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Cattarinussi G, Gugliotta AA, Sambataro F. The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6540. [PMID: 37569080 PMCID: PMC10418911 DOI: 10.3390/ijerph20156540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/24/2023] [Accepted: 08/04/2023] [Indexed: 08/13/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Alessio A. Gugliotta
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
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Falakshahi H, Rokham H, Miller R, Liu J, Calhoun VD. Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-6. [PMID: 38083176 DOI: 10.1109/embc40787.2023.10340856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Multimodal brain network analysis has the potential to provide insights into the mechanisms of brain disorders. Most previous studies have analyzed either unimodal brain graphs or focused on local/global graphic metrics with little consideration of details of disrupted paths in the patient group. As we show, the combination of multimodal brain graphs and disrupted path-based analysis can be highly illuminating to recognize path-based disease biomarkers. In this study, we first propose a way to estimate multimodal brain graphs using static functional network connectivity (sFNC) and gray matter features using a Gaussian graphical model of schizophrenia versus controls. Next, applying the graph theory approach we identify disconnectors or connectors in the patient group graph that create additional paths or cause absent paths compared to the control graph. Results showed several edges in the schizophrenia group graph that trigger missing or additional paths. Identified edges associated with these disrupted paths were identified both within and between dFNC and gray matter which highlights the importance of considering multimodal studies and moving beyond pairwise edges to provide a more comprehensive understanding of brain disorders.Clinical Relevance- We identified a path-based biomarker in schizophrenia, by imitating the structure of paths in a multimodal (sMIR+fMRI) brain graph of the control group. Identified cross-modal edges associated with disrupted paths were related to the middle temporal gyrus and cerebellar regions.
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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.
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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
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Alemán-Gómez Y, Baumgartner T, Klauser P, Cleusix M, Jenni R, Hagmann P, Conus P, Do KQ, Bach Cuadra M, Baumann PS, Steullet P. Multimodal Magnetic Resonance Imaging Depicts Widespread and Subregion Specific Anomalies in the Thalamus of Early-Psychosis and Chronic Schizophrenia Patients. Schizophr Bull 2023; 49:196-207. [PMID: 36065156 PMCID: PMC9810016 DOI: 10.1093/schbul/sbac113] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS Although the thalamus has a central role in schizophrenia pathophysiology, contributing to sensory, cognitive, and sleep alterations, the nature and dynamics of the alterations occurring within this structure remain largely elusive. Using a multimodal magnetic resonance imaging (MRI) approach, we examined whether anomalies: (1) differ across thalamic subregions/nuclei, (2) are already present in the early phase of psychosis (EP), and (3) worsen in chronic schizophrenia (SCHZ). STUDY DESIGN T1-weighted and diffusion-weighted images were analyzed to estimate gray matter concentration (GMC) and microstructural parameters obtained from the spherical mean technique (intra-neurite volume fraction [VFINTRA)], intra-neurite diffusivity [DIFFINTRA], extra-neurite mean diffusivity [MDEXTRA], extra-neurite transversal diffusivity [TDEXTRA]) within 7 thalamic subregions. RESULTS Compared to age-matched controls, the thalamus of EP patients displays previously unreported widespread microstructural alterations (VFINTRA decrease, TDEXTRA increase) that are associated with similar alterations in the whole brain white matter, suggesting altered integrity of white matter fiber tracts in the thalamus. In both patient groups, we also observed more localized and heterogenous changes (either GMC decrease, MDEXTRA increase, or DIFFINTRA decrease) in mediodorsal, posterior, and ventral anterior parts of the thalamus in both patient groups, suggesting that the nature of the alterations varies across subregions. GMC and DIFFINTRA in the whole thalamus correlate with global functioning, while DIFFINTRA in the subregion encompassing the medial pulvinar is significantly associated with negative symptoms in SCHZ. CONCLUSION Our data reveals both widespread and more localized thalamic anomalies that are already present in the early phase of psychosis.
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Affiliation(s)
- Yasser Alemán-Gómez
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
| | - Thomas Baumgartner
- Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Paul Klauser
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
- Department of Psychiatry, Service of Child and Adolescent Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Martine Cleusix
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
| | - Raoul Jenni
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philippe Conus
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Kim Q Do
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
| | - Meritxell Bach Cuadra
- Medical Image Analysis Laboratory (MIAL), Centre d’Imagerie BioMédicale (CIBM), Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philipp S Baumann
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Pascal Steullet
- Department of Psychiatry, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland
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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.
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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
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Shared Transdiagnostic Neuroanatomical Signatures Across First-episode Patients with Major Psychiatric Diseases and Individuals at Familial Risk. Neuroimage Clin 2022; 35:103074. [PMID: 35691252 PMCID: PMC9194955 DOI: 10.1016/j.nicl.2022.103074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Nowadays, increasing evidence has found transdiagnostic neuroimaging biomarkers across major psychiatric disorders (MPDs). However, it remains to be known whether this transdiagnostic pattern of abnormalities could also be seen in individuals at familial high-risk for MPDs (FHR). We aimed to examine shared neuroanatomical endophenotypes and protective biomarkers for MPDs. METHODS This study examined brain grey matter volume (GMV) of individuals by voxel-based morphometry method. A total of 287 individuals were included, involving 100 first-episode medication-naive MPDs, 87 FHR, and 110 healthy controls (HC). They all underwent high-resolution structural magnetic resonance imaging (MRI). RESULTS At the group level, we found MPDs were characterized by decreased GMV in the right fusiform gyrus, the right inferior occipital gyrus, and the left anterior and middle cingulate gyri compared to HC and FHR. Of note, the GMV of the left superior temporal gyrus was increased in FHR relative to MPDs and HC. At the subgroup level, the comparisons within the FHR group did not return any significant difference, and we found GMV difference among subgroups within the MPDs group only in the opercular part of the right inferior frontal gyrus. CONCLUSION Together, our findings uncover common structural disturbances across MPDs and substantial changes in grey matter that may relate to high hereditary risk across FHR, potentially underscoring the importance of a transdiagnostic way to explore the neurobiological mechanisms of major psychiatric disorders.
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Smesny S, Gussew A, Schack S, Langbein K, Wagner G, Reichenbach JR. Neurometabolic patterns of an "at risk for mental disorders" syndrome involve abnormalities in the thalamus and anterior midcingulate cortex. Schizophr Res 2022; 243:285-295. [PMID: 32444202 DOI: 10.1016/j.schres.2020.04.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 04/03/2020] [Accepted: 04/19/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND The ultra-high risk (UHR) paradigm allows the investigation of individuals at increased risk of developing psychotic or other mental disorders with the aim of making prevention and early intervention as specific as possible in terms of the individual outcome. METHODS Single-session 1H-/31P-Chemical Shift Imaging of thalamus, prefrontal (DLPFC) and anterior midcingulate (aMCC) cortices was applied to 69 UHR patients for psychosis and 61 matched healthy controls. N-acetylaspartate (NAA), glutamate/glutamine complex (Glx), energy (PCr, ATP) and phospholipid metabolites were assessed, analysed by ANOVA (or ANCOVA [with covariates]) and correlated with symptomatology (SCL-90R). RESULTS The thalamus showed decreased NAA, inversely correlated with self-rated aggressiveness, as well as increased PCr, and altered phospholipid breakdown. While the aMCC showed a pattern of NAA decrease and PCr increase, the DLPFC showed PCr increase only in the close-to-psychosis patient subgroup. There were no specific findings in transition patients. CONCLUSION The results do not support the notion of a specific pre-psychotic neurometabolic pattern, but likely reflect correlates of an "at risk for mental disorders syndrome". This includes disturbed neuronal (mitochondrial) metabolism in the thalamus and aMCC, with emphasis on left-sided structures, and altered PL remodeling across structures.
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Affiliation(s)
- Stefan Smesny
- Department of Psychiatry, Jena University Hospital, Philosophenweg 3, D-07743 Jena, Germany.
| | - Alexander Gussew
- Department of Radiology, Halle University Hospital, Ernst-Grube-Str. 40, 06120 Halle (Saale), Germany
| | - Stephan Schack
- Department of Psychiatry, Jena University Hospital, Philosophenweg 3, D-07743 Jena, Germany
| | - Kerstin Langbein
- Department of Psychiatry, Jena University Hospital, Philosophenweg 3, D-07743 Jena, Germany
| | - Gerd Wagner
- Department of Psychiatry, Jena University Hospital, Philosophenweg 3, D-07743 Jena, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Philosophenweg 3, D-07740 Jena, Germany
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Bulbul O, Kurt E, Ulasoglu-Yildiz C, Demiralp T, Ucok A. Altered Resting State Functional Connectivity and Its Correlation with Cognitive Functions at Ultra High Risk for Psychosis. Psychiatry Res Neuroimaging 2022; 321:111444. [PMID: 35093807 DOI: 10.1016/j.pscychresns.2022.111444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 01/06/2022] [Accepted: 01/17/2022] [Indexed: 01/10/2023]
Abstract
The aim of this study is to identify robust resting state-functional connectivity (rs-FC) alterations and their correlations with the neuropsychological characteristics of Ultra-High Risk (UHR) for psychosis subjects compared to healthy controls (HCs). Twenty individuals with UHR and sixteen HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a cognitive battery evaluating attention, episodic memory and executive functions. Compared to HCs, UHR individuals showed working memory and set-shifting impairments. In functional connectivity (FC) analyses, the Default Mode Network (DMN) of the UHR subjects displayed increased FC with the visual areas and decreased FC with the Dorsal Attention Network (DAN). Additionally, the salience network (SN) of the UHR subjects displayed increased connectivity with wide posterior cortical areas in the temporal, parietal and occipital lobes, corresponding to posterior nodes of the SN itself, the Somato-Motor Network (SMN) and the DAN. The SN connectivity with the left SMN and DAN was positively correlated with the Trail Making Test - B scores of the UHR subjects. These findings show that the SN and DMN, which mostly show abnormal connectivity patterns in psychosis, are also affected in UHR subjects, while the SN plays a more central role with its hyperconnectivity to the DAN and SMN.
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Affiliation(s)
- Oznur Bulbul
- Department of Psychiatry, Erenkoy Training and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey.
| | - Elif Kurt
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Psychology, Faculty of Humanities and Social Sciences, Istinye University, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Alp Ucok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
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Qi Z, Wang J, Gong J, Su T, Fu S, Huang L, Wang Y. Common and specific patterns of functional and structural brain alterations in schizophrenia and bipolar disorder: a multimodal voxel-based meta-analysis. J Psychiatry Neurosci 2022; 47:E32-E47. [PMID: 35105667 PMCID: PMC8812718 DOI: 10.1503/jpn.210111] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/12/2021] [Accepted: 11/16/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Schizophrenia and bipolar disorder have been linked to alterations in the functional activity and grey matter volume of some brain areas, reflected in impaired regional homogeneity and aberrant voxel-based morphometry. However, because of variable findings and methods used across studies, identifying patterns of brain alteration in schizophrenia and bipolar disorder has been difficult. METHODS We conducted a meta-analysis of differences in regional homogeneity and voxel-based morphometry between patients and healthy controls for schizophrenia and bipolar disorder separately, using seed-based d mapping. RESULTS We included 45 publications on regional homogeneity (26 in schizophrenia and 19 in bipolar disorder) and 190 publications on voxel-based morphometry (120 in schizophrenia and 70 in bipolar disorder). Patients with schizophrenia showed increased regional homogeneity in the frontal cortex and striatum and the supplementary motor area; they showed decreased regional homogeneity in the insula, primary sensory cortex (visual and auditory cortices) and sensorimotor cortex. Patients with bipolar disorder showed increased regional homogeneity in the frontal cortex and striatum; they showed decreased regional homogeneity in the insula. Patients with schizophrenia showed decreased grey matter volume in the superior temporal gyrus, inferior frontal gyrus, cingulate cortex and cerebellum. Patients with bipolar disorder showed decreased grey matter volume in the insula, cingulate cortex, frontal cortex and thalamus. Overlap analysis showed that patients with schizophrenia displayed decreased regional homogeneity and grey matter volume in the left insula and left superior temporal gyrus; patients with bipolar disorder displayed decreased regional homogeneity and grey matter volume in the left insula. LIMITATIONS The small sample size for our subgroup analysis (unmedicated versus medicated patients and substantial heterogeneity in the results for some regions could limit the interpretability and generalizability of the results. CONCLUSION Patients with schizophrenia and bipolar disorder shared a common pattern of regional functional and structural alterations in the insula and frontal cortex. Patients with schizophrenia showed more widespread functional and structural impairment, most prominently in the primary sensory motor areas.
