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Modelling schizophrenia: Opportunities and challenges
Asian Journal of Psychiatry 25 (2017) A1
Contents lists available at ScienceDirect
Asian Journal of Psychiatry journal homepage: www.elsevier.com/locate/ajp
Editorial
Modelling schizophrenia: Opportunities and challenges
Schizophrenia is a complex neuropsychiatric disorder caused by interactions between multiple genetic and environmental factors, with specific risk genes and environmental risk factors being identified. Despite incredible advances in molecular neuroscience and genetics accompanied by the development of a range of powerful imaging and other technologies to investigate the brain, however, our understanding of the pathophysiology of schizophrenia remains obscure (Nasrallah et al., 2011). Even as hundreds of thousands of “findings in schizophrenia” are reported annually, our understanding of its nature continues to be very limited. The profound heterogeneity of schizophrenia (Carpenter and Tandon, 2013), inadequacies in modelling features of the disease (Jennings et al., 2016; Sigurdsson, 2016), and the paucity of unifying constructs (Tandon, 1999) are major contributing factors. In this issue of the Journal, Seshadri et al. (2017) provide a systematic review of schizophrenia studies using human induced pluripotent stem cells (IPSCs) and discuss the potential role of cellular models in the elucidation of the neurobiology of schizophrenia. Using neural derivatives of human IPSCs from tissue obtained from persons with schizophrenia to explicate its pathophysiology holds great promise. In their comprehensive review, Seshadri and colleagues discuss possible future approaches and applications. If we are to truly realize the potential of this technology and make real progress in our understanding of the nature of schizophrenia, however, we must be cognizant of the following caveats: (i) Schizophrenia is not a singular disease but instead consists of a broad collection of disorders with multiple etiologies and pathologies. As we apply any particular model or tool to the study of schizophrenia, it is critical that we define a priori exactly what specific aspect of the disorder or which specific sub-group of persons with the disorder we are studying. In particular, the specific phenotype that we are attempting to model should be explicitly defined before starting the study; (ii) Limitations of cellular models utilizing IPSCs in clarifying the pathophysiology of schizophrenia should be recognized (Lin et al., 2016; Tobe et al., 2011; Young-Pearse and Morrow, 2016). For example, the pathology of schizophrenia develops over time and likely resides at the level of neural circuitry and connectivity and aberrations in circuit development- this is difficult to model in a “dish”; (iii) Clear questions about the nature of schizophrenia along with an explicit “hypothesis to be tested” need to be articulated before applying cellular models or other approaches to evaluation of that hypothesis. Unfortunately, we have tended to “put the cart http://dx.doi.org/10.1016/j.ajp.2017.02.026 1876-2018/© 2017 Published by Elsevier B.V.
before the horse” in our application of various technologies to the study of schizophrenia. We get so enamored by the potency of a new investigative technique that we apply it in an indiscriminate manner and are stuck with “another set of hundreds of new findings” that are uninformative; instead of building a coherent structure of knowledge about schizophrenia, they lie around like bricks in a brickyard (Platt, 1964). If we are to make truly meaningful progress in our understanding of schizophrenia and its treatment, a scientifically rigorous “hypothesis-testing” approach and a bidirectional translational approach (Tandon et al., 2015) are essential. This note of caution applies to cellular models as well. References Carpenter, W.T., Tandon, R., 2013. Psychotic disorders in DSM-5: Summary of changes. Asian J. Psychiatry 6, 266–268. Jennings, C.G., Landman, R., Zhou, Y., et al., 2016. Opportunities and challenges in modelling human brain disorders in transgenic primates. Nat. Neurosci. 19, 1123–1130. Lin, M., Lachman, H.M., Zheng, D., 2016. Transcriptomic analysis of iPSC-derived neurons and modelling of neuropsychiatric disorders. Mol. Clin. Neurosci. 73, 32–42. Nasrallah, H.A., Tandon, R., Keshavan, M.S., 2011. Beyond the facts in schizophrenia: closing the gaps in diagnosis pathophysiology, and treatment. Epidemiol. Psychiatr. Sci. 20, 317–327. Platt, J.R., 1964. Strong inference. Science 146, 347–353. Seshadri, M., Banerjee, D., Viswanath, B., et al., 2017. Cellular models to study schizophrenia. Asian J. Psychiatry 25, 46–53. Sigurdsson, T., 2016. Neural circuit dysfunction in schizophrenia: insights from animal models. Neuroscience 321, 42–65. Tandon, R., Rankupalli, B., Suryadevara, U., Thornton, J., 2015. Psychiatry is a clinical neuroscience, but how do we move the field? Asian J. Psychiatry 17, 135–137. Tandon, R., 1999. Moving beyond findings: concepts and model-building in schizophrenia. J. Psychiatr. Res. 33, 467–471. Tobe, B.T.D., Snyder, E.Y., Nye, J.S., 2011. Challenges of modelling complex neuropsychiatric disorders with human induced pluripotent stem cells (hiPSCs): From disease-in-a-dish to personalized drug discovery. Curr. Opin. Pharmacol. 11, 521–527. Young-Pearse, T.L., Morrow, E.M., 2016. Modelling developmental neuropsychiatric disorders with iPSC technology: challenges and opportunities. Curr. Opin. Neurobiol. 36, 66–73.
Rajiv Tandon* Dawn M. Bruijnzeel University of Florida, USA * Corresponding author at: University of Florida, P.O. Box 103424, Gainesville, FL 32610-3424, USA. E-mail address: tandon@ufl.edu (R. Tandon).
