAS of shared liability to BD, MDD, and SCZ in EAS and EUR populations.
Fig. 4: Summary for the enrichment analysis from the top significant genes defined by six gene-level methods.
Fig. 5: Cell-type-specific expression and intercellular signaling mechanisms associated with cross-disorder genetic risk.
Fig. 6: Effect size of genetic liability for BD, MDD, SCZ, and cross-disorder liability.

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Data availability

The summary statistics of BD, MDD, and SCZ in two ancestries are available here: https://pgc.unc.edu/for-researchers/download-results/.  The summary statistics of eQTL are available from GTEx: https://yanglab.westlake.edu.cn/software/smr/#eQTLsummarydata. The snRNA-seq data is available from https://www.ncbi.nlm.nih.gov/geo/. The gene specificity data per cell type for enrichment analysis is available from https://www.nature.com/articles/s41467-024-55611-1#Sec50. The summary statistics of IDPs are available from here: https://www.ebi.ac.uk/gwas/. The reference panel of two ancestries are available from 1000 Genomes Project: https://www.internationalgenome.org/data/. The UK Biobank data are available to any bona fide researcher following application: https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access. The data of CLASS-BD are available from the corresponding author upon reasonable request.

Code availability

Packages including ‘LAVA’ (version 1.0), ‘GenomicSEM’ (version 0.05), ‘MeSuSiE’ (version 1.0), ‘TwoSampleMR’ (version 0.6.6) and ‘survival’ (version 3.8-3) in R version 4.3.3 were used to perform local genetic correlation, gSEM model, cross-ancestry fine-mapping, Mendelian randomization, and survival analysis. Seurat (version 5.3.0), CellChat (version 2.1.0) in R were used to perform snRNA-seq data processing and cell-cell communication analysis. MiXeR (version 1.2) was used to estimate genetic overlapping. METAL was used to perform GWAS meta-analysis. LDSC (version 1.0.1) were used to perform genetic correlation analysis and enrichment analysis. mBAT (GCTA, version 1.94.1), FUMA, SMR (version 1.4.0), TWAS, PoPS, and PsyOPS were used to identify the pleiotropic genes. DBSLMM (version 1.0), PRS-CSx and PLINK2 were used to estimate in- and cross-ancestry PRS.

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Acknowledgements

We thank the GWAS Catalog, the Psychiatric Genomics Consortium, 1000 Genomes Project, and UK Biobank (Application 144904) for access to genome-wide association study data, and all research participants who provided DNA samples for these studies.

Funding

The study was supported by funding from the National Natural Science Foundation of China (82571735, 82173585), Key R&D Program of Zhejiang Province (2024C03098, 2025C02109), and The National Key Research and Development Program of China (2023YFC2506200, 2023YFC2506203).

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Author notes

  1. These authors contributed equally: Yu Feng, Ningning Jia.

Authors and Affiliations

  1. Department of Psychiatry, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    Yu Feng & Shaohua Hu

  2. Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China

    Ningning Jia & Shaohua Hu

  3. Department of Epidemiology, Centre for Global Health, School of Public Health, National Vaccine Innovation Platform, Key Laboratory of Public Health Safety and Emergency Prevention and Control Technology of Higher Education Institutions in Jiangsu Province, Nanjing Medical University, Nanjing, Jiangsu, 211166, China

    Peng Huang

  4. Nanhu Brain-computer Interface Institute, Hangzhou, Zhejiang, China

    Shaohua Hu

  5. The Zhejiang Key Laboratory of Precision Psychiatry, Hangzhou, 310003, China

    Shaohua Hu

  6. The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China

    Shaohua Hu

  7. MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University School of Medicine, Hangzhou, 310003, China

    Shaohua Hu

  8. Brain Research Institute of Zhejiang University, Hangzhou, 310003, China

    Shaohua Hu

  9. Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, 310003, China

    Shaohua Hu

  10. Division of Pediatric Pulmonary Medicine, UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, 15224, USA

    Sheng Yang

Authors
  1. Yu Feng
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  2. Ningning Jia
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  3. Peng Huang
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  4. Shaohua Hu
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  5. Sheng Yang
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Contributions

S.H. and S.Y. conceived and designed the study. Y.F., N.J., and P.H. analyzed the data. Y.F., N.J., and P.H. interpreted the findings. Y.F., S.Y., and S.H. drafted or substantively revised the paper.

Corresponding authors

Correspondence to Shaohua Hu or Sheng Yang.

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Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Ethical approval of UK Biobank study was granted by the National Health Service National Research Ethics Service (reference 11/NW/0382). Ethical approval of Chinese Longitudinal and Systematic Study of Bipolar Disorder was granted by the Medical Research Ethics Committee, and all participants provided written informed consent (Approval number: 2017-397). Written informed consent was secured from all participants and their legal guardians before they were enrolled in the study. It was a single-center study conducted at the First Affiliated Hospital, Zhejiang University School of Medicine (Clinical trial registration number: NCT05480150). All methods were performed in accordance with the relevant guidelines and regulations.

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Feng, Y., Jia, N., Huang, P. et al. Cross-ancestry genetic architecture reveals shared biological pathways of major psychiatric disorders. Mol Psychiatry (2026). https://doi.org/10.1038/s41380-026-03541-3

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