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Affiliation(s)
| | - Junjing Wang
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China (Qi, Su, Fu, Huang, Y. Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Qi, Su, Fu, Huang, Y. Wang); the Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou, China (J. Wang); and the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
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Marimpis AD, Dimitriadis SI, Goebel R. Dyconnmap: Dynamic connectome mapping-A neuroimaging python module. Hum Brain Mapp 2021; 42:4909-4939. [PMID: 34250674 PMCID: PMC8449119 DOI: 10.1002/hbm.25589] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 06/10/2021] [Accepted: 06/25/2021] [Indexed: 11/16/2022] Open
Abstract
Despite recent progress in the analysis of neuroimaging data sets, our comprehension of the main mechanisms and principles which govern human brain cognition and function remains incomplete. Network neuroscience makes substantial efforts to manipulate these challenges and provide real answers. For the last decade, researchers have been modelling brain structure and function via a graph or network that comprises brain regions that are either anatomically connected via tracts or functionally via a more extensive repertoire of functional associations. Network neuroscience is a relatively new multidisciplinary scientific avenue of the study of complex systems by pursuing novel ways to analyze, map, store and model the essential elements and their interactions in complex neurobiological systems, particularly the human brain, the most complex system in nature. Due to a rapid expansion of neuroimaging data sets' size and complexity, it is essential to propose and adopt new empirical tools to track dynamic patterns between neurons and brain areas and create comprehensive maps. In recent years, there is a rapid growth of scientific interest in moving functional neuroimaging analysis beyond simplified group or time‐averaged approaches and sophisticated algorithms that can capture the time‐varying properties of functional connectivity. We describe algorithms and network metrics that can capture the dynamic evolution of functional connectivity under this perspective. We adopt the word ‘chronnectome’ (integration of the Greek word ‘Chronos’, which means time, and connectome) to describe this specific branch of network neuroscience that explores how mutually informed brain activity correlates across time and brain space in a functional way. We also describe how good temporal mining of temporally evolved dynamic functional networks could give rise to the detection of specific brain states over which our brain evolved. This characteristic supports our complex human mind. The temporal evolution of these brain states and well‐known network metrics could give rise to new analytic trends. Functional brain networks could also increase the multi‐faced nature of the dynamic networks revealing complementary information. Finally, we describe a python module (https://github.com/makism/dyconnmap) which accompanies this article and contains a collection of dynamic complex network analytics and measures and demonstrates its great promise for the study of a healthy subject's repeated fMRI scans.
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Affiliation(s)
- Avraam D Marimpis
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,Brain Innovation B.V, Maastricht, The Netherlands
| | - Stavros I Dimitriadis
- Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom.,Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.,School of Psychology, Cardiff University, Cardiff, United Kingdom.,Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Rainer Goebel
- Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Brain Innovation B.V, Maastricht, The Netherlands
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11
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McWhinney S, Kolenic M, Franke K, Fialova M, Knytl P, Matejka M, Spaniel F, Hajek T. Obesity as a Risk Factor for Accelerated Brain Ageing in First-Episode Psychosis-A Longitudinal Study. Schizophr Bull 2021; 47:1772-1781. [PMID: 34080013 PMCID: PMC8530396 DOI: 10.1093/schbul/sbab064] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Obesity is highly prevalent in schizophrenia, with implications for psychiatric prognosis, possibly through links between obesity and brain structure. In this longitudinal study in first episode of psychosis (FEP), we used machine learning and structural magnetic resonance imaging (MRI) to study the impact of psychotic illness and obesity on brain ageing/neuroprogression shortly after illness onset. METHODS We acquired 2 prospective MRI scans on average 1.61 years apart in 183 FEP and 155 control individuals. We used a machine learning model trained on an independent sample of 504 controls to estimate the individual brain ages of study participants and calculated BrainAGE by subtracting chronological from the estimated brain age. RESULTS Individuals with FEP had a higher initial BrainAGE than controls (3.39 ± 6.36 vs 1.72 ± 5.56 years; β = 1.68, t(336) = 2.59, P = .01), but similar annual rates of brain ageing over time (1.28 ± 2.40 vs 1.07±1.74 estimated years/actual year; t(333) = 0.93, P = .18). Across both cohorts, greater baseline body mass index (BMI) predicted faster brain ageing (β = 0.08, t(333) = 2.59, P = .01). For each additional BMI point, the brain aged by an additional month per year. Worsening of functioning over time (Global Assessment of Functioning; β = -0.04, t(164) = -2.48, P = .01) and increases especially in negative symptoms on the Positive and Negative Syndrome Scale (β = 0.11, t(175) = 3.11, P = .002) were associated with faster brain ageing in FEP. CONCLUSIONS Brain alterations in psychosis are manifest already during the first episode and over time get worse in those with worsening clinical outcomes or higher baseline BMI. As baseline BMI predicted faster brain ageing, obesity may represent a modifiable risk factor in FEP that is linked with psychiatric outcomes via effects on brain structure.
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Affiliation(s)
- Sean McWhinney
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Marian Kolenic
- National Institute of Mental Health, Klecany, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Katja Franke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Jena, Germany
| | - Marketa Fialova
- National Institute of Mental Health, Klecany, Czech Republic
| | - Pavel Knytl
- National Institute of Mental Health, Klecany, Czech Republic
| | - Martin Matejka
- National Institute of Mental Health, Klecany, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada,National Institute of Mental Health, Klecany, Czech Republic,To whom correspondence should be addressed; Department of Psychiatry, Dalhousie University, QEII HSC, A. J. Lane Building, Room 3093, 5909 Veteran’s Memorial Lane, Halifax, Nova Scotia B3H 2E2, Canada; tel: (902) 473-8299, fax: (902) 473-1583, e-mail:
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12
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Voráčková V, Knytl P, Španiel F, Šustová P, Renka J, Mohr P. Cognitive profiles of healthy siblings of first-episode schizophrenia patients. Early Interv Psychiatry 2021; 15:554-562. [PMID: 32488980 DOI: 10.1111/eip.12982] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 02/11/2020] [Accepted: 04/28/2020] [Indexed: 12/25/2022]
Abstract
AIM Cognitive deficit in psychotic illness is intensively studied, different cognitive subtypes have been suggested. In recent years, there has been an increase in the number of studies in patients with schizophrenia and their relatives searching for endophenotypes of the disease. The aim of our study was to investigate cognitive performance and cognitive subtypes in the siblings of the patients. METHODS Four groups of subjects were included: patients with a first episode of psychotic illness, the siblings of these patients, and two control groups. All the study subjects (N = 84) had a battery of neuropsychological tests that measured basic cognitive domains - memory, executive functions, attention, visual-spatial skills, language skills and psychomotor speed - administered to them. The data were assessed with pairwise t-tests for group comparisons. The siblings were distributed into three groups according to their cognitive performance: non-deficit, partial deficit, and global deficit. Subsequently, the patients were assigned into three groups corresponding to their siblings' performance. RESULTS Our results revealed attenuation of abstract thinking in the siblings compared to the controls. As expected, the patients showed impairment across all cognitive domains. The patients and siblings demonstrated similar profiles in each subtype, in the severity of their impairment, and in their patterns of cognitive performance. CONCLUSIONS Our results suggest that the cognitive profile can be considered as an endophenotype of psychotic disorders.
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Affiliation(s)
- Veronika Voráčková
- Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany, Czech Republic.,Diagnostics and Treatment of Mental Disorders, National Institute of Mental Health, Klecany, Czech Republic.,Neuroscience, Third Faculty of Medicine, Charles University Prague, Prague, Czech Republic
| | - Pavel Knytl
- Diagnostics and Treatment of Mental Disorders, National Institute of Mental Health, Klecany, Czech Republic.,Neuroscience, Third Faculty of Medicine, Charles University Prague, Prague, Czech Republic
| | - Filip Španiel
- Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany, Czech Republic.,Neuroscience, Third Faculty of Medicine, Charles University Prague, Prague, Czech Republic
| | - Petra Šustová
- Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany, Czech Republic
| | - Jiří Renka
- Diagnostics and Treatment of Mental Disorders, National Institute of Mental Health, Klecany, Czech Republic.,Neuroscience, Third Faculty of Medicine, Charles University Prague, Prague, Czech Republic
| | - Pavel Mohr
- Diagnostics and Treatment of Mental Disorders, National Institute of Mental Health, Klecany, Czech Republic.,Neuroscience, Third Faculty of Medicine, Charles University Prague, Prague, Czech Republic
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13
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Quiñones GM, Mayeli A, Yushmanov VE, Hetherington HP, Ferrarelli F. Reduced GABA/glutamate in the thalamus of individuals at clinical high risk for psychosis. Neuropsychopharmacology 2021; 46:1133-1139. [PMID: 33273706 PMCID: PMC8115482 DOI: 10.1038/s41386-020-00920-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 11/02/2020] [Accepted: 11/15/2020] [Indexed: 12/14/2022]
Abstract
Youth at clinical high risk (CHR) are a unique population enriched for precursors of major psychiatric disorders, especially schizophrenia (SCZ). Recent neuroimaging findings point to abnormalities in the thalamus of patients with SCZ, including chronic and early course patients, as well as in CHR individuals relative to healthy comparison groups, thus suggesting that thalamic dysfunctions are present even before illness onset. Furthermore, modeling data indicate that alteration between excitatory and inhibitory control, as reflected by alteration in GABAergic and glutamatergic balance (i.e., GABA/Glu), may underlie thalamic deficits linked to the risk and development of psychosis. There is, however, a lack of in vivo evidence of GABA/Glu thalamic abnormalities in the CHR state. Magnetic resonance spectroscopic imaging (MRSI) 7 Tesla (7 T) provides enhanced resolution to quantify GABA and Glu levels in the thalamus of CHR individuals. In this study, we performed 7 T MRSI in 15 CHR and 20 healthy control (HC) participants. We found that GABA/Glu was significantly reduced in the right medial anterior and right medial posterior thalamus of CHR relative to HC groups. The GABA/Glu reduction was negatively correlated with general symptoms in the right medial anterior thalamus, as well as with disorganization symptoms in the right medial posterior thalamus. Altogether, these findings indicate that GABA/Glu abnormalities are present in the thalamus before the onset of full-blown psychosis and are associated with symptom severity, thus providing putative molecular and neuronal targets for early interventions in youth at CHR.
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Affiliation(s)
- Gonzalo M. Quiñones
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Ahmad Mayeli
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Victor E. Yushmanov
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Hoby P. Hetherington
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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14
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Lin X, Li W, Dong G, Wang Q, Sun H, Shi J, Fan Y, Li P, Lu L. Characteristics of Multimodal Brain Connectomics in Patients With Schizophrenia and the Unaffected First-Degree Relatives. Front Cell Dev Biol 2021; 9:631864. [PMID: 33718367 PMCID: PMC7947240 DOI: 10.3389/fcell.2021.631864] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 01/25/2021] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Increasing pieces of evidence suggest that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. As an essential strategy in psychiatric neuroscience, the research of brain connectivity-based neuroimaging biomarkers has gained increasing attention. Most of previous studies focused on a single modality of the brain connectomics. Multimodal evidence will not only depict the full profile of the brain abnormalities of patients but also contribute to our understanding of the neurobiological mechanisms of this disease. METHODS In the current study, 99 schizophrenia patients, 69 sex- and education-matched healthy controls, and 42 unaffected first-degree relatives of patients were recruited and scanned. The brain was parcellated into 246 regions and multimodal network analyses were used to construct brain connectivity networks for each participant. RESULTS Using the brain connectomics from three modalities as the features, the multi-kernel support vector machine method yielded high discrimination accuracies for schizophrenia patients (94.86%) and for the first-degree relatives (95.33%) from healthy controls. Using an independent sample (49 patients and 122 healthy controls), we tested the model and achieved a classification accuracy of 64.57%. The convergent pattern within the basal ganglia and thalamus-cortex circuit exhibited high discriminative power during classification. Furthermore, substantial overlaps of the brain connectivity abnormality between patients and the unaffected first-degree relatives were observed compared to healthy controls. CONCLUSION The current findings demonstrate that decreased functional communications between the basal ganglia, thalamus, and the prefrontal cortex could serve as biomarkers and endophenotypes for schizophrenia.
