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Spilka MJ, Millman ZB, Waltz JA, Walker EF, Levin JA, Powers AR, Corlett PR, Schiffman J, Gold JM, Silverstein SM, Ellman LM, Mittal VA, Woods SW, Zinbarg R, Strauss GP. A generalized reward processing deficit pathway to negative symptoms across diagnostic boundaries. Psychol Med 2025; 55:e6. [PMID: 39901872 DOI: 10.1017/s003329172400326x] [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] [Indexed: 02/05/2025]
Abstract
BACKGROUND Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms. METHODS Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort-cost computation. RESULTS k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores. CONCLUSIONS Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.
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Affiliation(s)
- Michael J Spilka
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Zachary B Millman
- Psychotic Disorders Division, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - James A Waltz
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Jason A Levin
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Albert R Powers
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | | | - Jason Schiffman
- Department of Psychological Science, University of California, Irvine, CA, USA
| | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Steven M Silverstein
- Departments of Psychiatry, Neuroscience and Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
| | - Lauren M Ellman
- Department of Psychology & Neuroscience, Temple University, Philadelphia, PA, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Richard Zinbarg
- Department of Psychology, Northwestern University, Evanston, IL, USA
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Cattarinussi G, Grimaldi DA, Aarabi MH, Sambataro F. Static and Dynamic Dysconnectivity in Early Psychosis: Relationship With Symptom Dimensions. Schizophr Bull 2024; 51:120-132. [PMID: 39212653 PMCID: PMC11661956 DOI: 10.1093/schbul/sbae142] [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] [Indexed: 09/04/2024]
Abstract
BACKGROUND AND HYPOTHESIS Altered functional connectivity (FC) has been frequently reported in psychosis. Studying FC and its time-varying patterns in early-stage psychosis allows the investigation of the neural mechanisms of this disorder without the confounding effects of drug treatment or illness-related factors. STUDY DESIGN We employed resting-state functional magnetic resonance imaging (rs-fMRI) to explore FC in individuals with early psychosis (EP), who also underwent clinical and neuropsychological assessments. 96 EP and 56 demographically matched healthy controls (HC) from the Human Connectome Project for Early Psychosis database were included. Multivariate analyses using spatial group independent component analysis were used to compute static FC and dynamic functional network connectivity (dFNC). Partial correlations between FC measures and clinical and cognitive variables were performed to test brain-behavior associations. STUDY RESULTS Compared to HC, EP showed higher static FC in the striatum and temporal, frontal, and parietal cortex, as well as lower FC in the frontal, parietal, and occipital gyrus. We found a negative correlation in EP between cognitive function and FC in the right striatum FC (pFWE = 0.009). All dFNC parameters, including dynamism and fluidity measures, were altered in EP, and positive symptoms were negatively correlated with the meta-state changes and the total distance (pFWE = 0.040 and pFWE = 0.049). CONCLUSIONS Our findings support the view that psychosis is characterized from the early stages by complex alterations in intrinsic static and dynamic FC, that may ultimately result in positive symptoms and cognitive deficits.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Mohammad Hadi Aarabi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia, USA
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Padova Neuroscience Center, University of Padova, Padua, Italy
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3
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Papp C, Mikaczo A, Szabo J, More CE, Viczjan G, Gesztelyi R, Zsuga J. Mesocorticolimbic and Cardiometabolic Diseases-Two Faces of the Same Coin? Int J Mol Sci 2024; 25:9682. [PMID: 39273628 PMCID: PMC11395462 DOI: 10.3390/ijms25179682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 08/26/2024] [Accepted: 09/04/2024] [Indexed: 09/15/2024] Open
Abstract
The risk behaviors underlying the most prevalent chronic noncommunicable diseases (NCDs) encompass alcohol misuse, unhealthy diets, smoking and sedentary lifestyle behaviors. These are all linked to the altered function of the mesocorticolimbic (MCL) system. As the mesocorticolimbic circuit is central to the reward pathway and is involved in risk behaviors and mental disorders, we set out to test the hypothesis that these pathologies may be approached therapeutically as a group. To address these questions, the identification of novel targets by exploiting knowledge-based, network-based and disease similarity algorithms in two major Thomson Reuters databases (MetaBase™, a database of manually annotated protein interactions and biological pathways, and IntegritySM, a unique knowledge solution integrating biological, chemical and pharmacological data) was performed. Each approach scored proteins from a particular approach-specific standpoint, followed by integration of the scores by machine learning techniques yielding an integrated score for final target prioritization. Machine learning identified characteristic patterns of the already known targets (control targets) with high accuracy (area under curve of the receiver operator curve was ~93%). The analysis resulted in a prioritized list of 250 targets for MCL disorders, many of which are well established targets for the mesocorticolimbic circuit e.g., dopamine receptors, monoamino oxidases and serotonin receptors, whereas emerging targets included DPP4, PPARG, NOS1, ACE, ARB1, CREB1, POMC and diverse voltage-gated Ca2+ channels. Our findings support the hypothesis that disorders involving the mesocorticolimbic circuit may share key molecular pathology aspects and may be causally linked to NCDs, yielding novel targets for drug repurposing and personalized medicine.
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Affiliation(s)
- Csaba Papp
- Department of Psychiatry, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Angela Mikaczo
- Department of Pulmonology, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
- Doctoral School of Pharmaceutical Sciences, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Janos Szabo
- Department of Psychiatry, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Csaba E More
- Department of Psychiatry, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Gabor Viczjan
- Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Rudolf Gesztelyi
- Department of Pharmacology and Pharmacotherapy, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
| | - Judit Zsuga
- Department of Psychiatry, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, H-4032 Debrecen, Hungary
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4
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Martin E, Chowdury A, Kopchick J, Thomas P, Khatib D, Rajan U, Zajac-Benitez C, Haddad L, Amirsadri A, Robison AJ, Thakkar KN, Stanley JA, Diwadkar VA. The mesolimbic system and the loss of higher order network features in schizophrenia when learning without reward. Front Psychiatry 2024; 15:1337882. [PMID: 39355381 PMCID: PMC11443173 DOI: 10.3389/fpsyt.2024.1337882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/16/2024] [Indexed: 10/03/2024] Open
Abstract
Introduction Schizophrenia is characterized by a loss of network features between cognition and reward sub-circuits (notably involving the mesolimbic system), and this loss may explain deficits in learning and cognition. Learning in schizophrenia has typically been studied with tasks that include reward related contingencies, but recent theoretical models have argued that a loss of network features should be seen even when learning without reward. We tested this model using a learning paradigm that required participants to learn without reward or feedback. We used a novel method for capturing higher order network features, to demonstrate that the mesolimbic system is heavily implicated in the loss of network features in schizophrenia, even when learning without reward. Methods fMRI data (Siemens Verio 3T) were acquired in a group of schizophrenia patients and controls (n=78; 46 SCZ, 18 ≤ Age ≤ 50) while participants engaged in associative learning without reward-related contingencies. The task was divided into task-active conditions for encoding (of associations) and cued-retrieval (where the cue was to be used to retrieve the associated memoranda). No feedback was provided during retrieval. From the fMRI time series data, network features were defined as follows: First, for each condition of the task, we estimated 2nd order undirected functional connectivity for each participant (uFC, based on zero lag correlations between all pairs of regions). These conventional 2nd order features represent the task/condition evoked synchronization of activity between pairs of brain regions. Next, in each of the patient and control groups, the statistical relationship between all possible pairs of 2nd order features were computed. These higher order features represent the consistency between all possible pairs of 2nd order features in that group and embed within them the contributions of individual regions to such group structure. Results From the identified inter-group differences (SCZ ≠ HC) in higher order features, we quantified the respective contributions of individual brain regions. Two principal effects emerged: 1) SCZ were characterized by a massive loss of higher order features during multiple task conditions (encoding and retrieval of associations). 2) Nodes in the mesolimbic system were over-represented in the loss of higher order features in SCZ, and notably so during retrieval. Discussion Our analytical goals were linked to a recent circuit-based integrative model which argued that synergy between learning and reward circuits is lost in schizophrenia. The model's notable prediction was that such a loss would be observed even when patients learned without reward. Our results provide substantial support for these predictions where we observed a loss of network features between the brain's sub-circuits for a) learning (including the hippocampus and prefrontal cortex) and b) reward processing (specifically constituents of the mesolimbic system that included the ventral tegmental area and the nucleus accumbens. Our findings motivate a renewed appraisal of the relationship between reward and cognition in schizophrenia and we discuss their relevance for putative behavioral interventions.
