Abstract

We generated cortical interneurons (cINs) from induced pluripotent stem cells derived from 14 healthy controls and 14 subjects with schizophrenia. Both healthy control cINs and schizophrenia cINs were authentic, fired spontaneously, received functional excitatory inputs from host neurons, and induced GABA-mediated inhibition in host neurons in vivo. However, schizophrenia cINs had dysregulated expression of protocadherin genes, which lie within documented schizophrenia loci. Mice lacking protocadherin-α showed defective arborization and synaptic density of prefrontal cortex cINs and behavioral abnormalities. Schizophrenia cINs similarly showed defects in synaptic density and arborization that were reversed by inhibitors of protein kinase C, a downstream kinase in the protocadherin pathway. These findings reveal an intrinsic abnormality in schizophrenia cINs in the absence of any circuit-driven pathology. They also demonstrate the utility of homogenous and functional populations of a relevant neuronal subtype for probing pathogenesis mechanisms during development.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Data availability

The RNA-seq data were deposited at GEO with accession numbers GSE118313 and GSE121376. The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Additional information

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

References

  1. 1.

    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).

  2. 2.

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

  3. 3.

    Buchanan, R. W. & Carpenter, W. T. Domains of psychopathology: an approach to the reduction of heterogeneity in schizophrenia. J. Nerv. Ment. Dis. 182, 193–204 (1994).

  4. 4.

    Elvevåg, B. & Goldberg, T. E. Cognitive impairment in schizophrenia is the core of the disorder. Crit. Rev. Neurobiol. 14, 1–21 (2000).

  5. 5.

    Ripke, S. et al. Schizophrenia working group of the psychiatric genomics consortium. biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

  6. 6.

    Fromer, M. et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci. 19, 1442–1453 (2016).

  7. 7.

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

  8. 8.

    Takahashi, K. & Yamanaka, S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663–676 (2006).

  9. 9.

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

  10. 10.

    Noh, H., Shao, Z., Coyle, J. T. & Chung, S. Modeling schizophrenia pathogenesis using patient-derived induced pluripotent stem cells (iPSCs). Biochim. Biophys. Acta Mol. Basis Dis. 1863, 2382–2387 (2017).

  11. 11.

    Benes, F. M. The GABA system in schizophrenia: cells, molecules and microcircuitry. Schizophr. Res. 167, 1–3 (2015).

  12. 12.

    Lewis, D. A., Hashimoto, T. & Volk, D. W. Cortical inhibitory neurons and schizophrenia. Nat. Rev. Neurosci. 6, 312–324 (2005).

  13. 13.

    Volk, D. W. & Lewis, D. A. Early developmental disturbances of cortical inhibitory neurons: contribution to cognitive deficits in schizophrenia. Schizophr. Bull. 40, 952–957 (2014).

  14. 14.

    Lewis, D. A. et al. Subunit-selective modulation of GABA type A receptor neurotransmission and cognition in schizophrenia. Am. J. Psychiatry 165, 1585–1593 (2008).

  15. 15.

    Belforte, J. E. et al. Postnatal NMDA receptor ablation in corticolimbic interneurons confers schizophrenia-like phenotypes. Nat. Neurosci. 13, 76–83 (2010).

  16. 16.

    Warren, L., Ni, Y., Wang, J. & Guo, X. Feeder-free derivation of human induced pluripotent stem cells with messenger RNA. Sci. Rep. 2, 657 (2012).

  17. 17.

    Kim, T. G. et al. Efficient specification of interneurons from human pluripotent stem cells by dorsoventral and rostrocaudal modulation. Stem Cells 32, 1789–1804 (2014).

  18. 18.

    Ma, T. et al. Subcortical origins of human and monkey neocortical interneurons. Nat. Neurosci. 16, 1588–1597 (2013).

  19. 19.

    Zhang, Y. et al. Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 78, 785–798 (2013).

  20. 20.

    Hasegawa, S. et al. Distinct and cooperative functions for the Protocadherin-α, -β and -γ clusters in neuronal survival and axon targeting. Front. Mol. Neurosci. 9, 155 (2016).

  21. 21.

    Hirayama, T. & Yagi, T. Clustered protocadherins and neuronal diversity. Prog. Mol. Biol. Transl. Sci. 116, 145–167 (2013).

  22. 22.

