REFERENCES
1. Feng Y, Jia N, Huang P, Hu S, Yang S. Cross-ancestry genetic architecture reveals shared biological pathways of major psychiatric disorders. Mol Psychiatry. 2026;31:4083-95.
2. Grotzinger AD, Rhemtulla M, de Vlaming R, et al. Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nat Hum Behav. 2019;3:513-25.
3. Mallard TT, Linnér RK, Grotzinger AD, et al. ; Bipolar Disorder Working Group of the Psychiatric Genomics Consortium. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities. Cell Genom. 2022;2:100140.
4. Lam M, Chen CY, Li Z, et al. ; Schizophrenia Working Group of the Psychiatric Genomics Consortium, Indonesia Schizophrenia Consortium, Genetic REsearch on schizophreniA neTwork-China and the Netherlands (GREAT-CN). Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet. 2019;51:1670-8.
5. Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.
6. Zhu Z, Zhang F, Hu H, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481-7.
7. Fröhlich AS, Gerstner N, Gagliardi M, et al. Single-nucleus transcriptomic profiling of human orbitofrontal cortex reveals convergent effects of aging and psychiatric disease. Nat Neurosci. 2024;27:2021-32.
8. Jaffe AE, Gao Y, Deep-Soboslay A, et al. Mapping DNA methylation across development, genotype and schizophrenia in the human frontal cortex. Nat Neurosci. 2016;19:40-7.
9. Bryois J, Garrett ME, Song L, et al. Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun. 2018;9:3121.
10. Gerstner N, Fröhlich AS, Matosin N, et al. Contrasting genetic predisposition and diagnosis in psychiatric disorders: a multi-omic single-nucleus analysis of the human OFC. Sci Adv. 2025;11:eadq2290.
11. Hemani G, Zheng J, Elsworth B, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7:e34408.
12. Ruan Y, Lin YF, Feng YA, et al. ; Stanley Global Asia Initiatives. Improving polygenic prediction in ancestrally diverse populations. Nat Genet. 2022;54:573-80.
