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Researchers Model Susceptibility to Schizophrenia in a Petri Dish

13 April 2011. Neurons have been successfully grown from induced pluripotent stem cells (iPSCs) derived from people with schizophrenia, according to a study in Nature appearing online 13 April 2011. Fred Gage of the Salk Institute in La Jolla, California, and colleagues report that, though these neurons resembled those from people without schizophrenia in many ways, they had deficits in forming connections with other neurons, and exhibited differences in gene expression—the researchers highlighted cAMP and Wnt pathway genes—when compared to control neurons. The connectivity and some gene expression aberrations could be "normalized" by treating the neurons with the antipsychotic loxapine.

The study adds schizophrenia to the few diseases that have so far been modeled using iPSCs derived from actual patients. With techniques to reprogram adult, readily obtainable tissue like skin cells into iPSCs, researchers can now try to generate cell types of interest from patient populations to better simulate at a cellular level what may be happening in a particular disease, even in a specific person. While recent studies of patient-specific iPSCs have focused on single gene disorders such as Rett’s syndrome (e.g., Marchetto et al., 2010), the new study marks one of the first attempts to study a disorder with heterogeneous genetic origins.

A brief report in Molecular Psychiatry in February described iPSCs derived from schizophrenia patients (Chiang et al., 2011), but the new study starts to get a handle on features potentially related to disease, comparing the connectivity patterns, synaptic markers, physiology, and gene expression profiles of neurons grown from iPSCs derived from control and schizophrenia subjects.

Missing connections
First author Kristen Brennand and colleagues started with fibroblast samples from four schizophrenia patients: one with childhood onset of the disorder, and three others with an affected parent. Control samples came from age- and ancestry-matched individuals with normal psychiatric evaluations. The fibroblasts were transformed into iPSCs using a lentivirus to introduce genes that reprogrammed the cells into a pluripotent state. The iPSCs were then differentiated into neural precursor cells, and then neurons, over the course of three months. Most turned out to express VGLUT, a marker of glutamatergic cells, about 30 percent expressed GABAergic neuron markers, and less than 10 percent were positive for tyrosine hydroxylase, an enzyme required to make dopamine.

Interconnected neurons derived from induced pluripotent stem cells (iPSCs) from schizophrenia patients. hiPSC neurons are shown expressing the neuronal proteins Beta-III-tubulin (red) and MAP2AB (green). Nuclei are stained with DAPI (blue). Magnification is 20x. Image credit: Kristen Brennand, Salk Institute for Biological Studies

When grown with astrocytes in the dish, the neurons formed connections with each other. Using a modified rabies virus to trace the number of direct inputs received by a given neuron (Wickersham et al., 2007), the researchers measured a decrease in connectivity, with schizophrenia-derived neurons receiving inputs from about half the number of neurons as controls did. Treatment with a variety of antipsychotic agents with affinity for both dopamine and serotonin receptors did not affect connectivity, with one exception: adding loxapine, which targets both dopamine and serotonin receptors about equally (Kapur et al., 1997), to the dish for three weeks boosted connectivity in the schizophrenia neurons.

The researchers also measured slightly fewer neurites, the processes destined to become dendrites or axons, in the schizophrenia hiPSC neurons compared to controls—something the authors compare to the reduced dendritic arborizations found in postmortem brain. The neurons from individuals with schizophrenia also had less staining for PSD95—a protein involved in anchoring proteins at glutamatergic synapses—than control neurons did.

These changes did not seem to compromise synaptic function, however. The researchers report that the schizophrenia hiPSC neurons exhibited normal action potentials, spontaneous excitatory and inhibitory synaptic activity, and spontaneous calcium signals. This overall picture of decreased connectivity with normal synaptic function runs counter to the synaptopathic view of schizophrenia and other disorders (Südhof, 2008) in which the number of synapses is postulated to remain normal, but synaptic function is compromised. The authors suggest that further analysis may, in fact, reveal some functional differences in the neurons derived from individuals with schizophrenia.

