Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Schizophrenia genomics: genetic complexity and functional insights

Nature Reviews Neuroscience volume 25, pages 611–624 (2024)Cite this article

Subjects

Abstract

Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The allelic spectrum of schizophrenia.
Fig. 2: A pathway from genomics to an aetiological theory of schizophrenia.

Similar content being viewed by others

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders 5th edn (American Psychiatric Association, 2013).

  2. World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Diagnostic Criteria for Research (World Health Organization, 1993).

  3. GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry 9, 137–150 (2022).

    Article  PubMed Central  Google Scholar 

  4. Knapp, M., Mangalore, R. & Simon, J. The global costs of schizophrenia. Schizophrenia Bull. 30, 279–293 (2004).

    Article  Google Scholar 

  5. Saha, S., Chant, D. & McGrath, J. A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time? Arch. Gen. Psychiatry 64, 1123–1131 (2007).

    Article  PubMed  Google Scholar 

  6. Jauhar, S., Johnstone, M. & McKenna, P. J. Schizophrenia. Lancet 399, 473–486 (2022).

    Article  CAS  PubMed  Google Scholar 

  7. McCutcheon, R. A., Reis Marques, T. & Howes, O. D. Schizophrenia — an overview. JAMA Psychiatry 77, 201–210 (2020).

    Article  PubMed  Google Scholar 

  8. Marder, S. R. & Cannon, T. D. Schizophrenia. N. Engl. J. Med. 381, 1753–1761 (2019).

    Article  CAS  PubMed  Google Scholar 

  9. Goff, D. C. The pharmacologic treatment of schizophrenia-2021. JAMA 325, 175–176 (2021).

    PubMed  Google Scholar 

  10. Hufner, K., Frajo-Apor, B. & Hofer, A. Neurology issues in schizophrenia. Curr. Psychiatry Rep. 17, 32 (2015).

    Article  PubMed  Google Scholar 

  11. McGrath, J., Saha, S., Chant, D. & Welham, J. Schizophrenia: a concise overview of incidence, prevalence, and mortality. Epidemiol. Rev. 30, 67–76 (2008).

    Article  PubMed  Google Scholar 

  12. Kahn, R. S. et al. Schizophrenia. Nat. Rev. Dis. Prim. 1, 15067 (2015).

    Article  PubMed  Google Scholar 

  13. Johnson, E. C. et al. The relationship between cannabis and schizophrenia: a genetically informed perspective. Addiction 116, 3227–3234 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Kendler, K. S. The prehistory of psychiatric genetics: 1780–1910. Am. J. Psychiatry 178, 490–508 (2021).

    Article  PubMed  Google Scholar 

  15. Lichtenstein, P. et al. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet 373, 234–239 (2009).

    Article  CAS  PubMed  Google Scholar 

  16. Lichtenstein, P. et al. Recurrence risks for schizophrenia in a Swedish national cohort. Psychol. Med. 36, 1417–1426 (2006).

    Article  PubMed  Google Scholar 

  17. Sullivan, P. F., Kendler, K. S. & Neale, M. C. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch. Gen. Psychiatry 60, 1187–1192 (2003).

    Article  PubMed  Google Scholar 

  18. Wray, N. R. & Gottesman, I. I. Using summary data from the Danish national registers to estimate heritabilities for schizophrenia, bipolar disorder, and major depressive disorder. Front. Genet. 3, 118 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sullivan, P. F. & Geschwind, D. H. Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders. Cell 177, 162–183 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Karayiorgou, M. et al. Schizophrenia susceptibility associated with interstitial deletions of chromosome 22q11. Proc. Natl Acad. Sci. USA 92, 7612–7616 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009).

    Article  PubMed Central  Google Scholar 

  22. Singh, T. et al. Rare loss-of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nat. Neurosci. 19, 571–577 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Morris, E., Inglis, A. & Austin, J. Psychiatric genetic counseling for people with copy number variants associated with psychiatric conditions. Clin. Genet. 102, 369–378 (2022).

    Article  CAS  PubMed  Google Scholar 

  24. CNV Working Group of the Psychiatric Genomics Consortium & Schizophrenia Working Group of the Psychiatric Genomics Consortium. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat. Genet. 49, 27–35 (2017).