    Swerdlow, N. R. et al. Startle gating deficits in a large cohort of patients with schizophrenia: relationship to medications, symptoms, neurocognition, and level of function. Arch. Gen. Psychiatry 63, 1325–1335 (2006).

  23. 23.

    Katori, S. et al. Protocadherin-alpha family is required for serotonergic projections to appropriately innervate target brain areas. J. Neurosci. 29, 9137–9147 (2009).

  24. 24.

    Fukuda, E. et al. Down-regulation of protocadherin-alpha A isoforms in mice changes contextual fear conditioning and spatial working memory. Eur. J. Neurosci. 28, 1362–1376 (2008).

  25. 25.

    Garrett, A. M., Schreiner, D., Lobas, M. A. & Weiner, J. A. γ-protocadherins control cortical dendrite arborization by regulating the activity of a FAK/PKC/MARCKS signaling pathway. Neuron 74, 269–276 (2012).

  26. 26.

    Southwell, D. G. et al. Interneurons from embryonic development to cell-based therapy. Science 344, 1240622 (2014).

  27. 27.

    Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).

  28. 28.

    Mayer, C. et al. Developmental diversification of cortical inhibitory interneurons. Nature 555, 457–462 (2018).

  29. 29.

    Phillips, G. R. et al. Gamma-protocadherins are targeted to subsets of synapses and intracellular organelles in neurons. J. Neurosci. 23, 5096–5104 (2003).

  30. 30.

    Wang, X. et al. Gamma protocadherins are required for survival of spinal interneurons. Neuron 36, 843–854 (2002).

  31. 31.

    Bonn, S., Seeburg, P. H. & Schwarz, M. K. Combinatorial expression of alpha- and gamma-protocadherins alters their presenilin-dependent processing. Mol. Cell. Biol. 27, 4121–4132 (2007).

  32. 32.

    Murata, Y., Hamada, S., Morishita, H., Mutoh, T. & Yagi, T. Interaction with protocadherin-gamma regulates the cell surface expression of protocadherin-alpha. J. Biol. Chem. 279, 49508–49516 (2004).

  33. 33.

    Chen, J. et al. alpha- and gamma-Protocadherins negatively regulate PYK2. J. Biol. Chem. 284, 2880–2890 (2009).

  34. 34.

    Lu, W. C. et al. The protocadherin alpha cluster is required for axon extension and myelination in the developing central nervous system. Neural Regen. Res. 13, 427–433 (2018).

  35. 35.

    Morishita, H. et al. Myelination triggers local loss of axonal CNR/protocadherin alpha family protein expression. Eur. J. Neurosci. 20, 2843–2847 (2004).

  36. 36.

    Kohmura, N. et al. Diversity revealed by a novel family of cadherins expressed in neurons at a synaptic complex. Neuron 20, 1137–1151 (1998).

  37. 37.

    Hirayama, T. & Yagi, T. Regulation of clustered protocadherin genes in individual neurons. Semin. Cell. Dev. Biol. 69, 122–130 (2017).

  38. 38.

    Jones, C. A., Watson, D. J. & Fone, K. C. Animal models of schizophrenia. Br. J. Pharmacol. 164, 1162–1194 (2011).

  39. 39.

    Pak, C. et al. Human neuropsychiatric disease modeling using conditional deletion reveals synaptic transmission defects caused by heterozygous mutations in NRXN1. Cell Stem Cell 17, 316–328 (2015).

  40. 40.

    Southwell, D. G. et al. Intrinsically determined cell death of developing cortical interneurons. Nature 491, 109–113 (2012).

  41. 41.

    Franco, R. & Cedazo-Minguez, A. Successful therapies for Alzheimer’s disease: why so many in animal models and none in humans? Front. Pharmacol. 5, 146 (2014).

  42. 42.

    Thomsen, M. S., Hansen, H. H., Timmerman, D. B. & Mikkelsen, J. D. Cognitive improvement by activation of alpha7 nicotinic acetylcholine receptors: from animal models to human pathophysiology. Curr. Pharm. Des. 16, 323–343 (2010).

  43. 43.

    Amrollahi, Z. et al. Double-blind, randomized, placebo-controlled 6-week study on the efficacy and safety of the tamoxifen adjunctive to lithium in acute bipolar mania. J. Affect Disord. 129, 327–331 (2011).

  44. 44.