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Affiliation(s)
- Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing, China
| | - WeiKai Li
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Guangheng Dong
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Qiandong Wang
- Department of Psychology, Beijing Normal University, Beijing, China
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing, China
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing, China
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
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15
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Liloia D, Brasso C, Cauda F, Mancuso L, Nani A, Manuello J, Costa T, Duca S, Rocca P. Updating and characterizing neuroanatomical markers in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis. Neurosci Biobehav Rev 2021; 123:83-103. [PMID: 33497790 DOI: 10.1016/j.neubiorev.2021.01.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/07/2021] [Accepted: 01/15/2021] [Indexed: 01/10/2023]
Abstract
Characterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess pathophysiological models of how the disorder develops is an important target for the clinical practice. We performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization. Results reveal a cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region found altered among c-HR, RDSZ and ChSZ. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ. These findings support the current neuroprogressive models of SZ and integrate this deterioration with the clinical evolution of the disease.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Claudio Brasso
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy.
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Andrea Nani
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Paola Rocca
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
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16
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Todeva-Radneva A, Paunova R, Kandilarova S, St Stoyanov D. The Value of Neuroimaging Techniques in the Translation and Transdiagnostic Validation of Psychiatric Diagnoses - Selective Review. Curr Top Med Chem 2021; 20:540-553. [PMID: 32003690 DOI: 10.2174/1568026620666200131095328] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/09/2019] [Accepted: 12/12/2019] [Indexed: 01/05/2023]
Abstract
Psychiatric diagnosis has long been perceived as more of an art than a science since its foundations lie within the observation, and the self-report of the patients themselves and objective diagnostic biomarkers are lacking. Furthermore, the diagnostic tools in use not only stray away from the conventional medical framework but also remain invalidated with evidence-based concepts. However, neuroscience, as a source of valid objective knowledge has initiated the process of a paradigm shift underlined by the main concept of psychiatric disorders being "brain disorders". It is also a bridge closing the explanatory gap among the different fields of medicine via the translation of the knowledge within a multidisciplinary framework. The contemporary neuroimaging methods, such as fMRI provide researchers with an entirely new set of tools to reform the current status quo by creating an opportunity to define and validate objective biomarkers that can be translated into clinical practice. Combining multiple neuroimaging techniques with the knowledge of the role of genetic factors, neurochemical imbalance and neuroinflammatory processes in the etiopathophysiology of psychiatric disorders is a step towards a comprehensive biological explanation of psychiatric disorders and a final differentiation of psychiatry as a well-founded medical science. In addition, the neuroscientific knowledge gained thus far suggests a necessity for directional change to exploring multidisciplinary concepts, such as multiple causality and dimensionality of psychiatric symptoms and disorders. A concomitant viewpoint transition of the notion of validity in psychiatry with a focus on an integrative validatory approach may facilitate the building of a collaborative bridge above the wall existing between the scientific fields analyzing the mind and those studying the brain.
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Affiliation(s)
- Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Drozdstoy St Stoyanov
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
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17
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Steullet P. Thalamus-related anomalies as candidate mechanism-based biomarkers for psychosis. Schizophr Res 2020; 226:147-157. [PMID: 31147286 DOI: 10.1016/j.schres.2019.05.027] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 05/15/2019] [Accepted: 05/17/2019] [Indexed: 02/08/2023]
Abstract
Identification of reliable biomarkers of prognosis in subjects with high risk to psychosis is an essential step to improve care and treatment of this population of help-seekers. Longitudinal studies highlight some clinical criteria, cognitive deficits, patterns of gray matter alterations and profiles of blood metabolites that provide some levels of prediction regarding the conversion to psychosis. Further effort is warranted to validate these results and implement these types of approaches in clinical settings. Such biomarkers may however fall short in entangling the biological mechanisms underlying the disease progression, an essential step in the development of novel therapies. Circuit-based approaches, which map on well-identified cerebral functions, could meet these needs. Converging evidence indicates that thalamus abnormalities are central to schizophrenia pathophysiology, contributing to clinical symptoms, cognitive and sensory deficits. This review highlights the various thalamus-related anomalies reported in individuals with genetic risks and in the different phases of the disorder, from prodromal to chronic stages. Several anomalies are potent endophenotypes, while others exist in clinical high-risk subjects and worsen in those who convert to full psychosis. Aberrant functional coupling between thalamus and cortex, low glutamate content and readouts from resting EEG carry predictive values for transition to psychosis or functional outcome. In this context, thalamus-related anomalies represent a valuable entry point to tackle circuit-based alterations associated with the emergence of psychosis. This review also proposes that longitudinal surveys of neuroimaging, EEG readouts associated with circuits encompassing the mediodorsal, pulvinar in high-risk individuals could unveil biological mechanisms contributing to this psychiatric disorder.
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Affiliation(s)
- Pascal Steullet
- Center of Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, Site de Cery, 1008 Prilly-Lausanne, Switzerland.
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18
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Self-Reported Cognitive Functions Predict the Trajectory of Paranoid Ideation Over a 15-Year Prospective Follow-Up. COGNITIVE THERAPY AND RESEARCH 2020. [DOI: 10.1007/s10608-020-10142-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Abstract
Background
This study investigated whether self-reported cognitive functions (i.e. task orientation, distractibility, persistence, flexibility, and perseverance) predict the trajectory of paranoid ideation over a 15-year prospective follow-up in adulthood.
Methods
The participants came from the population-based Young Finns study (N = 1210‒1213). Paranoid ideation was assessed with the Paranoid Ideation Scale of the Symptom Checklist-90 Revised (SCL-90R) in 1997, 2001, 2007, and 2012. Self-reported cognitive functions were evaluated in 1997 with the Task orientation, Distractibility, Persistence, and Flexibility scales of the DOTS-R (the Revised Dimensions of Temperament Survey) and the Perseverance scale of the FCB-TI (the Formal Characteristics of Behaviour – Temperament Inventory). The data was analyzed using growth curve models that were adjusted for age, sex, and socioeconomic factors in childhood and adulthood.
Results
Low self-reported task orientation, low persistence, high distractibility, low flexibility, and high perseverance predicted higher level of paranoid ideation over the 15-year follow-up.
Conclusions
Self-reported cognitive functions seem to predict paranoid ideation over a long-term follow-up. Promoting cognitive functions in early interventions may have long-term protective influences against the development of paranoid ideation in non-clinical populations.
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Falakshahi H, Vergara VM, Liu J, Mathalon DH, Ford JM, Voyvodic J, Mueller BA, Belger A, McEwen S, Potkin SG, Preda A, Rokham H, Sui J, Turner JA, Plis S, Calhoun VD. Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. IEEE Trans Biomed Eng 2020; 67:2572-2584. [PMID: 31944934 PMCID: PMC7538162 DOI: 10.1109/tbme.2020.2964724] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Multimodal measurements of the same phenomena provide complementary information and highlight different perspectives, albeit each with their own limitations. A focus on a single modality may lead to incorrect inferences, which is especially important when a studied phenomenon is a disease. In this paper, we introduce a method that takes advantage of multimodal data in addressing the hypotheses of disconnectivity and dysfunction within schizophrenia (SZ). METHODS We start with estimating and visualizing links within and among extracted multimodal data features using a Gaussian graphical model (GGM). We then propose a modularity-based method that can be applied to the GGM to identify links that are associated with mental illness across a multimodal data set. Through simulation and real data, we show our approach reveals important information about disease-related network disruptions that are missed with a focus on a single modality. We use functional MRI (fMRI), diffusion MRI (dMRI), and structural MRI (sMRI) to compute the fractional amplitude of low frequency fluctuations (fALFF), fractional anisotropy (FA), and gray matter (GM) concentration maps. These three modalities are analyzed using our modularity method. RESULTS Our results show missing links that are only captured by the cross-modal information that may play an important role in disconnectivity between the components. CONCLUSION We identified multimodal (fALFF, FA and GM) disconnectivity in the default mode network area in patients with SZ, which would not have been detectable in a single modality. SIGNIFICANCE The proposed approach provides an important new tool for capturing information that is distributed among multiple imaging modalities.
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Brain structural correlates of familial risk for mental illness: a meta-analysis of voxel-based morphometry studies in relatives of patients with psychotic or mood disorders. Neuropsychopharmacology 2020; 45:1369-1379. [PMID: 32353861 PMCID: PMC7297956 DOI: 10.1038/s41386-020-0687-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 04/19/2020] [Accepted: 04/22/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.
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21
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Saarinen AIL, Huhtaniska S, Pudas J, Björnholm L, Jukuri T, Tohka J, Granö N, Barnett JH, Kiviniemi V, Veijola J, Hintsanen M, Lieslehto J. Structural and functional alterations in the brain gray matter among first-degree relatives of schizophrenia patients: A multimodal meta-analysis of fMRI and VBM studies. Schizophr Res 2020; 216:14-23. [PMID: 31924374 DOI: 10.1016/j.schres.2019.12.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 12/20/2019] [Accepted: 12/20/2019] [Indexed: 11/27/2022]
Abstract
OBJECTIVE We conducted a multimodal coordinate-based meta-analysis (CBMA) to investigate structural and functional brain alterations in first-degree relatives of schizophrenia patients (FRs). METHODS We conducted a systematic literature search from electronic databases to find studies that examined differences between FRs and healthy controls using whole-brain functional magnetic resonance imaging (fMRI) or voxel-based morphometry (VBM). A CBMA of 30 fMRI (754 FRs; 959 controls) and 11 VBM (885 FRs; 775 controls) datasets were conducted using the anisotropic effect-size version of signed differential mapping. Further, we conducted separate meta-analyses about functional alterations in different cognitive tasks: social cognition, executive functioning, working memory, and inhibitory control. RESULTS FRs showed higher fMRI activation in the right frontal gyrus during cognitive tasks than healthy controls. In VBM studies, there were no differences in gray matter density between FRs and healthy controls. Furthermore, multi-modal meta-analysis obtained no differences between FRs and healthy controls. By utilizing the BrainMap database, we showed that the brain region which showed functional alterations in FRs (i) overlapped only slightly with the brain regions that were affected in the meta-analysis of schizophrenia patients and (ii) correlated positively with the brain regions that exhibited increased activity during cognitive tasks in healthy individuals. CONCLUSIONS Based on this meta-analysis, FRs may exhibit only minor functional alterations in the brain during cognitive tasks, and the alterations are much more restricted and only slightly overlapping with the regions that are affected in schizophrenia patients. The familial risk did not relate to structural alterations in the gray matter.
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Affiliation(s)
- Aino I L Saarinen
- Research Unit of Psychology, University of Oulu, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland; Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu, Finland.
| | - Sanna Huhtaniska
- Center for Life Course Health Research, University of Oulu, Finland
| | - Juho Pudas
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu, Finland
| | - Lassi Björnholm
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu, Finland
| | - Tuomas Jukuri
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu, Finland
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Niklas Granö
- Helsinki University Hospital, Department of Adolescent Psychiatry, Finland
| | - Jennifer H Barnett
- Cambridge Cognition, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland; Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Juha Veijola
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu, Finland; Department of Psychiatry, Oulu University Hospital, Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | | | - Johannes Lieslehto
- Center for Life Course Health Research, University of Oulu, Finland; Section for Neurodiagnostic Applications, Department of Psychiatry, Ludwig Maximilian University, Nussbaumstrasse 7, 80336 Munich, Bavaria, Germany
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22
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Saarinen A, Lieslehto J, Kiviniemi V, Tuovinen T, Veijola J, Hintsanen M. The relationship of genetic susceptibilities for psychosis with physiological fluctuation in functional MRI data. Psychiatry Res Neuroimaging 2020; 297:111031. [PMID: 32035357 DOI: 10.1016/j.pscychresns.2020.111031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 01/15/2020] [Accepted: 01/17/2020] [Indexed: 11/18/2022]
Abstract
Previously, schizophrenia is found to be related to the variability of the functional magnetic resonance imaging (fMRI) signal in the white matter. However, evidence about the relationship between genetic vulnerabilities and physiological fluctuation in the brain is lacking. We investigated whether familial risk for psychosis (FR) and polygenic risk score for schizophrenia (PRS) are linked with physiological fluctuation in fMRI data. We used data from the Oulu Brain and Mind study (n = 140-149, aged 20-24 years) that is a substudy of the Northern Finland Birth Cohort 1986. The participants underwent a resting-state fMRI scan. Coefficient of variation (CV) of blood oxygen level dependent (BOLD) signal (CVBOLD) was used as a proxy of physiological fluctuation in the brain. Familial risk was defined to be present if at least one parent had been diagnosed with psychosis previously. PRS was computed based on the results of the prior GWAS by the Schizophrenia Working Group. FR or PRS were not associated with CVBOLD in cerebrospinal fluid, white matter, or grey matter. The findings did not provide evidence for the previous suggestions that genetic vulnerabilities for schizophrenia become apparent in alterations of the variation of the BOLD signal in the brain.