Altered expression
With gene expression microarrays, the researchers detected deviations in expression of 596 genes in the schizophrenia neurons that were at least 1.3 times greater or less than the level found in controls. Of these genes, 25 percent had been previously linked to schizophrenia, either through genetic association or postmortem studies. The authors write that gene ontology analysis of the altered expression highlighted glutamate receptor genes, and cAMP and Wnt pathway genes. Other schizophrenia-related genes, including NRG1 and ANK3, had significantly elevated expression in schizophrenia-derived neurons compared to controls. Interestingly, the NRG1 increase was detected only in neurons, and not in fibroblasts or iPSCs from the schizophrenia patients, which argues that it is critical to look at the cell type relevant to a disease. Further study with qPCR verified patterns of altered expression for these and other schizophrenia suspects, and loxapine treatment usually boosted expression of these genes.

However, patients varied in their patterns of gene expression, which may reflect differences in the underlying genetic component contributing to each individual's schizophrenia. To address this, the researchers analyzed copy number variations (CNVs)—losses or gains of segments of DNA—which have been reported to substantially increase risk of schizophrenia (Walsh et al., 2008). They found 42 genes affected by CNVs among their four patients, none of which occurred at regions where CNVs have been previously associated with schizophrenia. Strikingly, only 12 of the genes affected by CNVs showed changes in neuronal expression that correlated with whether a copy of a gene was lost or gained. This suggests that compensatory mechanisms could be at work in these neurons, and indicates that neurons grown from iPSCs may deliver a reality check for ideas gleaned from human CNV studies, which often spur animal models based on an observed deletion or duplication of a particular gene.

Some of the results echo reported pathophysiology in schizophrenia; for example, NRG1 expression was elevated in the neurons grown from iPSCs derived from schizophrenia patients, similar to the increased levels found in postmortem brain tissue (see SRF related news story). Other results suggest new avenues of research, such as finding altered expression in genes related to axon guidance and NOTCH signaling (interestingly, NOTCH4 currently has a positive meta-analysis in SZGene).

A stem cell watershed
Despite the heterogeneous genetic risk factors likely at work in this small patient sample, it is interesting that some consistent results—such as the decrease in connectivity—were obtained. In fact, the authors predict that a narrower, more consistent pattern of expression changes affecting a smaller number of genes will emerge as the number of individuals with schizophrenia studied with iPSCs increases. This is consistent with a "watershed" model that proposes that a vast variety of gene malfunctions could contribute to schizophrenia by converging on the same key biological pathways.

The study marks the beginning of an era of stem cell research of schizophrenia. Future work will refine the description of these neurons and delineate how drugs may change them, and researchers will have to grapple with the interpretation of any results coming from the schizophrenia-derived neurons that happen to resemble, or diverge from, alterations noted in the brains of people with schizophrenia.—Michele Solis.

Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, Gage FH. Modelling schizophrenia using human induced pluripotent stem cells. Nature. 2011 April 13.

Comments on News and Primary Papers
Comment by:  Alan Mackay-Sim
Submitted 13 April 2011
Posted 13 April 2011

With a heritability of 50 percent, schizophrenia is very clearly a disease of disturbed biology, but to dissect the biological contribution to its etiology, researchers need relevant, patient-derived cell models. Ideally, we need cell models that can tell us how schizophrenia cell biology leads to an altered brain. Induced pluripotent stem (iPS) cells are genetically engineered cells, from a patient's cells (e.g., fibroblasts), that resemble embryonic stem cells, that can be used to generate neurons. There is much excitement that they will be useful as models for many brain disorders and diseases. Two new papers in Molecular Psychiatry and Nature report on applying iPS cell technology to schizophrenia by generating iPS cells from patients with a DISC1 mutation (Chiang et al., 2011) and from patients selected with a high likelihood of a genetic component to disease (Brennand et al., 2011).

When specific genes are implicated, then animal models can provide breakthroughs by determining the cellular functions of the implicated genes and their mutations. Although schizophrenia lacks single commonly mutated genes of large effect, some candidate genes, such as DISC1, are being identified in some families. This is now a very hot area for research that is identifying the role of this gene at the cellular level and in animal models. As such candidate genes are identified and their functions are ascertained, it will be essential to demonstrate their direct relevance in schizophrenia through patient-derived cellular models. In this regard, a new tool has emerged in the recent letter to Molecular Psychiatry reporting the generation of induced pluripotent cells from two patients with DISC1 mutation (Chiang et al., 2011). This preliminary study did not report a disease-associated phenotype in these iPS cells.