    Bebchuk, J. M. et al. A preliminary investigation of a protein kinase C inhibitor in the treatment of acute mania. Arch. Gen. Psychiatry 57, 95–97 (2000).

  45. 45.

    Yildiz, A., Guleryuz, S., Ankerst, D. P., Ongür, D. & Renshaw, P. F. Protein kinase C inhibition in the treatment of mania: a double-blind, placebo-controlled trial of tamoxifen. Arch. Gen. Psychiatry 65, 255–263 (2008).

  46. 46.

    Forstner, A. J. et al. Identification of shared risk loci and pathways for bipolar disorder and schizophrenia. PLoS One 12, e0171595 (2017).

  47. 47.

    Chung, D. W., Fish, K. N. & Lewis, D. A. Pathological basis for deficient excitatory drive to cortical parvalbumin interneurons in schizophrenia. Am. J. Psychiatry 173, 1131–1139 (2016).

  48. 48.

    Roberts, R. C., Barksdale, K. A., Roche, J. K. & Lahti, A. C. Decreased synaptic and mitochondrial density in the postmortem anterior cingulate cortex in schizophrenia. Schizophr. Res. 168, 543–553 (2015).

  49. 49.

    Akbarian, S. & Huang, H. S. Molecular and cellular mechanisms of altered GAD1/GAD67 expression in schizophrenia and related disorders. Brain. Res. Rev. 52, 293–304 (2006).

  50. 50.

    Bliss, L. A. et al. Use of postmortem human dura mater and scalp for deriving human fibroblast cultures. PLoS One 7, e45282 (2012).

  51. 51.

    Cho, J. H., Deisseroth, K. & Bolshakov, V. Y. Synaptic encoding of fear extinction in mPFC-amygdala circuits. Neuron 80, 1491–1507 (2013).

  52. 52.

    Zhao, S. et al. QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization. BMC Genomics 17, 39 (2016).

  53. 53.

    Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).

  54. 54.

    Scharpf, R. B., Irizarry, R. A., Ritchie, M. E., Carvalho, B. & Ruczinski, I. Using the R package crlmm for genotyping and copy number estimation. J. Stat. Softw. 40, 1–32 (2011).

  55. 55.

    Howie, B. N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

  56. 56.

    Delaneau, O., Coulonges, C. & Zagury, J. F. Shape-IT: new rapid and accurate algorithm for haplotype inference. BMC Bioinformatics 9, 540 (2008).

  57. 57.

    Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  58. 58.

    Hasegawa, S. et al. The protocadherin-alpha family is involved in axonal coalescence of olfactory sensory neurons into glomeruli of the olfactory bulb in mouse. Mol. Cell. Neurosci. 38, 66–79 (2008).

  59. 59.

    Herring, A. H. Applied Longitudinal Analysis, 2nd Edition, by Garrett M. Fitzmaurice, Nan M. Laird, and James H. Ware, John Wiley & Sons, 2011. J. Biopharm. Stat. 23, 940–941 (2013).

  60. 60.

    Laird, N. M. & Ware, J. H. Random-effects models for longitudinal data. Biometrics 38, 963–974 (1982).

  61. 61.

    Topol, A. et al. Dysregulation of miRNA-9 in a subset of schizophrenia patient-derived neural progenitor cells. Cell Rep. 15, 1024–1036 (2016).

Download references

Acknowledgements

We thank G. Genovese of Program in Medical and Population Genetics at Broad Institute of MIT and Harvard for providing consultation with genotype analysis. We thank S. Berretta at McLean Hospital/Harvard Medical School for her expert advice and help with human postmortem tissue study. We thank NIH Neurobiobank for providing human postmortem tissues. The authors are appreciative of the New York Medical College/Westchester Medical Center Translational Stem Cell Center for its support with confocal imaging. This study was supported by NIH MH107884 (S.C.), NYSTEM C32607GG (S.C.), Japan Society for the Promotion of Science (JSPS) KAKENHI grant JP17K01976 (T.H.), JSPS grant 16H01275 (T.Y.), AMED-CREST (T.Y.), the Initial Complement Funds from the University of California Riverside (J.-H.C.), NIH MH113894 (J.-H.C.) and NIH MH118339 (J.-H.C.).

