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Comparison of the multivariate genetic architecture of eight major psychiatric disorders across sex

Nature Genetics volume 57, pages 583–590 (2025)Cite this article

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Abstract

Differences in the patterning of genetic sharing between groups of individuals may arise from biological pathways, social mechanisms, phenotyping and ascertainment. We expand genomic structural equation modeling to allow for testing genomic structural invariance (GSI), that is, the formal comparison of multivariate genetic architecture across groups. We apply GSI to compare the autosomal multivariate genetic architecture of eight psychiatric disorders spanning three factors (psychotic, neurodevelopmental and internalizing) between cisgender males and females. We find that the genetic factor structure is largely similar across sex, permitting meaningful comparisons of associations at the level of the factors. However, in females, problematic alcohol use and posttraumatic stress disorder loaded more strongly on the internalizing factor, while the neurodevelopmental disorder factor exhibited weaker genetic correlations with the other factors. Four phenotypes (educational attainment, insomnia, smoking and deprivation) showed significant, albeit small, sex-differentiated associations with the psychotic factor. As genome-wide association study samples grow and diversify, GSI will become increasingly valuable for comparing multivariate genetic architecture across groups.

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Fig. 1: Patterns of sex-stratified genetic associations.
Fig. 2: Genetic correlations between disorder factors and relevant biobehavioral phenotypes among males and females.

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Data availability

Disorder-level summary statistics from previously published GWAS can be found at the citations in Table 1. Factor-level, sex-stratified summary statistics and sex-stratified GWAS summary statistics for PTSD and alcohol problems produced for this study are available at https://osf.io/spg7f/ (ref. 59); see the Supplementary Note for complete information on these phenotypes. The sex-stratified eight-disorder LDSC object that can be used to reproduce the results is available at https://osf.io/pd4fx (ref. 59).

Code availability

A tutorial for conducting GSI analyses and estimating localSRMD is available at https://rpubs.com/tedooooooooooo/localsrmd (ref. 59). The R code for all genomic SEM analyses can be found at https://osf.io/wya8p (ref. 59).

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Acknowledgements

This work was supported by a National Institutes of Health (NIH) grant no. R01MH120219. E.M.T.-D. is a faculty associate of the Population Research Center and the Center on Aging and Population Sciences at the University of Texas at Austin, which are supported by NIH grant nos. P2CHD042849 and P30AG066614, respectively.

Author information

Authors and Affiliations

  1. Department of Psychology, Michigan State University, East Lansing, MI, USA

    Ted Schwaba

  2. Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  3. Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA

    Travis T. Mallard & Jordan W. Smoller

  4. Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Travis T. Mallard, Phil H. Lee & Jordan W. Smoller

  5. Research Service, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA

    Adam X. Maihofer

  6. Department of Psychiatry, University of California, San Diego, CA, USA

    Adam X. Maihofer

  7. Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA

    Adam X. Maihofer

  8. Department of Psychology, University of California, Davis, Davis, CA, USA

    Mijke Rhemtulla

  9. Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA

    Phil H. Lee & Jordan W. Smoller

  10. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA

    Lea K. Davis

  11. Division of Data Driven and Digital Medicine, Department of Medicine, Mount Sinai Hospital, New York City, NY, USA

    Lea K. Davis

  12. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK

    Michel G. Nivard

  13. MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK

    Michel G. Nivard

  14. Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA

    Andrew D. Grotzinger

  15. Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA

    Andrew D. Grotzinger

  16. Department of Psychology, University of Texas at Austin, Austin, TX, USA

    Elliot M. Tucker-Drob

  17. Population Research Center, University of Texas at Austin, Austin, TX, USA

    Elliot M. Tucker-Drob

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  1. Ted Schwaba
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  2. Travis T. Mallard
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  3. Adam X. Maihofer
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  10. Elliot M. Tucker-Drob
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Contributions

T.S. and E.M.T.-D. designed the study and wrote the manuscript. T.S. conducted the multivariate analyses. T.T.M. and A.X.M. contributed new genome-wide analyses. T.S., E.M.T.-D., M.R. and M.G.N. conceptualized the statistical tests. L.K.D. consulted on the role of sex as a biological variable. T.T.M., A.X.M., M.R., P.H.L., J.W.S., L.K.D., M.G.N. and A.D.G. provided manuscript feedback and editing.

Corresponding author

Correspondence to Ted Schwaba.

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Nature Genetics thanks Jonathan Coleman, Frank Wendt and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary information

Supplementary Information

Supplementary localSRMD guide, Figs. 1–15 and Discussion.

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Supplementary Table 1

Supplementary Tables 1–18.

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Schwaba, T., Mallard, T.T., Maihofer, A.X. et al. Comparison of the multivariate genetic architecture of eight major psychiatric disorders across sex. Nat Genet 57, 583–590 (2025). https://doi.org/10.1038/s41588-025-02093-6

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