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Affiliation(s)
- Elizabeth Martin
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
- Department of Psychiatry, University of Texas Austin, Austin, TX, United States
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States
| | - John Kopchick
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Patricia Thomas
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Dalal Khatib
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Usha Rajan
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Caroline Zajac-Benitez
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Luay Haddad
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alireza Amirsadri
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alfred J. Robison
- Department of Physiology, Michigan State University, East Lansing, MI, United States
| | - Katherine N. Thakkar
- Department of Psychology, Michigan State University, East Lansing, MI, United States
| | - Jeffrey A. Stanley
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Vaibhav A. Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
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5
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Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye LT, Richard G, Fernandez-Cabello S, Parker N, Andreassen OA, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin CP, Tsai SJ, Rodrigue AL, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León MÁ, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul AS, Uslu O, Burhanoglu BB, Uyar Demir A, Rootes-Murdy K, Calhoun VD, Sim K, Green M, Quidé Y, Chung YC, Kim WS, Sponheim SR, Demro C, Ramsay IS, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park MTM, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen TE, Rossell SL, Hughes M, Woods W, Carruthers SP, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen DD, Preda A, Thomopoulos SI, Jahanshad N, Cui LB, Yao D, Thompson PM, Turner JA, van Erp TGM, Cheng W, Feng J. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm. Nat Commun 2024; 15:5996. [PMID: 39013848 PMCID: PMC11252381 DOI: 10.1038/s41467-024-50267-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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Affiliation(s)
- Yuchao Jiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, Canada
| | - Xiao Chang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
- German Center for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Magdeburg, Germany
| | - Kiyotaka Nemoto
- Department of Psychiatry, Division of Clinical Medicine, Institute of Medicine, University of Tsukuba, Tsukuba, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Genevieve Richard
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Sara Fernandez-Cabello
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Nadine Parker
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps Universität Marburg, Rudolf-Bultmann-Str. 8, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapie and Center for Brain, Behavior and Metabolism, Lübeck University, Lübeck, Germany
- Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience, University of Münster, Münster, Germany
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weihua Yue
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
- Chinese Institute for Brain Research, Beijing, PR China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, PR China
| | - Yuyanan Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Enpeng Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, PR China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - David Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Godfrey Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, TX, USA
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - María Ángeles Garcia-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
| | - Ali Saffet Gonul
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Ozgul Uslu
- Ege University Institute of Health Sciences Department of Neuroscience, Izmir, Turkey
| | | | - Aslihan Uyar Demir
- Ege University School of Medicine Department of Psychiatry, SoCAT Lab, Izmir, Turkey
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Melissa Green
- School of Clinical Medicine, University of New South Wales, SYD, Australia
| | - Yann Quidé
- School of Psychology, University of New South Wales, SYD, Australia
| | - Young Chul Chung
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Scott R Sponheim
- Minneapolis VA Medical Center, University of Minnesota, Minneapolis, MN, USA
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Ian S Ramsay
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | - Felice Iasevoli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Annarita Barone
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry - Department of Neuroscience, University "Federico II", Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University "Federico II", Naples, Italy
| | - Min Tae M Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, TO, Canada
- Centre for Addiction and Mental Health, TO, Canada
| | - Matthias Kirschner
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital University of Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, MEL, Australia
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Susan L Rossell
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Matthew Hughes
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - William Woods
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Sean P Carruthers
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Philip Sumner
- Centre for Mental Health and Brain Sciences, School of Health Sciences, Swinburne University, MEL, Australia
| | - Elysha Ringin
- National Institute of Mental Health, Klecany, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Philipp Homan
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich & Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, Zurich, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Wolfgang Omlor
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Giacomo Cecere
- Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Dana D Nguyen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Long-Biao Cui
- Department of Clinical Psychology, Fourth Military Medical University, Xi'an, PR China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- School of Data Science, Fudan University, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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6
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Kaliuzhna M, Carruzzo F, Kuenzi N, Tobler PN, Kirschner M, Geffen T, Katthagen T, Böge K, Zierhut MM, Schlagenhauf F, Kaiser S. Adaptive coding of reward in schizophrenia, its change over time and relationship to apathy. Brain 2024; 147:2459-2470. [PMID: 38608149 PMCID: PMC11224610 DOI: 10.1093/brain/awae112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/11/2024] [Accepted: 03/16/2024] [Indexed: 04/14/2024] Open
Abstract
Adaptive coding of reward is the process by which neurons adapt their response to the context of available compensations. Higher rewards lead to a stronger brain response, but the increase of the response depends on the range of available rewards. A steeper increase is observed in a narrow range and a more gradual slope in a wider range. In schizophrenia, adaptive coding appears to be affected in different domains, especially in the reward domain. Here, we tested adaptive coding of reward in a large group of patients with schizophrenia (n = 86) and control subjects (n = 66). We assessed: (i) the association between adaptive coding deficits and symptoms; (ii) the longitudinal stability of deficits (the same task was performed 3 months apart); and (iii) the stability of results between two experimental sites. We used functional MRI and the monetary incentive delay task to assess adaptation of participants to two different reward ranges: a narrow range and a wide range. We used a region-of-interest analysis to evaluate adaptation within striatal and visual regions. Patients and control subjects underwent a full demographic and clinical assessment. We found reduced adaptive coding in patients, with a decreased slope in the narrow reward range with respect to that of control participants, in striatal but not visual regions. This pattern was observed at both research sites. Upon retesting, patients increased their narrow-range slopes, showing improved adaptive coding, whereas control subjects slightly reduced them. At retesting, patients with overly steep slopes in the narrow range also showed higher levels of negative symptoms. Our data confirm deficits in reward adaptation in schizophrenia and reveal an effect of practice in patients, leading to improvement, with steeper slopes upon retesting. However, in some patients, an excessively steep slope may result in poor discriminability of larger rewards, owing to early saturation of the brain response. Together, the loss of precision of reward representation in new (first exposure, underadaptation) and more familiar (retest, overadaptation) situations might contribute to the multiple motivational symptoms in schizophrenia.
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Affiliation(s)
- Mariia Kaliuzhna
- Clinical and Experimental Psychopathology Laboratory, Department of Psychiatry, University of Geneva, 1205 Geneva, Switzerland
| | - Fabien Carruzzo
- Clinical and Experimental Psychopathology Laboratory, Department of Psychiatry, University of Geneva, 1205 Geneva, Switzerland
| | - Noémie Kuenzi
- Department of Psychiatry, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Philippe N Tobler
- Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, 8006 Zurich, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Tal Geffen
- Department of Psychiatry and Psychotherapy, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Teresa Katthagen
- Department of Psychiatry and Psychotherapy, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Kerem Böge
- Department of Psychiatry and Psychotherapy, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Marco M Zierhut
- Department of Psychiatry and Psychotherapy, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Florian Schlagenhauf
- Department of Psychiatry and Psychotherapy, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Stefan Kaiser
- Department of Psychiatry, Geneva University Hospitals, 1205 Geneva, Switzerland
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7
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Kim J, Vanrobaeys Y, Kelvington B, Peterson Z, Baldwin E, Gaine ME, Nickl-Jockschat T, Abel T. Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders. Mol Psychiatry 2024; 29:1310-1321. [PMID: 38278994 PMCID: PMC11189748 DOI: 10.1038/s41380-024-02411-0] [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: 02/08/2023] [Revised: 12/21/2023] [Accepted: 01/04/2024] [Indexed: 01/28/2024]
Abstract
Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del/+) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and highlighted three genes within the deleted region: thousand and one amino acid protein kinase 2 (Taok2), seizure-related 6 homolog-like 2 (Sez6l2), and major vault protein (Mvp). Using CRISPR/Cas9, we generated mice carrying null mutations in Taok2, Sez6l2, and Mvp (3 gene hemi-deletion (3g del/+)). Hemi-deletion of these 3 genes recapitulates sex-specific behavioral alterations in striatum-dependent behavioral tasks observed in 16p11.2 del/+ mice, specifically male-specific hyperactivity and impaired motivation for reward seeking. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice exclusively in males. Subsequent analysis identified translation dysregulation and/or extracellular signal-regulated kinase signaling as plausible molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Interestingly, ribosomal profiling supported the notion of translation dysregulation in both 3g del/+ and 16p11.2 del/+ male mice. However, mice carrying a 4-gene deletion (with an additional deletion of Mapk3) exhibited fewer phenotypic similarities with 16p11.2 del/+ mice. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice. These results support the importance of a polygenic approach to study NDDs and underscore that the effects of the large genetic deletions result from complex interactions between multiple candidate genes.
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Affiliation(s)
- Jaekyoon Kim
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA
| | - Yann Vanrobaeys
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA
- Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa, IA, USA
| | - Benjamin Kelvington
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA
| | - Zeru Peterson
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA, USA
| | - Emily Baldwin
- The Iowa Medical Scientist Training Program, University of Iowa, Iowa, IA, USA
| | - Marie E Gaine
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA
- Department of Pharmaceutical Sciences and Experimental Therapeutics, College of Pharmacy, University of Iowa, Iowa, IA, USA
| | - Thomas Nickl-Jockschat
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA.
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA.
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA, USA.
| | - Ted Abel
- Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa, IA, USA.
- Iowa Neuroscience Institute, University of Iowa, Iowa, IA, USA.
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa, IA, USA.
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8
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Martino M, Magioncalda P. A three-dimensional model of neural activity and phenomenal-behavioral patterns. Mol Psychiatry 2024; 29:639-652. [PMID: 38114633 DOI: 10.1038/s41380-023-02356-w] [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: 07/18/2023] [Revised: 11/16/2023] [Accepted: 11/27/2023] [Indexed: 12/21/2023]
Abstract
How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.
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Affiliation(s)
- Matteo Martino
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
| | - Paola Magioncalda
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
- Department of Radiology, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
- Department of Medical Research, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
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9
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Ma Y, Guo C, Luo Y, Gao S, Sun J, Chen Q, Lv X, Cao J, Lei Z, Fang J. Altered neural activity in the reward-related circuit associated with anhedonia in mild to moderate Major Depressive Disorder. J Affect Disord 2024; 345:216-225. [PMID: 37866737 DOI: 10.1016/j.jad.2023.10.085] [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: 05/29/2023] [Revised: 10/02/2023] [Accepted: 10/10/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND Anhedonia is a significant predictor of disease progression and treatment outcomes in Major Depressive Disorder (MDD), linked to reward network dysfunctions. However, understanding of its underlying neural mechanisms remains limited. This study aimed to investigate the brain functional mechanisms underlying MDD with anhedonia using resting-state functional magnetic resonance imaging (rs-fMRI). METHODS The Snaith-Hamilton Pleasure Scale (SHAPS) was used to evaluation MDD with anhedonia (anMDD) and non-anhedonia MDD (non-anMDD). Forty-eight patients with anMDD, Forty-four patients with non-anMDD, and Fifty healthy controls (HCs) were enrolled for the fMRI scans. A seed-based functional connectivity (FC) method was employed to explore reward network abnormalities. RESULTS anMDD patients exhibited lower FC values in Ventral Striatum (VS), right lateral Ventral Tegmental Area (VTA_R), left Thalamus (THA_L), and higher FC values in Ventromedial Prefrontal Cortex (vmPFC), left Anterior Insula (AI_L), and Presupplementary Motor Area (Pre-SMA) compared to HCs. Comparing anMDD to non-anMDD, significant differences were observed in FC values of VS, vmPFC, Pre-SMA, and THA_L regions. Correlation analysis revealed positive correlations between FC values of VS_R and NAc_R, as well as THA_L and Cerebellum_Crus1_L, with SHAPS scores. Negative correlations were observed between FC values of Pre-SMA and the right caudate, and between vmPFC and Frontal_Mid_Orb_L, and SHAPS scores. CONCLUSION Both anMDD and non-anMDD groups demonstrated abnormal FCs in the reward network. These findings indicate distinct roles of reward-related circuits in the two subtypes, contributing to a refined understanding of depression phenotypes and potential directions for targeted interventions.