  25. Singh, T. et al. Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature 604, 509–516 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Trubetskoy, V. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 604, 502–508 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

    Article  PubMed Central  Google Scholar 

  28. Szatkiewicz, J. et al. The genomics of major psychiatric disorders in a large pedigree from Northern Sweden. Transl. Psychiatry 9, 60 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Fu, J. M. et al. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat. Genet. 54, 1320–1331 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lam, M. et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat. Genet. 51, 1670–1678 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. McClellan, J. & King, M. C. Genomic analysis of mental illness: a changing landscape. JAMA 303, 2523–2524 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. Andrade-Guerrero, J. et al. Alzheimer’s disease: an updated overview of its genetics. Int. J. Mol. Sci. 24, 3754 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Halvorsen, M. et al. Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia. Nat. Commun. 11, 1842 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Murray, G. K. et al. Could polygenic risk scores be useful in psychiatry?: a review. JAMA Psychiatry 78, 210–219 (2021).

    Article  PubMed  Google Scholar 

  35. Visscher, P. M., Yengo, L., Cox, N. J. & Wray, N. R. Discovery and implications of polygenicity of common diseases. Science 373, 1468–1473 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wray, N. R. et al. From basic science to clinical application of polygenic risk scores: a primer. JAMA Psychiatry 78, 101–109 (2021).

    Article  PubMed  Google Scholar 

  37. Sullivan, P. F. et al. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 380, eabn2937 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Farrell, M. S. et al. Evaluating historical candidate genes for schizophrenia. Mol. Psychiatry 20, 555–562 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Franke, B. et al. Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat. Neurosci. 19, 420–431 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. van Erp, T. G. et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol. Psychiatry 21, 547–553 (2016).

    Article  PubMed  Google Scholar 

  42. Grasby, K. L. et al. The genetic architecture of the human cerebral cortex. Science 367, eaay6690 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gutman, B. A. et al. A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium. Hum. Brain Mapp. 43, 352–372 (2022).

    Article  PubMed  Google Scholar 

  44. Schijven, D. et al. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium. Proc. Natl Acad. Sci. USA 120, e2213880120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Boyle, E. A., Li, Y. I. & Pritchard, J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wray, N. R., Wijmenga, C., Sullivan, P. F., Yang, J. & Visscher, P. M. Common disease is more complex than implied by the core gene omnigenic model. Cell 173, 1573–1580 (2018).

    Article  CAS  PubMed  Google Scholar 

  47. Wainschtein, P. et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nat. Genet. 54, 263–273 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Pingault, J. B. et al. Using genetic data to strengthen causal inference in observational research. Nat. Rev. Genet. 19, 566–580 (2018).

    Article  CAS  PubMed  Google Scholar 

  49. Saccaro, L. F., Gasparini, S. & Rutigliano, G. Applications of Mendelian randomization in psychiatry: a comprehensive systematic review. Psychiatr. Genet. 32, 199–213 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Said, S. et al. Genetic analysis of over half a million people characterises C-reactive protein loci. Nat. Commun. 13, 2198 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Revez, J. A. et al. Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration. Nat. Commun. 11, 1647 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Christmas, M. J. et al. Evolutionary constraint and innovation across hundreds of placental mammals. Science 380, eabn3943 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Giniatullina, A. et al. Functional characterization of the PCLO p.Ser4814Ala variant associated with major depressive disorder reveals cellular but not behavioral differences. Neuroscience 300, 518–538 (2015).

    Article  CAS  PubMed  Google Scholar 

  54. Li, M. et al. A human-specific AS3MT isoform and BORCS7 are molecular risk factors in the 10q24.32 schizophrenia-associated locus. Nat. Med. 22, 649–656 (2016).

    Article  CAS  PubMed  Google Scholar 

  55. Rummel, C. K. et al. Massively parallel functional dissection of schizophrenia-associated noncoding genetic variants. Cell 186, 5165–5182 (2023).

    Article  CAS  PubMed  Google Scholar 

  56. Li, Y. E. et al. A comparative atlas of single-cell chromatin accessibility in the human brain. Science 382, eadf7044 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Dekker, J. Mapping the 3D genome: aiming for consilience. Nat. Rev. Mol. Cell Biol. 17, 741–742 (2016).