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Affiliation(s)
- Aino Saarinen
- Research Unit of Psychology, University of Oulu, Finland; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland; Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu.
| | - Johannes Lieslehto
- Section for Neurodiagnostic Applications, Department of Psychiatry, Ludwig Maximilian University, Nussbaumstrasse 7, 80336 Munich, Bavaria, Germany; Center for Life Course Health Research, University of Oulu, Finland
| | - Vesa Kiviniemi
- Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland; Department of Psychiatry, Oulu University Hospital, Oulu, Finland
| | - Timo Tuovinen
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu
| | - Juha Veijola
- Research Unit of Clinical Neuroscience, Department of Psychiatry, University of Oulu; Department of Psychiatry, Oulu University Hospital, Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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23
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Rogdaki M, Gudbrandsen M, McCutcheon RA, Blackmore CE, Brugger S, Ecker C, Craig MC, Daly E, Murphy DGM, Howes O. Magnitude and heterogeneity of brain structural abnormalities in 22q11.2 deletion syndrome: a meta-analysis. Mol Psychiatry 2020; 25:1704-1717. [PMID: 31925327 PMCID: PMC7387301 DOI: 10.1038/s41380-019-0638-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Revised: 12/02/2019] [Accepted: 12/12/2019] [Indexed: 12/23/2022]
Abstract
The 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder associated with a number of volumetric brain abnormalities. The syndrome is also associated with an increased risk for neuropsychiatric disorders including schizophrenia and autism spectrum disorder. An earlier meta-analysis showed reduced grey and white matter volumes in individuals with 22q11.2DS. Since this analysis was conducted, the number of studies has increased markedly, permitting more precise estimates of effects and more regions to be examined. Although 22q11.2DS is clinically heterogeneous, it is not known to what extent this heterogeneity is mirrored in neuroanatomy. The aim of this study was thus to investigate differences in mean brain volume and structural variability within regions, between 22q11.2DS and typically developing controls. We examined studies that reported measures of brain volume using MRI in PubMed, Web of Science, Scopus and PsycINFO from inception to 1 May 2019. Data were extracted from studies in order to calculate effect sizes representing case-control difference in mean volume, and in the variability of volume (as measured using the log variability ratio (lnVR) and coefficient of variation ratio (CVR)). We found significant overall decreases in mean volume in 22q11.2DS compared with control for: total brain (g = -0.96; p < 0.001); total grey matter (g = -0.81, p < 0.001); and total white matter (g = -0.81; p < 0.001). There was also a significant overall reduction of mean volume in 22q11.2DS subjects compared with controls in frontal lobe (g = -0.47; p < 0.001), temporal lobe (g = -0.84; p < 0.001), parietal lobe (g = -0.73; p = 0.053), cerebellum (g = -1.25; p < 0.001) and hippocampus (g = -0.90; p < 0.001). Significantly increased variability in 22q11.2DS individuals compared with controls was found only for the hippocampus (VR, 1.14; p = 0.036; CVR, 1.30; p < 0.001), and lateral ventricles (VR, 1.56; p = 0.004). The results support the notion that structural abnormalities in 22q11.2DS and schizophrenia are convergent, and also to some degree with findings in autism spectrum disorder. Finally, the increased variability seen in the hippocampus in 22q11.2DS may underlie some of the heterogeneity observed in the neuropsychiatric phenotype.
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Affiliation(s)
- Maria Rogdaki
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK. .,Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Imperial College, London, W12 0NN, UK.
| | - Maria Gudbrandsen
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK
| | - Robert A McCutcheon
- 0000 0001 2322 6764grid.13097.3cDepartment of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF UK
| | - Charlotte E Blackmore
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK
| | - Stefan Brugger
- 0000 0001 2113 8111grid.7445.2Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Imperial College, London, W12 0NN UK ,0000 0001 0807 5670grid.5600.3Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, Wales CF24 4HQ UK ,0000000121901201grid.83440.3bDivision of Psychiatry, UCL, Maple House, London, W1T 7NF UK
| | - Christine Ecker
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK ,Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt am Main, Goethe-University Frankfurt am Main, Frankfurt, Germany
| | - Michael C Craig
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK ,0000 0001 2324 5535grid.415717.1National Autism Unit, Bethlem Royal Hospital, London, UK
| | - Eileen Daly
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK
| | - Declan G M Murphy
- 0000 0001 2322 6764grid.13097.3cDepartment of Forensic and Neurodevelopmental Sciences, and the Sackler Institute for Translational Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, SE5 8AF UK ,0000 0001 2322 6764grid.13097.3cMRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Oliver Howes
- 0000 0001 2322 6764grid.13097.3cDepartment of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 8AF UK ,0000 0001 2113 8111grid.7445.2Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Imperial College, London, W12 0NN UK
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24
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Warland A, Kendall KM, Rees E, Kirov G, Caseras X. Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank. Mol Psychiatry 2020; 25:854-862. [PMID: 30679740 PMCID: PMC7156345 DOI: 10.1038/s41380-019-0355-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 12/11/2018] [Accepted: 12/26/2018] [Indexed: 11/09/2022]
Abstract
Schizophrenia is a highly heritable disorder for which anatomical brain alterations have been repeatedly reported in clinical samples. Unaffected at-risk groups have also been studied in an attempt to identify brain changes that do not reflect reverse causation or treatment effects. However, no robust associations have been observed between neuroanatomical phenotypes and known genetic risk factors for schizophrenia. We tested subcortical brain volume differences between 49 unaffected participants carrying at least one of the 12 copy number variants associated with schizophrenia in UK Biobank and 9063 individuals who did not carry any of the 93 copy number variants reported to be pathogenic. Our results show that CNV carriers have reduced volume in some of the subcortical structures previously shown to be reduced in schizophrenia. Moreover, these associations partially accounted for the association between pathogenic copy number variants and cognitive impairment, which is one of the features of schizophrenia.
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Affiliation(s)
- Anthony Warland
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Kimberley M. Kendall
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Elliott Rees
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - George Kirov
- 0000 0001 0807 5670grid.5600.3MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ UK
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
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25
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Johnsen LK, Ver Loren van Themaat AH, Larsen KM, Burton BK, Baaré WFC, Madsen KS, Nordentoft M, Siebner HR, Plessen KJ. Alterations in Task-Related Brain Activation in Children, Adolescents and Young Adults at Familial High-Risk for Schizophrenia or Bipolar Disorder - A Systematic Review. Front Psychiatry 2020; 11:632. [PMID: 32754058 PMCID: PMC7365908 DOI: 10.3389/fpsyt.2020.00632] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 06/17/2020] [Indexed: 12/31/2022] Open
Abstract
Children, adolescents, and young adults with at least one first-degree relative [familial high-risk (FHR)] with either schizophrenia (SZ) or bipolar disorder (BD) have a one-in-two risk of developing a psychiatric disorder. Here, we review functional magnetic resonance imaging (fMRI) studies which examined task-related brain activity in young individuals with FHR-SZ and FHR-BD. A systematic search identified all published task-related fMRI studies in children, adolescents, and young adults below an age of 27 years with a first-degree relative with SZ or BD, but without manifest psychotic or affective spectrum disorder themselves. The search identified 19 cross-sectional fMRI studies covering four main cognitive domains: 1) working memory (n = 3), 2) cognitive control (n = 4), 3) reward processing (n = 3), and 4) emotion processing (n = 9). Thirteen studies included FHR-BD, five studies included FHR-SZ, and one study included a pooled FHR group. In general, task performance did not differ between the respective FHR groups and healthy controls, but 18 out of the 19 fMRI studies revealed regional alterations in task-related activation. Brain regions showing group differences in peak activation were regions associated with the respective task domain and showed little overlap between FHR-SZ and FHR-BD. The low number of studies, together with the low number of subjects, and the substantial heterogeneity of employed methodological approaches within the domain of working memory, cognitive control, and reward processing impedes finite conclusions. Emotion processing was the most investigated task domain in FHR-BD. Four studies reported differences in activation of the amygdala, and two studies reported differences in activation of inferior frontal/middle gyrus. Together, these studies provide evidence for altered brain processing of emotions in children, adolescents, and young adults at FHR-BD. More studies of higher homogeneity, larger sample sizes and with a longitudinal study design are warranted to prove a shared or specific FHR-related endophenotypic brain activation in young first-degree relatives of individuals with SZ or BD, as well as to pinpoint specific alterations in brain activation during cognitive-, emotional-, and reward-related tasks.
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Affiliation(s)
- Line Korsgaard Johnsen
- Child and Adolescent Mental Health Centre, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Anna Hester Ver Loren van Themaat
- Child and Adolescent Mental Health Centre, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Kit Melissa Larsen
- Child and Adolescent Mental Health Centre, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark.,Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
| | - Birgitte Klee Burton
- Child and Adolescent Mental Health Centre, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark
| | - William Frans Christiaan Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark.,Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Merete Nordentoft
- Faculty of Health and Medical Sciences, Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Mental Health Centre, Research Unit, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark.,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Kerstin Jessica Plessen
- Child and Adolescent Mental Health Centre, Copenhagen University Hospital, Mental Health Services, Capital Region Psychiatry, Copenhagen, Denmark.,The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus University, Aarhus, Denmark.,Division of Child and Adolescent Psychiatry, Department of Psychiatry, The University Hospital of Lausanne (CHUV), Lausanne, Switzerland
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26
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de Zwarte SMC, Brouwer RM, Tsouli A, Cahn W, Hillegers MHJ, Hulshoff Pol HE, Kahn RS, van Haren NEM. Running in the Family? Structural Brain Abnormalities and IQ in Offspring, Siblings, Parents, and Co-twins of Patients with Schizophrenia. Schizophr Bull 2019; 45:1209-1217. [PMID: 30597053 PMCID: PMC6811835 DOI: 10.1093/schbul/sby182] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Structural brain abnormalities and cognitive deficits have been reported in patients with schizophrenia and to a lesser extent in their first-degree relatives (FDRs). Here we investigated whether brain abnormalities in nonpsychotic relatives differ per type of FDR and how these abnormalities are related to intelligent quotient (IQ). Nine hundred eighty individuals from 5 schizophrenia family cohorts (330 FDRs, 432 controls, 218 patients) were included. Effect sizes were calculated to compare brain measures of FDRs and patients with controls, and between each type of FDR. Analyses were repeated with a correction for IQ, having a nonpsychotic diagnosis, and intracranial volume (ICV). FDRs had significantly smaller ICV, surface area, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, thalamus, putamen, amygdala, and accumbens volumes as compared with controls (ds < -0.19, q < 0.05 corrected). Offspring showed the largest effect sizes relative to the other FDRs; however, none of the effects in the different relative types survived correction for multiple comparisons. After IQ correction, all effects disappeared in the FDRs after correction for multiple comparisons. The findings in FDRs were not explained by having a nonpsychotic disorder and were only partly explained by ICV. FDRs show brain abnormalities that are strongly covarying with IQ. On the basis of consistent evidence of genetic overlap between schizophrenia, IQ, and brain measures, we suggest that the brain abnormalities in FDRs are at least partly explained by genes predisposing to both schizophrenia risk and IQ.
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Affiliation(s)
- Sonja M C de Zwarte
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,To whom correspondence should be addressed; Department of Psychiatry, University Medical Center Utrecht, House A.01.126 A01.126, PO Box 85500, 3508 GA Utrecht, The Netherlands; tel: +31-88-75-67656, e-mail:
| | - Rachel M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Andromachi Tsouli
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Manon H J Hillegers
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,Department of Child and Adolescent Psychiatry/Psychology, Sophia Children’s Hospital, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Neeltje E M van Haren
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands,Department of Child and Adolescent Psychiatry/Psychology, Sophia Children’s Hospital, Erasmus Medical Center, Rotterdam, The Netherlands
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27
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Spalthoff R, Degenhardt F, Awasthi S, Heilmann-Heimbach S, Besteher B, Gaser C, Ripke S, Nöthen MM, Nenadić I. Effects of a neurodevelopmental genes based polygenic risk score for schizophrenia and single gene variants on brain structure in non-clinical subjects: A preliminary report. Schizophr Res 2019; 212:225-228. [PMID: 31395486 DOI: 10.1016/j.schres.2019.07.061] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 05/27/2019] [Accepted: 07/30/2019] [Indexed: 11/18/2022]
Abstract
We tested whether a polygenic risk score integrating the effects of genes affecting neurodevelopment is associated to brain structural variation in healthy subjects. We acquired magnetic resonance imaging and genetic data of 167 healthy adults and computed a neurodevelopmental polygenic risk score (nPRS). We correlated the nPRS with local gyrification, cortical thickness and grey matter density and explored effects of single nucleotide polymorphisms included in the score. We did not find significant correlations of this nPRS with either measure. Individuals with the risk allele at rs11139497 show increases in cortical thickness (p < 0.05, FWE corrected) of the left superior temporal gyrus.