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Affiliation(s)
- Yue Ma
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Chunlei Guo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Yi Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Shanshan Gao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jifei Sun
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Qingyan Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Xueyu Lv
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiudong Cao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhang Lei
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiliang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
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10
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Chase HW. A novel technique for delineating the effect of variation in the learning rate on the neural correlates of reward prediction errors in model-based fMRI. Front Psychol 2023; 14:1211528. [PMID: 38187436 PMCID: PMC10768009 DOI: 10.3389/fpsyg.2023.1211528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/28/2023] [Indexed: 01/09/2024] Open
Abstract
Introduction Computational models play an increasingly important role in describing variation in neural activation in human neuroimaging experiments, including evaluating individual differences in the context of psychiatric neuroimaging. In particular, reinforcement learning (RL) techniques have been widely adopted to examine neural responses to reward prediction errors and stimulus or action values, and how these might vary as a function of clinical status. However, there is a lack of consensus around the importance of the precision of free parameter estimation for these methods, particularly with regard to the learning rate. In the present study, I introduce a novel technique which may be used within a general linear model (GLM) to model the effect of mis-estimation of the learning rate on reward prediction error (RPE)-related neural responses. Methods Simulations employed a simple RL algorithm, which was used to generate hypothetical neural activations that would be expected to be observed in functional magnetic resonance imaging (fMRI) studies of RL. Similar RL models were incorporated within a GLM-based analysis method including derivatives, with individual differences in the resulting GLM-derived beta parameters being evaluated with respect to the free parameters of the RL model or being submitted to other validation analyses. Results Initial simulations demonstrated that the conventional approach to fitting RL models to RPE responses is more likely to reflect individual differences in a reinforcement efficacy construct (lambda) rather than learning rate (alpha). The proposed method, adding a derivative regressor to the GLM, provides a second regressor which reflects the learning rate. Validation analyses were performed including examining another comparable method which yielded highly similar results, and a demonstration of sensitivity of the method in presence of fMRI-like noise. Conclusion Overall, the findings underscore the importance of the lambda parameter for interpreting individual differences in RPE-coupled neural activity, and validate a novel neural metric of the modulation of such activity by individual differences in the learning rate. The method is expected to find application in understanding aberrant reinforcement learning across different psychiatric patient groups including major depression and substance use disorder.
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Affiliation(s)
- Henry W. Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
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11
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Luo Y, Dong D, Huang H, Zhou J, Zuo X, Hu J, He H, Jiang S, Duan M, Yao D, Luo C. Associating Multimodal Neuroimaging Abnormalities With the Transcriptome and Neurotransmitter Signatures in Schizophrenia. Schizophr Bull 2023; 49:1554-1567. [PMID: 37607339 PMCID: PMC10686354 DOI: 10.1093/schbul/sbad047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is a multidimensional disease. This study proposes a new research framework that combines multimodal meta-analysis and genetic/molecular architecture to solve the consistency in neuroimaging biomarkers of schizophrenia and whether these link to molecular genetics. STUDY DESIGN We systematically searched Web of Science, PubMed, and BrainMap for the amplitude of low-frequency fluctuations (ALFF) or fractional ALFF, regional homogeneity, regional cerebral blood flow, and voxel-based morphometry analysis studies investigating schizophrenia. The pooled-modality, single-modality, and illness duration-dependent meta-analyses were performed using the activation likelihood estimation algorithm. Subsequently, Spearman correlation and partial least squares regression analyses were conducted to assess the relationship between identified reliable convergent patterns of multimodality and neurotransmitter/transcriptome, using prior molecular imaging and brain-wide gene expression. STUDY RESULTS In total, 203 experiments comprising 10 613 patients and 10 461 healthy controls were included. Multimodal meta-analysis showed that brain regions of significant convergence in schizophrenia were mainly distributed in the frontotemporal cortex, anterior cingulate cortex, insula, thalamus, striatum, and hippocampus. Interestingly, the analyses of illness-duration subgroups identified aberrant functional and structural evolutionary patterns: Lines from the striatum to the cortical core networks to extensive cortical and subcortical regions. Subsequently, we found that these robust multimodal neuroimaging abnormalities were associated with multiple neurobiological abnormalities, such as dopaminergic, glutamatergic, serotonergic, and GABAergic systems. CONCLUSIONS This work links transcriptome/neurotransmitters with reliable structural and functional signatures of brain abnormalities underlying disease effects in schizophrenia, which provides novel insight into the understanding of schizophrenia pathophysiology and targeted treatments.
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Affiliation(s)
- Yuling Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Debo Dong
- Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaojun Zuo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jian Hu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Mental Health Center of Chengdu, The fourth people’s Hospital of Chengdu, Chengdu, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Mental Health Center of Chengdu, The fourth people’s Hospital of Chengdu, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical Sciences, Chengdu, China
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12
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Wang X, Zhang Y, Huang J, Wang Y, Niu Y, Lui SSY, Hui L, Chan RCK. Revisiting reward impairments in schizophrenia spectrum disorders: a systematic review and meta-analysis for neuroimaging findings. Psychol Med 2023; 53:7189-7202. [PMID: 36994747 DOI: 10.1017/s0033291723000703] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
BACKGROUND Abnormal reward functioning is central to anhedonia and amotivation symptoms of schizophrenia (SCZ). Reward processing encompasses a series of psychological components. This systematic review and meta-analysis examined the brain dysfunction related to reward processing of individuals with SCZ spectrum disorders and risks, covering multiple reward components. METHODS After a systematic literature search, 37 neuroimaging studies were identified and divided into four groups based on their target psychology components (i.e. reward anticipation, reward consumption, reward learning, effort computation). Whole-brain Seed-based d Mapping (SDM) meta-analyses were conducted for all included studies and each component. RESULTS The meta-analysis for all reward-related studies revealed reduced functional activation across the SCZ spectrum in the striatum, orbital frontal cortex, cingulate cortex, and cerebellar areas. Meanwhile, distinct abnormal patterns were found for reward anticipation (decreased activation of the cingulate cortex and striatum), reward consumption (decreased activation of cerebellum IV/V areas, insula and inferior frontal gyri), and reward learning processing (decreased activation of the striatum, thalamus, cerebellar Crus I, cingulate cortex, orbitofrontal cortex, and parietal and occipital areas). Lastly, our qualitative review suggested that decreased activation of the ventral striatum and anterior cingulate cortex was also involved in effort computation. CONCLUSIONS These results provide deep insights on the component-based neuro-psychopathological mechanisms for anhedonia and amotivation symptoms of the SCZ spectrum.
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Affiliation(s)
- Xuan Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yinghao Zhang
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Jia Huang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yanzhe Niu
- Department of Psychology, University of California, San Diego, La Jolla, USA
| | - Simon S Y Lui
- Department of Psychiatry, School of Clinical Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Li Hui
- Research Center of Biological Psychiatry, Suzhou Guangji Hospital, Medical College of Soochow University, Suzhou, Jiangsu, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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13
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Fuentes-Claramonte P, Garcia-Leon MA, Salgado-Pineda P, Ramiro N, Soler-Vidal J, Torres ML, Cano R, Argila-Plaza I, Panicali F, Sarri C, Jaurrieta N, Sánchez M, Boix-Quintana E, Albacete A, Maristany T, Sarró S, Raduà J, McKenna PJ, Salvador R, Pomarol-Clotet E. Do the negative symptoms of schizophrenia reflect reduced responsiveness to reward? Examination using a reward prediction error (RPE) task. Psychol Med 2023; 53:7106-7115. [PMID: 36987680 PMCID: PMC10719670 DOI: 10.1017/s0033291723000521] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/08/2023] [Accepted: 02/10/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND A leading theory of the negative symptoms of schizophrenia is that they reflect reduced responsiveness to rewarding stimuli. This proposal has been linked to abnormal (reduced) dopamine function in the disorder, because phasic release of dopamine is known to code for reward prediction error (RPE). Nevertheless, few functional imaging studies have examined if patients with negative symptoms show reduced RPE-associated activations. METHODS Matched groups of DSM-5 schizophrenia patients with high negative symptom scores (HNS, N = 27) or absent negative symptoms (ANS, N = 27) and healthy controls (HC, N = 30) underwent fMRI scanning while they performed a probabilistic monetary reward task designed to generate a measure of RPE. RESULTS In the HC, whole-brain analysis revealed that RPE was positively associated with activation in the ventral striatum, the putamen, and areas of the lateral prefrontal cortex and orbitofrontal cortex, among other regions. Group comparison revealed no activation differences between the healthy controls and the ANS patients. However, compared to the ANS patients, the HNS patients showed regions of significantly reduced activation in the left ventrolateral and dorsolateral prefrontal cortex, and in the right lingual and fusiform gyrus. HNS and ANS patients showed no activation differences in ventral striatal or midbrain regions-of-interest (ROIs), but the HNS patients showed reduced activation in a left orbitofrontal cortex ROI. CONCLUSIONS The findings do not suggest that a generalized reduction of RPE signalling underlies negative symptoms. Instead, they point to a more circumscribed dysfunction in the lateral frontal and possibly the orbitofrontal cortex.