Author information

Author notes

    • Teruyoshi Hirayama

    Present address: Department of Anatomy and Developmental Neurobiology, Tokushima University Graduate School of Medical Science, Tokushima, Japan

  1. These authors contributed equally: Zhicheng Shao, Haneul Noh.

Affiliations

  1. Department of Psychiatry, McLean Hospital/Harvard Medical School, Belmont, MA, USA

    • Zhicheng Shao
    • , Haneul Noh
    • , Peiyan Ni
    • , Christine Nguyen
    • , Sarah E. Cote
    • , Elizabeth Noyes
    • , Joyce Zhao
    • , Teagan Parsons
    • , Joseph T. Coyle
    • , Dost Ongur
    • , Bruce M. Cohen
    • , Donna L. McPhie
    •  & Sangmi Chung
  2. Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, Medical College, Xiamen University, Xiamen, Fujian, China

    • Zhicheng Shao
  3. Department of Cell biology and Anatomy, New York Medical College, Valhalla, NY, USA

    • Haneul Noh
    • , Peiyan Ni
    • , James M. Park
    • , Kelvin Zheng
    • , Joshua J. Park
    • , Alexander A. Moghadam
    • , Patric K. Stanton
    •  & Sangmi Chung
  4. Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, USA

    • Woong Bin Kim
    •  & Jun-Hyeong Cho
  5. Lieber Institute for Brain Development, Johns Hopkins University, Baltimore, MD, USA

    • Daniel R. Weinberger
    •  & Richard E. Straub
  6. Clinical and Translational Neuroscience Branch, National Institute of Mental Health, National Institutes of Health, Intramural Research Program, Baltimore, MD, USA

    • Karen F. Berman
    •  & Jose Apud
  7. Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA

    • Judith L. Rapoport
  8. Center for Quantitative Health, Massachusetts General Hospital, Boston, MA, USA

    • Roy H. Perlis
  9. Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, USA

    • Thomas A. Lanz
  10. Computational Sciences, Pfizer Inc., Cambridge, MA, USA

    • Hualin Simon Xi
  11. Department of Pathology, New York Medical College, Valhalla, NY, USA

    • Changhong Yin
    •  & Weihua Huang
  12. KOKORO-Biology Group, Laboratories for Integrated Biology, Graduate School of Frontier Biosciences, Osaka University, Osaka Prefecture, Japan

    • Teruyoshi Hirayama
    • , Emi Fukuda
    •  & Takeshi Yagi
  13. Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA

    • Sulagna Ghosh
    •  & Kevin C. Eggan
  14. Department of Public Health, New York Medical College, Valhalla, NY, USA

    • Hae-Young Kim
  15. New York Medical College/Westchester Medical Center Stem Cell Laboratory, Departments of Physiology and Medicine, New York Medical College, Valhalla, NY, USA