A disease-associated phenotype is best identified by comparing iPS cells from patients and controls, as now demonstrated by Brennand et al. (2011). This work is a significant new contribution to the field because it has demonstrated differences in the biology of neurons derived from patients and controls. As proof of principle, they have identified differences in the way patient neurons branch (they have fewer branches) and connect with each other (they connect to fewer other neurons). Most importantly, the patient neurons had normal physiological properties. That is to say, their physiology was not different from controls. These are interesting and important distinctions that are a reassuring proof of principle for this model, suggesting that the etiology of schizophrenia derives from altered connectivity of neuronal circuits and not from basic neuronal functions. This fits with the postulated “neurodevelopmental hypothesis” of schizophrenia. Patient neurons also had decreased levels of synaptic proteins (PSD95, glutamate receptor), which is consistent with “synaptic hypotheses” of schizophrenia. These are early days yet, but this cell model already demonstrates how a relevant cell model can provide a path for unifying etiological hypotheses.

Another aim for developing cell models of schizophrenia is to use them for drug discovery. Patient-control differences in cell functions can be the basis for screening chemical compounds that ameliorate this difference. Here, too, Brennand et al. (2011) demonstrate proof of principle by showing that loxapine treatment of the patient neurons increased their connectivity towards control levels. Only loxapine, of five antipsychotic drugs tested, had this effect, but the results are a clear sign of the utility of such cells for drug screening to find new potential drug candidates.

These two papers are a great start to using iPS cells as models of schizophrenia.


Chiang CH, Su1Y, Wen Z, Yoritomo N, Ross CA, Margolis RL, Song H, Ming G-I. (2011) Integration-free induced pluripotent stem cells derived from schizophrenia patients with a DISC1 mutation. Molecular Psychiatry advance online publication, 22 February 2011. Abstract

Brennand KJ, Simone A, Jou1 J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, Gage FH (2011). Modeling schizophrenia using human induced pluripotent stem cells. Nature.

View all comments by Alan Mackay-SimComment by:  Akira Sawa, SRF Advisor
Submitted 13 April 2011
Posted 13 April 2011

I fully appreciate the efforts of Brennand and colleagues as pioneers. Indeed, this is great work. Like any pioneering work, this paper will be both applauded and criticized. The strength of the paper is in providing ways for us to analyze iPS cells and derived neurons. The multifaceted approach taken in this study will be a great platform for many investigators.

Schizophrenia is, clinically, a very heterogeneous condition, but for the past several years, basic scientists have tended to oversimplify the disorder. It is also true that this trend makes the neurobiology of schizophrenia move productively forward in some ways. I believe that the new tools for studying the biology of schizophrenia, such as iPSC-derived neurons, will teach us how difficult it is to draw simplified pathways for the disorder. Nonetheless, some common pathway(s) may be identified in the future, I optimistically hope.

Based on the great experimental procedures that this paper provides, many other groups may need to address whether or not these data are reproducible or not in “general” cases of schizophrenia. In such studies, the most important issue is to examine detailed clinical information of the subjects in comparison with this study.

View all comments by Akira Sawa

Comments on Related News

Related News: Polymorphisms and Schizophrenia—The Ups and Downs of Neuregulin Expression

Comment by:  William Carpenter, SRF Advisor (Disclosure)
Submitted 22 April 2006
Posted 22 April 2006
  I recommend the Primary Papers

Related News: Polymorphisms and Schizophrenia—The Ups and Downs of Neuregulin Expression

Comment by:  Stephan Heckers, SRF Advisor
Submitted 29 April 2006
Posted 29 April 2006
  I recommend the Primary Papers

The gene Neuregulin 1 (NRG1) on chromosome 8p has been identified as one of the risk genes for schizophrenia. It is unclear how the DNA sequence variation linked to schizophrenia leads to abnormalities of mRNA expression. This would be important to know, in order to understand the downstream effects of the neuregulin gene on neuronal functioning in schizophrenia.

Law and colleagues explored this question in post-mortem specimens of the hippocampus of control subjects and patients with schizophrenia. This elegant study of the expression of four types of NRG1 mRNA (types I-IV) is exactly what we need to translate findings from the field of human genetics into the field of schizophrenia neuropathology. The findings are complex and cannot be translated easily into a model of neuregulin dysfunction in schizophrenia. I would like to highlight two findings.

First, the level of NRG1 type I mRNA expression was increased in the hippocampus of schizophrenia patients. This confirms an earlier study of NRG1 mRNA expression in schizophrenia. It remains to be seen how this change in NRG1 type I mRNA expression relates to the finer details of neuregulin dysfunction in schizophrenia.