    Article  CAS  PubMed  Google Scholar 

  58. Won, H. et al. Chromosome conformation elucidates regulatory relationships in developing human brain. Nature 538, 523–527 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Tan, L. et al. Lifelong restructuring of 3D genome architecture in cerebellar granule cells. Science 381, 1112–1119 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Fiziev, P. & Ernst, J. ChromTime: modeling spatio-temporal dynamics of chromatin marks. Genome Biol. 19, 109 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. van Rossum, J. M. The significance of dopamine-receptor blockade for the mechanism of action of neuroleptic drugs. Arch. Int. Pharmacodyn. Ther. 160, 492–494 (1966).

    PubMed  Google Scholar 

  62. Howes, O. D. & Kapur, S. The dopamine hypothesis of schizophrenia: version III — the final common pathway. Schizophr. Bull. 35, 549–562 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Howes, O. D. & Onwordi, E. C. The synaptic hypothesis of schizophrenia version III: a master mechanism. Mol. Psychiatry 28, 1843–1856 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Osimo, E. F., Beck, K., Reis Marques, T. & Howes, O. D. Synaptic loss in schizophrenia: a meta-analysis and systematic review of synaptic protein and mRNA measures. Mol. Psychiatry 24, 549–561 (2019).

    Article  CAS  PubMed  Google Scholar 

  65. Trepanier, M. O., Hopperton, K. E., Mizrahi, R., Mechawar, N. & Bazinet, R. P. Postmortem evidence of cerebral inflammation in schizophrenia: a systematic review. Mol. Psychiatry 21, 1009–1026 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Weinstein, J. J. et al. Pathway-specific dopamine abnormalities in schizophrenia. Biol. Psychiatry 81, 31–42 (2017).

    Article  CAS  PubMed  Google Scholar 

  67. Davalieva, K., Maleva Kostovska, I. & Dwork, A. J. Proteomics research in schizophrenia. Front. Cell Neurosci. 10, 18 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Laskaris, L. E. et al. Microglial activation and progressive brain changes in schizophrenia. Br. J. Pharmacol. 173, 666–680 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Schwerk, A., Alves, F. D., Pouwels, P. J. & van Amelsvoort, T. Metabolic alterations associated with schizophrenia: a critical evaluation of proton magnetic resonance spectroscopy studies. J. Neurochem. 128, 1–87 (2014).

    Article  CAS  PubMed  Google Scholar 

  70. Dean, B. Neurochemistry of schizophrenia: the contribution of neuroimaging postmortem pathology and neurochemistry in schizophrenia. Curr. Top. Med. Chem. 12, 2375–2392 (2012).

    Article  CAS  PubMed  Google Scholar 

  71. Gonzalez-Burgos, G. & Lewis, D. A. NMDA receptor hypofunction, parvalbumin-positive neurons, and cortical gamma oscillations in schizophrenia. Schizophr. Bull. 38, 950–957 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Sohal, V. S. Neurobiology of schizophrenia. Curr. Opin. Neurobiol. 84, 102820 (2023).

    Article  PubMed  Google Scholar 

  73. Glantz, L. A. & Lewis, D. A. Decreased dendritic spine density on prefrontal cortical pyramidal neurons in schizophrenia. Arch. Gen. Psychiatry 57, 65–73 (2000).

    Article  CAS  PubMed  Google Scholar 

  74. Dienel, S. J., Fish, K. N. & Lewis, D. A. The nature of prefrontal cortical GABA neuron alterations in schizophrenia: markedly lower somatostatin and parvalbumin gene expression without missing neurons. Am. J. Psychiatry 180, 495–507 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Aryal, S. et al. Deep proteomics identifies shared molecular pathway alterations in synapses of patients with schizophrenia and bipolar disorder and mouse model. Cell Rep. 42, 112497 (2023).

