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Exploring the genetic overlap between twelve psychiatric disorders

Nature Genetics volume 54, pages 1795–1802 (2022)Cite this article

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Abstract

The widespread comorbidity among psychiatric disorders demonstrated in epidemiological studies1,2,3,4,5 is mirrored by non-zero, positive genetic correlations from large-scale genetic studies6,7,8,9,10. To identify shared biological processes underpinning this observed phenotypic and genetic covariance and enhance molecular characterization of general psychiatric disorder liability11,12,13, we used several strategies aimed at uncovering pleiotropic, that is, cross-trait-associated, single-nucleotide polymorphisms (SNPs), genes and biological pathways. We conducted cross-trait meta-analysis on 12 psychiatric disorders to identify pleiotropic SNPs. The meta-analytic signal was driven by schizophrenia, hampering interpretation and joint biological characterization of the cross-trait meta-analytic signal. Subsequent pairwise comparisons of psychiatric disorders identified substantial pleiotropic overlap, but mainly among pairs of psychiatric disorders, and mainly at less stringent P-value thresholds. Only annotations related to evolutionarily conserved genomic regions were significant for multiple (9 out of 12) psychiatric disorders. Overall, identification of shared biological mechanisms remains challenging due to variation in power and genetic architecture between psychiatric disorders.

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Fig. 1: SNP-based heritability, genetic correlations and cross-trait meta-analysis lead SNP P values of the 12 psychiatric disorders.
Fig. 2: Schematic overview of all annotation analyses conducted on 12 psychiatric disorders.
Fig. 3: Results of Fisher’s exact tests for gene enrichment overlap across 12 psychiatric disorders.
Fig. 4: Polygenicity and discoverability of nine psychiatric disorders.

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Data availability

GWAS summary statistics on ADHD, ASD, BIP, ANO, DEP, TS, OCD, alcohol use disorder and SCZ are publicly available for download at the psychiatric genomics consortium website: https://www.med.unc.edu/pgc/download-results/. Genome-wide summary statistics on INS are available at: https://ctg.cncr.nl/software/summary_statistics/. Genome-wide summary statistics on post-traumatic stress disorder and ANX were obtained from the Million Veteran Program (https://www.research.va.gov/mvp/) and transferred through correspondence with Daniel Levey (daniel.levey@yale.edu). All GWAS summary statistics are based on Human Genome Build 37 (GRCh37/hg19). Summary statistics from the cross-trait meta-analysis of 12 psychiatric disorders and of 11 psychiatric disorders excluding SCZ are available at https://ctg.cncr.nl/software/summary_statistics.

Precomputed LD scores were obtained from https://github.com/bulik/ldsc. Single-cell RNA sequencing data used for cell-type analyses were obtained from http://dropviz.org/. Gene information was obtained from the GeneCard database (v5.12.0 Build 702; https://www.genecards.org). Figure 2 and supplementary figure 1 were made with the help of the scientific illustration program BioRender (www.BioRender.com) with subscription including permission to published.

Code availability

All software (and version, where applicable) used to conduct the analyses in this paper are freely available online:

FUMA(v1.4.0) GWAS platform: http://fuma.ctglab.nl/

MAGMA(v.1.10) gene-based and gene property analysis: https://ctg.cncr.nl/software/magma

LAVA(v0.1.0) local genetic correlations: https://ctg.cncr.nl/software/lava

mvGWAMA(v0.0.2) and effective sample size calculation: https://github.com/Kyoko-wtnb/mvGWAMA

Functional categories for stratified heritability (BaselineLD; v2.2): https://alkesgroup.broadinstitute.org/LDSCORE/

Synaptic Gene Ontologies (v1.1) platform: https://www.syngoportal.org

Complex Trait Genetics Virtual Lab platform (beta-0.4): https://view.genoma.io/

MiXeR (v1.3) Analysis: https://github.com/precimed/mixer

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Acknowledgements

C.R., D.P. and S.v.d.S were funded by Netherlands Organization for Scientific Research (NWO; Gravitation: BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology; grant 024.004.012 to D.P.). P.R.J. was funded by the Netherlands Organization for Scientific Research (ZonMW VENI-09150162010138 to P.R.J.). D.P., J.W. and C.d.L. were funded by the Netherlands Organization for Scientific Research (NWO VICI 453-14-005 to D.P.), and M.N., D.P., J.W. and C.d.L. were funded a European Research Council advanced grant (ERC-2018-AdG GWAS2FUNC 834057 to D.P.). The analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO 480-05-003), VU University (Amsterdam, the Netherlands) and the Dutch Brain Foundation and hosted by the Dutch National Computing and Networking Services SurfSARA. This research was conducted using the UK Biobank resource under application number 16406 and is based in part on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, supported by awards CSP 575B and Merit 1|01CX001849.e. We thank the numerous participants, researchers and staff from many studies who collected and contributed to the data. In particular, we would like to express our gratitude to all UK Biobank and Million Veteran Program participants who have been so generous to share their data for analysis. Figure 2 and Supplementary Figure 1 were created with BioRender.com. These figures were, in part, adapted from the ‘Central Dogma’, ‘Expression of ACE2 Receptor in Human Host Tissues’ and ‘Notch Signaling Pathway’ templates by BioRender.com (2020) and can be retrieved from https://app.biorender.com/biorender-templates.

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Author notes

  1. These authors jointly supervised this work: Mats Nagel, Sophie van der Sluis.

Authors and Affiliations

  1. Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands

    Cato Romero, Danielle Posthuma & Sophie van der Sluis

  2. Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Josefin Werme, Philip R. Jansen, Christiaan de Leeuw, Danielle Posthuma & Mats Nagel

  3. Department of Human Genetics, section Clinical Genetic, Amsterdam University Medical Centers, Amsterdam, the Netherlands

    Philip R. Jansen

  4. VA Connecticut Healthcare System, Psychiatry Service, West Haven, CT, USA

    Joel Gelernter, Daniel Levey & Renato Polimanti

  5. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

    Joel Gelernter, Daniel Levey & Renato Polimanti

  6. VA San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA

    Murray B. Stein

  7. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA

    Murray B. Stein

  8. Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA

    Murray B. Stein

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Contributions

S.v.d.S and D.P. conceived of the study. C.R. and M.N. performed the main analyses. J.W. and C.d.L. were consulted on LAVA analyses and results. J.G., M.B.S, D.L. and R.P. conducted the original study on PTSD and provided early access to the PTSD and ANX summary statistics. C.R., M.N. and S.v.d.S. wrote the paper. All authors discussed the results and commented on the paper.

Corresponding author

Correspondence to Sophie van der Sluis.

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Competing interests

C.d.L. is funded by Hoffman-La Roche. The other authors declare no competing interests.

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Nature Genetics thanks Na Cai and Duncan Palmer for their contribution to the peer review of this work. Peer reviewer reports are available.

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Table of contents, Supplementary Figures 1–27, Notes 1–7 and References.

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Romero, C., Werme, J., Jansen, P.R. et al. Exploring the genetic overlap between twelve psychiatric disorders. Nat Genet 54, 1795–1802 (2022). https://doi.org/10.1038/s41588-022-01245-2

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