Second, one single nucleotide polymorphism (SNP8NRG243177) of the risk haplotype linked to schizophrenia in earlier studies predicts NRG1 type IV mRNA expression. The SNP determines a binding site for transcription factors, providing clues for how DNA sequence variation may lead, via modulation of mRNA expression, to neuronal dysfunction in schizophrenia. It is exciting to see that we can now test specific hypotheses of molecular mechanisms in the brains of patients who have suffered from schizophrenia. The study by Law et al. is an encouraging step in the right direction.

View all comments by Stephan Heckers

Related News: Polymorphisms and Schizophrenia—The Ups and Downs of Neuregulin Expression

Comment by:  Bryan Roth, SRF Advisor
Submitted 5 May 2006
Posted 5 May 2006
  I recommend the Primary Papers

I think this is a very interesting and potentially significant paper. It is important to point out, however, that it deals with changes in mRNA abundance rather than alterations in neuregulin protein expression. No measures of isoform protein expression were performed, and it is conceivable that neuregulin isoform protein expression could be increased, decreased, or not changed. A second point is that although statistically significant changes in mRNA were measured, they are modest.

Finally, although multiple comparisons were performed, the authors chose not to perform Bonferroni corrections, noting in the primary paper that, "Correction for random effects, such as Bonferroni correction, would be an excessively conservative approach, particularly given that we have restricted our primary analyses to planned comparisons (based on strong prior clinical association and physical location of the SNPs) of four SNPs and a single haplotype comprised of these SNPs. Because the SNPs are in moderate LD, the degree of independence between markers is low and, therefore, correcting for multiple testing would result in a high type II error rate. The prior probability and the predictable association between the deCODE haplotype and expression of NRG1 isoforms (especially type IV, which is its immediate physical neighbor) combined with the LD between SNPs in this haplotype makes statistical correction for these comparisons inappropriate. Nevertheless, our finding regarding type IV expression and the deCODE haplotype and SNP8NRG243177 requires independent replication."

It will thus be important to determine if these changes in neuregulin mRNA isoform abundance are mirrored by significant changes in neuregulin isoform protein expression and if the findings can be independently replicated with other cohorts.

View all comments by Bryan Roth

Related News: Polymorphisms and Schizophrenia—The Ups and Downs of Neuregulin Expression

Comment by:  Patricia Estani
Submitted 9 June 2007
Posted 10 June 2007
  I recommend the Primary Papers

Related News: Deciphering Themes for Schizophrenia’s Genetic Variation

Comment by:  Patrick Sullivan, SRF AdvisorDanielle Posthuma
Submitted 16 November 2012
Posted 16 November 2012

Gilman et al. pose exceptionally important and salient questions: given that increasingly detailed genomic data have established that many genes are now strongly implicated in the etiology of schizophrenia, how do we understand this? How can these different components of the “parts list” for schizophrenia be pieced together to derive a cogent etiological hypothesis for further testing?

The authors use a new computational approach to address these questions, and derive lists related to axon guidance, neuronal cell mobility, synaptic function, and chromosomal remodeling. Additional analyses suggest the coherence of their lists. These are good clues that deserve further evaluation.

It was intriguing that the authors included multiple types of genetic variation—rare but potent copy number variants (e.g., Kirov et al., 2012), rare exonic mutations (Xu et al., 2012), and common variations from genomewide association studies (Ripke et al., 2011)—as most authors have tended to conduct these analyses separately.

In sum, a nice contribution to the literature and initial steps towards tackling a tough problem in human genetics. But, there are four issues for readers to bear in mind in evaluating the results.

First, we hope that the authors make their program freely available. This is the standard in the field. Many of us are interested in evaluating the capacities of their program. To our knowledge, it is not now available, although it has been used in multiple published papers. We could find no link in the paper or on the senior author’s lab page.

Second, readers need to remember that this was an in-silico analysis. It produces hypotheses but does not (and cannot) provide proof. The methods are subject to multiple biases, and it was not clear how well these were controlled (see point 4 as well). We wondered whether known biases like gene size and LD patterns were well controlled.

Third, we would have liked to see greater scholarship. There is an unfortunate trend for computational biologists to produce tools without benchmarking them against existing tools or rigorously determining power and error rates. The lack of finding significant clusters in control sets is insufficient in showing the validity of their program. Are the authors’ claims that their new tool represents superiority truly justified?