    Article  CAS  PubMed  Google Scholar 

  76. Walker, R. L. et al. Genetic control of expression and splicing in developing human brain informs disease mechanisms. Cell 179, 750–771 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Benjamin, K. J. M. et al. Analysis of the caudate nucleus transcriptome in individuals with schizophrenia highlights effects of antipsychotics and new risk genes. Nat. Neurosci. 25, 1559–1568 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Kim, M. et al. Brain gene co-expression networks link complement signaling with convergent synaptic pathology in schizophrenia. Nat. Neurosci. 24, 799–809 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Batiuk, M. Y. et al. Upper cortical layer-driven network impairment in schizophrenia. Sci. Adv. 8, eabn8367 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Ruzicka, W. et al. Single-cell multi-cohort dissection of the schizophrenia transcriptome. Science 384, eadg5136 (2024).

    Article  CAS  PubMed  Google Scholar 

  81. Aguilar, D. D. & McNally, J. M. Subcortical control of the default mode network: role of the basal forebrain and implications for neuropsychiatric disorders. Brain Res. Bull. 185, 129–139 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Medoff, D. R., Holcomb, H. H., Lahti, A. C. & Tamminga, C. A. Probing the human hippocampus using rCBF: contrasts in schizophrenia. Hippocampus 11, 543–550 (2001).

    Article  CAS  PubMed  Google Scholar 

  83. Perrottelli, A., Giordano, G. M., Brando, F., Giuliani, L. & Mucci, A. EEG-based measures in at-risk mental state and early stages of schizophrenia: a systematic review. Front. Psychiatry 12, 653642 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Amann, L. C. et al. Mouse behavioral endophenotypes for schizophrenia. Brain Res. Bull. 83, 147–161 (2010).

    Article  PubMed  Google Scholar 

  85. Birnbaum, R. & Weinberger, D. R. Genetic insights into the neurodevelopmental origins of schizophrenia. Nat. Rev. Neurosci. 18, 727–740 (2017).

    Article  CAS  PubMed  Google Scholar 

  86. Murray, R. M. & Lewis, S. W. Is schizophrenia a neurodevelopmental disorder? Br. Med. J. 295, 681–682 (1987).

    Article  CAS  Google Scholar 

  87. Weinberger, D. R. Implications of normal brain development for the pathogenesis of schizophrenia. Arch. Gen. Psychiatry 44, 660–669 (1987).

    Article  CAS  PubMed  Google Scholar 

  88. Owen, M. J., O’Donovan, M. C., Thapar, A. & Craddock, N. Neurodevelopmental hypothesis of schizophrenia. Br. J. Psychiatry 198, 173–175 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Mortensen, P. B. et al. Effects of family history and place and season of birth on the risk of schizophrenia. N. Engl. J. Med. 340, 603–608 (1999).

    Article  CAS  PubMed  Google Scholar 

  90. Bryois, J. et al. Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease. Nat. Genet. 52, 482–493 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Yao, S. et al. Connecting genomic results for psychiatric disorders to human brain 1 cell types and regions reveals convergence with functional connectivity. Preprint at medRxiv https://doi.org/10.1101/2024.01.18.24301478 (2024).

  92. Thyme, S. B. et al. Phenotypic landscape of schizophrenia-associated genes defines candidates and their shared functions. Cell 177, 478–491 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Sekar, A. et al. Schizophrenia risk from complex variation of complement component 4. Nature 530, 177–183 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Hyman, S. E. & Nestler, E. J. Initiation and adaptation: a paradigm for understanding psychotropic drug action. Am. J. Psychiatry 153, 151–162 (1996).

    Article  CAS  PubMed  Google Scholar 

  95. Hyman, S. E. Use of mouse models to investigate the contributions of CNVs associated with schizophrenia and autism to disease mechanisms. Curr. Opin. Genet. Dev. 68, 99–105 (2021).

    Article  CAS  PubMed  Google Scholar 

  96. Zhang, W. et al. Mouse genome rewriting and tailoring of three important disease loci. Nature 623, 423–431 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Jin, X. et al. In vivo perturb-seq reveals neuronal and glial abnormalities associated with autism risk genes. Science 370, eaaz6063 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Zhang, S. et al. Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons. Cell Genom. 3, 100399 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Schrode, N. et al. Synergistic effects of common schizophrenia risk variants. Nat. Genet. 51, 1475–1485 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Page, S. C. et al. Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance. Proc. Natl Acad. Sci. USA 119, e2109395119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Stachowiak, E. K. et al. Cerebral organoids reveal early cortical maldevelopment in schizophrenia-computational anatomy and genomics, role of FGFR1. Transl. Psychiatry 7, 6 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Brennand, K. et al. Phenotypic differences in hiPSC NPCs derived from patients with schizophrenia. Mol. Psychiatry 20, 361–368 (2015).