    • Leonard M. Eisenberg

Authors

  1. Search for Zhicheng Shao in:

  2. Search for Haneul Noh in:

  3. Search for Woong Bin Kim in:

  4. Search for Peiyan Ni in:

  5. Search for Christine Nguyen in:

  6. Search for Sarah E. Cote in:

  7. Search for Elizabeth Noyes in:

  8. Search for Joyce Zhao in:

  9. Search for Teagan Parsons in:

  10. Search for James M. Park in:

  11. Search for Kelvin Zheng in:

  12. Search for Joshua J. Park in:

  13. Search for Joseph T. Coyle in:

  14. Search for Daniel R. Weinberger in:

  15. Search for Richard E. Straub in:

  16. Search for Karen F. Berman in:

  17. Search for Jose Apud in:

  18. Search for Dost Ongur in:

  19. Search for Bruce M. Cohen in:

  20. Search for Donna L. McPhie in:

  21. Search for Judith L. Rapoport in:

  22. Search for Roy H. Perlis in:

  23. Search for Thomas A. Lanz in:

  24. Search for Hualin Simon Xi in:

  25. Search for Changhong Yin in:

  26. Search for Weihua Huang in:

  27. Search for Teruyoshi Hirayama in:

  28. Search for Emi Fukuda in:

  29. Search for Takeshi Yagi in:

  30. Search for Sulagna Ghosh in:

  31. Search for Kevin C. Eggan in:

  32. Search for Hae-Young Kim in:

  33. Search for Leonard M. Eisenberg in:

  34. Search for Alexander A. Moghadam in:

  35. Search for Patric K. Stanton in:

  36. Search for Jun-Hyeong Cho in:

  37. Search for Sangmi Chung in:

Contributions

Z.S., H.N., P.N., W.B.K., J.T.C., R.H.S., B.M.C., T.H., E.F., T.Y., S.G., K.C.E., A.A.M., P.K.S., J.-H.C. and S.C. designed the experiments. Z.S., H.N., P.N., C.N., S.E.C., E.N., J.Z., T.P., J.M.P., K.Z. and J.J.P. performed analysis of iPSC-derived interneurons. W.B.K., A.A.M., P.K.S. and J.-H.C. performed electrophysiological studies. T.A.L., H.S.X., C.Y. and W.H. did RNA-seq analysis. T.H., E.F. and T.Y. generated PCDHA KO mice and performed behavioral analysis of PCDHA KO mice. R.E.S., S.G. and K.C.E. performed genotype analysis. L.M.E performed confocal analysis. H.-Y.K. performed statistical analysis. H.N., J.T.C., T.A.L., H.S.X., W.H., T.H., E.F., T.Y., S.G., K.C.E., A.A.M., P.K.S., J.-H.C. and S.C. wrote the manuscript. D.R.W., R.E.S., K.F.B., J.A., D.O., B.M.C., D.L.M., J.L.R. and R.H.P. provided subject cell lines and reviewed data interpretation and manuscript contents. T.H., T.Y., J.-H.C. and S.C. supported this study financially.

Competing interests

T.A.L. and H.S.X. were employees of Pfizer, Inc. at the time this work was performed.

Corresponding authors

Correspondence to Jun-Hyeong Cho or Sangmi Chung.

Integrated supplementary information

  1. Supplementary Figure 1 Immunocytochemistry analysis of generated cINs for cIN phenotypes.

    Related to Fig. 1. The lines used in these experiments are summarized in Supplementary Table 3. After 8 weeks’ differentiation, cINs were stained for (a) β-Tubulin III, (b) SOX6 and (c) GAD1. (Scale bar = 100μm). Similar results were obtained upon repetition of 3 independent differentiations. (d) Cell counting analysis of cINs used in this study. Percentages of cells positive for each marker were quantified in relation to DAPI-stained total nuclei from 3 independent differentiations. 500 cells were counted for each line. There was no significant difference among different lines based on a one-way ANOVA (β-Tubulin III p = 0.0629 for healthy control and p = 0.1244 for schizophrenia; SOX6 p = 0.8148 for healthy control and p = 0.1042 for schizophrenia; GAD1 p = 0.0973 for healthy control and p = 0.3592 for schizophrenia). Data are presented as mean ±SEM.

  2. Supplementary Figure 2 Immunocytochemistry analysis of generated cINs for other neural subtype phenotypes.

    Related to Fig. 1. The lines used in these experiments are summarized in Supplementary Table 3. (a) Immunocytochemistry analysis of VIP+, CCK+, Calretinin+, and COUPTFII+ cells after 8 weeks’ differentiation (Scale bar = 25 or 50 μm). Bottom: Proportions of VIP+ neurons (Non-detectable for both healthy control and schizophrenia), CCK+ neurons (Non-detectable for both healthy control and schizophrenia), Calretinin+ neurons (p = 0.6056, chi-square test) and COUPTFII+ neurons (p = 0.7737, chi-square test) between groups (n = three 429 µm x 327 µm images per group). (b) Immunocytochemistry analysis of OLIG2+, GFAP+, ChAT+, TH+ and 5-HT+ cells. The interneurons were analyzed after 8 weeks’ differentiation (Scale bar = 25 or 50 μm). Bottom: Proportions of OLIG2+ neurons (p = 0.9611, chi-square test), GFAP+ neurons (Non-detectable for both healthy control and schizophrenia), ChAT+ neurons (Non-detectable for both healthy control and schizophrenia), TH+ neurons (p = 0.7012, chi-square test) and 5-HT+ neurons (p = 0.9741, chi-square test) between groups (n = three 429 µm x 327 µm images per group). (c) Positive control staining for VIP, CCK, GFAP, or ChAT antibodies on mouse brain sections. Each staining was repeated with 3 different mouse brains with comparable results.