Moreover, there are a lot of tools for performing analyses of these sorts (e.g., INRICH, FORGE, MAGENTA, Ingenuity, ALIGATOR, among many others). Indeed, these sorts of analyses are in the toolkits of most psychiatric genetics groups and are routinely applied. Given that there are many papers reporting results, a scholarly treatment of how their results compare to those of others and what the added value of their program is would have been useful.

Fourth, and most importantly, pathway analysis is completely dependent on the input—the genetic findings and the pathways. The findings that the authors used had issues. The CNV list is likely to change soon as the PGC CNV group completes its integrated analyses of tens of thousands of subjects. The exome list was based on a small and atypical sample, and much larger studies are in preparation (see SRF comment). The authors did not seem to confront the issue that all humans contain a lot of deleterious exonic variation. And (spoiler alert), the GWAS list is soon to increase markedly. More and more precise findings are sure to alter the results.

The pathways used were pretty standard—GO, KEGG, protein-protein interaction databases. Unfortunately, although widely used, these pathways have multiple issues. The content of many GO annotations and KEGG pathways have not been constructed by experts in the area. As one salient example, synaptic gene lists in standard pathway databases were quite imperfectly related to lists created by experts (Ruano et al., 2010). The authors also relied somewhat uncritically on the PPI databases. These have multiple issues, and some (unpublished) data suggest substantial error (i.e., large fractions of the predicted interactions are not, in fact, real or biologically meaningful). The fraction of the proteome screened adequately by these methods is small. Some interactions in these databases are non-specific, or occur between molecules that are never in the same place at the same time.

Indeed, the genes overrepresented in PPI databases were selected due to disease relevance or biological importance (e.g., there is a lot of work on P53). In general, the more a gene is investigated, the more interactions are found.

Still, this is a key paper, albeit a snapshot based on imperfect input data, and we look forward to seeing whether additional analyses confirm a role in schizophrenia of the networks identified currently with their program.


Kirov G, Pocklington AJ, Holmans P, Ivanov D, Ikeda M, Ruderfer D, Moran J, Chambert K, Toncheva D, Georgieva L, Grozeva D, Fjodorova M, Wollerton R, Rees E, Nikolov I, van de Lagemaat LN, Bayés A, Fernandez E, Olason PI, Böttcher Y, Komiyama NH, Collins MO, Choudhary J, Stefansson K, Stefansson H, Grant SG, Purcell S, Sklar P, O'Donovan MC, Owen MJ. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol Psychiatry. 2012 Feb; 17(2):142-53. Abstract

Xu B, Ionita-Laza I, Roos JL, Boone B, Woodrick S, Sun Y, Levy S, Gogos JA, Karayiorgou M. De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia. Nat Genet. 2012 Oct 3. Abstract

Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, Lin DY, Duan J, Ophoff RA, Andreassen OA, Scolnick E, Cichon S, St Clair D, Corvin A, Gurling H, Werge T, Rujescu D, Blackwood DH, Pato CN, Malhotra AK, Purcell S, Dudbridge F, Neale BM, Rossin L, Visscher PM, Posthuma D, Ruderfer DM, Fanous A, Stefansson H, Steinberg S, Mowry BJ, Golimbet V, de Hert M, Jönsson EG, Bitter I, Pietiläinen OP, Collier DA, Tosato S, Agartz I, Albus M, Alexander M, Amdur RL, Amin F, Bass N, Bergen SE, Black DW, Børglum AD, Brown MA, Bruggeman R, Buccola NG, Byerley WF, Cahn W, Cantor RM, Carr VJ, Catts SV, Choudhury K, Cloninger CR, Cormican P, Craddock N, Danoy PA, Datta S, de Haan L, Demontis D, Dikeos D, Djurovic S, Donnelly P, Donohoe G, Duong L, Dwyer S, Fink-Jensen A, Freedman R, Freimer NB, Friedl M, Georgieva L, Giegling I, Gill M, Glenthøj B, Godard S, Hamshere M, Hansen M, Hansen T, Hartmann AM, Henskens FA, Hougaard DM, Hultman CM, Ingason A, Jablensky AV, Jakobsen KD, Jay M, Jürgens G, Kahn RS, Keller MC, Kenis G, Kenny E, Kim Y, Kirov GK, Konnerth H, Konte B, Krabbendam L, Krasucki R, Lasseter VK, Laurent C, Lawrence J, Lencz T, Lerer FB, Liang KY, Lichtenstein P, Lieberman JA, Linszen DH, Lönnqvist J, Loughland CM, Maclean AW, Maher BS, Maier W, Mallet J, Malloy P, Mattheisen M, Mattingsdal M, McGhee KA, McGrath JJ, McIntosh A, McLean DE, McQuillin A, Melle I, Michie PT, Milanova V, Morris DW, Mors O, Mortensen PB, Moskvina V, Muglia P, Myin-Germeys I, Nertney DA, Nestadt G, Nielsen J, Nikolov I, Nordentoft M, Norton N, Nöthen MM, O'Dushlaine CT, Olincy A, Olsen L, O'Neill FA, Orntoft TF, Owen MJ, Pantelis C, Papadimitriou G, Pato MT, Peltonen L, Petursson H, Pickard B, Pimm J, Pulver AE, Puri V, Quested D, Quinn EM, Rasmussen HB, Réthelyi JM, Ribble R, Rietschel M, Riley BP, Ruggeri M, Schall U, Schulze TG, Schwab SG, Scott RJ, Shi J, Sigurdsson E, Silverman JM, Spencer CC, Stefansson K, Strange A, Strengman E, Stroup TS, Suvisaari J, Terenius L, Thirumalai S, Thygesen JH, Timm S, Toncheva D, van den Oord E, van Os J, van Winkel R, Veldink J, Walsh D, Wang AG, Wiersma D, Wildenauer DB, Williams HJ, Williams NM, Wormley B, Zammit S, Sullivan PF, O'Donovan MC, Daly MJ, Gejman PV. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011 Oct ; 43(10):969-76. Abstract

Ruano D, Abecasis GR, Glaser B, Lips ES, Cornelisse LN, de Jong AP, Evans DM, Davey Smith G, Timpson NJ, Smit AB, Heutink P, Verhage M, Posthuma D. Functional gene group analysis reveals a role of synaptic heterotrimeric G proteins in cognitive ability. Am J Hum Genet. 2010 Feb 12;86(2):113-25. Abstract

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Related News: Neural Progenitor Cells Model Aspects of Schizophrenia

Comment by:  Nao GamoAkira Sawa (SRF Advisor)
Submitted 7 May 2014
Posted 7 May 2014

This study introduces a novel use of neural progenitor cells (NPCs) derived from human induced pluripotent stem cells (hiPSCs) to address mechanisms that may possibly underlie a predisposition to schizophrenia. Brennand et al. (2014) generated hiPSC-derived NPCs from patients with schizophrenia and control subjects. These NPCs, as well as six-week-old neurons differentiated from them, showed gene expression profiles similar to those of the fetal forebrain. Thus, these cells were used to address early disease etiology, in particular, focusing on mechanisms related to disruptions in prefrontal cortical development. Interestingly, the researchers found overlap in gene signatures between the six-week-old neurons and NPCs from patients, raising the possibility that disease predisposition may already be established at the NPC stage.

Particularly striking is the reduced migration of schizophrenia NPCs relative to control NPCs as they differentiated into neurons. This reduced migration may be due to schizophrenia NPCs remaining in a proliferative state before differentiating, as suggested by previous work from our group (Ishizuka et al., 2011). The authors also proposed that this reduced migration might lead to reduced synaptic connectivity, which they previously reported in schizophrenia hiPSC-derived neurons (Brennand et al., 2011).

The study also found differential expression of various genes and proteins, including those involved in neuronal differentiation and migration, glutamate receptor signaling, and cellular adhesion. The schizophrenia NPCs showed smaller mitochondria with altered cellular distribution relative to control NPCs, as well as oxidative stress, although the effects of oxidative stress might be limited to a subset of schizophrenia NPCs. This is a telling observation, in light of recent human and animal studies that suggest a role for oxidative stress in schizophrenia (Emiliani et al., 2014).

While it is as yet unknown whether these observations truly reflect disease predisposition, this work is innovative in taking advantage of the tools at hand. It is understood in the field that hiPSC-derived neurons can take months to fully functionally mature, and it would be difficult to simulate experience-dependent shaping of neuronal networks in a dish. However, instead of tolerating such shortcomings, the authors have used them to their advantage by addressing mechanisms that may occur at the fetal stage. Furthermore, NPCs are proliferative and suitable for high-throughput assays. This point is particularly useful when studying a disease with such heterogeneous etiology.

