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The promises and challenges of human brain organoids as models of neuropsychiatric disease

Abstract

Neuropsychiatric disorders such as autism spectrum disorder (ASD), schizophrenia (SCZ) and bipolar disorder (BPD) are of great societal and medical importance, but the complexity of these diseases and the challenges of modeling the development and function of the human brain have made these disorders difficult to study experimentally. The recent development of 3D brain organoids derived from human pluripotent stem cells offers a promising approach for investigating the phenotypic underpinnings of these highly polygenic disorders and for understanding the contribution of individual risk variants and complex genetic background to human pathology. Here we discuss the advantages, limitations and future applications of human brain organoids as in vitro models of neuropsychiatric disease.

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Figure 1: hPSC-based modeling of neuropsychiatric disorders.
Figure 2: Strategies for the generation, characterization and systems-level analysis of 3D cellular models of the human brain.

References

  1. 1

    World Health Organization. The Global Burden of Disease: 2004 Update (WHO Press, 2008).

  2. 2

    Collins, P.Y. et al. Grand challenges in global mental health. Nature 475, 27–30 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3

    Hyman, S.E. Revolution stalled. Sci. Transl. Med. 4, 155cm11 (2012).

    PubMed  Google Scholar 

  4. 4

    Gratten, J., Wray, N.R., Keller, M.C. & Visscher, P.M. Large-scale genomics unveils the genetic architecture of psychiatric disorders. Nat. Neurosci. 17, 782–790 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5

    McCarroll, S.A., Feng, G. & Hyman, S.E. Genome-scale neurogenetics: methodology and meaning. Nat. Neurosci. 17, 756–763 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Doherty, J.L. & Owen, M.J. Genomic insights into the overlap between psychiatric disorders: implications for research and clinical practice. Genome Med. 6, 29 (2014).

    PubMed  PubMed Central  Google Scholar 

  7. 7

    Mouchlianitis, E., McCutcheon, R. & Howes, O.D. Brain-imaging studies of treatment-resistant schizophrenia: a systematic review. Lancet Psychiatry 3, 451–463 (2016).

    PubMed  PubMed Central  Google Scholar 

  8. 8

    Ecker, C., Bookheimer, S.Y. & Murphy, D.G. Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan. Lancet Neurol. 14, 1121–1134 (2015).

    PubMed  Google Scholar 

  9. 9

    Heyes, S. et al. Genetic disruption of voltage-gated calcium channels in psychiatric and neurological disorders. Prog. Neurobiol. 134, 36–54 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10

    Moyer, C.E., Shelton, M.A. & Sweet, R.A. Dendritic spine alterations in schizophrenia. Neurosci. Lett. 601, 46–53 (2015).

    CAS  PubMed  Google Scholar 

  11. 11

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

    CAS  PubMed  Google Scholar 

  12. 12

    de Bartolomeis, A., Latte, G., Tomasetti, C. & Iasevoli, F. Glutamatergic postsynaptic density protein dysfunctions in synaptic plasticity and dendritic spines morphology: relevance to schizophrenia and other behavioral disorders pathophysiology, and implications for novel therapeutic approaches. Mol. Neurobiol. 49, 484–511 (2014).

    CAS  PubMed  Google Scholar 

  13. 13

    Egbujo, C.N., Sinclair, D. & Hahn, C.G. Dysregulations of synaptic vesicle trafficking in schizophrenia. Curr. Psychiatry Rep. 18, 77 (2016).

    PubMed  PubMed Central  Google Scholar 

  14. 14

    Martínez-Cerdeño, V. Dendrite and spine modifications in autism and related neurodevelopmental disorders in patients and animal models. Dev. Neurobiol. http://dx.doi.org/10.1002/dneu.22417 (2016).

  15. 15

    Lewis, D.A., Curley, A.A., Glausier, J.R. & Volk, D.W. Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia. Trends Neurosci. 35, 57–67 (2012).