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Affiliation(s)
- Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | - Maria Angeles Garcia-Leon
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | | | - Joan Soler-Vidal
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
- Benito Menni CASM, Sant Boi de Llobregat, Barcelona, Spain
- Universitat de Barcelona, Barcelona, Spain
| | | | - Ramon Cano
- Hospital Mare de Déu de la Mercè, Barcelona, Spain
| | | | | | - Carmen Sarri
- Benito Menni CASM, Sant Boi de Llobregat, Barcelona, Spain
| | | | - Manel Sánchez
- Hospital Sagrat Cor, Martorell, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Auria Albacete
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | - Joaquim Raduà
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institute, Stockholm, Sweden
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Peter J. McKenna
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
- CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental), Instituto de Salud Carlos III, Barcelona, Spain
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14
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Fitzgerald E, Arcego DM, Shen MJ, O'Toole N, Wen X, Nagy C, Mostafavi S, Craig K, Silveira PP, Rayan NA, Diorio J, Meaney MJ, Zhang TY. Sex and cell-specific gene expression in corticolimbic brain regions associated with psychiatric disorders revealed by bulk and single-nuclei RNA sequencing. EBioMedicine 2023; 95:104749. [PMID: 37549631 PMCID: PMC10432187 DOI: 10.1016/j.ebiom.2023.104749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 06/28/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023] Open
Abstract
BACKGROUND There are sex-specific differences in the prevalence, symptomology and course of psychiatric disorders. However, preclinical models have primarily used males, such that the molecular mechanisms underlying sex-specific differences in psychiatric disorders are not well established. METHODS In this study, we compared transcriptome-wide gene expression profiles in male and female rats within the corticolimbic system, including the cingulate cortex, nucleus accumbens medial shell (NAcS), ventral dentate gyrus and the basolateral amygdala (n = 22-24 per group/region). FINDINGS We found over 3000 differentially expressed genes (DEGs) in the NAcS between males and females. Of these DEGs in the NAcS, 303 showed sex-dependent conservation DEGs in humans and were significantly enriched for gene ontology terms related to blood vessel morphogenesis and regulation of cell migration. Single nuclei RNA sequencing in the NAcS of male and female rats identified widespread sex-dependent expression, with genes upregulated in females showing a notable enrichment for synaptic function. Female upregulated genes in astrocytes, Drd3+MSNs and oligodendrocyte were also enriched in several psychiatric genome-wide association studies (GWAS). INTERPRETATION Our data provide comprehensive evidence of sex- and cell-specific molecular profiles in the NAcS. Importantly these differences associate with anxiety, bipolar disorder, schizophrenia, and cross-disorder, suggesting an intrinsic molecular basis for sex-based differences in psychiatric disorders that strongly implicates the NAcS. FUNDING This work was supported by funding from the Hope for Depression Research Foundation (MJM).
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Affiliation(s)
- Eamon Fitzgerald
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada
| | - Danusa Mar Arcego
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada
| | - Mo Jun Shen
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nicholas O'Toole
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada
| | - Xianglan Wen
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada
| | - Corina Nagy
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada
| | - Sara Mostafavi
- Paul G. Allen School of Computer Science and Engineering, University of Washington, 185 E Stevens Way NE, Seattle, WA 9819, USA
| | - Kelly Craig
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada
| | - Patricia Pelufo Silveira
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nirmala Arul Rayan
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences and Brain - Body Initiative, Agency for Science, Technology and Research (A∗STAR), Singapore
| | - Josie Diorio
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada
| | - Michael J Meaney
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada; Translational Neuroscience Program, Singapore Institute for Clinical Sciences and Brain - Body Initiative, Agency for Science, Technology and Research (A∗STAR), Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tie-Yuan Zhang
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, H4H 1R3, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montréal, H4H 1R3, Canada.
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15
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Gangl N, Conring F, Federspiel A, Wiest R, Walther S, Stegmayer K. Resting-state perfusion in motor and fronto-limbic areas is linked to diminished expression of emotion and speech in schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:51. [PMID: 37573445 PMCID: PMC10423240 DOI: 10.1038/s41537-023-00384-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/25/2023] [Indexed: 08/14/2023]
Abstract
Negative symptoms (NS) are a core component of schizophrenia affecting community functioning and quality of life. We tested neural correlates of NS considering NS factors and consensus subdomains. We assessed NS using the Clinical Assessment Interview for Negative Symptoms and the Scale for Assessment of Negative Symptoms. Arterial spin labeling was applied to measure resting-state cerebral blood flow (rCBF) in 47 schizophrenia patients and 44 healthy controls. Multiple regression analyses calculated the relationship between rCBF and NS severity. We found an association between diminished expression (DE) and brain perfusion within the cerebellar anterior lobe and vermis, and the pre-, and supplementary motor area. Blunted affect was linked to fusiform gyrus and alogia to fronto-striatal rCBF. In contrast, motivation and pleasure was not associated with rCBF. These results highlight the key role of motor areas for DE. Considering NS factors and consensus subdomains may help identifying specific pathophysiological pathways of NS.
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Affiliation(s)
- Nicole Gangl
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland.
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland.
| | - Frauke Conring
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Andrea Federspiel
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Roland Wiest
- Support Center of Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Katharina Stegmayer
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
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16
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Zeng J, You L, Yang F, Luo Y, Yu S, Yan J, Liu M, Yang X. A meta-analysis of the neural substrates of monetary reward anticipation and outcome in alcohol use disorder. Hum Brain Mapp 2023; 44:2841-2861. [PMID: 36852619 PMCID: PMC10089105 DOI: 10.1002/hbm.26249] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 01/23/2023] [Accepted: 02/13/2023] [Indexed: 03/01/2023] Open
Abstract
The capacity to anticipate and detect rewarding outcomes is fundamental for the development of adaptive decision-making and goal-oriented behavior. Delineating the neural correlates of different stages of reward processing is imperative for understanding the neurobiological mechanism underlying alcohol use disorder (AUD). To examine the neural correlates of monetary anticipation and outcome in AUD patients, we performed two separate voxel-wise meta-analyses of functional neuroimaging studies, including 12 studies investigating reward anticipation and 7 studies investigating reward outcome using the monetary incentive delay task. During the anticipation stage, AUD patients displayed decreased activation in response to monetary cues in mesocortical-limbic circuits and sensory areas, including the ventral striatum (VS), insula, hippocampus, inferior occipital gyrus, supramarginal gyrus, lingual gyrus and fusiform gyrus. During the outcome stage, AUD patients exhibited reduced activation in the dorsal striatum, VS and insula, and increased activation in the orbital frontal cortex and medial temporal area. Our findings suggest that different activation patterns are associated with nondrug rewards during different reward processing stages, potentially reflecting a changed sensitivity to monetary reward in AUD.
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Affiliation(s)
- Jianguang Zeng
- School of Economics and Business AdministrationChongqing UniversityChongqingChina
| | - Lantao You
- School of Economics and Business AdministrationChongqing UniversityChongqingChina
| | - Fan Yang
- Department of Ultrasonography, West China Second University HospitalSichuan UniversityChengduChina
- Chengdu Chenghua District Maternal and Child Health HospitalSichuan UniversityChengduChina
| | - Ya Luo
- Department of Psychiatry, State Key Lab of BiotherapyWest China Hospital of Sichuan UniversityChengduChina
| | - Shuxian Yu
- School of Economics and Business AdministrationChongqing UniversityChongqingChina
| | - Jiangnan Yan
- School of Economics and Business AdministrationChongqing UniversityChongqingChina
| | - Mengqi Liu
- Department of RadiologyThe First Affiliated Hospital of Chongqing Medical UniversityChongqingChina
| | - Xun Yang
- School of Public AffairsChongqing UniversityChongqingChina
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17
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Wolf RC, Werler F, Schmitgen MM, Wolf ND, Wittemann M, Reith W, Hirjak D. Functional correlates of neurological soft signs in heavy cannabis users. Addict Biol 2023; 28:e13270. [PMID: 36825488 DOI: 10.1111/adb.13270] [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: 08/10/2022] [Revised: 12/03/2022] [Accepted: 01/20/2023] [Indexed: 02/17/2023]
Abstract
Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination, sensorimotor integration and complex motor task performance. Abnormal NSS levels can also be detected in non-dependent individuals with heavy cannabis use (HCU), yet very little is known about the functional correlates underlying such deficits. Here, we used resting-state functional magnetic resonance imaging (MRI) to investigate associations between NSS and intrinsic neural activity (INA) in HCU (n = 21) and controls (n = 26). Compared with controls, individuals with HCU showed significantly higher NSS across all investigated subdomains. Three of these subdomains, that is, motor coordination, sensorimotor integration and complex motor task behaviour, were associated with specific use-dependent variables, particularly age of onset of cannabis use and current cannabis use. Between-group comparisons of INA revealed lower regional homogeneity (ReHo) in left precentral gyrus, left inferior occipital gyrus, right triangular pat of the inferior frontal gyrus and right precentral gyrus in HCU compared with controls. In addition, HCU showed also higher ReHo in right cerebellum and left postcentral gyrus compared with controls. Complex motor task behaviour in HCU was significantly related to INA in postcentral, inferior frontal and occipital cortices. Our findings indicate abnormal ReHo in HCU in regions associated with sensorimotor, executive control and visuomotor-integration processes. Importantly, we show associations between ReHo, cannabis-use behaviour and execution of complex motor tasks. Given convergent findings in manifest psychotic disorders, this study suggests an HCU endophenotype that may present with a cumulative risk for psychosis.
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Affiliation(s)
- Robert Christian Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Florian Werler
- Department of General Psychiatry at the Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Mike M Schmitgen
- Department of General Psychiatry at the Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Nadine D Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Miriam Wittemann
- Department of Psychiatry and Psychotherapy, Saarland University, Saarbrücken, Germany
| | - Wolfgang Reith
- Department of Neuroradiology, Saarland University, Saarbrücken, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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18
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Abel T, Kim J, Vanrobaeys Y, Peterson Z, Kelvington B, Gaine M, Nickl-Jockschat T. Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders. RESEARCH SQUARE 2023:rs.3.rs-2565823. [PMID: 36824977 PMCID: PMC9949238 DOI: 10.21203/rs.3.rs-2565823/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and identified 3 genes of particular importance within the deleted region: thousand and one amino acid protein kinase 2 (Taok2), seizure-related 6 homolog-like 2 (Sez6l2), and major vault protein (Mvp). Using the CRISPR/Cas9 technique, we generated 3 gene hemi-deletion (3g del/+) mice carrying null mutations in Taok2, Sez6l2, and Mvp. We assessed striatum-dependent phenotypes of these 3g del/+ mice in behavioral, molecular, and imaging studies. Hemi-deletion of Taok2, Sez6l2, and Mvp induces sex-specific behavioral alterations in striatum-dependent behavioral tasks, specifically male-specific hyperactivity and impaired motivation for reward seeking, resembling behavioral phenotypes of 16p11.2 del/+ mice. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice, but only in males. Pathway analysis identified ribosomal dysfunction and translation dysregulation as molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice, unlike single gene mutation studies. These results support the importance of a polygenic approach to study NDDs and our novel strategy to identify genes of interest using gene expression patterns in brain regions, such as the striatum, which are impacted in these disorders.