The true value of this experimental system will be revealed when it can predict actual brain mechanisms and clinical characteristics of individuals as well as groups of patients. The authors acknowledge that the sample size is currently small, and that the effect sizes of their observations are insufficient to predict diagnosis. It would be interesting to observe neuronal phenotypes in cells from patients with similar clinical characteristics. In addition, cells from patients with similar genetic backgrounds should be tested to control for possible biases in genetic architecture, for example, in cells from family members, or known mutations that can be created in control cell lines. We are optimistic that hiPSCs will prove a useful tool to study biological mechanisms of schizophrenia (Gamo et al., 2014, in press).


Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, Gage FH. Modelling schizophrenia using human induced pluripotent stem cells. Nature . 2011 May 12 ; 473(7346):221-5. Abstract

Emiliani FE, Sedlak TW, Sawa A. Oxidative stress and schizophrenia: recent breakthroughs from an old story. Curr Opin Psychiatry . 2014 May ; 27(3):185-90. Abstract

Gamo and Sawa (in press). Human Stem Cells and Surrogate Tissues for Basic and Translational Study of Mental Disorders. Biol. Psychiatry.

Ishizuka K, Kamiya A, Oh EC, Kanki H, Seshadri S, Robinson JF, Murdoch H, Dunlop AJ, Kubo K, Furukori K, Huang B, Zeledon M, Hayashi-Takagi A, Okano H, Nakajima K, Houslay MD, Katsanis N, Sawa A. DISC1-dependent switch from progenitor proliferation to migration in the developing cortex. Nature . 2011 May 5 ; 473(7345):92-6. Abstract

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Related News: Neural Progenitor Cells Model Aspects of Schizophrenia

Comment by:  Bryan MowrySamuel Nayler
Submitted 29 May 2014
Posted 29 May 2014

In a recent follow-up to their 2011 paper, Brennand et al. report considerable progress toward generation of a defined neuronal population generated from patient-derived induced pluripotent stem (iPS) cells. The advent of the iPS cell has been somewhat Promethean in that pluripotent stem cells are now a commonly utilized laboratory tool for disease modeling. While marked progress has occurred on a number of fronts, it is still not known to what degree stem cell-derived neurons truly resemble mature neurons that exist in the brain of a living human. Moreover, it is an open question what these cells can tell us about the onset of a clinically heterogeneous, polygenic disease such as schizophrenia.

Using gene expression analysis, Brennand et al. compare their samples to a developmental spectrum of samples from the Allen Brain Atlas to show that their iPSC-derived neurons most closely resemble early fetal forebrain neurons. This may provide precisely the model system that will allow researchers to validate the neurodevelopmental theory of schizophrenia, provided early molecular mechanisms can be identified that predispose to schizophrenia in later life. Brennand and colleagues go on to show functional phenotypic differences in schizophrenia patient-derived neurons relating to elevated oxidative stress and extra-mitochondrial oxygen consumption, as well as reduced migrational ability. It remains to be seen how relatable these phenomena are to events which occur in vivo and whether they may be informative in identifying and characterizing the underlying molecular and cellular mechanisms in schizophrenia.

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Related News: 15q11.2 Deletions Point to Cytoskeleton, Altered Migration in Schizophrenia

Comment by:  Kristen Brennand
Submitted 15 July 2014
Posted 15 July 2014

In their recent Cell Stem Cell publication, Yoon et al. convincingly demonstrate that, of the genes encompassed by the 15q11.2 copy number variation—a major risk factor for both schizophrenia and autism—haploinsufficiency of the gene CYFIP1 may play a major role in the cellular defects observed in patient-derived neural stem cells (NSCs) (Yoon et al., 2014). This paper goes beyond simply demonstrating that 15q11.2 iPSC-derived NSCs have a polarity defect that is associated with a destabilization of the CYFIP1-interacting WAVE1/2 protein complex. Using complementary strategies, the authors show defects in neural polarity between iPSC-derived neural rosettes in vitro and embryonic mouse radial glia cells in vivo.