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Affiliation(s)
- Robert Spalthoff
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Swapnil Awasthi
- Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin 10117, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Bianca Besteher
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Department of Neurology, Jena University Hospital, Jena, Germany
| | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Dept. of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin 10117, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Department of Psychiatry and Psychotherapy, Phillips University Marburg/Marburg University Hospital UKGM, Marburg, Germany.
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28
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Cao H, Ingvar M, Hultman CM, Cannon T. Evidence for cerebello-thalamo-cortical hyperconnectivity as a heritable trait for schizophrenia. Transl Psychiatry 2019; 9:192. [PMID: 31431615 PMCID: PMC6702223 DOI: 10.1038/s41398-019-0531-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 05/13/2019] [Accepted: 06/20/2019] [Indexed: 12/18/2022] Open
Abstract
Our recent study has demonstrated that increased connectivity in the cerebello-thalamo-cortical (CTC) circuitry is a state-independent neural trait that can potentially predict the onset of psychosis. One possible cause of such "trait" abnormality would be genetic predisposition. Here, we tested this hypothesis using multi-paradigm functional magnetic resonance imaging (fMRI) data from two independent twin cohorts. In a sample of 85 monozygotic (MZ) and 52 dizygotic (DZ) healthy twin pairs acquired from the Human Connectome Project, we showed that the connectivity pattern of the identified CTC circuitry was more similar in the MZ twins (r = 0.54) compared with that in the DZ twins (r = 0.22). The structural equation modeling analysis revealed a heritability estimate of 0.52 for the CTC connectivity, suggesting a moderately strong genetic effect. Moreover, using an independent schizophrenia cotwin sample (10 discordant MZ cotwins, 30 discordant DZ cotwins, and 32 control cotwins), we observed a significant linear relationship between genetic distance to schizophrenia and the connectivity strength in the CTC circuitry (i.e., schizophrenia MZ cotwins > schizophrenia DZ cotwins > control twins, P = 0.045). The present data provide converging evidence that increased connectivity in the CTC circuitry is likely to be a heritable trait that is associated with the genetic risk of schizophrenia.
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Affiliation(s)
- Hengyi Cao
- Department of Psychology, Yale University, New Haven, CT, USA.
| | - Martin Ingvar
- 0000 0004 1937 0626grid.4714.6Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Christina M. Hultman
- 0000 0004 1937 0626grid.4714.6Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tyrone Cannon
- 0000000419368710grid.47100.32Department of Psychology, Yale University, New Haven, CT USA ,0000000419368710grid.47100.32Department of Psychiatry, Yale University, New Haven, CT USA
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29
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Ding Y, Ou Y, Pan P, Shan X, Chen J, Liu F, Zhao J, Guo W. Brain structural abnormalities as potential markers for detecting individuals with ultra-high risk for psychosis: A systematic review and meta-analysis. Schizophr Res 2019; 209:22-31. [PMID: 31104914 DOI: 10.1016/j.schres.2019.05.015] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Revised: 02/28/2019] [Accepted: 05/06/2019] [Indexed: 02/01/2023]
Abstract
OBJECTIVE This study aims to determine whether structural alterations can be used as neuroimaging markers to detect individuals with ultra-high risk (UHR) for psychosis for the diagnosis of schizophrenia and improvement of treatment outcomes. METHODS Embase and Pubmed databases were searched for related studies in July 2018. The search was performed without restriction on time and regions or languages. A total of 188 articles on voxel-based morphometry (VBM) and 96 articles on cortical thickness were obtained, and another 6 articles were included after the reference lists were checked. Our researchers assessed and extracted the data in accordance with the PRISMA guideline. The data were processed with a seed-based mapping method. RESULTS Fourteen VBM and nine cortical thickness studies were finally included in our study. In individuals with UHR, the gray matter volumes in the bilateral median cingulate (Z = 1.034), the right fusiform gyrus (Z = 1.051), the left superior temporal gyrus (Z = 1.048), and the right thalamus (Z = 1.039) increased relative to those of healthy controls. By contrast, the gray matter volumes in the right gyrus rectus (Z = -2.109), the right superior frontal gyrus (Z = -2.321), and the left superior frontal gyrus (Z = -2.228) decreased. The robustness of these findings was verified through Jackknife sensitivity analysis, and heterogeneity across studies was low. Typically, cortical thickness alterations were not detected in individuals with UHR. CONCLUSIONS Structural abnormalities of the thalamocortical circuit may underpin the neurophysiology of psychosis and mark the vulnerability of transition to psychosis in UHR subjects.
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Affiliation(s)
- Yudan Ding
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Yangpan Ou
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Pan Pan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Xiaoxiao Shan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Jindong Chen
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Wenbin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China.
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Resting-state fMRI in Parkinson's disease patients with cognitive impairment: A meta-analysis. Parkinsonism Relat Disord 2019; 62:16-27. [DOI: 10.1016/j.parkreldis.2018.12.016] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 10/29/2018] [Accepted: 12/15/2018] [Indexed: 12/14/2022]
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Ramsay IS. An Activation Likelihood Estimate Meta-analysis of Thalamocortical Dysconnectivity in Psychosis. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:859-869. [PMID: 31202821 DOI: 10.1016/j.bpsc.2019.04.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 03/26/2019] [Accepted: 04/13/2019] [Indexed: 02/08/2023]
Abstract
BACKGROUND Thalamocortical dysconnectivity is hypothesized to underlie the pathophysiology of psychotic disorders, including schizophrenia and bipolar disorder, and individuals at clinical high risk. Numerous studies have examined connectivity networks seeding from the thalamus during rest, revealing a pattern of thalamo-fronto-cerebellar hypoconnectivity and thalamosensory hyperconnectivity. However, given variability in these networks, as well as their relationships with clinical and cognitive symptoms, thalamocortical connectivity's status as a biomarker and treatment target for psychotic disorders remains unclear. METHODS A literature search was performed to identify thalamic seed-based connectivity studies conducted in patients with psychotic disorders. Activation likelihood estimate analysis examined the reported coordinates for hypoconnectivity (healthy control participants > patients with psychosis) and hyperconnectivity (patients with psychosis > healthy control participants). The relationship between hypoconnectivity and hyperconnectivity, as well as their relationships with clinical and cognitive measures, was meta-analyzed. RESULTS Each activation likelihood estimate included 20 experiments (from 17 publications). Thalamocortical hypoconnectivity was observed in middle frontal, cingulate, and thalamic regions, while hyperconnectivity was observed in motor, somatosensory, temporal, occipital, and insular cortical regions. Meta-analysis of the studies reporting correlations between hypo- and hyperconnectivity showed a strong negative relationship. Meta-analysis of studies reporting correlations between hyperconnectivity and symptoms showed small but significant positive relationships. CONCLUSIONS Activation likelihood estimates of thalamocortical hypoconnectivity revealed a network of prefrontal and thalamic regions, while hyperconnections identified sensory areas. The strong negative relationship between these thalamocortical deflections suggests that they arrive from a common mechanism and may account for aspects of psychosis. These findings identify reliable thalamocortical networks that may guide future studies and serve as crucial treatment targets for psychotic disorders.
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Affiliation(s)
- Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota.
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Wang X, Zhao N, Shi J, Wu Y, Liu J, Xiao Q, Hu J. Discussion on the Application of Multi-modal Magnetic Resonance Imaging Fusion in Schizophrenia. J Med Syst 2019; 43:131. [DOI: 10.1007/s10916-019-1215-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Accepted: 02/13/2019] [Indexed: 10/27/2022]
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Zhu F, Liu Y, Liu F, Yang R, Li H, Chen J, Kennedy DN, Zhao J, Guo W. Functional asymmetry of thalamocortical networks in subjects at ultra-high risk for psychosis and first-episode schizophrenia. Eur Neuropsychopharmacol 2019; 29:519-528. [PMID: 30770234 DOI: 10.1016/j.euroneuro.2019.02.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 01/29/2019] [Accepted: 02/02/2019] [Indexed: 01/18/2023]
Abstract
Disrupted functional asymmetry has been implicated in schizophrenia. However, it remains unknown whether disrupted functional asymmetry originates from intra-hemispheric and/or inter-hemispheric functional connectivity (FC) in the patients, and whether it starts at very early stage of psychosis. Seventy-six patients with first-episode, drug-naive schizophrenia, 74 subjects at ultra-high risk for psychosis (UHR), and 71 healthy controls underwent resting-state functional magnetic resonance imaging. The 'Parameter of asymmetry' (PAS) metric was calculated and support vector machine (SVM) classification analysis was applied to analyze the data. Compared with healthy controls, patients exhibited decreased PAS in the left thalamus/pallidum, right hippocampus/parahippocampus, right inferior frontal gyrus/insula, right thalamus, and left inferior parietal lobule, and increased PAS in the left calcarine, right superior occipital gyrus/middle occipital gyrus, and right precentral gyrus/postcentral gyrus. By contrast, UHR subjects showed decreased PAS in the left thalamus relative to healthy controls. A negative correlation was observed between decreased PAS in the right hippocampus/parahippocampus and Brief Visuospatial Memory Test-Revised (BVMT-R) scores in the patients (r = -0.364, p = 0.002). Moreover, the PAS values in the left thalamus could discriminate the patients/UHR subjects from the controls with acceptable sensitivities (68.42%/81.08%). First-episode patients and UHR subjects shared decreased PAS in the left thalamus. This observed pattern of functional asymmetry highlights the involvement of the thalamus in the pathophysiology of psychosis and may also be applied as a very early marker for psychosis.
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Affiliation(s)
- Furong Zhu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Yi Liu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Ru Yang
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jindong Chen
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - David N Kennedy
- Department of Psychiatry, Division of Neuroinformatics, University of Massachusetts Medical School, UMass Memorial Medical Center, Worcester, MA 01605, United States
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Wenbin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
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Polygenic Scores for Neuropsychiatric Traits and White Matter Microstructure in the Pediatric Population. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:243-250. [DOI: 10.1016/j.bpsc.2018.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 07/08/2018] [Accepted: 07/09/2018] [Indexed: 12/31/2022]
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35
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Schwarz E, Doan NT, Pergola G, Westlye LT, Kaufmann T, Wolfers T, Brecheisen R, Quarto T, Ing AJ, Di Carlo P, Gurholt TP, Harms RL, Noirhomme Q, Moberget T, Agartz I, Andreassen OA, Bellani M, Bertolino A, Blasi G, Brambilla P, Buitelaar JK, Cervenka S, Flyckt L, Frangou S, Franke B, Hall J, Heslenfeld DJ, Kirsch P, McIntosh AM, Nöthen MM, Papassotiropoulos A, de Quervain DJF, Rietschel M, Schumann G, Tost H, Witt SH, Zink M, Meyer-Lindenberg A. Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder. Transl Psychiatry 2019; 9:12. [PMID: 30664633 PMCID: PMC6341112 DOI: 10.1038/s41398-018-0225-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Accepted: 07/16/2018] [Indexed: 12/18/2022] Open
Abstract
Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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Affiliation(s)
- Emanuel Schwarz
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Giulio Pergola
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Thomas Wolfers
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Center for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - Ralph Brecheisen
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - Tiziana Quarto
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Alex J Ing
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Pasquale Di Carlo
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | | | - Torgeir Moberget
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm County Council, Stockholm, Sweden
- Department of Psychiatry Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Marcella Bellani
- Section of Psychiatry, Azienda Ospedaliera Universitaria Integrata Verona, Verona, VR, Italy
- Department of Neurosciences, Biomedicine and Movements Sciences, University of Verona, Verona, VR, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Institute of Psichiatry, Policlinico Bari, Azienda Ospedaliero Universitaria Consorziale Policlinico Bari, Bari, BA, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Jan K Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm County Council, Stockholm, Sweden
| | - Lena Flyckt
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm County Council, Stockholm, Sweden
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Departments of Human Genetics and Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeremy Hall
- Neuroscience and Mental Health Research Institute, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Dirk J Heslenfeld
- Department of Cognitive Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Peter Kirsch
- Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
- Bernstein Center for Computational Neuroscience Heidelberg-Mannheim, Mannheim, Germany
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, EH10 5HF, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, George Square, Edinburgh, EH8 9JZ, UK
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Andreas Papassotiropoulos
- Division of Molecular Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland
- Transfaculty Research Platform Molecular and Cognitive Neuroscience, University of Basel, Basel, Switzerland
- Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland
- Department Biozentrum, Life Sciences Training Facility, University of Basel, CH-4056, Basel, Switzerland
| | - Dominique J-F de Quervain
- Transfaculty Research Platform Molecular and Cognitive Neuroscience, University of Basel, Basel, Switzerland
- Psychiatric University Clinics, University of Basel, CH-4055, Basel, Switzerland
- Division of Cognitive Neuroscience, Department of Psychology, University of Basel, CH-4055, Basel, Switzerland
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Heike Tost
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Mathias Zink
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- District Hospital Mittelfranken, Department of Psychiatry, Psychotherapy and Psychosomatics, Ansbach, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
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Hajek T, Franke K, Kolenic M, Capkova J, Matejka M, Propper L, Uher R, Stopkova P, Novak T, Paus T, Kopecek M, Spaniel F, Alda M. Brain Age in Early Stages of Bipolar Disorders or Schizophrenia. Schizophr Bull 2019; 45:190-198. [PMID: 29272464 PMCID: PMC6293219 DOI: 10.1093/schbul/sbx172] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia. METHODS We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age. RESULTS Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age. CONCLUSIONS Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.