    CAS  PubMed  Google Scholar 

  16. 16

    Zikopoulos, B. & Barbas, H. Altered neural connectivity in excitatory and inhibitory cortical circuits in autism. Front. Hum. Neurosci. 7, 609 (2013).

    PubMed  PubMed Central  Google Scholar 

  17. 17

    Elsayed, M. & Magistretti, P.J. A new outlook on mental illnesses: glial involvement beyond the glue. Front. Cell. Neurosci. 9, 468 (2015).

    PubMed  PubMed Central  Google Scholar 

  18. 18

    Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379 (2013).

  19. 19

    Cross-Disorder Group of the Psychiatric Genomics Consortium. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat. Genet. 45, 984–994 (2013).

  20. 20

    Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Kelava, I. & Lancaster, M.A. Stem cell models of human brain development. Cell Stem Cell 18, 736–748 (2016).

    CAS  PubMed  Google Scholar 

  22. 22

    Wen, Z., Christian, K.M., Song, H. & Ming, G.L. Modeling psychiatric disorders with patient-derived iPSCs. Curr. Opin. Neurobiol. 36, 118–127 (2016).

    CAS  PubMed  Google Scholar 

  23. 23

    Urnov, F.D. et al. Highly efficient endogenous human gene correction using designed zinc-finger nucleases. Nature 435, 646–651 (2005).

    CAS  Google Scholar 

  24. 24

    Miller, J.C. et al. A TALE nuclease architecture for efficient genome editing. Nat. Biotechnol. 29, 143–148 (2011).

    CAS  PubMed  Google Scholar 

  25. 25

    Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26

    Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27

    González, F. et al. An iCRISPR platform for rapid, multiplexable, and inducible genome editing in human pluripotent stem cells. Cell Stem Cell 15, 215–226 (2014).

    PubMed  PubMed Central  Google Scholar 

  28. 28

    Hockemeyer, D. & Jaenisch, R. Induced pluripotent stem cells meet genome editing. Cell Stem Cell 18, 573–586 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Zhang, S.C., Wernig, M., Duncan, I.D., Brüstle, O. & Thomson, J.A. In vitro differentiation of transplantable neural precursors from human embryonic stem cells. Nat. Biotechnol. 19, 1129–1133 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Chambers, S.M. et al. Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling. Nat. Biotechnol. 27, 275–280 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Shi, Y., Kirwan, P., Smith, J., Robinson, H.P.C. & Livesey, F.J. Human cerebral cortex development from pluripotent stem cells to functional excitatory synapses. Nat. Neurosci. 15, 477–486 (2012).

    CAS  PubMed  Google Scholar 

  32. 32

    Elkabetz, Y. et al. Human ES cell-derived neural rosettes reveal a functionally distinct early neural stem cell stage. Genes Dev. 22, 152–165 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33

    Lancaster, M.A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013).

    CAS  Article  Google Scholar 

  34. 34

    Qian, X. et al. Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell 165, 1238–1254 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Kadoshima, T. et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc. Natl. Acad. Sci. USA 110, 20284–20289 (2013).

    CAS  PubMed  Google Scholar 

  36. 36

    Otani, T., Marchetto, M.C., Gage, F.H., Simons, B.D. & Livesey, F.J. 2D and 3D stem cell models of primate cortical development identify species-specific differences in progenitor behavior contributing to brain size. Cell Stem Cell 18, 467–480 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Cugola, F.R. et al. The Brazilian Zika virus strain causes birth defects in experimental models. Nature 534, 267–271 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    Dang, J. et al. Zika virus depletes neural progenitors in human cerebral organoids through activation of the innate immune receptor TLR3. Cell Stem Cell 19, 258–265 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Garcez, P.P. et al. Zika virus impairs growth in human neurospheres and brain organoids. Science 352, 816–818 (2016).

    CAS  PubMed  Google Scholar 

  40. 40

    Watanabe, K. et al. Directed differentiation of telencephalic precursors from embryonic stem cells. Nat. Neurosci. 8, 288–296 (2005).

    CAS  PubMed  Google Scholar 

  41. 41

    Eiraku, M. et al. Self-organized formation of polarized cortical tissues from ESCs and its active manipulation by extrinsic signals. Cell Stem Cell 3, 519–532 (2008).

    CAS  PubMed  Google Scholar 

  42. 42

    Ying, Q.L., Stavridis, M., Griffiths, D., Li, M. & Smith, A. Conversion of embryonic stem cells into neuroectodermal precursors in adherent monoculture. Nat. Biotechnol. 21, 183–186 (2003).

    CAS  PubMed  Google Scholar 

  43. 43

    Pas¸ca, A.M. et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat. Methods 12, 671–678 (2015).

    Google Scholar 

  44. 44

    Rigamonti, A. et al. Large-scale production of mature neurons from human pluripotent stem cells in a three-dimensional suspension culture system. Stem Cell Reports 6, 993–1008 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Sakaguchi, H. et al. Generation of functional hippocampal neurons from self-organizing human embryonic stem cell-derived dorsomedial telencephalic tissue. Nat. Commun. 6, 8896 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Jo, J. et al. Midbrain-like organoids from human pluripotent stem cells contain functional dopaminergic and neuromelanin-producing neurons. Cell Stem Cell 19, 248–257 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47

    Muguruma, K., Nishiyama, A., Kawakami, H., Hashimoto, K. & Sasai, Y. Self-organization of polarized cerebellar tissue in 3D culture of human pluripotent stem cells. Cell Rep. 10, 537–550 (2015).

    CAS  PubMed  Google Scholar 

  48. 48

    Woodhams, P.L. & Atkinson, D.J. Regeneration of entorhino-dentate projections in organotypic slice cultures: mode of axonal regrowth and effects of growth factors. Exp. Neurol. 140, 68–78 (1996).

    CAS  PubMed  Google Scholar 

  49. 49

    Eiraku, M. et al. Self-organizing optic-cup morphogenesis in three-dimensional culture. Nature 472, 51–56 (2011).

    CAS  PubMed  Google Scholar 

  50. 50

    Camp, J.G. et al. Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc. Natl. Acad. Sci. USA 112, 15672–15677 (2015).

    CAS  PubMed  Google Scholar 

  51. 51

    Yin, X. et al. Engineering stem cell organoids. Cell Stem Cell 18, 25–38 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Flaherty, E.K. & Brennand, K.J. Using hiPSCs to model neuropsychiatric copy number variations (CNVs) has potential to reveal underlying disease mechanisms. Brain Res. http://dx.doi.org/10.1016/j.brainres.2015.11.009 (2015).

  53. 53

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

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Marchetto, M.C. et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell 143, 527–539 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Chen, H.M. et al. Transcripts involved in calcium signaling and telencephalic neuronal fate are altered in induced pluripotent stem cells from bipolar disorder patients. Transl. Psychiatry 4, e375 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Madison, J.M. et al. Characterization of bipolar disorder patient-specific induced pluripotent stem cells from a family reveals neurodevelopmental and mRNA expression abnormalities. Mol. Psychiatry 20, 703–717 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Mertens, J. et al. Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder. Nature 527, 95–99 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    Wen, Z. et al. Synaptic dysregulation in a human iPS cell model of mental disorders. Nature 515, 414–418 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Yoon, K.J. et al. Modeling a genetic risk for schizophrenia in iPSCs and mice reveals neural stem cell deficits associated with adherens junctions and polarity. Cell Stem Cell 15, 79–91 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Shcheglovitov, A. et al. SHANK3 and IGF1 restore synaptic deficits in neurons from 22q13 deletion syndrome patients. Nature 503, 267–271 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Adamo, A. et al. 7q11.23 dosage-dependent dysregulation in human pluripotent stem cells affects transcriptional programs in disease-relevant lineages. Nat. Genet. 47, 132–141 (2015).

    CAS  PubMed  Google Scholar 

  62. 62

    Mariani, J. et al. FOXG1-dependent dysregulation of GABA/glutamate neuron differentiation in autism spectrum disorders. Cell 162, 375–390 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Robicsek, O. et al. Abnormal neuronal differentiation and mitochondrial dysfunction in hair follicle-derived induced pluripotent stem cells of schizophrenia patients. Mol. Psychiatry 18, 1067–1076 (2013).

    CAS  PubMed  Google Scholar 

  64. 64

    Hashimoto-Torii, K. et al. Roles of heat shock factor 1 in neuronal response to fetal environmental risks and its relevance to brain disorders. Neuron 82, 560–572 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Griesi-Oliveira, K. et al. Modeling non-syndromic autism and the impact of TRPC6 disruption in human neurons. Mol. Psychiatry 20, 1350–1365 (2015).

    CAS  PubMed  Google Scholar 

  66. 66

    Muotri, A.R. et al. L1 retrotransposition in neurons is modulated by MeCP2. Nature 468, 443–446 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Larimore, J. et al. MeCP2 regulates the synaptic expression of a Dysbindin-BLOC-1 network component in mouse brain and human induced pluripotent stem cell-derived neurons. PLoS One 8, e65069 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68

    Liu, J. et al. Signaling defects in iPSC-derived fragile X premutation neurons. Hum. Mol. Genet. 21, 3795–3805 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69

    Pas¸ca, S.P. et al. Using iPSC-derived neurons to uncover cellular phenotypes associated with Timothy syndrome. Nat. Med. 17, 1657–1662 (2011).

    Google Scholar 

  70. 70

    Tian, Y. et al. Alteration in basal and depolarization induced transcriptional network in iPSC derived neurons from Timothy syndrome. Genome Med. 6, 75 (2014).

    PubMed  PubMed Central  Google Scholar 

  71. 71

    Ananiev, G., Williams, E.C., Li, H. & Chang, Q. Isogenic pairs of wild type and mutant induced pluripotent stem cell (iPSC) lines from Rett syndrome patients as in vitro disease model. PLoS One 6, e25255 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Cheung, A.Y. et al. Isolation of MECP2-null Rett Syndrome patient hiPS cells and isogenic controls through X-chromosome inactivation. Hum. Mol. Genet. 20, 2103–2115 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Ricciardi, S. et al. CDKL5 ensures excitatory synapse stability by reinforcing NGL-1-PSD95 interaction in the postsynaptic compartment and is impaired in patient iPSC-derived neurons. Nat. Cell Biol. 14, 911–923 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Macosko, E.Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75

    Klein, A.M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. 76

    Lee, J.H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

    Tieng, V. et al. Engineering of midbrain organoids containing long-lived dopaminergic neurons. Stem Cells Dev. 23, 1535–1547 (2014).

    CAS  PubMed  Google Scholar 

  78. 78

    Falk, A. et al. Modeling psychiatric disorders: from genomic findings to cellular phenotypes. Mol. Psychiatry 21, 1167–1179 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Tomassy, G.S., Dershowitz, L.B. & Arlotta, P. Diversity matters: a revised guide to myelination. Trends Cell Biol. 26, 135–147 (2016).

    CAS  PubMed  Google Scholar 

  80. 80

    Hong, S., Dissing-Olesen, L. & Stevens, B. New insights on the role of microglia in synaptic pruning in health and disease. Curr. Opin. Neurobiol. 36, 128–134 (2016).

    CAS  PubMed  Google Scholar 

  81. 81

    Bilimoria, P.M. & Stevens, B. Microglia function during brain development: New insights from animal models. Brain Res. 1617, 7–17 (2015).

    CAS  PubMed  Google Scholar 

  82. 82

    Ginhoux, F. & Prinz, M. Origin of microglia: current concepts and past controversies. Cold Spring Harb. Perspect. Biol. 7, a020537 (2015).

    PubMed  PubMed Central  Google Scholar 

  83. 83

    Young-Pearse, T.L. & Morrow, E.M. Modeling developmental neuropsychiatric disorders with iPSC technology: challenges and opportunities. Curr. Opin. Neurobiol. 36, 66–73 (2016).

    CAS  PubMed  Google Scholar 

  84. 84

    Muffat, J. et al. Efficient derivation of microglia-1 like cells from human pluripotent stem cells. Nat. Med. 22, http://dx.doi.org/10.1038/nm.4189 (2016).

  85. 85

    Schwartz, M.P. et al. Human pluripotent stem cell-derived neural constructs for predicting neural toxicity. Proc. Natl. Acad. Sci. USA 112, 12516–12521 (2015).

    CAS  PubMed  Google Scholar 

  86. 86

    Hochbaum, D.R. et al. All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins. Nat. Methods 11, 825–833 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Tsien, R.Y. New calcium indicators and buffers with high selectivity against magnesium and protons: design, synthesis, and properties of prototype structures. Biochemistry 19, 2396–2404 (1980).

    CAS  PubMed  Google Scholar 

  88. 88

    Scholvin, J. et al. Close-packed silicon microelectrodes for scalable spatially oversampled neural recording. IEEE Trans. Biomed. Eng. 63, 120–130 (2016).

    PubMed  PubMed Central  Google Scholar 

  89. 89

    Sullivan, P.F., Daly, M.J. & O'Donovan, M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat. Rev. Genet. 13, 537–551 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Polderman, T.J. et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat. Genet. 47, 702–709 (2015).

    CAS  PubMed  Google Scholar 

  91. 91

    Sanders, S.J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237–241 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. 92

    He, X. et al. Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes. PLoS Genet. 9, e1003671 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93

    Stefansson, H. et al. CNVs conferring risk of autism or schizophrenia affect cognition in controls. Nature 505, 361–366 (2014).

    CAS  PubMed  Google Scholar 

  94. 94

    Lencz, T. et al. Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT). Mol. Psychiatry 19, 168–174 (2014).

    CAS  PubMed  Google Scholar 

  95. 95

    Robinson, E.B. et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat. Genet. 48, 552–555 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Moreno-De-Luca, A. et al. Developmental brain dysfunction: revival and expansion of old concepts based on new genetic evidence. Lancet Neurol. 12, 406–414 (2013).

    PubMed  PubMed Central  Google Scholar 

  97. 97

    Moreno-De-Luca, D., Moreno-De-Luca, A., Cubells, J.F. & Sanders, S.J. Cross-disorder comparison of four neuropsychiatric CNV loci. Curr. Genet. Med. Rep. 2, 151–161 (2014).

    Google Scholar 

  98. 98

    Malhotra, D. & Sebat, J. CNVs: harbingers of a rare variant revolution in psychiatric genetics. Cell 148, 1223–1241 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. 99

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

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank S. Hyman, L. Rubin, E. Robinson and K. Lilliehook for their critical discussion and suggestions for this manuscript. We are grateful to N. Maria and J. Nguyen for editing of the manuscript, and D. Sun for creating the illustrations for this article. P.A. is a NYSC Robertson Investigator. Work in the Arlotta lab is supported by grants to P.A. the US National Institutes of Health (NS078164 and MH101268), the Stanley Center for Psychiatric Disease of the Broad Institute of MIT and Harvard, and the Harvard Brain Initiative. We apologize to colleagues whose work we could not cite because of space limitations.

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Correspondence to Paola Arlotta.

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Quadrato, G., Brown, J. & Arlotta, P. The promises and challenges of human brain organoids as models of neuropsychiatric disease. Nat Med 22, 1220–1228 (2016). https://doi.org/10.1038/nm.4214

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