1
|
Stephens RL, Leavitt I, Cornea E, Jarskog LF, Gilmore JH. Early cognitive development and psychopathology in children at familial high risk for schizophrenia. Schizophr Res 2024; 271:262-270. [PMID: 39068878 DOI: 10.1016/j.schres.2024.07.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 07/10/2024] [Accepted: 07/13/2024] [Indexed: 07/30/2024]
Abstract
Schizophrenia is a neurodevelopmental disorder associated with deficits in cognitive development and childhood psychopathology. Previous studies have focused on older children and the few studies of early childhood have yielded inconsistent findings. We studied cognitive development and psychopathology in children at familial high risk (FHR) of schizophrenia and matched controls from 1 to 6 years and hypothesized that FHR children would show consistent deficits across cognitive and behavioral measures in early childhood. STUDY DESIGN Cognitive development in children at high familial risk for schizophrenia or schizoaffective disorder (n = 33) and matched healthy controls (n = 66) was assessed at 1 and 2 years with the Mullen Scales of Early Learning, and at 4 and 6 years with the Stanford Binet Intelligence Scales, BRIEF-P/BRIEF and CANTAB. Psychopathology was assessed at 4 and 6 years with the BASC-2. General linear models were used to examine differences on outcome scores, and chi-square analyses were used to explore differences in the proportion of "at risk" or "below average" score profiles. STUDY RESULTS FHR children scored significantly lower than controls on Mullen Composite at age 2, and demonstrated broad deficits in IQ, executive function and working memory and 4 and 6 years. FHR children were also rated as significantly worse on most items of the BASC-2 at ages 4 and 6. CONCLUSIONS Children at FHR for schizophrenia demonstrate abnormal cognitive development and psychopathology at younger ages than previously detected, suggesting that early detection and intervention needs to be targeted to very early childhood.
Collapse
Affiliation(s)
- Rebecca L Stephens
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Isabel Leavitt
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - L Fredrik Jarskog
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
| |
Collapse
|
2
|
Prasad KM, Muldoon B, Theis N, Iyengar S, Keshavan MS. Multipronged investigation of morphometry and connectivity of hippocampal network in relation to risk for psychosis using ultrahigh field MRI. Schizophr Res 2023; 256:88-97. [PMID: 37196534 PMCID: PMC10363272 DOI: 10.1016/j.schres.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 04/10/2023] [Accepted: 05/02/2023] [Indexed: 05/19/2023]
Abstract
Hippocampal abnormalities are associated with psychosis-risk states. Given the complexity of hippocampal anatomy, we conducted a multipronged examination of morphometry of regions connected with hippocampus, and structural covariance network (SCN) and diffusion-weighted circuitry among 27 familial high-risk (FHR) individuals who were past the highest risk for conversion to psychoses and 41 healthy controls using ultrahigh-field high-resolution 7 Tesla (7T) structural and diffusion MRI data. We obtained fractional anisotropy and diffusion streams of white matter connections and examined correspondence of diffusion streams with SCN edges. Nearly 89 % of the FHR group had an axis-I disorder including 5 with schizophrenia. Therefore, we compared the entire FHR group regardless of the diagnosis (All_FHR = 27) and FHR-without-schizophrenia (n = 22) with 41 controls in this integrative multimodal analysis. We found striking volume loss in bilateral hippocampus, particularly the head, bilateral thalamus, caudate, and prefrontal regions. All_FHR and FHR-without-SZ SCNs showed significantly lower assortativity and transitivity but higher diameter compared to controls, but FHR-without-SZ SCN differed on every graph metric compared to All_FHR suggesting disarrayed network with no hippocampal hubs. Fractional anisotropy and diffusion streams were lower in FHR suggesting white matter network impairment. White matter edges showed significantly higher correspondence with SCN edges in FHR compared to controls. These differences correlated with psychopathology and cognitive measures. Our data suggest that hippocampus may be a "neural hub" contributing to psychosis risk. Higher correspondence of white matter tracts with SCN edges suggest that shared volume loss may be more coordinated among regions within the hippocampal white matter circuitry.