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Affiliation(s)
- Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.,National Institute of Mental Health, Klecany, Czech Republic
| | - Katja Franke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Jena, Germany
| | - Marian Kolenic
- National Institute of Mental Health, Klecany, Czech Republic
| | - Jana Capkova
- National Institute of Mental Health, Klecany, Czech Republic
| | - Martin Matejka
- National Institute of Mental Health, Klecany, Czech Republic.,Psychiatric Hospital Bohnice, Prague, Czech Republic
| | - Lukas Propper
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Pavla Stopkova
- National Institute of Mental Health, Klecany, Czech Republic
| | - Tomas Novak
- National Institute of Mental Health, Klecany, Czech Republic
| | - Tomas Paus
- Rotman Research Institute and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada.,Center for Developing Brain, Child Mind Institute, New York, NY
| | | | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.,National Institute of Mental Health, Klecany, Czech Republic
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Thorup AAE, Hemager N, Søndergaard A, Gregersen M, Prøsch ÅK, Krantz MF, Brandt JM, Carmichael L, Melau M, Ellersgaard DV, Burton BK, Greve AN, Uddin MJ, Ohland J, Nejad AB, Johnsen LK, Ver Loren van Themaat AH, Andreassen AK, Vedum L, Knudsen CB, Stadsgaard H, M. Jepsen JR, Siebner HR, Østergaard L, Bliksted VF, Plessen KJ, Mors O, Nordentoft M. The Danish High Risk and Resilience Study-VIA 11: Study Protocol for the First Follow-Up of the VIA 7 Cohort -522 Children Born to Parents With Schizophrenia Spectrum Disorders or Bipolar Disorder and Controls Being Re-examined for the First Time at Age 11. Front Psychiatry 2018; 9:661. [PMID: 30631284 PMCID: PMC6315161 DOI: 10.3389/fpsyt.2018.00661] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Accepted: 11/19/2018] [Indexed: 12/31/2022] Open
Abstract
Introduction: Offspring of parents with severe mental illness have an increased risk of developing mental illnesses themselves. Familial high risk cohorts give a unique opportunity for studying the development over time, both the illness that the individual is predisposed for and any other diagnoses. These studies can also increase our knowledge of etiology of severe mental illness and provide knowledge about the underlying mechanisms before illness develops. Interventions targeting this group are often proposed due to the potential possibility of prevention, but evidence about timing and content is lacking. Method: A large, representative cohort of 522 7-year old children born to parents with schizophrenia, bipolar disorder or controls was established based on Danish registers. A comprehensive baseline assessment including neurocognition, motor functioning, psychopathology, home environment, sociodemographic data, and genetic information was conducted from January 1, 2013 to January 31, 2016. This study is the first follow-up of the cohort, carried out when the children turn 11 years of age. By assessing the cohort at this age, we will evaluate the children twice before puberty. All instruments have been selected with a longitudinal perspective and most of them are identical to those used at inclusion into the study at age 7. A diagnostic interview, motor tests, and a large cognitive battery are conducted along with home visits and information from teachers. This time we examine the children's brains by magnetic resonance scans and electroencephalograms. Measures of physical activity and sleep are captured by a chip placed on the body, while we obtain biological assays by collecting blood samples from the children. Discussion: Findings from the VIA 7 study revealed large variations across domains between children born to parents with schizophrenia, bipolar and controls, respectively. This study will further determine whether the children at familial risk reveal delayed developmental courses, but catch up at age 11, or whether the discrepancies between the groups have grown even larger. We will compare subgroups within each of the familial high risk groups in order to investigate aspects of resilience. Data on brain structure and physical parameters will add a neurobiological dimension to the study.
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Affiliation(s)
- Anne A. E. Thorup
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Nicoline Hemager
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Anne Søndergaard
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Maja Gregersen
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Åsa Kremer Prøsch
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Mette F. Krantz
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Julie M. Brandt
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Line Carmichael
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Marianne Melau
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Ditte V. Ellersgaard
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Birgitte K. Burton
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
| | - Aja N. Greve
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Md Jamal Uddin
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Jessica Ohland
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
| | - Ayna B. Nejad
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Danish Research Centre for Magnetic Resonance, Section 714, Hvidovre Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Line K. Johnsen
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Danish Research Centre for Magnetic Resonance, Section 714, Hvidovre Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Anna Hester Ver Loren van Themaat
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Danish Research Centre for Magnetic Resonance, Section 714, Hvidovre Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Anna K. Andreassen
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Lotte Vedum
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Christina B. Knudsen
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Henriette Stadsgaard
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Jens Richardt M. Jepsen
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Center for Neuropsychiatric Schizophrenia Research (CNSR) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Section 714, Hvidovre Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience, Aarhus University, Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark
| | - Vibeke F. Bliksted
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
- Center of Functionally Integrative Neuroscience, Aarhus University, Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark
| | - Kerstin J. Plessen
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Research Unit, Child and Adolescent Mental Health Center, University of Copenhagen, Copenhagen, Denmark
- Division of Adolescent and Child Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Ole Mors
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark
| | - Merete Nordentoft
- The Lundbeck Foundation Intiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Mental Health Center Copenhagen, Research Unit, University of Copenhagen, Copenhagen, Denmark
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Egloff L, Lenz C, Studerus E, Harrisberger F, Smieskova R, Schmidt A, Huber C, Simon A, Lang UE, Riecher-Rössler A, Borgwardt S. Sexually dimorphic subcortical brain volumes in emerging psychosis. Schizophr Res 2018; 199:257-265. [PMID: 29605160 DOI: 10.1016/j.schres.2018.03.034] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 01/27/2018] [Accepted: 03/18/2018] [Indexed: 01/27/2023]
Abstract
BACKGROUND In schizophrenic psychoses, the normal sexual dimorphism of the brain has been shown to be disrupted or even reversed. Little is known, however, at what time point in emerging psychosis this occurs. We have therefore examined, if these alterations are already present in the at-risk mental state (ARMS) for psychosis and in first episode psychosis (FEP) patients. METHODS Data from 65 ARMS (48 (73.8%) male; age=25.1±6.32) and 50 FEP (37 (74%) male; age=27±6.56) patients were compared to those of 70 healthy controls (HC; 27 (38.6%) male; age=26±4.97). Structural T1-weighted images were acquired using a 3 Tesla magnetic resonance imaging (MRI) scanner. Linear mixed effects models were used to investigate whether subcortical brain volumes are dependent on sex. RESULTS We found men to have larger total brain volumes (p<0.001), and smaller bilateral caudate (p=0.008) and hippocampus volume (p<0.001) than women across all three groups. Older subjects had more GM and WM volume than younger subjects. No significant sex×group interaction was found. CONCLUSIONS In emerging psychosis there still seem to exist patterns of normal sexual dimorphism in total brain and caudate volume. The only structure affected by reversed sexual dimorphism was the hippocampus, with women showing larger volumes than men even in HC. Thus, we conclude that subcortical volumes may not be primarily affected by disrupted sexual dimorphism in emerging psychosis.
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Affiliation(s)
- Laura Egloff
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland; University of Basel, Department of Psychology, Division of Clinical Psychology and Epidemiology, Basel, Switzerland
| | - Claudia Lenz
- University of Basel, Institute of Forensic Medicine, Basel, Switzerland
| | - Erich Studerus
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Fabienne Harrisberger
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Renata Smieskova
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - André Schmidt
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Christian Huber
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Andor Simon
- University Hospital of Bern, University Hospital of Psychiatry, Bern, Switzerland; Specialized Early Psychosis Outpatient Service for Adolescents and Young Adults, Department of Psychiatry, Bruderholz, Switzerland
| | - Undine E Lang
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Anita Riecher-Rössler
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland
| | - Stefan Borgwardt
- University of Basel Psychiatric Hospital, Department of Psychiatry, Basel, Switzerland.
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Rozycki M, Satterthwaite TD, Koutsouleris N, Erus G, Doshi J, Wolf DH, Fan Y, Gur RE, Gur RC, Meisenzahl EM, Zhuo C, Yin H, Yan H, Yue W, Zhang D, Davatzikos C. Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals. Schizophr Bull 2018; 44:1035-1044. [PMID: 29186619 PMCID: PMC6101559 DOI: 10.1093/schbul/sbx137] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Past work on relatively small, single-site studies using regional volumetry, and more recently machine learning methods, has shown that widespread structural brain abnormalities are prominent in schizophrenia. However, to be clinically useful, structural imaging biomarkers must integrate high-dimensional data and provide reproducible results across clinical populations and on an individual person basis. Using advanced multi-variate analysis tools and pooled data from case-control imaging studies conducted at 5 sites (941 adult participants, including 440 patients with schizophrenia), a neuroanatomical signature of patients with schizophrenia was found, and its robustness and reproducibility across sites, populations, and scanners, was established for single-patient classification. Analyses were conducted at multiple scales, including regional volumes, voxelwise measures, and complex distributed patterns. Single-subject classification was tested for single-site, pooled-site, and leave-site-out generalizability. Regional and voxelwise analyses revealed a pattern of widespread reduced regional gray matter volume, particularly in the medial prefrontal, temporolimbic and peri-Sylvian cortex, along with ventricular and pallidum enlargement. Multivariate classification using pooled data achieved a cross-validated prediction accuracy of 76% (AUC = 0.84). Critically, the leave-site-out validation of the detected schizophrenia signature showed accuracy/AUC range of 72-77%/0.73-0.91, suggesting a robust generalizability across sites and patient cohorts. Finally, individualized patient classifications displayed significant correlations with clinical measures of negative, but not positive, symptoms. Taken together, these results emphasize the potential for structural neuroimaging data to provide a robust and reproducible imaging signature of schizophrenia. A web-accessible portal is offered to allow the community to obtain individualized classifications of magnetic resonance imaging scans using the methods described herein.
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Affiliation(s)
- Martin Rozycki
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Theodore D Satterthwaite
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA,Brain Behavior Laboratory, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Jimit Doshi
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Daniel H Wolf
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA,Brain Behavior Laboratory, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Raquel E Gur
- Brain Behavior Laboratory, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Ruben C Gur
- Brain Behavior Laboratory, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Eva M Meisenzahl
- Department of Psychiatry and Psychotherapy, Heinrich Heine University Dusseldorf, Dusseldorf, Germany
| | | | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Hao Yan
- Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders, Sixth Hospital, Peking University, Beijing, China
| | - Weihua Yue
- Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders, Sixth Hospital, Peking University, Beijing, China
| | - Dai Zhang
- Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health & National Clinical Research Center for Mental Disorders, Sixth Hospital, Peking University, Beijing, China
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA,To whom correspondence should be addressed; University of Pennsylvania, Richards Building, 7th Floor, 3700 Hamilton Walk, Philadelphia, PA 19104; tel: 215-746-4067, fax: 215-746-4060, e-mail:
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40
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Neilson E, Bois C, Clarke TK, Hall L, Johnstone EC, Owens DGC, Whalley HC, McIntosh AM, Lawrie SM. Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study. Psychol Med 2018; 48:1532-1539. [PMID: 29065934 DOI: 10.1017/s0033291717003087] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia. METHODS The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes. RESULTS We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification. CONCLUSIONS These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.