  3. Supplementary Figure 3 Neuronal properties of cINs transplanted into mouse cerebral cortex.

    Related to Fig. 2. The lines used in these experiments are summarized in Supplementary Table 3. (a) Representative trace of photostimulation-induced action potential (AP) firings recorded in a grafted cell. Action-potential firings were induced by blue light illumination and recorded in current-clamp mode. Photostimulation induced action-potential firings in all 11 grafted cells examined. (b) Rm of grafted human cINs from the healthy control (22 cells) and schizophrenia groups (24 cells). (c) Cm of grafted human cINs from the healthy control (22 cells) and schizophrenia groups (24 cells). (d) Na+ current density of grafted cINs from the healthy control (12 cells) and schizophrenia groups (10 cells). Na+ current density was calculated by dividing Na+ currents measured as in Fig. 2c. (e) K+ current density of grafted cINs from the healthy control (12 cells) and schizophrenia groups (12 cells). K+ current density was calculated by dividing K+ currents measured as in Fig. 2c. (f) Afterhyperpolarization (AHP) of grafted cINs from the healthy control (14 cells) and schizophrenia groups (18 cells). (g) Action potential threshold of grafted cINs from the healthy control (14 cells) and schizophrenia groups (18 cells). (h) Action potential half-width of grafted cINs from the healthy control (9 cells) and schizophrenia groups (13 cells). (i) Resting membrane potential (RMP) of grafted cINs from the healthy control (18 cells) and schizophrenia groups (20 cells). * p = 0.0465. (j) The proportion of cINs with spontaneous action potential (sAP) firings at RMP among all cINs examined. Total 19-21 grafted cells were examined for each group. (k) Average sAP frequency of grafted cINs from the healthy control (14 cells) and schizophrenia groups (13 cells). In (b)-(i) and (k), graphs in left panels indicate data combined for each group (healthy control and schizophrenia; mean ± the SEM), whereas plots in right panels indicate data split for each line (mean ± standard deviation). Circles indicate data obtained from each individual cell. For detailed statistics information, see Supplementary Table 15.

  4. Supplementary Figure 4 Electrophysiological analysis shows the neuronal property of iPSC-derived cINs in vitro.

    Related to Fig. 2. The lines used are summarized in Supplementary Table 3. (a) Representative trace of action potentials induced by depolarizing current injection into cINs near threshold (30 pA, 800 ms long) and recorded in vitro in current-clamp mode (C-clamp) at approximate –70 mV. The experiment was repeated independently in 41 cells with similar results. (b) Representative traces of currents induced by voltage pulses in cINs in vitro. Membrane potential was held at –70 mV in voltage clamp mode (V-Clamp). Left, square voltage steps (800 ms) from –80 mV to –10 mV in increments of 10 mV induced both transient inward and sustained outward currents, mediated by voltage-gated Na+ and K+ channels, respectively. Right, the same trace expanded to visualize the transient inward current. The experiment was repeated independently in 31 cells with similar results. (c) Intrinsic membrane property of iPSC-derived cINs in vitro, including resting membrane potential (RMP), afterhyperpolarization (AHP), action potential threshold, and action potential half-width in cINs in the healthy control (n = 4 lines using average of 4~7 neurons per line) and schizophrenia groups (n = 4 lines using average of 3~6 neurons per line). Data are presents as mean ± SEM. Welch’s t-test (two-sided) was used for statistical analysis.

  5. Supplementary Figure 5 Synaptic properties of cINs transplanted into mouse cerebral cortex.

    Related to Fig. 2. The lines used in these experiments are summarized in Supplementary Table 3. (a) Left: Grafted human interneurons were recorded in acute brain slices. Grafted cells, identified with green fluorescence (GFP+), receive excitatory synaptic inputs from host neurons. Right: Representative trace of postsynaptic responses recorded in a GFP+ grafted cell. Spontaneous excitatory postsynaptic currents (sEPSCs) were recorded in GFP+ grafted cells at –85 mV in voltage-clamp mode in the healthy control (black traces) and schizophrenia groups (red traces). The experiment was repeated independently in 26 cells with similar results. (b) The frequency of sEPSCs in grafted cINs from the healthy control (12 cells) and schizophrenia groups (14 cells). (c) The amplitude of sEPSCs in grafted cINs from the healthy control (12 cells) and schizophrenia groups (14 cells). (d) Left: blue light illumination evokes action-potential firings and induces GABA release in GFP+ interneurons expressing ChR2, generating inhibitory postsynaptic responses in GFP host neuron (Rec). Right: the amplitude of inhibitory postsynaptic currents induced by photostimulation of grafted cINs from the healthy control (15 cells) and schizophrenia groups (13 cells). In (b)-(d), graphs in left panels indicate data combined for each group (healthy control and schizophrenia; mean ± SEM), whereas plots in right panels indicate data split for each line (mean ± standard deviation). Circles indicate data obtained from each individual cell. For detailed statistics information, see Supplementary Table 15.