Collapse
Affiliation(s)
- Konasale M Prasad
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, PA, United States of America; VA Pittsburgh Healthcare System, Pittsburgh, PA, United States of America.
| | - Brendan Muldoon
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Nicholas Theis
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America
| |
Collapse
|
3
|
Xie M, Cai J, Liu Y, Wei W, Zhao Z, Dai M, Wu Y, Huang Y, Tang Y, Xiao L, Zhang G, Li C, Guo W, Ma X, Deng W, Du X, Wang Q, Li T. Association between childhood trauma and white matter deficits in first-episode schizophrenia. Psychiatry Res 2023; 323:115111. [PMID: 36924585 DOI: 10.1016/j.psychres.2023.115111] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/28/2023] [Accepted: 02/14/2023] [Indexed: 03/18/2023]
Abstract
OBJECTIVE This study aimed to investigate the relationship between childhood trauma (ChT) and white matter (WM) deficits in first-episode schizophrenia (FES). METHODS A total of 103 individuals with FES and 206 healthy control individuals (HCs) were enrolled and assessed based on ChT Questionnaire (CTQ) and Positive and Negative Symptoms Scale (PANSS). Diffusion tensor imaging was acquired on a Signa 3.0 T scanner. Map of fractional anisotropy (FA) was analyzed using Tract-Based Spatial Statistics. Hierarchical logistic regression analyses were used to examine associations of sociodemographic characteristics, total CTQ scores, and WM deficits. RESULTS Compared with the HCs group, the FES group showed significantly lower FA in several WM bundles (left anterior thalamic radiation, left inferior frontal-occipital fasciculus, left cingulum, forceps major, and forceps minor), and the mean FA value in these WM bundles was inversely related to the total CTQ score. In addition, a higher CTQ score may increase the risk of schizophrenia, while higher FA values may decrease the risk of schizophrenia. CONCLUSION This study demonstrates that individuals with FES evince widespread cerebral WM abnormalities and that these abnormalities were associated with ChT. These results provide clues about the neural basis and potential biomarkers of schizophrenia.
Collapse
Affiliation(s)
- Min Xie
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Jia Cai
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yunjia Liu
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Wei Wei
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China
| | - Zhengyang Zhao
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Minhan Dai
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yulu Wu
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yunqi Huang
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yiguo Tang
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Liling Xiao
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Guangya Zhang
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu, China
| | - Chuanwei Li
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu, China
| | - Wanjun Guo
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China
| | - Xiaohong Ma
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Wei Deng
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China
| | - Xiangdong Du
- Suzhou Psychiatry Hospital, Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu, China
| | - Qiang Wang
- Mental Health Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
| | - Tao Li
- Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang, China.
| |
Collapse
|
4
|
Vanes LD, Murray RM, Nosarti C. Adult outcome of preterm birth: Implications for neurodevelopmental theories of psychosis. Schizophr Res 2022; 247:41-54. [PMID: 34006427 DOI: 10.1016/j.schres.2021.04.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 12/22/2022]
Abstract
Preterm birth is associated with an elevated risk of developmental and adult psychiatric disorders, including psychosis. In this review, we evaluate the implications of neurodevelopmental, cognitive, motor, and social sequelae of preterm birth for developing psychosis, with an emphasis on outcomes observed in adulthood. Abnormal brain development precipitated by early exposure to the extra-uterine environment, and exacerbated by neuroinflammation, neonatal brain injury, and genetic vulnerability, can result in alterations of brain structure and function persisting into adulthood. These alterations, including abnormal regional brain volumes and white matter macro- and micro-structure, can critically impair functional (e.g. frontoparietal and thalamocortical) network connectivity in a manner characteristic of psychotic illness. The resulting executive, social, and motor dysfunctions may constitute the basis for behavioural vulnerability ultimately giving rise to psychotic symptomatology. There are many pathways to psychosis, but elucidating more precisely the mechanisms whereby preterm birth increases risk may shed light on that route consequent upon early neurodevelopmental insult.