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Affiliation(s)
- E Neilson
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - C Bois
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - T-K Clarke
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - L Hall
- International Centre for Life,Institute of Genetic Medicine,Newcastle University,Central Parkway,Newcastle upon Tyne,UK
| | - E C Johnstone
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - D G C Owens
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - H C Whalley
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - A M McIntosh
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - S M Lawrie
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
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41
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Wang YM, Zou LQ, Xie WL, Yang ZY, Zhu XZ, Cheung EFC, Sørensen TA, Møller A, Chan RCK. Altered grey matter volume and cortical thickness in patients with schizo-obsessive comorbidity. Psychiatry Res Neuroimaging 2018; 276:65-72. [PMID: 29628272 DOI: 10.1016/j.pscychresns.2018.03.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 03/23/2018] [Accepted: 03/23/2018] [Indexed: 02/05/2023]
Abstract
Recent findings suggest that schizo-obsessive comorbidity (SOC) may be a unique diagnostic entity. We examined grey matter (GM) volume and cortical thickness in 22 patients with SOC, and compared them with 21 schizophrenia (SCZ) patients, 22 obsessive-compulsive disorder (OCD) patients and 22 healthy controls (HCs). We found that patients with SOC exhibited reduced GM volume in the left thalamus, the left inferior semi-lunar lobule of the cerebellum, the bilateral medial orbitofrontal cortex (medial oFC), the medial superior frontal gyrus (medial sFG), the rectus gyrus and the anterior cingulate cortex (aCC) compared with HCs. Patients with SOC also exhibited reduced cortical thickness in the right superior temporal gyrus (sTG), the right angular gyrus, the right supplementary motor area (SMA), the right middle cingulate cortex (mCC) and the right middle occipital gyrus (mOG) compared with HCs. Together with the differences in GM volume and cortical thickness between patients with SOC and patients with only SCZ or only OCD, these findings highlight the GM changes specific to patients with SOC.
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Affiliation(s)
- Yong-Ming Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, PR China; Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Lai-Quan Zou
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou, Guangdong, PR China
| | - Wen-Lan Xie
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Zhuo-Ya Yang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Xiong-Zhao Zhu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, PR China
| | - Eric F C Cheung
- Castle Peak Hospital, Hong Kong Special Administrative Region, PR China
| | - Thomas Alrik Sørensen
- Sino-Danish Center for Education and Research, Beijing 100190, PR China; Centre for Cognitive Neuroscience, Institute of Communication and Psychology, Aalborg University, Denmark
| | - Arne Møller
- Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Denmark; Centre of Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, PR China; Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China.
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van der Stouwe ECD, van Busschbach JT, de Vries B, Cahn W, Aleman A, Pijnenborg GHM. Neural correlates of exercise training in individuals with schizophrenia and in healthy individuals: A systematic review. Neuroimage Clin 2018; 19:287-301. [PMID: 30023171 PMCID: PMC6050351 DOI: 10.1016/j.nicl.2018.04.018] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 03/27/2018] [Accepted: 04/16/2018] [Indexed: 12/17/2022]
Abstract
A body of evidence has revealed positive effects of physical exercise on behavioral, cognitive and physical outcomes in patients with schizophrenia. Notably, the effect of exercise at the neural level may be particularly relevant as well as it is hypothesized that exercise may stimulate the brain in a way that might normalize neural alterations related to the disorder. The aim of the current systematic review was to provide an up to date overview of studies investigating the neural effects of exercise in individuals with a schizophrenia spectrum disorder and healthy individuals. The majority of included studies focused on hippocampal effects, reporting beneficial effects of exercise. In addition, in schizophrenia increased extrastriate body area (EBA) activation and increased white matter fiber integrity in tracts relevant to the disorder were found and in healthy individuals decreased connectivity of the dorsolateral prefrontal cortex (DLPFC) indicating greater cognitive efficiency was reported. Comparing individuals with a schizophrenia spectrum disorder and healthy individuals within a similar age range, most studies found similar effects on hippocampal volume and white matter tracts for both groups, although the effect in schizophrenia spectrum disorders may be attenuated which is in line with previous literature on brain plasticity. The current review indicates a lack of studies investigating neural correlates other than the hippocampus. Although those studies that did focus on other neural correlates revealed promising results, these have not been replicated in other studies and call for replication. Furthermore, future studies should expand their focus, by investigating neural mechanisms underlying positive effects of physical exercise on positive symptoms, negative symptoms and symptoms such as depression, social withdrawal and social cognition.
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Affiliation(s)
- E C D van der Stouwe
- Department of Neuroscience, BCN Neuroimaging Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713, AW, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Rob Giel Onderzoekcentrum, Hanzeplein 1, 9713, GZ, Groningen, The Netherlands.
| | - J T van Busschbach
- University of Groningen, University Medical Center Groningen, University Center of Psychiatry, Rob Giel Onderzoekcentrum, Hanzeplein 1, 9713, GZ, Groningen, The Netherlands; Department of Movement and Education, Windesheim University of Applied Sciences, Campus 2-6, 8017, CA, Zwolle, The Netherlands.
| | - B de Vries
- Department of Clinical Psychology, University of Groningen, Grote Kruisstraat 2/1, 9712, TS, Groningen, The Netherlands.
| | - W Cahn
- Department of Psychiatry, Rudolf Magnus Institute for Neuroscience, University Medical Center Utrecht, Heigelberglaan 100, 3584, CX, Utrecht, The Netherlands.
| | - A Aleman
- Department of Neuroscience, BCN Neuroimaging Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713, AW, Groningen, The Netherlands.
| | - G H M Pijnenborg
- Department of Neuroscience, BCN Neuroimaging Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713, AW, Groningen, The Netherlands; Department of Clinical Psychology, University of Groningen, Grote Kruisstraat 2/1, 9712, TS, Groningen, The Netherlands; Department of Psychotic Disorders, GGZ-Drenthe, Dennenweg 9, 9404, LA, Assen, The Netherlands.
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Kolenic M, Franke K, Hlinka J, Matejka M, Capkova J, Pausova Z, Uher R, Alda M, Spaniel F, Hajek T. Obesity, dyslipidemia and brain age in first-episode psychosis. J Psychiatr Res 2018; 99:151-158. [PMID: 29454222 DOI: 10.1016/j.jpsychires.2018.02.012] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 02/06/2018] [Accepted: 02/09/2018] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Obesity and dyslipidemia may negatively affect brain health and are frequent medical comorbidities of schizophrenia and related disorders. Despite the high burden of metabolic disorders, little is known about their effects on brain structure in psychosis. We investigated, whether obesity or dyslipidemia contributed to brain alterations in first-episode psychosis (FEP). METHODS 120 participants with FEP, who were undergoing their first psychiatric hospitalization, had <24 months of untreated psychosis and were 18-35 years old and 114 controls within the same age range participated in the study. We acquired 3T brain structural MRI, fasting lipids and body mass index. We used machine learning trained on an independent sample of 504 controls to estimate the individual brain age of study participants and calculated the BrainAGE score by subtracting the chronological from the estimated brain age. RESULTS In a multiple regression model, the diagnosis of FEP (B = 1.15, SE B = 0.31, p < 0.001) and obesity/overweight (B = 0.92, SE B = 0.35, p = 0.008) were each additively associated with BrainAGE scores (R2 = 0.22, F(3, 230) = 21.92, p < 0.001). BrainAGE scores were highest in participants with FEP and obesity/overweight (3.83 years, 95%CI = 2.35-5.31) and lowest in normal weight controls (-0.27 years, 95%CI = -1.22-0.69). LDL-cholesterol, HDL-cholesterol or triglycerides were not associated with BrainAGE scores. CONCLUSIONS Overweight/obesity may be an independent risk factor for diffuse brain alterations manifesting as advanced brain age already early in the course of psychosis. These findings raise the possibility that targeting metabolic health and intervening already at the level of overweight/obesity could slow brain ageing in FEP.
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Affiliation(s)
- Marian Kolenic
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic
| | - Katja Franke
- Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Erlanger Alle 101, D - 07747, Jena, Germany
| | - Jaroslav Hlinka
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Institute of Computer Science, Czech Academy of Sciences, Pod Vodarenskou Vezi 271/2, 182 07, Prague, Czech Republic
| | - Martin Matejka
- 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic; Psychiatric Hospital Bohnice, Ústavní 91, 181 00, Prague, Czech Republic; Psychiatric Hospital Kosmonosy, Lípy 15, 293 06, Kosmonosy, Czech Republic
| | - Jana Capkova
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; 3rd School of Medicine, Charles University, Ruská 87, 100 00, Prague, Czech Republic
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, 686 Bay Street, 10-9705, Toronto, ON M5G 0A4, Canada
| | - Rudolf Uher
- Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada
| | - Martin Alda
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada
| | - Filip Spaniel
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic
| | - Tomas Hajek
- National Institute of Mental Health, Topolová 748, 250 67, Klecany, Czech Republic; Dalhousie University, Department of Psychiatry, 5909, Veteran's Memorial Lane, Halifax, NS B3H 2E2, Canada.
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Conjoint and dissociated structural and functional abnormalities in first-episode drug-naive patients with major depressive disorder: a multimodal meta-analysis. Sci Rep 2017; 7:10401. [PMID: 28871117 PMCID: PMC5583354 DOI: 10.1038/s41598-017-08944-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Accepted: 07/21/2017] [Indexed: 02/05/2023] Open
Abstract
Published MRI evidence of structural and resting-state functional brain abnormalities in MDD has been inconsistent. To eliminate interference by repeated disease episodes and antidepressant treatment, we conducted the first multimodal voxel-wise meta-analysis of studies of voxel-based morphometry (VBM) and the amplitude of low-frequency fluctuation (ALFF) in first-episode drug-naive MDD patients, using the Seed-based d Mapping method (SDM). Fifteen VBM data sets and 11 ALFF data sets were included. SDM-based multimodal meta-analysis was used to highlight brain regions with both structural and functional abnormalities. This identified conjoint structural and functional abnormalities in left lateral orbitofrontal cortex and right supplementary motor area, and also dissociated abnormalities of structure (decreased grey matter in right dorsolateral prefrontal cortex and right inferior temporal gyrus; increased grey matter in right insula, right putamen, left temporal pole, and bilateral thalamus) and function (increased brain activity in left supplementary motor area, left parahippocampal gyrus, and hippocampus; decreased brain activity in right lateral orbitofrontal cortex). This study reveals a complex pattern of conjoint and dissociated structural and functional abnormalities, supporting the involvement of basal ganglia-thalamocortical circuits, representing emotional, cognitive and psychomotor abnormalities, in the pathophysiology of early-stage MDD. Specifically, this study adds to Psychoradiology, an emerging subspecialty of radiology, which seems primed to play a major clinical role in guiding diagnostic and treatment planning decisions in patients with mental disorder.
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Dukart J, Smieskova R, Harrisberger F, Lenz C, Schmidt A, Walter A, Huber C, Riecher-Rössler A, Simon A, Lang UE, Fusar-Poli P, Borgwardt S. Age-related brain structural alterations as an intermediate phenotype of psychosis. J Psychiatry Neurosci 2017; 42:307-319. [PMID: 28459416 PMCID: PMC5573573 DOI: 10.1503/jpn.160179] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND There is only limited agreement with respect to location, directionality and functional implications of brain structural alterations observed in patients with schizophrenia. Additionally, their link to occurrence of psychotic symptoms remains unclear. A viable way of addressing these questions is to examine populations in an at-risk mental state (ARMS) before the transition to psychosis. METHODS We tested for structural brain alterations in individuals in an ARMS compared with healthy controls and patients with first-episode psychosis (FEP) using voxel-based morphometry and measures of cortical thickness. Furthermore, we evaluated if these alterations were modified by age and whether they were linked to the observed clinical symptoms. RESULTS Our sample included 59 individuals with ARMS, 26 healthy controls and 59 patients with FEP. We found increased grey matter volume and cortical thickness in individuals with ARMS and a similar pattern of structural alterations in patients with FEP. We further found stronger age-related reductions in grey matter volume and cortical thickness in both patients with FEP and individuals with ARMS, linking these alterations to observed clinical symptoms. LIMITATIONS The ARMS group comprised subgroups with heterogeneous levels of psychosis risk and medication status. Furthermore, the cross-sectional nature of our study and the reduced number of older patients limit conclusions with respect to observed interactions with age. CONCLUSION Our findings on consistent structural alterations in individuals with ARMS and patients with FEP and their link to clinical symptoms have major implications for understanding their time of occurrence and relevance to psychotic symptoms. Interactions with age found for these alterations may explain the heterogeneity of findings reported in the literature.