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19
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Kim J, Vanrobaeys Y, Peterson Z, Kelvington B, Gaine ME, Nickl-Jockschat T, Abel T. Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.09.527866. [PMID: 36798381 PMCID: PMC9934710 DOI: 10.1101/2023.02.09.527866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and identified 3 genes of particular importance within the deleted region: thousand and one amino acid protein kinase 2 ( Taok2 ), seizure-related 6 homolog-like 2 ( Sez6l2 ), and major vault protein ( Mvp ). Using the CRISPR/Cas9 technique, we generated 3 gene hemi-deletion (3g del/+) mice carrying null mutations in Taok2, Sez6l2 , and Mvp . We assessed striatum-dependent phenotypes of these 3g del/+ mice in behavioral, molecular, and imaging studies. Hemi-deletion of Taok2, Sez6l2 , and Mvp induces sex-specific behavioral alterations in striatum-dependent behavioral tasks, specifically male-specific hyperactivity and impaired motivation for reward seeking, resembling behavioral phenotypes of 16p11.2 del/+ mice. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice, but only in males. Pathway analysis identified ribosomal dysfunction and translation dysregulation as molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice, unlike single gene mutation studies. These results support the importance of a polygenic approach to study NDDs and our novel strategy to identify genes of interest using gene expression patterns in brain regions, such as the striatum, which are impacted in these disorders.
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20
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Roberts RC, McCollum LA, Schoonover KE, Mabry SJ, Roche JK, Lahti AC. Ultrastructural evidence for glutamatergic dysregulation in schizophrenia. Schizophr Res 2022; 249:4-15. [PMID: 32014360 PMCID: PMC7392793 DOI: 10.1016/j.schres.2020.01.016] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/16/2020] [Accepted: 01/18/2020] [Indexed: 12/14/2022]
Abstract
The aim of this paper is to summarize ultrastructural evidence for glutamatergic dysregulation in several linked regions in postmortem schizophrenia brain. Following a brief summary of glutamate circuitry and how synapses are identified at the electron microscopic (EM) level, we will review EM pathology in the cortex and basal ganglia. We will include the effects of antipsychotic drugs and the relation of treatment response. We will discuss how these findings support or confirm other postmortem findings as well as imaging results. Briefly, synaptic and mitochondrial density in anterior cingulate cortex was decreased in schizophrenia, versus normal controls (NCs), in a selective layer specific pattern. In dorsal striatum, increases in excitatory synaptic density were detected in caudate matrix, a compartment associated with cognitive and motor function, and in the putamen patches, a region associated with limbic function and in the core of the nucleus accumbens. Patients who were treatment resistant or untreated had significantly elevated numbers of excitatory synapses in limbic striatal areas in comparison to NCs and responders. Protein levels of vGLUT2, found in subcortical glutamatergic neurons, were increased in the nucleus accumbens in schizophrenia. At the EM level, schizophrenia subjects had an increase in density of excitatory synapses in several areas of the basal ganglia. In the substantia nigra, the protein levels of vGLUT2 were elevated in untreated patients compared to NCs. The density of inhibitory synapses was decreased in schizophrenia versus NCs. In schizophrenia, glutamatergic synapses are differentially affected depending on the brain region, treatment status, and treatment response.
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Affiliation(s)
- Rosalinda C Roberts
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America.
| | - Lesley A McCollum
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America
| | - Kirsten E Schoonover
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America
| | - Samuel J Mabry
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America
| | - Joy K Roche
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama, Birmingham, AL 35294, United States of America
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21
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Sakreida K, Chiu WH, Dukart J, Eickhoff SB, Frodl T, Gaser C, Landgrebe M, Langguth B, Mirlach D, Rautu IS, Wittmann M, Poeppl TB. Disentangling dyskinesia from parkinsonism in motor structures of patients with schizophrenia. Brain Commun 2022; 4:fcac190. [PMID: 35912135 PMCID: PMC9337227 DOI: 10.1093/braincomms/fcac190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 05/09/2022] [Accepted: 07/20/2022] [Indexed: 11/29/2022] Open
Abstract
Patients with schizophrenia frequently suffer from motor abnormalities, but underlying alterations in neuroarchitecture remain unclear. Here, we aimed to disentangle dyskinesia from parkinsonism in motor structures of patients with schizophrenia and to assess associated molecular architecture. We measured grey matter of motor regions and correlated volumetric estimates with dyskinesia and parkinsonism severity. Associations with molecular architecture were identified by cross-modal spatial correlations between ensuing maps of abnormality-related volume alterations and neurotransmitter maps from healthy populations. Both phenomena were linked to (specific) striatal and basal forebrain reductions as well as to D1 receptor density. Dyskinesia also manifested in cerebellar decrease, while parkinsonism was associated with less motor cortex volume. The parkinsonism-related brain pattern was additionally associated with 5-HT1A/2A and µ-opioid receptors distribution. Findings suggest the need to develop psychopharmacological compounds that display not only selectivity for receptor subtypes but also anatomical selectivity for alleviating dyskinesia without worsening parkinsonism and vice versa.
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Affiliation(s)
- Katrin Sakreida
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University , Aachen 52074 , Germany
| | - Wei-Hua Chiu
- Department of Neurology, Grossman School of Medicine, New York University , New York, NY 10017 , USA
| | - Juergen Dukart
- Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich , Jülich 52425 , Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf , Düsseldorf 40225 , Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich , Jülich 52425 , Germany
- Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf , Düsseldorf 40225 , Germany
| | - Thomas Frodl
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University , Aachen 52074 , Germany
| | - Christian Gaser
- Department of Neurology, Jena University Hospital , Jena 07747 , Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital , Jena 07743 , Germany
| | - Michael Landgrebe
- Department of Psychiatry, Psychotherapy and Psychosomatics, kbo-Lech-Mangfall-Klinik Agatharied , Hausham 83734 , Germany
| | - Berthold Langguth
- Department of Psychiatry and Psychotherapy, University of Regensburg , Regensburg 93053 , Germany
| | - Daniela Mirlach
- Department of Psychiatry and Psychotherapy, University of Regensburg , Regensburg 93053 , Germany
| | - Ioana-Sabina Rautu
- Unité de Recherche en Neurosciences Cognitives (UNESCOG), Center for Research in Cognition and Neurosciences (CRCN), Université Libre de Bruxelles (ULB) , Brussels 1050 , Belgium
| | - Markus Wittmann
- Department of Psychiatry, Psychosomatics and Psychotherapy, District Hospital Wöllershof , Störnstein 92721 , Germany
| | - Timm B Poeppl
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University , Aachen 52074 , Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg , Regensburg 93053 , Germany
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22
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Korann V, Jacob A, Lu B, Devi P, Thonse U, Nagendra B, Maria Chacko D, Dey A, Padmanabha A, Shivakumar V, Dawn Bharath R, Kumar V, Varambally S, Venkatasubramanian G, Deshpande G, Rao NP. Effect of Intranasal Oxytocin on Resting-state Effective Connectivity in Schizophrenia. Schizophr Bull 2022; 48:1115-1124. [PMID: 35759349 PMCID: PMC9434443 DOI: 10.1093/schbul/sbac066] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVES Evidence from several lines of research suggests the critical role of neuropeptide oxytocin in social cognition and social behavior. Though a few studies have examined the effect of oxytocin on clinical symptoms of schizophrenia, the underlying neurobiological changes are underexamined. Hence, in this study, we examined the effect of oxytocin on the brain's effective connectivity in schizophrenia. METHODS 31 male patients with schizophrenia (SCZ) and 21 healthy male volunteers (HV) underwent resting functional magnetic resonance imaging scans with intra-nasal oxytocin (24 IU) and placebo administered in counterbalanced order. We conducted a whole-brain effective connectivity analysis using a multivariate vector autoregressive granger causality model. We performed a conjunction analysis to control for spurious changes and canonical correlation analysis between changes in connectivity and clinical and demographic variables. RESULTS Three connections, sourced from the left caudate survived the FDR correction threshold with the conjunction analysis; connections to the left supplementary motor area, left precentral gyrus, and left frontal inferior triangular gyrus. At baseline, SCZ patients had significantly weaker connectivity from caudate to these three regions. Oxytocin, but not placebo, significantly increased the strength of connectivity in these connections. Better cognitive insight and lower negative symptoms were associated with a greater increase in connectivity with oxytocin. CONCLUSIONS These findings provide a preliminary mechanistic understanding of the effect of oxytocin on brain connectivity in schizophrenia. The study findings provide the rationale to examine the potential utility of oxytocin for social cognitive deficits in schizophrenia.