  6. Supplementary Figure 6 RNA-seq analysis of 4 healthy control and 4 schizophrenia cINs from three independent differentiations.

    Related to Fig. 3. The lines used in this experiment are summarized in Supplementary Table 3. (a) Number of reads generated. Rate (%) = Read number of Pseudoaligned / Read number of Input x 100. (b) Total detected gene number. The gene numbers were counted for those with RPKM > 1. (c) Average of pairwise comparison r2 values. iPSC RNA-seq r2 values are from this study (n = 12 differentiations), while postmortem RNA-seq r2 values were calculated from a publicly available RNA-seq dataset (accession number of GSE87194, n = 19 subjects). (d) Principal component analysis of healthy control and schizophrenia cINs (n = 12 differentiations). (e) Principal component analysis of iPSCs (n = 3 lines), healthy control or schizophrenia cINs (n =12 differentiations), and fibroblasts (n = 3 lines). RNA-seq data of iPSC and fibroblasts were from Choi et al. (Choi, J., et al. A comparison of genetically matched cell lines reveals the equivalence of human iPSCs and ESCs. Nature biotechnology 33, 1173-1181 (2015)). (f) Table of differentially expressed (DE) genes between 4 healthy control and 4 schizophrenia cINs in three independent differentiations (n=12 differentiations) with adjusted p<0.1. Differential expression was analyzed in R by the Voom function in Limma with adjusted multiple testing.

  7. Supplementary Figure 7 RNA-seq analysis of 4 healthy control and 4 schizophrenia cINs for other neural subtype marker expression.

    Related to Fig. 3. The lines used in this experiment are summarized in Supplementary Table 3. RNA-seq transcriptome profiling of cINs derived from 4 healthy control versus 4 schizophrenia iPSCs in three independent differentiations (n = 12 differentiations). Gene expression is shown as reads per kilobase of transcript per million mapped reads (RPKM). Differential expression was analyzed in R by the Voom function in Limma with adjusted multiple testing. Center and error bars show mean ± SEM.

  8. Supplementary Figure 8 Correlation between genotype and gene expression level.

    Related to Fig. 4. The lines used are summarized in Supplementary Table 3. The breakdown data for each line are summarized in Supplementary Table 5-6. (a) rtPCR analysis of PCDHA3, PCDHA6 and PCDHA8 in glutamatergic neurons derived from 4 healthy control versus 4 schizophrenia iPSCs in two independent differentiation (n = 8 differentiations). The expression levels of each gene were normalized using that of the GAPDH gene. Center and error bars show mean ± SEM. (b) eQTL profiles of PCDHA2 in brain cerebellum tissues modified from GTex portal. cis-eQTLs for PCDHA2 at FDR < 5% are plotted by red dots. Green bars designate schizophrenia risk loci (Chr5: 140,023,664-140,222,664). Red box indicates the loci on Chromosome 5 displayed below in detail. More detailed information on this analysis can be found in the GTEx portal (https://gtexportal.org/home/) . (c) Table of PCDHA2 eQTL that has high association with schizophrenia as obtained from the CommonMind portal and GTex portal. More detailed information on this analysis can be found in the CommonMind portal (https://www.synapse.org/#!Synapse:syn2759792/wiki/69613) and the GTEx portal (https://gtexportal.org/home/). (d) eQTL of PCDHA2, PCDHA3, PCDHA6 and PCDHA8 as obtained from the CommonMind portal. More detailed information on this analysis can be found in the CommonMind portal (https://www.synapse.org/#!Synapse:syn2759792/wiki/69613). (e) Quantitative rtPCR analysis of entire PCDHA family and entire PCDHG family in cINs derived from 14 healthy control versus 14 schizophrenia iPSCs in two independent differentiations (n = 28 differentiations). Analyzed using primers against PCDHA-CR and PCDHG-CR. Expression levels of each gene were normalized by those of GAPDH gene. Center and error bars show mean ± SEM. (f) Quantitative rtPCR analysis of entire PCDHA family and entire PCDHG family in glutamatergic neurons derived from 4 healthy control versus 4 schizophrenia iPSCs in two independent differentiations (n = 8 differentiations). Analyzed using primers against PCDHA-CR and PCDHG-CR. The expression levels of each gene were normalized by that of the GAPDH gene. Center and error bars show mean ± SEM. (g) eQTL of other protocadherin family members that are strongly affected in schizophrenia cINs, as adopted from GTEx portal. More detailed information on this analysis can be found in the GTEx portal (https://gtexportal.org/home/). Abbreviation; SNP: single nucleotide polymorphism, FDR: false discovery rate. For detailed statistics information, see also Supplementary Table 16.