    Article  CAS  PubMed  Google Scholar 

  103. Brennand, K. J. et al. Modelling schizophrenia using human induced pluripotent stem cells. Nature 473, 221–225 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Mollon, J., Almasy, L., Jacquemont, S. & Glahn, D. C. The contribution of copy number variants to psychiatric symptoms and cognitive ability. Mol. Psychiatry 28, 1480–1493 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Mulle, J. G., Sullivan, P. F. & Hjerling-Leffler, J. Editorial overview: rare CNV disorders and neuropsychiatric phenotypes: opportunities, challenges, solutions. Curr. Opin. Genet. Dev. 68, iii–ix (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Marshall, C. R. et al. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat. Genet. 49, 27–35 (2017).

    Article  CAS  PubMed  Google Scholar 

  107. Fung, W. L. et al. Practical guidelines for managing adults with 22q11.2 deletion syndrome. Genet. Med. 17, 599–609 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Moreno-De-Luca, D. & Martin, C. L. All for one and one for all: heterogeneity of genetic etiologies in neurodevelopmental psychiatric disorders. Curr. Opin. Genet. Dev. 68, 71–78 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Tansey, K. E. et al. Common alleles contribute to schizophrenia in CNV carriers. Mol. Psychiatry 21, 1085–1089 (2016).

    Article  CAS  PubMed  Google Scholar 

  110. Silva, A. I. et al. Neuroimaging findings in neurodevelopmental copy number variants: identifying molecular pathways to convergent phenotypes. Biol. Psychiatry 92, 341–361 (2022).

    Article  CAS  PubMed  Google Scholar 

  111. Caseras, X. et al. Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank. Br. J. Psychiatry 218, 104–111 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Gordon, A. et al. Transcriptomic networks implicate neuronal energetic abnormalities in three mouse models harboring autism and schizophrenia-associated mutations. Mol. Psychiatry 26, 1520–1534 (2021).

    Article  CAS  PubMed  Google Scholar 

  113. Sebastian, R. et al. Schizophrenia-associated NRXN1 deletions induce developmental-timing- and cell-type-specific vulnerabilities in human brain organoids. Nat. Commun. 14, 3770 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  114. Nehme, R. et al. The 22q11.2 region regulates presynaptic gene-products linked to schizophrenia. Nat. Commun. 13, 3690 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Pak, C. et al. Cross-platform validation of neurotransmitter release impairments in schizophrenia patient-derived NRXN1-mutant neurons. Proc. Natl Acad. Sci. USA 118, e2025598118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Khan, T. A. et al. Neuronal defects in a human cellular model of 22q11.2 deletion syndrome. Nat. Med. 26, 1888–1898 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Flaherty, E. et al. Neuronal impact of patient-specific aberrant NRXN1alpha splicing. Nat. Genet. 51, 1679–1690 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Parnell, E. et al. Excitatory dysfunction drives network and calcium handling deficits in 16p11.2 duplication schizophrenia induced pluripotent stem cell-derived neurons. Biol. Psychiatry 94, 153–163 (2023).

    Article  CAS  PubMed  Google Scholar 

  119. Farsi, Z. et al. Brain-region-specific changes in neurons and glia and dysregulation of dopamine signaling in Grin2a mutant mice. Neuron 111, 3378–3396 (2023).

    Article  CAS  PubMed  Google Scholar 

  120. Mukai, J. et al. Recapitulation and reversal of schizophrenia-related phenotypes in setd1a-deficient mice. Neuron 104, 471–487 e412 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Fromer, M. et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Genovese, G. et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat. Neurosci. 19, 1433–1441 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Koopmans, F. et al. SynGO: an evidence-based, expert-curated knowledge base for the synapse. Neuron 103, 217–234 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Ongen, H. et al. Estimating the causal tissues for complex traits and diseases. Nat. Genet. 49, 1676–1683 (2017).