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Affiliation(s)
| | | | - Bonian Lu
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA
| | - Priyanka Devi
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Umesh Thonse
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Bhargavi Nagendra
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Dona Maria Chacko
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Avyarthana Dey
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Anantha Padmanabha
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Venkataram Shivakumar
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Rose Dawn Bharath
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Vijay Kumar
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Shivarama Varambally
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Ganesan Venkatasubramanian
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | | | - Naren P Rao
- To whom correspondence should be addressed; tel: +91-80-26995879, e-mail:
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23
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Hirjak D, Schmitgen MM, Werler F, Wittemann M, Kubera KM, Wolf ND, Sambataro F, Calhoun VD, Reith W, Wolf RC. Multimodal MRI data fusion reveals distinct structural, functional and neurochemical correlates of heavy cannabis use. Addict Biol 2022; 27:e13113. [PMID: 34808703 DOI: 10.1111/adb.13113] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/24/2021] [Accepted: 10/29/2021] [Indexed: 12/19/2022]
Abstract
Heavy cannabis use (HCU) is frequently associated with a plethora of cognitive, psychopathological and sensorimotor phenomena. Although HCU is frequent, specific patterns of abnormal brain structure and function underlying HCU in individuals presenting without cannabis-use disorder or other current and life-time major mental disorders are unclear at present. This multimodal magnetic resonance imaging (MRI) study examined resting-state functional MRI (rs-fMRI) and structural MRI (sMRI) data from 24 persons with HCU and 16 controls. Parallel independent component analysis (p-ICA) was used to examine covarying components among grey matter volume (GMV) maps computed from sMRI and intrinsic neural activity (INA), as derived from amplitude of low-frequency fluctuations (ALFF) maps computed from rs-fMRI data. Further, we used JuSpace toolbox for cross-modal correlations between MRI-based modalities with nuclear imaging derived estimates, to examine specific neurotransmitter system changes underlying HCU. We identified two transmodal components, which significantly differed between the HCU and controls (GMV: p = 0.01, ALFF p = 0.03, respectively). The GMV component comprised predominantly cerebello-temporo-thalamic regions, whereas the INA component included fronto-parietal regions. Across HCU, loading parameters of both components were significantly associated with distinct HCU behavior. Finally, significant associations between GMV and the serotonergic system as well as between INA and the serotonergic, dopaminergic and μ-opioid receptor system were detected. This study provides novel multimodal neuromechanistic insights into HCU suggesting co-altered structure/function-interactions in neural systems subserving cognitive and sensorimotor functions.
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Affiliation(s)
- Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim Heidelberg University Mannheim Germany
| | - Mike M. Schmitgen
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Florian Werler
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Miriam Wittemann
- Department of Psychiatry and Psychotherapy Saarland University Saarbrücken Germany
| | - Katharina M. Kubera
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Nadine D. Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Fabio Sambataro
- Department of Neurosciences, Padua Neuroscience Center University of Padua Padua Italy
| | - Vince D. Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology Emory University Atlanta Georgia USA
| | - Wolfgang Reith
- Department of Neuroradiology Saarland University Saarbrücken Germany
| | - Robert Christian Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
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24
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Damme KSF, Gupta T, Haase CM, Mittal VA. Responses to positive affect and unique resting-state connectivity in individuals at clinical high-risk for psychosis. Neuroimage Clin 2022; 33:102946. [PMID: 35091254 PMCID: PMC8800133 DOI: 10.1016/j.nicl.2022.102946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/10/2021] [Accepted: 01/19/2022] [Indexed: 11/25/2022]
Abstract
Individuals at clinical high-risk for psychosis (CHR) report dampened positive affect, while this deficit appears to be an important clinical marker, our current understanding of underlying causes is limited. Dysfunctional regulatory strategies (i.e., abnormal use of dampening, self-focused, or emotion-focused strategies) may account for dampening affect but has not yet been examined. Participants (57 CHR and 56 healthy controls) completed the Response to Positive Affect Scale, clinical interviews, and resting-state scan examining nucleus accumbens (NAcc) connectivity. Individuals at CHR for psychosis showed greater dampening (but no differences in self/emotion-focus) in self-reported response to positive affect compared to healthy controls. In individuals at CHR, higher levels of dampening and lower levels of self-focus were associated with higher positive and lower negative symptoms. Dampening responses were related to decreased dorsal and rostral anterior cingulate cortex-NAcc resting-state connectivity in the CHR group but increased dorsal and rostral anterior cingulate cortex-NAcc resting-state connectivity in the healthy control group. Self-focused responses were related to increased dorsolateral prefrontal cortex-NAcc resting-state connectivity in the CHR group but decreased resting-state connectivity in the healthy control group. Self-reported dampening of positive affect was elevated in individuals at CHR for psychosis. Dampening and self-focused responses were associated with distinct resting-state connectivity compared to peers, suggesting unique mechanisms underlying these emotion regulation strategies. Responses to positive affect may be a useful target for cognitive treatment, but individuals at CHR show distinct neurocorrelates and may require a tailored approach.
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Affiliation(s)
- Katherine S F Damme
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Evanston and Chicago, IL, USA.
| | - Tina Gupta
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Evanston and Chicago, IL, USA
| | - Claudia M Haase
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Evanston and Chicago, IL, USA; Human Development and Social Policy, Northwestern University, Evanston, IL, USA; Institute for Policy Research (IPR), Northwestern University, Chicago, IL, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Evanston and Chicago, IL, USA; Human Development and Social Policy, Northwestern University, Evanston, IL, USA; Institute for Policy Research (IPR), Northwestern University, Chicago, IL, USA; Department of Psychiatry, Northwestern University, Chicago, IL, USA; Medical Social Sciences, Northwestern University, Chicago, IL, USA
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25
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Tadayonnejad R, Majid DA, Tsolaki E, Rane R, Wang H, Moody TD, Pauli WM, Pouratian N, Bari AA, Murray SB, O'Doherty JP, Feusner JD. Mesolimbic Neurobehavioral Mechanisms of Reward Motivation in Anorexia Nervosa: A Multimodal Imaging Study. Front Psychiatry 2022; 13:806327. [PMID: 35321230 PMCID: PMC8934777 DOI: 10.3389/fpsyt.2022.806327] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 02/10/2022] [Indexed: 01/04/2023] Open
Abstract
Diminished motivation to pursue and obtain primary and secondary rewards has been demonstrated in anorexia nervosa (AN). However, the neurobehavioral mechanisms underlying the behavioral activation component of aberrant reward motivation remains incompletely understood. This work aims to explore this underexplored facet of reward motivation in AN. We recruited female adolescents with AN, restricting type (n = 32) and a healthy control group (n = 28). All participants underwent functional magnetic resonance imaging (fMRI) while performing a monetary reward task. Diffusion MRI data was also collected to examine the reward motivation circuit's structural connectivity. Behavioral results demonstrated slower speed of reward-seeking behavior in those with AN compared with controls. Accompanying this was lower functional connectivity and reduced white matter structural integrity of the connection between the ventral tegmental area/substantia nigra pars compacta and the nucleus accumbens within the mesolimbic circuit. Further, there was evidence of neurobehavioral decoupling in AN between reward-seeking behavior and mesolimbic regional activation and functional connectivity. Aberrant activity of the bed nucleus of the stria terminalis (BNST) and its connectivity with the mesolimbic system was also evident in AN during the reward motivation period. Our findings suggest functional and structural dysconnectivity within a mesolimbic reward circuit, neurofunctional decoupling from reward-seeking behavior, and abnormal BNST function and circuit interaction with the mesolimbic system. These results show behavioral indicators of aberrant reward motivation in AN, particularly in its activational component. This is mediated neuronally by mesolimbic reward circuit functional and structural dysconnectivity as well as neurobehavioral decoupling. Based on these findings, we suggest a novel circuit-based mechanism of impaired reward processing in AN, with the potential for translation to developing more targeted and effective treatments in this difficult-to-treat psychiatric condition.
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Affiliation(s)
- Reza Tadayonnejad
- Division of Neuromodulation, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, United States
| | - Ds-Adnan Majid
- Cognitive Neuroscience, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Evangelia Tsolaki
- Department of Neursurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Riddhi Rane
- Cognitive Neuroscience, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Huan Wang
- Cognitive Neuroscience, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Teena D Moody
- Cognitive Neuroscience, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Wolfgang M Pauli
- Artificial Intelligence Platform, Microsoft, Redmon, WA, United States
| | - Nader Pouratian
- Department of Neursurgery, University of California, Los Angeles, Los Angeles, CA, United States.,University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Ausaf A Bari
- Department of Neursurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Stuart B Murray
- Department of Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, CA, United States
| | - John P O'Doherty
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, United States.,Computation & Neural Systems Program, California Institute of Technology, Pasadena, CA, United States
| | - Jamie D Feusner
- Cognitive Neuroscience, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
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26
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Sambataro F, Hirjak D, Fritze S, Kubera KM, Northoff G, Calhoun VD, Meyer‐Lindenberg A, Wolf RC. Intrinsic neural network dynamics in catatonia. Hum Brain Mapp 2021; 42:6087-6098. [PMID: 34585808 PMCID: PMC8596986 DOI: 10.1002/hbm.25671] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/07/2021] [Accepted: 09/16/2021] [Indexed: 12/17/2022] Open
Abstract
Catatonia is a transnosologic psychomotor syndrome with high prevalence in schizophrenia spectrum disorders (SSD). There is mounting neuroimaging evidence that catatonia is associated with aberrant frontoparietal, thalamic and cerebellar regions. Large-scale brain network dynamics in catatonia have not been investigated so far. In this study, resting-state fMRI data from 58 right-handed SSD patients were considered. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). Group spatial independent component analysis was carried out with a multiple analysis of covariance (MANCOVA) approach to estimate and test the underlying intrinsic components (ICs) in SSD patients with (NCRS total score ≥ 3; n = 30) and without (NCRS total score = 0; n = 28) catatonia. Functional network connectivity (FNC) during rest was calculated between pairs of ICs and transient changes in connectivity were estimated using sliding windowing and clustering (to capture both static and dynamic FNC). Catatonic patients showed increased static FNC in cerebellar networks along with decreased low frequency oscillations in basal ganglia (BG) networks. Catatonic patients had reduced state changes and dwelled more in a state characterized by high within-network correlation of the sensorimotor, visual, and default-mode network with respect to noncatatonic patients. Finally, in catatonic patients according to DSM-IV-TR (n = 44), there was a significant correlation between increased within FNC in cortico-striatal state and NCRS motor scores. The data support a neuromechanistic model of catatonia that emphasizes a key role of disrupted sensorimotor network control during distinct functional states.