Collapse
Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| |
Collapse
|
5
|
Short SJ, Jang DK, Steiner RJ, Stephens RL, Girault JB, Styner M, Gilmore JH. Diffusion Tensor Based White Matter Tract Atlases for Pediatric Populations. Front Neurosci 2022; 16:806268. [PMID: 35401073 PMCID: PMC8985548 DOI: 10.3389/fnins.2022.806268] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 01/27/2022] [Indexed: 01/14/2023] Open
Abstract
Diffusion Tensor Imaging (DTI) is a non-invasive neuroimaging method that has become the most widely employed MRI modality for investigations of white matter fiber pathways. DTI has proven especially valuable for improving our understanding of normative white matter maturation across the life span and has also been used to index clinical pathology and cognitive function. Despite its increasing popularity, especially in pediatric research, the majority of existing studies examining infant white matter maturation depend on regional or white matter skeleton-based approaches. These methods generally lack the sensitivity and spatial specificity of more advanced functional analysis options that provide information about microstructural properties of white matter along fiber bundles. DTI studies of early postnatal brain development show that profound microstructural and maturational changes take place during the first two years of life. The pattern and rate of these changes vary greatly throughout the brain during this time compared to the rest of the life span. For this reason, appropriate image processing of infant MR imaging requires the use of age-specific reference atlases. This article provides an overview of the pre-processing, atlas building, and the fiber tractography procedures used to generate two atlas resources, one for neonates and one for 1- to 2-year-old populations. Via the UNC-NAMIC DTI Fiber Analysis Framework, our pediatric atlases provide the computational templates necessary for the fully automatic analysis of infant DTI data. To the best of our knowledge, these atlases are the first comprehensive population diffusion fiber atlases in early pediatric ages that are publicly available.
Collapse
Affiliation(s)
- Sarah J. Short
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Dae Kun Jang
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
| | - Rachel J. Steiner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rebecca L. Stephens
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jessica B. Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - John H. Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| |
Collapse
|
6
|
Räsänen N, Tiihonen J, Koskuvi M, Lehtonen Š, Koistinaho J. The iPSC perspective on schizophrenia. Trends Neurosci 2021; 45:8-26. [PMID: 34876311 DOI: 10.1016/j.tins.2021.11.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/29/2021] [Accepted: 11/10/2021] [Indexed: 12/17/2022]
Abstract
Over a decade of schizophrenia research using human induced pluripotent stem cell (iPSC)-derived neural models has provided substantial data describing neurobiological characteristics of the disorder in vitro. Simultaneously, translation of the results into general mechanistic concepts underlying schizophrenia pathophysiology has been trailing behind. Given that modeling brain function using cell cultures is challenging, the gap between the in vitro models and schizophrenia as a clinical disorder has remained wide. In this review, we highlight reproducible findings and emerging trends in recent schizophrenia-related iPSC studies. We illuminate the relevance of the results in the context of human brain development, with a focus on processes coinciding with critical developmental periods for schizophrenia.