    Article  CAS  PubMed  Google Scholar 

  126. Li, M. et al. Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 362, eaat7615 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Tian, W. et al. Single-cell DNA methylation and 3D genome architecture in the human brain. Science 382, eadf5357 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Zhu, K. et al. Multi-omic profiling of the developing human cerebral cortex at the single-cell level. Sci. Adv. 9, eadg3754 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Jagadeesh, K. A. et al. Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics. Nat. Genet. 54, 1479–1492 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Zhang, M. J. et al. Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nat. Genet. 54, 1572–1580 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Wang, R., Lin, D. Y. & Jiang, Y. EPIC: inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing. PLoS Genet. 18, e1010251 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Ziffra, R. S. et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature 598, 205–213 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Watanabe, K., Umicevic Mirkov, M., de Leeuw, C. A., van den Heuvel, M. P. & Posthuma, D. Genetic mapping of cell type specificity for complex traits. Nat. Commun. 10, 3222 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Skene, N. G. et al. Genetic identification of brain cell types underlying schizophrenia. Nat. Genet. 50, 825–833 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Lake, B. B. et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nat. Biotechnol. 36, 70–80 (2018).

    Article  CAS  PubMed  Google Scholar 

  136. Calderon, D. et al. Inferring relevant cell types for complex traits by using single-cell gene expression. Am. J. Hum. Genet. 101, 686–699 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Siletti, K. et al. Transcriptomic diversity of cell types across the adult human brain. Science 382, eadd7046 (2023).

    Article  CAS  PubMed  Google Scholar 

  138. Munguba, H. et al. Postnatal Sox6 regulates synaptic function of cortical parvalbumin-expressing neurons. J. Neurosci. 41, 8876–8886 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Leek, J. T. et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat. Rev. Genet. 11, 733–739 (2010).

    Article  CAS  PubMed  Google Scholar 

  140. Strittmatter, W. J. et al. Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc. Natl Acad. Sci. USA 90, 1977–1981 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Horvath, G. A., Stowe, R. M., Ferreira, C. R. & Blau, N. Clinical and biochemical footprints of inherited metabolic diseases. III. Psychiatric presentations. Mol. Genet. Metab. 130, 1–6 (2020).

    Article  CAS  PubMed  Google Scholar 

  142. Taliun, D. et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590, 290–299 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Mukamel, R. E. et al. Repeat polymorphisms underlie top genetic risk loci for glaucoma and colorectal cancer. Cell 186, 3659–3673.e23 (2023).

    Article  CAS  PubMed  Google Scholar 

  144. Hanks, S. C. et al. Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing. Am. J. Hum. Genet. 109, 1653–1666 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Peterson, R. E. et al. Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. Cell 179, 589–603 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Graham, S. E. et al. The power of genetic diversity in genome-wide association studies of lipids. Nature 600, 675–679 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).

    Article  CAS  PubMed  Google Scholar 

  148. Wolter, J. M. et al. Cellular genome-wide association study identifies common genetic variation influencing lithium-induced neural progenitor proliferation. Biol. Psychiatry 93, 8–17 (2023).

    Article  CAS  PubMed  Google Scholar 

  149. GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).

    Article  Google Scholar 

  150. Zhang, S. et al. Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants. Science 369, 561–565 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Forrest, M. P. et al. Open chromatin profiling in hiPSC-derived neurons prioritizes functional noncoding psychiatric risk variants and highlights neurodevelopmental loci. Cell Stem Cell 21, 305–318.e8 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Encode Project Consortium et al. Perspectives on ENCODE. Nature 583, 693–698 (2020).

    Article  Google Scholar 

  153. Hawrylycz, M. et al. A guide to the BRAIN initiative cell census network data ecosystem. PLoS Biol. 21, e3002133 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Sey, N. Y. A., Pratt, B. M. & Won, H. Annotating genetic variants to target genes using H-MAGMA. Nat. Protoc. 18, 22–35 (2023).

    Article  CAS  PubMed  Google Scholar 

  155. Rajarajan, P. et al. Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk. Science 362, eaat4311 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. McAfee, J. C. et al. Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants. Cell Genom. 3, 100404 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Klann, T. S. et al. CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nat. Biotechnol. 35, 561–568 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Yang, X. et al. Functional characterization of gene regulatory elements and neuropsychiatric disease-associated risk loci in iPSCs and iPSC-derived neurons. Preprint at bioRxiv https://doi.org/10.1101/2023.08.30.555359 (2023).