In an elegant series of studies, the authors employ both shRNA-knockdown of Cyfip1 in E13.5 mouse neocortex and subsequent rescue by lentiviral overexpression of shRNA-resistant Cyfip1. This work demonstrates that decreased Cyfip1 contributes not just to aberrant localization of Pax6+ radial glia cells outside the ventricular zone, but also the ectopic expansion of Tbr2+ intermediate progenitor cells and Cux1+ cortical neurons toward the upper cortical layers. The authors also present evidence that retroviral-mediated knockdown of Cyfip1, specifically in replicating radial glial cells, leads to decreased levels of several components of the WAVE signaling complex, including WAVE1, WAVE2, Abi1, and Nap1; moreover, knockdown of Abi1 (or its downstream effectors) leads to similar RGC defects in neural polarity and localization.

The only potential criticism of this compelling study—and it’s a minor one—is that the study of epistasis interactions between gene expression variants of WAVE signaling components does not extend far enough. Because it includes just 64 postmortem samples, from healthy controls only, it falls short of convincingly establishing that common variants in WAVE components contribute to schizophrenia. Despite this limitation, statistically significant interactions were identified, which will hopefully compel geneticists with access to larger patient cohorts to further investigate the contribution of common variants in WAVE signaling components to psychiatric disease. If more comprehensive follow-up analysis of larger GWAS datasets confirms the association of CYFIP1 and other WAVE components to genetically diverse cases of schizophrenia and autism, this may open up a new therapeutic avenue with application beyond just 15q11.2 patients with deletions in CYFIP1.

Two other important conclusions can be drawn from this study. First, although generally considered to be a disease of functional mature nuerons, it appears that some of the genetic risk factors for schizophrenia may act early in neural development and at the level of neural progenitor cells, prior to their differentiation into functional neurons. This is in line with the neurodevelopmental hypothesis of schizophrenia and is consistent with several other recent iPSC-based studies of schizophrenia by myself (Brennand et al., 2014) and others (Robicsek et al., 2013). Second, it suggests that common variants contributing to schizophrenia risk may overlap with genes encompassed by highly penetrant CNVs, and focuses attention on a new risk allele under-explored to date in GWAS and postmortem expression studies.

Though published in a stem cell journal, this paper demonstrates the utility of patient-derived iPSC-based models in the study of the neurodevelopment of psychiatric disease; thus, it is worthy of attention beyond the stem cell audience and should be noted particularly by psychiatrists and geneticists.


Brennand K, Savas JN, Kim Y, Tran N, Simone A, Hashimoto-Torii K, Beaumont KG, Kim HJ, Topol A, Ladran I, Abdelrahim M, Matikainen-Ankney B, Chao SH, Mrksich M, Rakic P, Fang G, Zhang B, Yates JR, Gage FH. Phenotypic differences in hiPSC NPCs derived from patients with schizophrenia. Mol Psychiatry . 2014 Apr 1. Abstract

Robicsek O, Karry R, Petit I, Salman-Kesner N, Müller FJ, Klein E, Aberdam D, Ben-Shachar D. Abnormal neuronal differentiation and mitochondrial dysfunction in hair follicle-derived induced pluripotent stem cells of schizophrenia patients. Mol Psychiatry . 2013 Oct ; 18(10):1067-76. Abstract

Yoon KJ, Nguyen HN, Ursini G, Zhang F, Kim NS, Wen Z, Makri G, Nauen D, Shin JH, Park Y, Chung R, Pekle E, Zhang C, Towe M, Hussaini SM, Lee Y, Rujescu D, St Clair D, Kleinman JE, Hyde TM, Krauss G, Christian KM, Rapoport JL, Weinberger DR, Song H, Ming GL. Modeling a Genetic Risk for Schizophrenia in iPSCs and Mice Reveals Neural Stem Cell Deficits Associated with Adherens Junctions and Polarity. Cell Stem Cell . 2014 Jul 3 ; 15(1):79-91. Abstract

View all comments by Kristen Brennand

Related News: Patient-Derived Bipolar Neurons Reproduce Clinical Response to Lithium

Comment by:  Irving Gottesman, SRF Advisor
Submitted 4 November 2015
Posted 10 November 2015
  I recommend the Primary Papers

When a superstar such as Fred Gage uses the endophenotype strategy with skin cells from bipolar patients to gather induced pluripotent stem cell (iPSC) technology, it is high praise indeed for a strategy highlighted in SRF.

View all comments by Irving Gottesman