Collapse
Affiliation(s)
- Noora Räsänen
- Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Jari Tiihonen
- Neuroscience Center, University of Helsinki, Helsinki, Finland; Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden; Center for Psychiatric Research, Stockholm City Council, Stockholm, Sweden; Department of Forensic Psychiatry, University of Eastern Finland, Niuvanniemi Hospital, Kuopio, Finland
| | - Marja Koskuvi
- Neuroscience Center, University of Helsinki, Helsinki, Finland; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Šárka Lehtonen
- Neuroscience Center, University of Helsinki, Helsinki, Finland; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jari Koistinaho
- Neuroscience Center, University of Helsinki, Helsinki, Finland; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
| |
Collapse
|
7
|
Copeland A, Silver E, Korja R, Lehtola SJ, Merisaari H, Saukko E, Sinisalo S, Saunavaara J, Lähdesmäki T, Parkkola R, Nolvi S, Karlsson L, Karlsson H, Tuulari JJ. Infant and Child MRI: A Review of Scanning Procedures. Front Neurosci 2021; 15:666020. [PMID: 34321992 PMCID: PMC8311184 DOI: 10.3389/fnins.2021.666020] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/04/2021] [Indexed: 12/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a safe method to examine human brain. However, a typical MR scan is very sensitive to motion, and it requires the subject to lie still during the acquisition, which is a major challenge for pediatric scans. Consequently, in a clinical setting, sedation or general anesthesia is often used. In the research setting including healthy subjects anesthetics are not recommended for ethical reasons and potential longer-term harm. Here we review the methods used to prepare a child for an MRI scan, but also on the techniques and tools used during the scanning to enable a successful scan. Additionally, we critically evaluate how studies have reported the scanning procedure and success of scanning. We searched articles based on special subject headings from PubMed and identified 86 studies using brain MRI in healthy subjects between 0 and 6 years of age. Scan preparations expectedly depended on subject's age; infants and young children were scanned asleep after feeding and swaddling and older children were scanned awake. Comparing the efficiency of different procedures was difficult because of the heterogeneous reporting of the used methods and the success rates. Based on this review, we recommend more detailed reporting of scanning procedure to help find out which are the factors affecting the success of scanning. In the long term, this could help the research field to get high quality data, but also the clinical field to reduce the use of anesthetics. Finally, we introduce the protocol used in scanning 2 to 5-week-old infants in the FinnBrain Birth Cohort Study, and tips for calming neonates during the scans.
Collapse
Affiliation(s)
- Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Satu J. Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Susanne Sinisalo
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatric Neurology, Turku University Hospital, University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology and Speech-Language Pathology, Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
8
|
Hoffmann A, Ziller M, Spengler D. Progress in iPSC-Based Modeling of Psychiatric Disorders. Int J Mol Sci 2019; 20:E4896. [PMID: 31581684 PMCID: PMC6801734 DOI: 10.3390/ijms20194896] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 09/29/2019] [Accepted: 09/30/2019] [Indexed: 12/19/2022] Open
Abstract
Progress in iPSC-based cellular systems provides new insights into human brain development and early neurodevelopmental deviations in psychiatric disorders. Among these, studies on schizophrenia (SCZ) take a prominent role owing to its high heritability and multifarious evidence that it evolves from a genetically induced vulnerability in brain development. Recent iPSC studies on patients with SCZ indicate that functional impairments of neural progenitor cells (NPCs) in monolayer culture extend to brain organoids by disrupting neocorticogenesis in an in vitro model. In addition, the formation of hippocampal circuit-like structures in vitro is impaired in patients with SCZ as is the case for glia development. Intriguingly, chimeric-mice experiments show altered oligodendrocyte and astrocyte development in vivo that highlights the importance of cell-cell interactions in the pathogenesis of early-onset SCZ. Likewise, cortical imbalances in excitatory-inhibitory signaling may result from a cell-autonomous defect in cortical interneuron (cIN) development. Overall, these findings indicate that genetic risk in SCZ impacts neocorticogenesis, hippocampal circuit formation, and the development of distinct glial and neuronal subtypes. In light of this remarkable progress, we discuss current limitations and further steps necessary to harvest the full potential of iPSC-based investigations on psychiatric disorders.
Collapse
Affiliation(s)
- Anke Hoffmann
- Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, Germany.
| | - Michael Ziller
- Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, Germany.
| | - Dietmar Spengler
- Department of Translational Research in Psychiatry, Max-Planck Institute of Psychiatry, 80804 Munich, Germany.
| |
Collapse
|