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Affiliation(s)
- Fabio Sambataro
- Department of Neuroscience (DNS)University of PadovaPadovaItaly
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Katharina M. Kubera
- Center for Psychosocial Medicine, Department of General PsychiatryHeidelberg UniversityGermany
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health ResearchUniversity of OttawaOttawaOntarioCanada
| | - Vince D. Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of TechnologyEmory UniversityAtlantaGeorgia
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg UniversityMannheimGermany
| | - Robert C. Wolf
- Center for Psychosocial Medicine, Department of General PsychiatryHeidelberg UniversityGermany
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27
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Kesby JP, Murray GK, Knolle F. Neural Circuitry of Salience and Reward Processing in Psychosis. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 3:33-46. [PMID: 36712572 PMCID: PMC9874126 DOI: 10.1016/j.bpsgos.2021.12.003] [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] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/25/2021] [Accepted: 12/01/2021] [Indexed: 02/01/2023] Open
Abstract
The processing of salient and rewarding stimuli is integral to engaging our attention, stimulating anticipation for future events, and driving goal-directed behaviors. Widespread impairments in these processes are observed in psychosis, which may be associated with worse functional outcomes or mechanistically linked to the development of symptoms. Here, we summarize the current knowledge of behavioral and functional neuroimaging in salience, prediction error, and reward. Although each is a specific process, they are situated in multiple feedback and feedforward systems integral to decision making and cognition more generally. We argue that the origin of salience and reward processing dysfunctions may be centered in the subcortex during the earliest stages of psychosis, with cortical abnormalities being initially more spared but becoming more prominent in established psychotic illness/schizophrenia. The neural circuits underpinning salience and reward processing may provide targets for delaying or preventing progressive behavioral and neurobiological decline.
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Affiliation(s)
- James P. Kesby
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia,QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia,Address correspondence to James Kesby, Ph.D.
| | - Graham K. Murray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia,Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Franziska Knolle
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom,Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany,Franziska Knolle, Ph.D.
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28
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Saleh Y, Jarratt-Barnham I, Fernandez-Egea E, Husain M. Mechanisms Underlying Motivational Dysfunction in Schizophrenia. Front Behav Neurosci 2021; 15:709753. [PMID: 34566594 PMCID: PMC8460905 DOI: 10.3389/fnbeh.2021.709753] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/20/2021] [Indexed: 12/24/2022] Open
Abstract
Negative symptoms are a debilitating feature of schizophrenia which are often resistant to pharmacological intervention. The mechanisms underlying them remain poorly understood, and diagnostic methods rely on phenotyping through validated questionnaires. Deeper endo-phenotyping is likely to be necessary in order to improve current understanding. In the last decade, valuable behavioural insights have been gained through the use of effort-based decision making (EBDM) tasks. These have highlighted impairments in reward-related processing in schizophrenia, particularly associated with negative symptom severity. Neuroimaging investigations have related these changes to dysfunction within specific brain networks including the ventral striatum (VS) and frontal brain regions. Here, we review the behavioural and neural evidence associated with negative symptoms, shedding light on potential underlying mechanisms and future therapeutic possibilities. Findings in the literature suggest that schizophrenia is characterised by impaired reward based learning and action selection, despite preserved hedonic responses. Associations between amotivation and reward-processing deficits have not always been clear, and may be mediated by factors including cognitive dysfunction or dysfunctional or self-defeatist beliefs. Successful endo-phenotyping of negative symptoms as a function of objective behavioural and neural measurements is crucial in advancing our understanding of this complex syndrome. Additionally, transdiagnostic research–leveraging findings from other brain disorders, including neurological ones–can shed valuable light on the possible common origins of motivation disorders across diseases and has important implications for future treatment development.
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Affiliation(s)
- Youssuf Saleh
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Isaac Jarratt-Barnham
- Department of Psychiatry, Herchel Smith Building for Brain & Mind Sciences, University of Cambridge, Cambridge, United Kingdom.,Cambridge Psychosis Centre, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Emilio Fernandez-Egea
- Department of Psychiatry, Herchel Smith Building for Brain & Mind Sciences, University of Cambridge, Cambridge, United Kingdom.,Cambridge Psychosis Centre, Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
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29
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Wolf RC, Werler F, Wittemann M, Schmitgen MM, Kubera KM, Wolf ND, Reith W, Hirjak D. Structural correlates of sensorimotor dysfunction in heavy cannabis users. Addict Biol 2021; 26:e13032. [PMID: 33951262 DOI: 10.1111/adb.13032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/21/2021] [Accepted: 03/05/2021] [Indexed: 12/12/2022]
Abstract
Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination and sensorimotor integration. Whether such abnormalities may also apply to non-dependent individuals with heavy cannabis use (HCU) is unknown, as much as the neural correlates underlying such deficits. In this study, we investigated associations between NSS and gray matter volume (GMV) in males with HCU and male controls. Twenty-four persons with HCU and 17 controls were examined using standardized assessment of NSS and structural magnetic resonance imaging (MRI) at 3 T. GMV was calculated using voxel-based morphometry algorithms provided by the Computational Anatomy Toolbox (CAT12). Individuals with HCU showed higher NSS total scores compared to controls. In particular, significant NSS-subdomain effects were found for "motor coordination" (MoCo), "complex motor tasks" (CoMT), and "hard signs" (HS) expression in HCU (p < 0.05, Bonferroni-corrected). Compared to controls, persons with HCU showed significant NSS/GMV interactions in putamen and inferior frontal cortex (MoCo), right cerebellum (CoMT) and middle and superior frontal cortices, and bilateral precentral cortex and thalamus (HS). In between-group analyses, individuals with HCU showed lower GMV in the right anterior orbital and precentral gyrus, as well as higher GMV in the right superior frontal gyrus and left supplementary motor cortex compared to controls. The data support the notion of abnormal sensorimotor performance associated with HCU. The data also provide a neuromechanistic understanding of such deficits, particularly with respect to aberrant cortical-thalamic-cerebellar-cortical circuit.
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Affiliation(s)
- Robert Christian Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Heidelberg Germany
| | - Florian Werler
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Heidelberg Germany
| | - Miriam Wittemann
- Department of Psychiatry and Psychotherapy Saarland University Saarbrücken Germany
| | - Mike M. Schmitgen
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Heidelberg Germany
| | - Katharina M. Kubera
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Heidelberg Germany
| | - Nadine D. Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Heidelberg Germany
| | - Wolfgang Reith
- Department of Neuroradiology Saarland University Saarbrücken Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim Heidelberg University Mannheim Germany
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30
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[The sensorimotor domain in the research domain criteria system: progress and perspectives]. DER NERVENARZT 2021; 92:915-924. [PMID: 34115150 DOI: 10.1007/s00115-021-01144-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/30/2021] [Indexed: 10/21/2022]
Abstract
Over the past three decades research interest in hypokinetic, hyperkinetic, sensorimotor and psychomotor abnormalities in mental disorders has steadily increased. This development has led to an increasing number of scientific initiatives that have not only highlighted the clinical need for early detection of extrapyramidal motor symptoms, tardive dyskinesia and catatonia but also provided numerous neurobiological findings and clinically relevant results based on the pathology of the sensorimotor system in patients with mental disorders. In view of these developments in January 2019 the National Institute of Mental Health (NIMH) research domain criteria (RDoC) initiative introduced a sixth domain called the sensorimotor domain to address deficits in the sensorimotor system and associated behavioral abnormalities. To draw attention to the rapid progress just since the introduction of the sensorimotor domain, a 2-year (1 January 2019-18 February 2021) systematic review is presented highlighting recent neuroimaging findings and discussing challenges for future research. In summary, aberrant sensorimotor processing in mental disorders is associated with dysfunction of the cerebello-thalamo-motor cortex network, which interacts with (social)cognitive and affective systems. Initial longitudinal and interventional studies highlight the translational potential of the sensorimotor domain.
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Janouschek H, Chase HW, Sharkey RJ, Peterson ZJ, Camilleri JA, Abel T, Eickhoff SB, Nickl-Jockschat T. The functional neural architecture of dysfunctional reward processing in autism. Neuroimage Clin 2021; 31:102700. [PMID: 34161918 PMCID: PMC8239466 DOI: 10.1016/j.nicl.2021.102700] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 05/10/2021] [Accepted: 05/11/2021] [Indexed: 12/30/2022]
Abstract
Functional imaging studies have found differential neural activation patterns during reward-paradigms in patients with autism spectrum disorder (ASD) compared to neurotypical controls. However, publications report conflicting results on the directionality and location of these aberrant activations. We here quantitatively summarized relevant fMRI papers in the field using the anatomical likelihood estimation (ALE) algorithm. Patients with ASD consistently showed hypoactivations in the striatum across studies, mainly in the right putamen and accumbens. These regions are functionally involved in the processing of rewards and are enrolled in extensive neural networks involving limbic, cortical, thalamic and mesencephalic regions. The striatal hypo-activations found in our ALE meta-analysis, which pooled over contrasts derived from the included studies on reward-processing in ASD, highlight the role of the striatum as a key neural correlate of impaired reward processing in autism. These changes were present for studies using social and non-social stimuli alike. The involvement of these regions in extensive networks associated with the processing of both positive and negative emotion alike might hint at broader impairments of emotion processing in the disorder.