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Affiliation(s)
- Juergen Dukart
- Correspondence to: J. Dukart, Biomarkers & Clinical Imaging, NORD DTA, F. Hoffmann-La Roche, Grenzacherstrasse 170, 4070 Basel, Switzerland;
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Zarogianni E, Storkey AJ, Johnstone EC, Owens DGC, Lawrie SM. Improved individualized prediction of schizophrenia in subjects at familial high risk, based on neuroanatomical data, schizotypal and neurocognitive features. Schizophr Res 2017; 181:6-12. [PMID: 27613509 DOI: 10.1016/j.schres.2016.08.027] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 08/29/2016] [Accepted: 08/29/2016] [Indexed: 01/11/2023]
Abstract
To date, there are no reliable markers for predicting onset of schizophrenia in individuals at high risk (HR). Substantial promise is, however, shown by a variety of pattern classification approaches to neuroimaging data. Here, we examined the predictive accuracy of support vector machine (SVM) in later diagnosing schizophrenia, at a single-subject level, using a cohort of HR individuals drawn from multiply affected families and a combination of neuroanatomical, schizotypal and neurocognitive variables. Baseline structural magnetic resonance imaging (MRI), schizotypal and neurocognitive data from 17 HR subjects, who subsequently developed schizophrenia and a matched group of 17 HR subjects who did not make the transition, yet had psychotic symptoms, were included in the analysis. We employed recursive feature elimination (RFE), in a nested cross-validation scheme to identify the most significant predictors of disease transition and enhance diagnostic performance. Classification accuracy was 94% when a self-completed measure of schizotypy, a declarative memory test and structural MRI data were combined into a single learning algorithm; higher than when either quantitative measure was used alone. The discriminative neuroanatomical pattern involved gray matter volume differences in frontal, orbito-frontal and occipital lobe regions bilaterally as well as parts of the superior, medial temporal lobe and cerebellar regions. Our findings suggest that an early SVM-based prediction of schizophrenia is possible and can be improved by combining schizotypal and neurocognitive features with neuroanatomical variables. However, our predictive model needs to be tested by classifying a new, independent HR cohort in order to estimate its validity.
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Affiliation(s)
- Eleni Zarogianni
- Division of Psychiatry, School of Clinical Sciences, University of Edinburgh, The Royal Edinburgh Hospital, Morningside Park, UK.
| | - Amos J Storkey
- Institute for Adaptive and Neural Computation, University of Edinburgh, UK
| | - Eve C Johnstone
- Division of Psychiatry, School of Clinical Sciences, University of Edinburgh, The Royal Edinburgh Hospital, Morningside Park, UK
| | - David G C Owens
- Division of Psychiatry, School of Clinical Sciences, University of Edinburgh, The Royal Edinburgh Hospital, Morningside Park, UK
| | - Stephen M Lawrie
- Division of Psychiatry, School of Clinical Sciences, University of Edinburgh, The Royal Edinburgh Hospital, Morningside Park, UK
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Li W, Chen Z, Wu M, Zhu H, Gu L, Zhao Y, Kuang W, Bi F, Kemp GJ, Gong Q. Characterization of brain blood flow and the amplitude of low-frequency fluctuations in major depressive disorder: A multimodal meta-analysis. J Affect Disord 2017; 210:303-311. [PMID: 28068619 DOI: 10.1016/j.jad.2016.12.032] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2016] [Accepted: 12/22/2016] [Indexed: 11/30/2022]
Abstract
BACKGROUND In healthy subjects, there is an association between amplitude of low-frequency fluctuations (ALFF) and regional cerebral blood flow (rCBF). To date, no published meta-analysis has investigated changes in the regional ALFF in medication-free depressed patients. METHODS In this study, we aimed to explore whether resting-state rCBF and ALFF changes co-occur in the depressed brain without the potential confound of medication. Using signed differential mapping (SDM), we conducted two meta-analyses, one of rCBF studies and one of ALFF studies, involving medication-free patients with major depressive disorder (MDD). In addition, we conducted a multimodal meta-analysis to identify brain regions that showed abnormalities in both rCBF and ALFF. RESULTS A total of 16 studies were included in this series. We identified abnormalities in resting-state rCBF and ALFF in the left insula in medication-free MDD patients compared with healthy controls (HC). In addition, we observed altered resting-state rCBF in the limbic-subcortical-cortical circuit and altered ALFF in the default mode network (DMN) and some motor-related brain regions. LIMITATIONS The analysis techniques, patient characteristics and clinical variables of the included studies were heterogeneous. CONCLUSIONS The conjoint alterations in ALFF and rCBF in the left insula may represent core neuropathological changes in medication-free patients with MDD and merit further studying.
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Affiliation(s)
- Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Ziqi Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Min Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Hongyan Zhu
- Laboratory of Stem Cell Biology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
| | - Lei Gu
- Laboratory of Stem Cell Biology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Feng Bi
- Department of Oncology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Graham J Kemp
- Magnetic Resonance and Image Analysis Research Centre and Institute of Ageing and Chronic Disease, University of Liverpool, United Kingdom
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China
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48
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Pergola G, Trizio S, Di Carlo P, Taurisano P, Mancini M, Amoroso N, Nettis MA, Andriola I, Caforio G, Popolizio T, Rampino A, Di Giorgio A, Bertolino A, Blasi G. Grey matter volume patterns in thalamic nuclei are associated with familial risk for schizophrenia. Schizophr Res 2017; 180:13-20. [PMID: 27449252 DOI: 10.1016/j.schres.2016.07.005] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Revised: 07/05/2016] [Accepted: 07/07/2016] [Indexed: 12/19/2022]
Abstract
Previous evidence suggests reduced thalamic grey matter volume (GMV) in patients with schizophrenia (SCZ). However, it is not considered an intermediate phenotype for schizophrenia, possibly because previous studies did not assess the contribution of individual thalamic nuclei and employed univariate statistics. Here, we hypothesized that multivariate statistics would reveal an association of GMV in different thalamic nuclei with familial risk for schizophrenia. We also hypothesized that accounting for the heterogeneity of thalamic GMV in healthy controls would improve the detection of subjects at familial risk for the disorder. We acquired MRI scans for 96 clinically stable SCZ, 55 non-affected siblings of patients with schizophrenia (SIB), and 249 HC. The thalamus was parceled into seven regions of interest (ROIs). After a canonical univariate analysis, we used GMV estimates of thalamic ROIs, together with total thalamic GMV and premorbid intelligence, as features in Random Forests to classify HC, SIB, and SCZ. Then, we computed a Misclassification Index for each individual and tested the improvement in SIB detection after excluding a subsample of HC misclassified as patients. Random Forests discriminated SCZ from HC (accuracy=81%) and SIB from HC (accuracy=75%). Left anteromedial thalamic volumes were significantly associated with both multivariate classifications (p<0.05). Excluding HC misclassified as SCZ improved greatly HC vs. SIB classification (Cohen's d=1.39). These findings suggest that multivariate statistics identify a familial background associated with thalamic GMV reduction in SCZ. They also suggest the relevance of inter-individual variability of GMV patterns for the discrimination of individuals at familial risk for the disorder.
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Affiliation(s)
- Giulio Pergola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Silvestro Trizio
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Pasquale Di Carlo
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Paolo Taurisano
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Marina Mancini
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Nicola Amoroso
- National Institute of Nuclear of Physics-Branch of Bari, Via E. Orabona 4, 70125 Bari, Italy; Interuniversity Department of Physics 'M. Merlin', University of Bari 'Aldo Moro', Via E. Orabona 4, 70125 Bari, Italy
| | - Maria Antonietta Nettis
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Ileana Andriola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy
| | - Grazia Caforio
- Psychiatry Unit, Bari University Hospital, Piazza Giulio Cesare 11, 70124, Bari, Italy
| | - Teresa Popolizio
- IRCCS "Casa Sollievo della Sofferenza", Viale Cappuccini, 1, I-71013 San Giovanni Rotondo, Italy
| | - Antonio Rampino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit, Bari University Hospital, Piazza Giulio Cesare 11, 70124, Bari, Italy
| | - Annabella Di Giorgio
- IRCCS "Casa Sollievo della Sofferenza", Viale Cappuccini, 1, I-71013 San Giovanni Rotondo, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari 'Aldo Moro', Piazza Giulio Cesare 11, 70124 Bari, Italy; Psychiatry Unit, Bari University Hospital, Piazza Giulio Cesare 11, 70124, Bari, Italy
| | - Giuseppe Blasi
- Psychiatry Unit, Bari University Hospital, Piazza Giulio Cesare 11, 70124, Bari, Italy; IRCCS "Casa Sollievo della Sofferenza", Viale Cappuccini, 1, I-71013 San Giovanni Rotondo, Italy.
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49
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Takano Y, Aoki Y, Yahata N, Kawakubo Y, Inoue H, Iwashiro N, Natsubori T, Koike S, Gonoi W, Sasaki H, Takao H, Kasai K, Yamasue H. Neural basis for inferring false beliefs and social emotions in others among individuals with schizophrenia and those at ultra-high risk for psychosis. Psychiatry Res Neuroimaging 2017; 259:34-41. [PMID: 27960147 DOI: 10.1016/j.pscychresns.2016.11.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 11/12/2016] [Accepted: 11/20/2016] [Indexed: 01/14/2023]
Abstract
Inferring beliefs and social emotions of others has different neural substrates and possibly different roles in the pathophysiology of different clinical phases of schizophrenia. The current study investigated the neural basis for inferring others' beliefs and social emotions, as individual concepts, in 17 subjects at ultra-high risk for psychosis (UHR), 16 patients with schizophrenia and 20 healthy controls. Brain activity significantly differed from normal in both the left superior temporal sulcus (STS) and the inferior frontal gyrus (IFG) in the schizophrenia group while inferring others' beliefs, whereas those of UHR group were in the middle of those in the schizophrenia and healthy-control groups. Brain activity during inferring others' social emotions significantly differed in both the left STS and right IFG among individuals at UHR; however, there was no significant difference in the schizophrenia group. In contrast, brain activity differed in the left IFG of those in both the schizophrenia and UHR groups while inferring social emotion. Regarding the difference in direction of the abnormality, both the UHR and schizophrenia groups were characterized by hyper-STS and hypo-IFG activations when inferring others' beliefs and emotions. These findings might reflect different aspects of the same pathophysiological process at different clinical phases of psychosis.
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Affiliation(s)
- Yosuke Takano
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Yuta Aoki
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan; The Child Study Center at NYU Langone Medical Center, One Park Avenue, New York, NY 10016, USA
| | - Noriaki Yahata
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Yuki Kawakubo
- Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hideyuki Inoue
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Norichika Iwashiro
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Tatsunobu Natsubori
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Shinsuke Koike
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Wataru Gonoi
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hiroki Sasaki
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hidemasa Takao
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hidenori Yamasue
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan; Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashiku, Hamamatsu City 431-3192, Japan.
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50
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Szendi I, Szabó N, Domján N, Kincses ZT, Palkó A, Vécsei L, Racsmány M. A New Division of Schizophrenia Revealed Expanded Bilateral Brain Structural Abnormalities of the Association Cortices. Front Psychiatry 2017; 8:127. [PMID: 28775696 PMCID: PMC5517392 DOI: 10.3389/fpsyt.2017.00127] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2016] [Accepted: 06/30/2017] [Indexed: 11/18/2022] Open
Abstract
The phenomenological and, consequently, pathophysiological heterogeneity of schizophrenia may be substantially decreased by determining etiologically valid subgroups. In a cross-sectional study, we analyzed the brain structural impairments of outpatients with schizophrenia using concurrent subgrouping methods, partly to enhance the extensity of exploration, and partly to estimate the validation of the divisions. High resolution T1-weighted MR images were obtained for 21 patients and 13 healthy controls. Localized gray matter volumetric deficits were defined with optimized voxel-based morphometry. Employing two concurrent methods (i.e., the widely known deficit-non-deficit division vs. the neurocognitive clusters we identified earlier) the patient group was iteratively divided into two subgroups, and their volumetric peculiarities were compared with one another and with healthy controls. Our division revealed more significant differences demonstrating bilateral brain structural deficits, which affected the association cortices, primarily the heteromodal fields and partly the unimodal fields. This is the first study that showed that abnormalities of the association cortices can be bihemispherial and expanded in schizophrenia, even in the cases of outpatients living integrated in society. Our result suggests that the extended association cortex abnormalities could constitute substantial and determining neurological substrates in the phenomenology and aetiopathogenesis of schizophrenia, at least in a subgroup of patients with more unfavorable neurocognitive characteristics.
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Affiliation(s)
- István Szendi
- Department of Psychiatry, University of Szeged, Szeged, Hungary
| | - Nikoletta Szabó
- Department of Neurology, University of Szeged, Szeged, Hungary
| | - Nóra Domján
- Department of Psychiatry, University of Szeged, Szeged, Hungary
| | | | - András Palkó
- Department of Radiology, University of Szeged, Szeged, Hungary
| | - László Vécsei
- Department of Neurology, University of Szeged, Szeged, Hungary.,Neuroscience Research Group, Hungarian Academy of Sciences, University of Szeged, Szeged, Hungary
| | - Mihály Racsmány
- Research Group on Frontostriatal Disorders, Hungarian Academy of Sciences, Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
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