  159. Anzalone, A. V. et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576, 149–157 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Ren, X. et al. High throughput PRIME editing screens identify functional DNA variants in the human genome. Mol. Cell 83, 4633–4645 (2023).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

J.H.-L. was supported by the Swedish Research Council (Vetenskapsrådet, award 2018-00799), Swedish Brain Foundation (Hjärnfonden, award FO2018-0272) and European Research Council (SCHIZTYPE, grant agreement 819540). P.F.S. was supported by the Swedish Research Council (Vetenskapsrådet, award D0886501) and the US National Institute of Mental Health (R01s MH124871, MH121545 and MH123724).

Author information

Authors and Affiliations

  1. Department of Genetics, University of North Carolina, Chapel Hill, NC, USA

    Patrick F. Sullivan

  2. Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA

    Patrick F. Sullivan

  3. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Patrick F. Sullivan & Shuyang Yao

  4. Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden

    Jens Hjerling-Leffler

Authors
  1. Patrick F. Sullivan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuyang Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jens Hjerling-Leffler
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors researched data for the article and contributed substantially to discussion of the content. P.F.S. and J.H-L. wrote the article and reviewed and/or edited the manuscript before submission.

Corresponding authors

Correspondence to Patrick F. Sullivan or Jens Hjerling-Leffler.

Ethics declarations

Competing interests

P.F.S. is a consultant and shareholder for Neumora Therapeutics.

Peer review

Peer review information

Nature Reviews Neuroscience thanks Kristen Brennand, Brien Riley and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Psychiatric Genetics Consortium: https://pgc.unc.edu/

Supplementary information

Glossary

Brain organoids

Three-dimensional cell cultures that mimic the structure and function of the brain, derived from pluripotent stem cells.

Copy number variants

(CNVs). Structural variations in the genome, in which large sections of DNA (containing from one gene to many genes) are duplicated or deleted, potentially influencing traits or diseases.

Dopamine hypothesis

A theory proposing that dysregulation of dopamine neurotransmission in the brain contributes to the development of schizophrenia.

Epigenomic

Referring to chemical modifications to DNA and histone proteins that regulate gene expression without altering the DNA sequence.

Genetic risk factors

Variations in the DNA sequence that increase the likelihood of developing a particular trait or disease (such as schizophrenia).

Genetic variants

Measurable differences in DNA sequence among individuals, including SNPs, coding and non-coding variants, copy number variants, insertion and deletions.

Genome-wide association study

(GWAS). A method to identify genetic variations across the entire genome associated with traits or diseases.

Heritability

The proportion of the total variation in a trait in a population that is owing to genetic differences among individuals.

Induced pluripotent stem cell

An adult cell reprogrammed to exhibit embryonic stem-cell-like properties and capable of differentiating into various cell types.

Linkage disequilibrium

The nonrandom association or correlation of alleles at different loci within a population. Linkage disequilibrium is detectible between pairs of genetic markers with tens of kilobases but may span many megabases in specific regions.

Mendelian randomization

A method using genetic variants as instrumental variables to investigate causal relationships between modifiable exposures and health outcomes.

Polygenic risk score

(PRS). A numerical score calculated from multiple genetic variants associated with a trait or disease, used as a summation of genetic predisposition of an individual.

Single-cell RNA sequencing

A sequencing technique to analyse gene expression in single cells (or single nuclei), providing insights into cellular heterogeneity and functional diversity.

SNPs

Variations in a single nucleotide at a specific position in the genome.

Whole-exome sequencing

(WES). Sequencing of the protein-coding regions of the genome.

Whole-genome sequencing

Sequencing of the entire genome, including coding and non-coding regions, providing a comprehensive view of the genetic makeup of an individual.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sullivan, P.F., Yao, S. & Hjerling-Leffler, J. Schizophrenia genomics: genetic complexity and functional insights. Nat. Rev. Neurosci. 25, 611–624 (2024). https://doi.org/10.1038/s41583-024-00837-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41583-024-00837-7

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing