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Yu T, Pei WZ, Xu CY, Deng CC, Zhang XL. Identification of male schizophrenia patients using brain morphology based on machine learning algorithms. World J Psychiatry 2024; 14:804-811. [PMID: 38984327 PMCID: PMC11230103 DOI: 10.5498/wjp.v14.i6.804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/01/2024] [Accepted: 05/21/2024] [Indexed: 06/19/2024] Open
Abstract
BACKGROUND Schizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task. AIM To employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls. METHODS The least absolute shrinkage and selection operator and t tests were applied to select important features from structural magnetic resonance images as input features for classification. Four commonly used machine learning algorithms, the general linear model, random forest (RF), k-nearest neighbors, and support vector machine algorithms, were used to develop the classification models. The performance of the classification models was evaluated according to the area under the receiver operating characteristic curve (AUC). RESULTS A total of 8 important features with significant differences between groups were considered as input features for the establishment of classification models based on the four machine learning algorithms. Compared to other machine learning algorithms, RF yielded better performance in the discrimination of male schizophrenic individuals from healthy controls, with an AUC of 0.886. CONCLUSION Our research suggests that brain morphological features can be used to improve the early diagnosis of schizophrenia in male patients.
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Affiliation(s)
- Tao Yu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Wen-Zhi Pei
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chun-Yuan Xu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chen-Chen Deng
- Department of Gynaecology, Anhui Maternal and Child Health Hospital, Hefei 230032, Anhui Province, China
| | - Xu-Lai Zhang
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
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Hudgins SN, Curtin A, Tracy J, Ayaz H. Impaired Cortico-Thalamo-Cerebellar Integration Across Schizophrenia, Bipolar II, and Attention Deficit Hyperactivity Disorder Patients Suggests Potential Neural Signatures for Psychiatric Illness. RESEARCH SQUARE 2024:rs.3.rs-4145883. [PMID: 38586053 PMCID: PMC10996788 DOI: 10.21203/rs.3.rs-4145883/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Understanding aberrant functional changes between brain regions has shown promise for characterizing and differentiating the symptoms associated with progressive psychiatric disorders. The functional integration between the thalamus and cerebellum significantly influences learning and memory in cognition. Observed in schizophrenic patients, dysfunction within the corticalthalamocerebellar (CTC) circuitry is linked to challenges in prioritizing, processing, coordinating, and responding to information. This study explored whether abnormal CTC functional network connectivity patterns are present across schizophrenia (SCHZ) patients, bipolar II disorder (BIPOL) patients, and ADHD patients by examining both task- and task-free conditions compared to healthy volunteers (HC). Leveraging fMRI data from 135 participants (39 HC, 27 SCHZ patients, 38 BIPOL patients, and 31 ADHD patients), we analyzed functional network connectivity (FNC) patterns across 115 cortical, thalamic, subcortical, and cerebellar regions of interest (ROIs). Guiding our investigation: First, do the brain regions of the CTC circuit exhibit distinct abnormal patterns at rest in SCHZ, ADHD, and BIPOL? Second, do working memory tasks in these patients engage common regions of the circuit in similar or unique patterns? Consistent with previous findings, our observations revealed FNC patterns constrained in the cerebellar, thalamic, striatal, hippocampal, medial prefrontal and insular cortices across all three psychiatric cohorts when compared to controls in both task and task-free conditions. Post hoc analysis suggested a predominance in schizophrenia and ADHD patients during rest, while the task condition demonstrated effects across all three disorders. Factor-by-covariance GLM MANOVA further specified regions associated with clinical symptoms and trait assessments. Our study provides evidence suggesting that dysfunctional CTC circuitry in both task-free and task-free conditions may be an important broader neural signature of psychiatric illness.
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Zhan L, Gao Y, Huang L, Zhang H, Huang G, Wang Y, Sun J, Xie Z, Li M, Jia X, Cheng L, Yu Y. Brain functional connectivity alterations of Wernicke's area in individuals with autism spectrum conditions in multi-frequency bands: A mega-analysis. Heliyon 2024; 10:e26198. [PMID: 38404781 PMCID: PMC10884452 DOI: 10.1016/j.heliyon.2024.e26198] [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: 08/06/2023] [Revised: 02/05/2024] [Accepted: 02/08/2024] [Indexed: 02/27/2024] Open
Abstract
Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01-0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01-0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.
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Affiliation(s)
- Linlin Zhan
- School of Western Studies, Heilongjiang University, Harbin, China
| | - Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Lina Huang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Hongqiang Zhang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Guofeng Huang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yadan Wang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Lulu Cheng
- School of Foreign Studies, China University of Petroleum (East China), Qingdao, China
- Shanghai Center for Research in English Language Education, Shanghai International Studies University, Shanghai, China
| | - Yang Yu
- Psychiatry Department, The Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang, Hangzhou, China
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4
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Worker A, Berthert P, Lawrence AJ, Kia SM, Arango C, Dinga R, Galderisi S, Glenthøj B, Kahn RS, Leslie A, Murray RM, Pariante CM, Pantelis C, Weiser M, Winter-van Rossum I, McGuire P, Dazzan P, Marquand AF. Extreme deviations from the normative model reveal cortical heterogeneity and associations with negative symptom severity in first-episode psychosis from the OPTiMiSE and GAP studies. Transl Psychiatry 2023; 13:373. [PMID: 38042835 PMCID: PMC10693627 DOI: 10.1038/s41398-023-02661-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/03/2023] [Accepted: 11/09/2023] [Indexed: 12/04/2023] Open
Abstract
There is currently no quantifiable method to predict long-term clinical outcomes in patients presenting with a first episode of psychosis. A major barrier to developing useful markers for this is biological heterogeneity, where many different pathological mechanisms may underly the same set of symptoms in different individuals. Normative modelling has been used to quantify this heterogeneity in established psychotic disorders by identifying regions of the cortex which are thinner than expected based on a normative healthy population range. These brain atypicalities are measured at the individual level and therefore potentially useful in a clinical setting. However, it is still unclear whether alterations in individual brain structure can be detected at the time of the first psychotic episode, and whether they are associated with subsequent clinical outcomes. We applied normative modelling of cortical thickness to a sample of first-episode psychosis patients, with the aim of quantifying heterogeneity and to use any pattern of cortical atypicality to predict symptoms and response to antipsychotic medication at timepoints from baseline up to 95 weeks (median follow-ups = 4). T1-weighted brain magnetic resonance images from the GAP and OPTiMiSE samples were processed with Freesurfer V6.0.0 yielding 148 cortical thickness features. An existing normative model of cortical thickness (n = 37,126) was adapted to integrate data from each clinical site and account for effects of gender and site. Our test sample consisted of control participants (n = 149, mean age = 26, SD = 6.7) and patient data (n = 295, mean age = 26, SD = 6.7), this sample was used for estimating deviations from the normative model and subsequent statistical analysis. For each individual, the 148 cortical thickness features were mapped to centiles of the normative distribution and converted to z-scores reflecting the distance from the population mean. Individual cortical thickness metrics of +/- 2.6 standard deviations from the mean were considered extreme deviations from the norm. We found that no more than 6.4% of psychosis patients had extreme deviations in a single brain region (regional overlap) demonstrating a high degree of heterogeneity. Mann-Whitney U tests were run on z-scores for each region and significantly lower z-scores were observed in FEP patients in the frontal, temporal, parietal and occipital lobes. Finally, linear mixed-effects modelling showed that negative deviations in cortical thickness in parietal and temporal regions at baseline are related to more severe negative symptoms over the medium-term. This study shows that even at the early stage of symptom onset normative modelling provides a framework to identify individualised cortical markers which can be used for early personalised intervention and stratification.
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Affiliation(s)
- Amanda Worker
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Pierre Berthert
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT), University of Oslo, and Oslo University Hospital, Oslo, Norway
| | - Andrew J Lawrence
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Seyed Mostafa Kia
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, the Netherlands
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañon, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense Madrid, Madrid, Spain
| | - Richard Dinga
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Birte Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) and Center for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Center, Glostrup, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anoushka Leslie
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Carmine M Pariante
- National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust and King's College London, London, UK
- Biological Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Mark Weiser
- Department of Psychiatry, Sheba Medical Center, Tel Hashomer, Tel Aviv, 52621, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Inge Winter-van Rossum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust and King's College London, London, UK
| | - Andre F Marquand
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands.
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands.
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5
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Chopra S, Segal A, Oldham S, Holmes A, Sabaroedin K, Orchard ER, Francey SM, O’Donoghue B, Cropley V, Nelson B, Graham J, Baldwin L, Tiego J, Yuen HP, Allott K, Alvarez-Jimenez M, Harrigan S, Fulcher BD, Aquino K, Pantelis C, Wood SJ, Bellgrove M, McGorry PD, Fornito A. Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis. JAMA Psychiatry 2023; 80:1246-1257. [PMID: 37728918 PMCID: PMC10512169 DOI: 10.1001/jamapsychiatry.2023.3293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 06/21/2023] [Indexed: 09/22/2023]
Abstract
Importance Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. Objective To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. Design, Settings, and Participants This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Main Outcomes and Measures Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Results Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. Conclusion and Relevance These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.
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Affiliation(s)
- Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Ashlea Segal
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Kristina Sabaroedin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Department of Radiology, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Hotchkiss Brain Institute and Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Edwina R. Orchard
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
- Child Study Centre, Yale University, New Haven, Connecticut
| | - Shona M. Francey
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lara Baldwin
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Susy Harrigan
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Mental Health, Melbourne School of Global and Population Health, The University of Melbourne, Parkville, Victoria, Australian
| | - Ben D. Fulcher
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Kevin Aquino
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Centre for Complex Systems, University of Sydney, Sydney, New South Wales, Australia
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton, Victoria, Australia
- NorthWestern Mental Health, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Western Health Sunshine Hospital, St Albans, Victoria, Australia
| | - Stephen J. Wood
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- School of Psychology, University of Birmingham, Edgbaston, United Kingdom
| | - Mark Bellgrove
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
| | - Patrick D. McGorry
- Orygen, Parkville, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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6
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Merritt K, Luque Laguna P, Sethi A, Drakesmith M, Ashley SA, Bloomfield M, Fonville L, Perry G, Lancaster T, Dimitriadis SI, Zammit S, Evans CJ, Lewis G, Kempton MJ, Linden DEJ, Reichenberg A, Jones DK, David AS. The impact of cumulative obstetric complications and childhood trauma on brain volume in young people with psychotic experiences. Mol Psychiatry 2023; 28:3688-3697. [PMID: 37903876 PMCID: PMC10730393 DOI: 10.1038/s41380-023-02295-6] [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: 01/04/2023] [Revised: 09/28/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023]
Abstract
Psychotic experiences (PEs) occur in 5-10% of the general population and are associated with exposure to childhood trauma and obstetric complications. However, the neurobiological mechanisms underlying these associations are unclear. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we studied 138 young people aged 20 with PEs (n = 49 suspected, n = 53 definite, n = 36 psychotic disorder) and 275 controls. Voxel-based morphometry assessed whether MRI measures of grey matter volume were associated with (i) PEs, (ii) cumulative childhood psychological trauma (weighted summary score of 6 trauma types), (iii) cumulative pre/peri-natal risk factors for psychosis (weighted summary score of 16 risk factors), and (iv) the interaction between PEs and cumulative trauma or pre/peri-natal risk. PEs were associated with smaller left posterior cingulate (pFWE < 0.001, Z = 4.19) and thalamus volumes (pFWE = 0.006, Z = 3.91). Cumulative pre/perinatal risk was associated with smaller left subgenual cingulate volume (pFWE < 0.001, Z = 4.54). A significant interaction between PEs and cumulative pre/perinatal risk found larger striatum (pFWE = 0.04, Z = 3.89) and smaller right insula volume extending into the supramarginal gyrus and superior temporal gyrus (pFWE = 0.002, Z = 4.79), specifically in those with definite PEs and psychotic disorder. Cumulative childhood trauma was associated with larger left dorsal striatum (pFWE = 0.002, Z = 3.65), right prefrontal cortex (pFWE < 0.001, Z = 4.63) and smaller left insula volume in all participants (pFWE = 0.03, Z = 3.60), and there was no interaction with PEs group. In summary, pre/peri-natal risk factors and childhood psychological trauma impact similar brain pathways, namely smaller insula and larger striatum volumes. The effect of pre/perinatal risk was greatest in those with more severe PEs, whereas effects of trauma were seen in all participants. In conclusion, environmental risk factors affect brain networks implicated in schizophrenia, which may increase an individual's propensity to develop later psychotic disorders.
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Affiliation(s)
- Kate Merritt
- Division of Psychiatry, Institute of Mental Health, University College London, London, UK.
| | - Pedro Luque Laguna
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Arjun Sethi
- Department of Forensic & Neurodevelopmental Sciences, IOPPN, King's College London, London, UK
| | - Mark Drakesmith
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Sarah A Ashley
- Division of Psychiatry, Institute of Mental Health, University College London, London, UK
| | - Michael Bloomfield
- Division of Psychiatry, Institute of Mental Health, University College London, London, UK
| | | | - Gavin Perry
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Tom Lancaster
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
- Department of Psychology, Bath University, Bath, UK
| | - Stavros I Dimitriadis
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
- Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Barcelona, Passeig de la Vall d'Hebron, 171, 08035, Barcelona, Spain
| | - Stanley Zammit
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
- Bristol Medical School (PHS), University of Bristol, Bristol, UK
| | - C John Evans
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Glyn Lewis
- Division of Psychiatry, Institute of Mental Health, University College London, London, UK
| | - Matthew J Kempton
- Psychosis Studies Department, IOPPN, King's College London, London, UK
| | - David E J Linden
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Derek K Jones
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, UK
| | - Anthony S David
- Division of Psychiatry, Institute of Mental Health, University College London, London, UK
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7
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Scarpazza C, Costa C, Battaglia U, Berryessa C, Bianchetti ML, Caggiu I, Devinsky O, Ferracuti S, Focquaert F, Forgione A, Gilbert F, Pennati A, Pietrini P, Rainero I, Sartori G, Swerdlow R, Camperio Ciani AS. Acquired Pedophilia: international Delphi-method-based consensus guidelines. Transl Psychiatry 2023; 13:11. [PMID: 36653356 PMCID: PMC9849353 DOI: 10.1038/s41398-023-02314-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 12/22/2022] [Accepted: 01/09/2023] [Indexed: 01/19/2023] Open
Abstract
Idiopathic and acquired pedophilia are two different disorders with two different etiologies. However, the differential diagnosis is still very difficult, as the behavioral indicators used to discriminate the two forms of pedophilia are underexplored, and clinicians are still devoid of clear guidelines describing the clinical and neuroscientific investigations suggested to help them with this difficult task. Furthermore, the consequences of misdiagnosis are not known, and a consensus regarding the legal consequences for the two kinds of offenders is still lacking. The present study used the Delphi method to reach a global consensus on the following six topics: behavioral indicators/red flags helpful for differential diagnosis; neurological conditions potentially leading to acquired pedophilia; neuroscientific investigations important for a correct understanding of the case; consequences of misdiagnosis; legal consequences; and issues and future perspectives. An international and multidisciplinary board of scientists and clinicians took part in the consensus statements as Delphi members. The Delphi panel comprised 52 raters with interdisciplinary competencies, including neurologists, psychiatrists, neuropsychologists, forensic psychologists, expert in ethics, etc. The final recommendations consisted of 63 statements covering the six different topics. The current study is the first expert consensus on a delicate topic such as pedophilia. Important exploitable consensual recommendations that can ultimately be of immediate use by clinicians to help with differential diagnosis and plan and guide therapeutic interventions are described, as well as future perspectives for researchers.
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Affiliation(s)
- Cristina Scarpazza
- Department of General Psychology, University of Padova, Padova, Italy. .,Padova Neuroscience Center (PNC), University of Padova, Padova, Italy. .,IRCCS S. Camillo Hospital, Venezia, Italy.
| | - Cristiano Costa
- grid.5608.b0000 0004 1757 3470Padova Neuroscience Center (PNC), University of Padova, Padova, Italy ,grid.5608.b0000 0004 1757 3470Department of Neuroscience, University of Padova, Padova, Italy
| | - Umberto Battaglia
- grid.5608.b0000 0004 1757 3470Department of Applied Psychology, FISPPA – University of Padova, Padova, Italy
| | - Colleen Berryessa
- grid.430387.b0000 0004 1936 8796School of Criminal Justice, Rutgers University, Newark, NJ USA
| | - Maria Lucia Bianchetti
- grid.5608.b0000 0004 1757 3470Department of General Psychology, University of Padova, Padova, Italy
| | - Ilenia Caggiu
- grid.5608.b0000 0004 1757 3470Department of General Psychology, University of Padova, Padova, Italy
| | - Orrin Devinsky
- grid.137628.90000 0004 1936 8753Epilepsy Center, NYU School of Medicine, New York, USA
| | - Stefano Ferracuti
- grid.7841.aDepartment of Human Neurosciences Sapienza Università di Roma, Rome, Italy
| | - Farah Focquaert
- grid.5342.00000 0001 2069 7798Bioethics Institute Ghent, Department of Philosophy and Moral Sciences, Ghent University, Ghent, Belgium
| | - Arianna Forgione
- grid.5608.b0000 0004 1757 3470Department of General Psychology, University of Padova, Padova, Italy
| | - Fredric Gilbert
- grid.1009.80000 0004 1936 826XEthics, Policy & Public Engagement (EPPE) ARC Centre of Excellence for Electromaterials Science (ACES), Faculty of Arts, University of Tasmania, Hobart, Australia
| | | | - Pietro Pietrini
- grid.462365.00000 0004 1790 9464IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Innocenzo Rainero
- grid.7605.40000 0001 2336 6580Neurology I, Department of Neuroscience “Rita Levi Montalcini”, University of Torino, Turin, Italy
| | - Giuseppe Sartori
- grid.5608.b0000 0004 1757 3470Department of General Psychology, University of Padova, Padova, Italy
| | - Russell Swerdlow
- grid.412016.00000 0001 2177 6375University of Kansas Medical Center, Kansas City, KS USA
| | - Andrea S. Camperio Ciani
- grid.5608.b0000 0004 1757 3470Department of Applied Psychology, FISPPA – University of Padova, Padova, Italy
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8
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Cheng L, Zhan L, Huang L, Zhang H, Sun J, Huang G, Wang Y, Li M, Li H, Gao Y, Jia X. The atypical functional connectivity of Broca's area at multiple frequency bands in autism spectrum disorder. Brain Imaging Behav 2022; 16:2627-2636. [PMID: 36163448 DOI: 10.1007/s11682-022-00718-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2022] [Indexed: 11/30/2022]
Abstract
As a developmental disorder, autism spectrum disorder (ASD) has drawn much attention due to its severe impacts on one's language capacity. Broca's area, an important brain region of the language network, is largely involved in language-related functions. Using the Autism Brain Image Data Exchange (ABIDE) dataset, a mega-analysis was performed involving a total of 1454 participants (including 618 individuals with ASD and 836 healthy controls (HCs). To detect the neural pathophysiological mechanism of ASD from the perspective of language, we conducted a functional connectivity (FC) analysis with Broca's area as the seed in multiple frequency bands (conventional: 0.01-0.08 Hz; slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz). We found that compared with HC, ASD patients demonstrated increased FC in the left thalamus, left precuneus, left anterior cingulate and paracingulate gyri, and left medial orbital of the superior frontal gyrus in the conventional frequency band (0.01-0.08 Hz). The results of the slow-5 frequency band (0.01-0.027 Hz) presented increased FC values of the left precuneus, left medial orbital of the superior frontal gyrus, right medial orbital of the superior frontal gyrus and right thalamus. No significant cluster was detected in the slow-4 frequency band (0.027-0.073 Hz). In conclusion, the abnormal functional connectivity in patients with ASD has frequency-specific properties. Furthermore, the slow-5 frequency band (0.01-0.027 Hz) mainly contributed to the findings of the conventional frequency band (0.01-0.08 Hz). The current study might shed new light on the neural pathophysiological mechanism of language impairments in people with ASD.
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Affiliation(s)
- Lulu Cheng
- School of Foreign Studies, China University of Petroleum (East China), Qingdao, 266580, China.,Shanghai Center for Research in English Language Education, Shanghai International Studies University, Shanghai, China
| | - Linlin Zhan
- Faculty of Western Languages, Heilongjiang University, Harbin, China
| | - Lina Huang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Hongqiang Zhang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Guofeng Huang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yadan Wang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China
| | - Huayun Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China.,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China
| | - Yanyan Gao
- School of Teacher Education, Zhejiang Normal University, Jinhua, China. .,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China.
| | - Xize Jia
- School of Teacher Education, Zhejiang Normal University, Jinhua, China. .,Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, 321004, China.
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9
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Can we predict who will benefit from cognitive-behavioural therapy? A systematic review and meta-analysis of machine learning studies. Clin Psychol Rev 2022; 97:102193. [DOI: 10.1016/j.cpr.2022.102193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 06/29/2022] [Accepted: 08/04/2022] [Indexed: 11/23/2022]
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10
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Iftimovici A, Chaumette B, Duchesnay E, Krebs MO. Brain anomalies in early psychosis: From secondary to primary psychosis. Neurosci Biobehav Rev 2022; 138:104716. [PMID: 35661683 DOI: 10.1016/j.neubiorev.2022.104716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 03/12/2022] [Accepted: 05/25/2022] [Indexed: 10/18/2022]
Abstract
Brain anomalies are frequently found in early psychoses. Although they may remain undetected for many years, their interpretation is critical for differential diagnosis. In secondary psychoses, their identification may allow specific management. They may also shed light on various pathophysiological aspects of primary psychoses. Here we reviewed cases of secondary psychoses associated with brain anomalies, reported over a 20-year period in adolescents and young adults aged 13-30 years old. We considered age at first psychotic symptoms, relevant medical history, the nature of psychiatric symptoms, clinical red flags, the nature of the brain anomaly reported, and the underlying disease. We discuss the relevance of each brain area in light of normal brain function, recent case-control studies, and postulated pathophysiology. We show that anomalies in all regions, whether diffuse, multifocal, or highly localized, may lead to psychosis, without necessarily being associated with non-psychiatric symptoms. This underlines the interest of neuroimaging in the initial workup, and supports the hypothesis of psychosis as a global network dysfunction that involves many different regions.
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Affiliation(s)
- Anton Iftimovici
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; NeuroSpin, Atomic Energy Commission, Gif-sur Yvette, France; GHU Paris Psychiatrie et Neurosciences, Paris, France.
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; GHU Paris Psychiatrie et Neurosciences, Paris, France
| | | | - Marie-Odile Krebs
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; GHU Paris Psychiatrie et Neurosciences, Paris, France
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11
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Lei D, Qin K, Pinaya WHL, Young J, Van Amelsvoort T, Marcelis M, Donohoe G, Mothersill DO, Corvin A, Vieira S, Lui S, Scarpazza C, Arango C, Bullmore E, Gong Q, McGuire P, Mechelli A. Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia. Schizophr Bull 2022; 48:881-892. [PMID: 35569019 PMCID: PMC9212102 DOI: 10.1093/schbul/sbac047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is increasingly understood as a disorder of brain dysconnectivity. Recently, graph-based approaches such as graph convolutional network (GCN) have been leveraged to explore complex pairwise similarities in imaging features among brain regions, which can reveal abstract and complex relationships within brain networks. STUDY DESIGN We used GCN to investigate topological abnormalities of functional brain networks in schizophrenia. Resting-state functional magnetic resonance imaging data were acquired from 505 individuals with schizophrenia and 907 controls across 6 sites. Whole-brain functional connectivity matrix was extracted for each individual. We examined the performance of GCN relative to support vector machine (SVM), extracted the most salient regions contributing to both classification models, investigated the topological profiles of identified salient regions, and explored correlation between nodal topological properties of each salient region and severity of symptom. STUDY RESULTS GCN enabled nominally higher classification accuracy (85.8%) compared with SVM (80.9%). Based on the saliency map, the most discriminative brain regions were located in a distributed network including striatal areas (ie, putamen, pallidum, and caudate) and the amygdala. Significant differences in the nodal efficiency of bilateral putamen and pallidum between patients and controls and its correlations with negative symptoms were detected in post hoc analysis. CONCLUSIONS The present study demonstrates that GCN allows classification of schizophrenia at the individual level with high accuracy, indicating a promising direction for detection of individual patients with schizophrenia. Functional topological deficits of striatal areas may represent a focal neural deficit of negative symptomatology in schizophrenia.
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Affiliation(s)
| | | | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jonathan Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | - Therese Van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- Mental Health Care Institute Eindhoven (GGzE), Eindhoven, The Netherlands
| | - Gary Donohoe
- School of Psychology & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - David O Mothersill
- Psychology Department, School of Business, National College of Ireland, Dublin, Ireland
| | - Aiden Corvin
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of General Psychology, University of Padova, Padova, Italy
- Padova Neuroscience Centre, University of Padova, Padova, Italy
| | - Celso Arango
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañon, School of Medicine, Universidad Complutense Madrid, IiSGM, CIBERSAM, Madrid, Spain
| | - Ed Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Qiyong Gong
- To whom correspondence should be addressed; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No 37 Guo Xue Xiang, Chengdu, 610041, China; tel: 86-18980601593, fax: 028-85423503,
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
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12
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Zhang M, Hong X, Yang F, Fan H, Fan F, Song J, Wang Z, Tan Y, Tan S, Elliot Hong L. Structural brain imaging abnormalities correlate with positive symptom in schizophrenia. Neurosci Lett 2022; 782:136683. [PMID: 35595192 DOI: 10.1016/j.neulet.2022.136683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 03/04/2022] [Accepted: 05/13/2022] [Indexed: 10/18/2022]
Abstract
Accumulating evidence indicates neuroanatomical mechanisms underlying positive symptoms in schizophrenia; however, the exact structural determinants of positive symptoms remain unclear. This study aimed to investigate associations between positive symptoms and structural brain changes, including alterations in grey matter (GM) volume and cortical thickness, in patients with first-episode schizophrenia (FES). This study included 44 patients with FES and 48 healthy controls (HCs). Clinical symptoms of patients were evaluated and individual-level GM volume and cortical thickness were assessed. Patients with FES showed reduced GM volume in the right superior temporal gyrus (STG) and increased cortical thickness in the left inferior segment of the circular sulcus of the insula (S_circular_insula_inf) compared with HCs. Increased thickness of the left S_circular_insula_inf correlated positively with positive symptoms in patients with FES. Exploratory correlation analysis found that increased thickness of the left S_circular_insula_inf correlated positively with conceptual disorganization and excitement symptoms, and the right STG GM volume correlated negatively with hallucinations. This study suggests that GM abnormalities in the STG and altered cortical thickness of the S_circular_insula_inf, which were detected at the early stage of schizophrenia, may underlie positive symptoms in patients with FES.
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Affiliation(s)
- Meng Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Xiang Hong
- Chongqing Three Gorges Central Hospital, Chongqing 404000, China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Hongzhen Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Jiaqi Song
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China.
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21288, USA
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13
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Antonucci LA, Penzel N, Sanfelici R, Pigoni A, Kambeitz-Ilankovic L, Dwyer D, Ruef A, Sen Dong M, Öztürk ÖF, Chisholm K, Haidl T, Rosen M, Ferro A, Pergola G, Andriola I, Blasi G, Ruhrmann S, Schultze-Lutter F, Falkai P, Kambeitz J, Lencer R, Dannlowski U, Upthegrove R, Salokangas RKR, Pantelis C, Meisenzahl E, Wood SJ, Brambilla P, Borgwardt S, Bertolino A, Koutsouleris N. Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression. Br J Psychiatry 2022; 220:1-17. [PMID: 35152923 DOI: 10.1192/bjp.2022.16] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
BACKGROUND Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning. AIMS We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample. METHOD Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD). RESULTS Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD. CONCLUSIONS Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.
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Affiliation(s)
- Linda A Antonucci
- Department of Education Science, Psychology and Communication Science, University of Bari Aldo Moro, Italy; and Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Nora Penzel
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany; and Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Rachele Sanfelici
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany; and Institute for Psychiatry, Max Planck School of Cognition, Germany
| | - Alessandro Pigoni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Italy; and Social and Affective Neuroscience Group, MoMiLab, IMT School for Advanced Studies Lucca, Italy
| | - Lana Kambeitz-Ilankovic
- Department of Education Science, Psychology and Communication Science, University of Bari Aldo Moro, Italy; and Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Dominic Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Mark Sen Dong
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Ömer Faruk Öztürk
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany; and Institute for Psychiatry, International Max Planck Research School for Translational Psychiatry, Germany
| | - Katharine Chisholm
- Institute for Mental Health, University of Birmingham, UK; and Department of Psychology, Aston University, UK
| | - Theresa Haidl
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Marlene Rosen
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Adele Ferro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Italy
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Italy
| | - Ileana Andriola
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Italy
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Heinrich-Heine University Düsseldorf, Germany; Department of Psychology and Mental Health, Faculty of Psychology, Airlangga University, Indonesia; and University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, UK; and Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, UK
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, UK; and Early Intervention Service, Birmingham Women's and Children's NHS Foundation Trust, UK
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Australia
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Heinrich-Heine University Düsseldorf, Germany
| | - Stephen J Wood
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany; Orygen, Australia; Centre for Youth Mental Health, University of Melbourne, Australia; and School of Psychology, University of Birmingham, UK
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Italy; and Department of Pathophysiology and Transplantation, University of Milan, Italy
| | - Stefan Borgwardt
- Institute for Translational Psychiatry, University of Münster, UK; and Department of Psychiatry (Psychiatric University Hospital, University Psychiatric Clinics Basel), University of Basel, Switzerland
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Italy
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Germany
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14
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Kirschner M, Hodzic-Santor B, Antoniades M, Nenadic I, Kircher T, Krug A, Meller T, Grotegerd D, Fornito A, Arnatkeviciute A, Bellgrove MA, Tiego J, Dannlowski U, Koch K, Hülsmann C, Kugel H, Enneking V, Klug M, Leehr EJ, Böhnlein J, Gruber M, Mehler D, DeRosse P, Moyett A, Baune BT, Green M, Quidé Y, Pantelis C, Chan R, Wang Y, Ettinger U, Debbané M, Derome M, Gaser C, Besteher B, Diederen K, Spencer TJ, Fletcher P, Rössler W, Smigielski L, Kumari V, Premkumar P, Park HRP, Wiebels K, Lemmers-Jansen I, Gilleen J, Allen P, Kozhuharova P, Marsman JB, Lebedeva I, Tomyshev A, Mukhorina A, Kaiser S, Fett AK, Sommer I, Schuite-Koops S, Paquola C, Larivière S, Bernhardt B, Dagher A, Grant P, van Erp TGM, Turner JA, Thompson PM, Aleman A, Modinos G. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study. Mol Psychiatry 2022; 27:1167-1176. [PMID: 34707236 PMCID: PMC9054674 DOI: 10.1038/s41380-021-01359-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/02/2021] [Accepted: 10/08/2021] [Indexed: 02/04/2023]
Abstract
Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.
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Affiliation(s)
- Matthias Kirschner
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada ,grid.7400.30000 0004 1937 0650Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Benazir Hodzic-Santor
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Mathilde Antoniades
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Igor Nenadic
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Tilo Kircher
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Axel Krug
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany ,grid.10388.320000 0001 2240 3300Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Tina Meller
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Dominik Grotegerd
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Alex Fornito
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Aurina Arnatkeviciute
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Mark A. Bellgrove
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Jeggan Tiego
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Katharina Koch
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Carina Hülsmann
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Harald Kugel
- grid.5949.10000 0001 2172 9288University Clinic for Radiology, University of Münster, Münster, Germany
| | - Verena Enneking
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Melissa Klug
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth J. Leehr
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Joscha Böhnlein
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - David Mehler
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Pamela DeRosse
- grid.416477.70000 0001 2168 3646Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY USA ,grid.250903.d0000 0000 9566 0634The Feinstein Institutes for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY USA ,grid.512756.20000 0004 0370 4759Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY USA
| | - Ashley Moyett
- grid.416477.70000 0001 2168 3646Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY USA
| | - Bernhard T. Baune
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, VIC Australia
| | - Melissa Green
- grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW Australia ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia (NeuRA), Randwick, NSW Australia
| | - Yann Quidé
- grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW Australia ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia (NeuRA), Randwick, NSW Australia
| | - Christos Pantelis
- grid.1008.90000 0001 2179 088XMelbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, VIC Australia
| | - Raymond Chan
- grid.9227.e0000000119573309Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- grid.9227.e0000000119573309Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Ulrich Ettinger
- grid.10388.320000 0001 2240 3300University of Bonn, Bonn, Germany
| | - Martin Debbané
- grid.8591.50000 0001 2322 4988University of Geneva, Geneva, Switzerland
| | - Melodie Derome
- grid.8591.50000 0001 2322 4988University of Geneva, Geneva, Switzerland
| | - Christian Gaser
- grid.275559.90000 0000 8517 6224Jena University Hospital, Jena, Germany
| | - Bianca Besteher
- grid.275559.90000 0000 8517 6224Jena University Hospital, Jena, Germany
| | - Kelly Diederen
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Tom J. Spencer
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Paul Fletcher
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Wulf Rössler
- grid.412004.30000 0004 0478 9977Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland ,grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité University Medicine, Berlin, Germany ,grid.11899.380000 0004 1937 0722Institute of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Lukasz Smigielski
- grid.412004.30000 0004 0478 9977Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Veena Kumari
- grid.7728.a0000 0001 0724 6933Brunel University London, Uxbridge, UK
| | - Preethi Premkumar
- grid.7728.a0000 0001 0724 6933Brunel University London, Uxbridge, UK
| | - Haeme R. P. Park
- grid.9654.e0000 0004 0372 3343School of Psychology, University of Auckland, Auckland, New Zealand
| | - Kristina Wiebels
- grid.9654.e0000 0004 0372 3343School of Psychology, University of Auckland, Auckland, New Zealand
| | | | - James Gilleen
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK ,grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Paul Allen
- grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Petya Kozhuharova
- grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Jan-Bernard Marsman
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Irina Lebedeva
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Alexander Tomyshev
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Anna Mukhorina
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Stefan Kaiser
- grid.150338.c0000 0001 0721 9812Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - Anne-Kathrin Fett
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK ,grid.28577.3f0000 0004 1936 8497City, University London, London, UK
| | - Iris Sommer
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sanne Schuite-Koops
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Casey Paquola
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Sara Larivière
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Boris Bernhardt
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Alain Dagher
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Phillip Grant
- grid.440934.e0000 0004 0593 1824Fresenius University of Applied Sciences, Frankfurt am Main, Germany
| | - Theo G. M. van Erp
- grid.266093.80000 0001 0668 7243Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA USA ,grid.266093.80000 0001 0668 7243Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA USA
| | - Jessica A. Turner
- grid.256304.60000 0004 1936 7400Imaging Genetics and Neuroinformatics Lab, Georgia State University, Atlanta, GA USA
| | - Paul M. Thompson
- grid.42505.360000 0001 2156 6853Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA USA
| | - André Aleman
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Gemma Modinos
- Department of Psychosis Studies, King's College London, London, UK. .,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
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15
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Scarpazza C, Miolla A, Zampieri I, Melis G, Sartori G, Ferracuti S, Pietrini P. Translational Application of a Neuro-Scientific Multi-Modal Approach Into Forensic Psychiatric Evaluation: Why and How? Front Psychiatry 2021; 12:597918. [PMID: 33613339 PMCID: PMC7892615 DOI: 10.3389/fpsyt.2021.597918] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 01/14/2021] [Indexed: 01/01/2023] Open
Abstract
A prominent body of literature indicates that insanity evaluations, which are intended to provide influential expert reports for judges to reach a decision "beyond any reasonable doubt," suffer from a low inter-rater reliability. This paper reviews the limitations of the classical approach to insanity evaluation and the criticisms to the introduction of neuro-scientific approach in court. Here, we explain why in our opinion these criticisms, that seriously hamper the translational implementation of neuroscience into the forensic setting, do not survive scientific scrutiny. Moreover, we discuss how the neuro-scientific multimodal approach may improve the inter-rater reliability in insanity evaluation. Critically, neuroscience does not aim to introduce a brain-based concept of insanity. Indeed, criteria for responsibility and insanity are and should remain clinical. Rather, following the falsificationist approach and the convergence of evidence principle, the neuro-scientific multimodal approach is being proposed as a way to improve reliability of insanity evaluation and to mitigate the influence of cognitive biases on the formulation of insanity opinions, with the final aim to reduce errors and controversies.
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Affiliation(s)
- Cristina Scarpazza
- Department of General Psychology, University of Padova, Padova, Italy
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Alessio Miolla
- Department of General Psychology, University of Padova, Padova, Italy
| | - Ilaria Zampieri
- Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Giulia Melis
- Department of General Psychology, University of Padova, Padova, Italy
| | - Giuseppe Sartori
- Department of General Psychology, University of Padova, Padova, Italy
| | - Stefano Ferracuti
- Department of Human Neurosciences, “Sapienza” University of Rome, Rome, Italy
| | - Pietro Pietrini
- Molecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca, Italy
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16
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Kirschner M, Schmidt A, Hodzic-Santor B, Burrer A, Manoliu A, Zeighami Y, Yau Y, Abbasi N, Maatz A, Habermeyer B, Abivardi A, Avram M, Brandl F, Sorg C, Homan P, Riecher-Rössler A, Borgwardt S, Seifritz E, Dagher A, Kaiser S. Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum. Schizophr Bull 2020; 47:849-863. [PMID: 33257954 PMCID: PMC8084448 DOI: 10.1093/schbul/sbaa169] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Negative symptoms such as anhedonia and apathy are among the most debilitating manifestations of schizophrenia (SZ). Imaging studies have linked these symptoms to morphometric abnormalities in 2 brain regions implicated in reward and motivation: the orbitofrontal cortex (OFC) and striatum. Higher negative symptoms are generally associated with reduced OFC thickness, while higher apathy specifically maps to reduced striatal volume. However, it remains unclear whether these tissue losses are a consequence of chronic illness and its treatment or an underlying phenotypic trait. Here, we use multicentre magnetic resonance imaging data to investigate orbitofrontal-striatal abnormalities across the SZ spectrum from healthy populations with high schizotypy to unmedicated and medicated first-episode psychosis (FEP), and patients with chronic SZ. Putamen, caudate, accumbens volume, and OFC thickness were estimated from T1-weighted images acquired in all 3 diagnostic groups and controls from 4 sites (n = 337). Results were first established in 1 discovery dataset and replicated in 3 independent samples. There was a negative correlation between apathy and putamen/accumbens volume only in healthy individuals with schizotypy; however, medicated patients exhibited larger putamen volume, which appears to be a consequence of antipsychotic medications. The negative association between reduced OFC thickness and total negative symptoms also appeared to vary along the SZ spectrum, being significant only in FEP patients. In schizotypy, there was increased OFC thickness relative to controls. Our findings suggest that negative symptoms are associated with a temporal continuum of orbitofrontal-striatal abnormalities that may predate the occurrence of SZ. Thicker OFC in schizotypy may represent either compensatory or pathological mechanisms prior to the disease onset.
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Affiliation(s)
- Matthias Kirschner
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,To whom correspondence should be addressed; 3801 Rue University, Montréal QC, H3A 2B4 Canada; tel: +1 514-398-1726, fax: +1 514–398–8948, e-mail:
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | | | - Achim Burrer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Andrei Manoliu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,Wellcome Centre for Human Neuroimaging, University College London, London, UK,Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Yashar Zeighami
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Yvonne Yau
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Nooshin Abbasi
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Anke Maatz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | | | - Aslan Abivardi
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Mihai Avram
- Department of Neuroradiology and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany,Department of Psychiatry, Psychosomatics and Psychotherapy, Schleswig Holstein University Hospital, University Lübeck, Lübeck Germany
| | - Felix Brandl
- Department of Psychiatry and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany,Department of Psychiatry and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, New York, NY,Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Northwell/Hofstra, Hempstead, NY
| | | | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Stefan Kaiser
- Department of Psychiatry, Division of Adult Psychiatry, Geneva University Hospitals, Geneva, Switzerland
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17
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Tourette syndrome or PANDAS-a case report. Wien Med Wochenschr 2020; 171:289-292. [PMID: 32955635 DOI: 10.1007/s10354-020-00779-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 08/12/2020] [Indexed: 10/23/2022]
Abstract
Tourette syndrome (TS), a relatively common disorder, has been gaining more attention during the past two decades because of an increased number of reports. Nevertheless, it is still not completely understood. Furthermore, a clinical entity called "pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections" (PANDAS) has been introduced, which describes a tic disorder, accompanied by psychiatric disorders such as obsessive compulsive disorder (OCD), after a streptococcal infection in childhood. We present a case report of a 19-year-old adolescent Ukrainian female, with a history of anxiety disorder and OCD, who, despite TS remission during childhood, presented with new-onset motor and phonic tics after 1 month of severe tonsillitis. Blood and cerebrospinal cultures showed Streptococcus pyogenes, with magnetic resonance imaging revealing hypo-intense changes in the caudate nucleus on both sides. Treatment with clonazepam and fluoxetine, along with behavioral therapy, have improved the severity of her condition. This report presents a case of TS reemergence against the background of immunological reaction or PANDAS with a late adolescent onset.
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18
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Apathy is not associated with reduced ventral striatal volume in patients with schizophrenia. Schizophr Res 2020; 223:279-288. [PMID: 32928618 DOI: 10.1016/j.schres.2020.08.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 05/04/2020] [Accepted: 08/24/2020] [Indexed: 01/18/2023]
Abstract
BACKGROUND A growing body of neuroimaging research has revealed a relationship between blunted activation of the ventral striatum (VS) and apathy in schizophrenia. In contrast, the association between reduced striatal volume and apathy is less well established, while the relationship between VS function and structure in patients with schizophrenia remains an open question. Here, we aimed to replicate previous structural findings in a larger independent sample and to investigate the relationship between VS hypoactivation and VS volume. METHODS We included brain structural magnetic resonance imaging (MRI) data from 60 patients with schizophrenia (SZ) that had shown an association of VS hypoactivation with apathy during reward anticipation and 58 healthy controls (HC). To improve replicability, we applied analytical methods employed in two previously published studies: Voxel-based morphometry and the Multiple Automatically Generated Templates (MAGeT) algorithm. VS and dorsal striatum (DS) volume were correlated with apathy correcting for age, gender and total brain volume. Additionally, left VS activity was correlated with left VS volume. RESULTS We failed to replicate the association between apathy and reduced VS volume and did not find a correlation with DS volume. Functional and structural left VS measures exhibited a trend-level correlation (rs = 0.248, p = 0.067, r2 = 0.06). CONCLUSIONS Our present data suggests that functional and structural striatal neuroimaging correlates of apathy can occur independently. Replication of previous findings may have been limited by other factors (medication, illness duration, age) potentially related to striatal volume changes in SZ. Finally, associations between reward-related VS function and structure should be further explored.
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19
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Kirschner M, Shafiei G, Markello RD, Makowski C, Talpalaru A, Hodzic-Santor B, Devenyi GA, Paquola C, Bernhardt BC, Lepage M, Chakravarty MM, Dagher A, Mišić B. Latent Clinical-Anatomical Dimensions of Schizophrenia. Schizophr Bull 2020; 46:1426-1438. [PMID: 32744604 PMCID: PMC8496914 DOI: 10.1093/schbul/sbaa097] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.
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Affiliation(s)
- Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Carolina Makowski
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Alexandra Talpalaru
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada
| | - Benazir Hodzic-Santor
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Gabriel A Devenyi
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Martin Lepage
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada,To whom correspondence should be addressed; tel: 514-398-1857, fax: 514-398-1857, e-mail:
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