  9. Supplementary Figure 9 Arborization and synapse analysis of Pcdha KO mice.

    Related to Fig. 5. (a) Tracing of PV+ cINs in the PFC of littermate wild type or Pcdha KO (Pcdha Δα/Δα) mice (n = 100 neurons). Neurites within 150 µm of the center of PV+ cell body were traced (Scale bar = 50 µm). (b) GABAergic synapse analysis of Pcdha KO versus wild type litter mates (n = 25 images, scale bar = 5 µm). (c) Glutamatergic synapse analysis of Pcdha KO versus wild type litter mates (n = 25 images, scale bar = 5 µm).

  10. Supplementary Figure 10 Arborization analysis of developing schizophrenia cINs.

    Related to Fig. 6. The lines used are summarized in Supplementary Table 3. (a) Linear regression model of the expression level of PCDHA2, PCDHA3, PCDHA6 and PCDHA8 in cINs (x-axis) and total branch numbers (y-axis). n = 18 lines. (b) Tracing of PKC inhibitor-treated healthy control or schizophrenia cINs (n = 160 neurons from two independent differentiations, scale bar = 100 µm). (c) Quantitative real-time PCR analysis of PCDHA or PCDHG expression in cINs transfected with PCDHA siRNA or PCDHG siRNA, compared to negative control siRNA, analyzed three days after transfection (n = 3 differentiations). Data were normalized by GAPDH expression level. Two-sided unpaired t-test was used for analysis. Center and error bars show mean ± SEM. (d) Tracing of GFP+ cINs treated with negative control siRNA, PCDHA siRNA, PCDHG siRNA or mixture (PCDHA siRNA+PCDHG siRNA) (n = 60 neurons, scale bar = 50 µm).

  11. Supplementary Figure 11 Analysis of cINs transplanted in the cortex of Nod Scid mice.

    Related to Fig. 7. The lines used are summarized in Supplementary Table 3 (a) Immunocytochemistry analysis of cINs transplanted in the cortex of Nod Scid mice after 7 months’ grafting (scale bar = 50 µm). Proportion of PV+ neurons among NCAM+ neurons between groups (n = 100 NCAM+ neurons, p = 0.7883, chi-square test). (b) GABAergic synapse analysis of healthy control versus schizophrenia cINs (n = 14 images, scale bar = 5 µm). (c) Glutamatergic synapse analysis of healthy control versus schizophrenia cINs (n = 14 images, scale bar = 5 µm). (d) Linear regression model of PCDHA expression level in cINs (x-axis) and number of inhibitory synapses (juxtaposed GFP+ VGAT+ puncta and Gephyrin+ puncta) per 100 µm2 of GFP+ cINs (y-axis). n = 14 lines.

  12. Supplementary Figure 12 Arborization and synapse analysis of schizophrenia cINs in postmortem tissue.

    Related to Fig. 8. (a) Tracing of layer 3 PV+ cINs in healthy control or schizophrenia postmortem PFC (n = 160 neurons, scale bar = 50 µm). (b) Inhibitory synapse analysis of layer 3 PV+ cINs in healthy control or schizophrenia postmortem PFC (n = 32 images, scale bar = 5 µm). (c) Excitatory synapse analysis of layer 3 PV+ cINs in healthy control or schizophrenia postmortem PFC (n = 32 images, scale bar = 5 µm).

Supplementary information

  1. Supplementary Figures 1–12

    Supplementary Figs. 1–12 and Supplementary Tables 1–18

  2. Reporting Summary

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/s41593-018-0313-z