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Affiliation(s)
- Hildegard Janouschek
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Rachel J Sharkey
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Zeru J Peterson
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Julia A Camilleri
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ted Abel
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Thomas Nickl-Jockschat
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychiatry, University of Iowa, Iowa City, IA, USA; Department of Neuroscience and Pharmacology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
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Baranger DAA, Lindenmuth M, Nance M, Guyer AE, Keenan K, Hipwell AE, Shaw DS, Forbes EE. The longitudinal stability of fMRI activation during reward processing in adolescents and young adults. Neuroimage 2021; 232:117872. [PMID: 33609668 PMCID: PMC8238413 DOI: 10.1016/j.neuroimage.2021.117872] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 02/12/2021] [Accepted: 02/13/2021] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND The use of functional neuroimaging has been an extremely fruitful avenue for investigating the neural basis of human reward function. This approach has included identification of potential neurobiological mechanisms of psychiatric disease and examination of environmental, experiential, and biological factors that may contribute to disease risk via effects on the reward system. However, a central and largely unexamined assumption of much of this research is that neural reward function is an individual difference characteristic that is relatively stable and trait-like over time. METHODS In two independent samples of adolescents and young adults studied longitudinally (Ns = 145 & 139, 100% female and 100% male, ages 15-21 and 20-22, 2-4 scans and 2 scans respectively), we tested within-person stability of reward-task BOLD activation, with a median of 1 and 2 years between scans. We examined multiple commonly used contrasts of active states and baseline in both the anticipation and feedback phases of a card-guessing reward task. We examined the effects of cortical parcellation resolution, contrast, network (reward regions and resting-state networks), region-size, and activation strength and variability on the stability of reward-related activation. RESULTS In both samples, contrasts of an active state relative to a baseline were more stable (ICC: intra-class correlation; e.g., Win>Baseline; mean ICC = 0.13 - 0.33) than contrasts of two active states (e.g., Win>Loss; mean ICC = 0.048 - 0.05). Additionally, activation in reward regions was less stable than in many non-task networks (e.g., dorsal attention), and activation in regions with greater between-subject variability showed higher stability in both samples. CONCLUSIONS These results show that some contrasts from functional neuroimaging activation during a card guessing reward task have partially trait-like properties in adolescent and young adult samples over 1-2 years. Notably, results suggest that contrasts intended to map cognitive function and show robust group-level effects (i.e. Win > Loss) may be less effective in studies of individual differences and disease risk. The robustness of group-level activation should be weighed against other factors when selecting regions of interest in individual difference fMRI studies.
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Affiliation(s)
- David A A Baranger
- University of Pittsburgh School of Medicine, Department of Psychiatry, 121 Meyran Avenue, Pittsburgh, PA 15213, United States.
| | - Morgan Lindenmuth
- University of Pittsburgh School of Medicine, Department of Psychiatry, 121 Meyran Avenue, Pittsburgh, PA 15213, United States
| | - Melissa Nance
- University of Pittsburgh School of Medicine, Department of Psychiatry, 121 Meyran Avenue, Pittsburgh, PA 15213, United States
| | - Amanda E Guyer
- Center for Mind and Brain, University of California Davis, Davis, CA, United States; Department of Human Ecology, University of California Davis, Davis, CA, United States
| | - Kate Keenan
- University of Chicago, Department of Psychiatry and Behavioral Neuroscience, Chicago, IL, United States
| | - Alison E Hipwell
- University of Pittsburgh School of Medicine, Department of Psychiatry, 121 Meyran Avenue, Pittsburgh, PA 15213, United States
| | - Daniel S Shaw
- University of Pittsburgh, Department of Psychology, Pittsburgh, PA, United States
| | - Erika E Forbes
- University of Pittsburgh School of Medicine, Department of Psychiatry, 121 Meyran Avenue, Pittsburgh, PA 15213, United States; University of Pittsburgh, Department of Psychology, Pittsburgh, PA, United States
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Leroy A, Amad A, D'Hondt F, Pins D, Jaafari N, Thomas P, Jardri R. Reward anticipation in schizophrenia: A coordinate-based meta-analysis. Schizophr Res 2020; 218:2-6. [PMID: 31948895 DOI: 10.1016/j.schres.2019.12.041] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 12/26/2019] [Accepted: 12/31/2019] [Indexed: 11/17/2022]
Abstract
Reward processing impairments have been linked with positive and negative symptoms of schizophrenia. Here, we performed a coordinate-based meta-analysis that combined eleven BOLD-fMRI studies comparing reward anticipation signals between schizophrenia patients and healthy controls. We observed a reduced difference in activation in schizophrenia patients within a frontal-striatal network. Meta-regressions revealed that this functional signature was linked to the severity of psychotic symptoms and persisted even after controlling for the dose of antipsychotic medications.
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Affiliation(s)
- Arnaud Leroy
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France.
| | - Ali Amad
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France; Groupement De Recherche en Psychiatrie CNRS-3557, France
| | - Fabien D'Hondt
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France; Centre national de ressources et de résilience Lille-Paris (CN2R), Lille, France
| | - Delphine Pins
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France; Groupement De Recherche en Psychiatrie CNRS-3557, France
| | - Nematollah Jaafari
- Groupement De Recherche en Psychiatrie CNRS-3557, France; Unité de Recherche Clinique Intersectorielle en Psychiatrie Pierre Deniker, Centre Hospitalier Henri Laborit, 86021 Poitiers, France; Univ. Poitiers & CHU Poitiers, INSERM U1084, Laboratoire Expérimental et Clinique en Neurosciences, 86021 Poitiers, France
| | - Pierre Thomas
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France; Groupement De Recherche en Psychiatrie CNRS-3557, France
| | - Renaud Jardri
- Univ. Lille, INSERM U1172, CHU Lille, Centre Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Hôpital Fontan, plateforme CURE, F-59000 Lille, France; Groupement De Recherche en Psychiatrie CNRS-3557, France
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Openshaw RL, Thomson DM, Thompson R, Penninger JM, Pratt JA, Morris BJ, Dawson N. Map2k7 Haploinsufficiency Induces Brain Imaging Endophenotypes and Behavioral Phenotypes Relevant to Schizophrenia. Schizophr Bull 2020; 46:211-223. [PMID: 31219577 PMCID: PMC6942167 DOI: 10.1093/schbul/sbz044] [Citation(s) in RCA: 10] [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] [Indexed: 12/14/2022]
Abstract
c-Jun N-terminal kinase (JNK) signaling contributes to functional plasticity in the brain and cognition. Accumulating evidence implicates a role for MAP kinase kinase 7 (MAP2K7), a JNK activator encoded by the Map2k7 gene, and other JNK pathway components in schizophrenia (ScZ). Mice haploinsufficient for Map2k7 (Map2k7+/- mice) display ScZ-relevant cognitive deficits, although the mechanisms are unclear. Here we show that Map2k7+/- mice display translationally relevant alterations in brain function, including hippocampal and mesolimbic system hypermetabolism with a contrasting prefrontal cortex (PFC) hypometabolism, reminiscent of patients with ScZ. In addition Map2k7+/- mice show alterations in functional brain network connectivity paralleling those reported in early ScZ, including PFC and hippocampal hyperconnectivity and compromised mesolimbic system functional connectivity. We also show that although the cerebral metabolic response to ketamine is preserved, the response to dextroamphetamine (d-amphetamine) is significantly attenuated in Map2k7+/- mice, supporting monoamine neurotransmitter system dysfunction but not glutamate/NMDA receptor (NMDA-R) dysfunction as a consequence of Map2k7 haploinsufficiency. These effects are mirrored behaviorally with an attenuated impact of d-amphetamine on sensorimotor gating and locomotion, whereas similar deficits produced by ketamine are preserved, in Map2k7+/- mice. In addition, Map2k7+/- mice show a basal hyperactivity and sensorimotor gating deficit. Overall, these data suggest that Map2k7 modifies brain and monoamine neurotransmitter system function in a manner relevant to the positive and cognitive symptoms of ScZ.
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Affiliation(s)
- Rebecca L Openshaw
- Institute of Neuroscience and Psychology, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UK
| | - David M Thomson
- Strathclyde Institute of Pharmacy and Biomedical Science, University of Strathclyde, Glasgow, UK
| | - Rhiannon Thompson
- Institute of Neuroscience and Psychology, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UK
| | - Josef M Penninger
- Institute for Molecular Biotechnology of Austrian Academy of Sciences (IMBA), Vienna, Austria
| | - Judith A Pratt
- Strathclyde Institute of Pharmacy and Biomedical Science, University of Strathclyde, Glasgow, UK
| | - Brian J Morris
- Institute of Neuroscience and Psychology, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UK
| | - Neil Dawson
- Division of Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster University, Lancaster, UK,To whom correspondence should be addressed; tel: +44 (0)1524 594 896, e-mail:
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Chase HW, Loriemi P, Wensing T, Eickhoff SB, Nickl-Jockschat T. Meta-analytic evidence for altered mesolimbic responses to reward in schizophrenia. Hum Brain Mapp 2018; 39:2917-2928. [PMID: 29573046 DOI: 10.1002/hbm.24049] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 01/25/2018] [Accepted: 03/08/2018] [Indexed: 11/08/2022] Open
Abstract
Dysfunction of reward-related neural circuitry in schizophrenia (SCZ) has been widely reported, and may provide insight into the motivational and cognitive disturbances that characterize the disorder. Although previous meta-analyses of reward learning paradigms in SCZ have been performed, a meta-analysis of whole-brain coordinate maps in SCZ alone has not been conducted. In this study, we performed an activation likelihood estimate (ALE) meta-analysis, and performed a follow-up analysis of functional connectivity and functional decoding of identified regions. We report several salient findings that extend prior work in this area. First, an alteration in reward-related activation was observed in the right ventral striatum, but this was not solely driven by hypoactivation in the SCZ group compared to healthy controls. Second, the region was characterized by functional connectivity primarily with the lateral prefrontal cortex and pre-supplementary motor area (preSMA), as well as subcortical regions such as the thalamus which show structural deficits in SCZ. Finally, although the meta-analysis showed no regions outside the ventral striatum to be significantly altered, regions with higher functional connectivity with the ventral striatum showed a greater number of subthreshold foci. Together, these findings confirm the alteration of ventral striatal function in SCZ, but suggest that a network-based approach may assist future analysis of the functional underpinnings of the disorder.
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Affiliation(s)
- Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Polina Loriemi
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.,Juelich Aachen Research Alliance - Translational Brain Medicine, Aachen, Germany
| | - Tobias Wensing
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.,Juelich Aachen Research Alliance - Translational Brain Medicine, Aachen, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.,Juelich Aachen Research Alliance - Translational Brain Medicine, Aachen, Germany.,Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, USA.,Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
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