Contents lists available at ScienceDirect
Asian Journal of Psychiatry journal homepage: www.elsevier.com/locate/ajp
Editorial
Modelling schizophrenia: Opportunities and challenges
Schizophrenia is a complex neuropsychiatric disorder caused by interactions between multiple genetic and environmental factors, with specific risk genes and environmental risk factors being identified. Despite incredible advances in molecular neuroscience and genetics accompanied by the development of a range of powerful imaging and other technologies to investigate the brain, however, our understanding of the pathophysiology of schizophrenia remains obscure (Nasrallah et al., 2011). Even as hundreds of thousands of “findings in schizophrenia” are reported annually, our understanding of its nature continues to be very limited. The profound heterogeneity of schizophrenia (Carpenter and Tandon, 2013), inadequacies in modelling features of the disease (Jennings et al., 2016; Sigurdsson, 2016), and the paucity of unifying constructs (Tandon, 1999) are major contributing factors. In this issue of the Journal, Seshadri et al. (2017) provide a systematic review of schizophrenia studies using human induced pluripotent stem cells (IPSCs) and discuss the potential role of cellular models in the elucidation of the neurobiology of schizophrenia. Using neural derivatives of human IPSCs from tissue obtained from persons with schizophrenia to explicate its pathophysiology holds great promise. In their comprehensive review, Seshadri and colleagues discuss possible future approaches and applications. If we are to truly realize the potential of this technology and make real progress in our understanding of the nature of schizophrenia, however, we must be cognizant of the following caveats: (i) Schizophrenia is not a singular disease but instead consists of a broad collection of disorders with multiple etiologies and pathologies. As we apply any particular model or tool to the study of schizophrenia, it is critical that we define a priori exactly what specific aspect of the disorder or which specific sub-group of persons with the disorder we are studying. In particular, the specific phenotype that we are attempting to model should be explicitly defined before starting the study; (ii) Limitations of cellular models utilizing IPSCs in clarifying the pathophysiology of schizophrenia should be recognized (Lin et al., 2016; Tobe et al., 2011; Young-Pearse and Morrow, 2016). For example, the pathology of schizophrenia develops over time and likely resides at the level of neural circuitry and connectivity and aberrations in circuit development- this is difficult to model in a “dish”; (iii) Clear questions about the nature of schizophrenia along with an explicit “hypothesis to be tested” need to be articulated before applying cellular models or other approaches to evaluation of that hypothesis. Unfortunately, we have tended to “put the cart http://dx.doi.org/10.1016/j.ajp.2017.02.026 1876-2018/© 2017 Published by Elsevier B.V.
before the horse” in our application of various technologies to the study of schizophrenia. We get so enamored by the potency of a new investigative technique that we apply it in an indiscriminate manner and are stuck with “another set of hundreds of new findings” that are uninformative; instead of building a coherent structure of knowledge about schizophrenia, they lie around like bricks in a brickyard (Platt, 1964). If we are to make truly meaningful progress in our understanding of schizophrenia and its treatment, a scientifically rigorous “hypothesis-testing” approach and a bidirectional translational approach (Tandon et al., 2015) are essential. This note of caution applies to cellular models as well. References Carpenter, W.T., Tandon, R., 2013. Psychotic disorders in DSM-5: Summary of changes. Asian J. Psychiatry 6, 266–268. Jennings, C.G., Landman, R., Zhou, Y., et al., 2016. Opportunities and challenges in modelling human brain disorders in transgenic primates. Nat. Neurosci. 19, 1123–1130. Lin, M., Lachman, H.M., Zheng, D., 2016. Transcriptomic analysis of iPSC-derived neurons and modelling of neuropsychiatric disorders. Mol. Clin. Neurosci. 73, 32–42. Nasrallah, H.A., Tandon, R., Keshavan, M.S., 2011. Beyond the facts in schizophrenia: closing the gaps in diagnosis pathophysiology, and treatment. Epidemiol. Psychiatr. Sci. 20, 317–327. Platt, J.R., 1964. Strong inference. Science 146, 347–353. Seshadri, M., Banerjee, D., Viswanath, B., et al., 2017. Cellular models to study schizophrenia. Asian J. Psychiatry 25, 46–53. Sigurdsson, T., 2016. Neural circuit dysfunction in schizophrenia: insights from animal models. Neuroscience 321, 42–65. Tandon, R., Rankupalli, B., Suryadevara, U., Thornton, J., 2015. Psychiatry is a clinical neuroscience, but how do we move the field? Asian J. Psychiatry 17, 135–137. Tandon, R., 1999. Moving beyond findings: concepts and model-building in schizophrenia. J. Psychiatr. Res. 33, 467–471. Tobe, B.T.D., Snyder, E.Y., Nye, J.S., 2011. Challenges of modelling complex neuropsychiatric disorders with human induced pluripotent stem cells (hiPSCs): From disease-in-a-dish to personalized drug discovery. Curr. Opin. Pharmacol. 11, 521–527. Young-Pearse, T.L., Morrow, E.M., 2016. Modelling developmental neuropsychiatric disorders with iPSC technology: challenges and opportunities. Curr. Opin. Neurobiol. 36, 66–73.
Rajiv Tandon* Dawn M. Bruijnzeel University of Florida, USA * Corresponding author at: University of Florida, P.O. Box 103424, Gainesville, FL 32610-3424, USA. E-mail address: tandon@ufl.edu (R. Tandon).