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Maitra R, Lemmers-Jansen ILJ, Vooren M, Vanes L, Szentgyorgyi T, Crisp C, Mouchlianitis E, Shergill SS. Understanding the mechanisms underlying cognitive control in psychosis. Psychol Med 2024:1-10. [PMID: 38780379 DOI: 10.1017/s0033291724001119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
BACKGROUND Cognitive control (CC) involves a top-down mechanism to flexibly respond to complex stimuli and is impaired in schizophrenia. METHODS This study investigated the impact of increasing complexity of CC processing in 140 subjects with psychosis and 39 healthy adults, with assessments of behavioral performance, neural regions of interest and symptom severity. RESULTS The lowest level of CC (Stroop task) was impaired in all patients; the intermediate level of CC (Faces task) with explicit emotional information was most impaired in patients with first episode psychosis. Patients showed activation of distinct neural CC and reward networks, but iterative learning based on the higher-order of CC during the trust game, was most impaired in chronic schizophrenia. Subjects with first episode psychosis, and patients with lower symptom load, demonstrate flexibility of the CC network to facilitate learning, which appeared compromised in the more chronic stages of schizophrenia. CONCLUSION These data suggest optimal windows for opportunities to introduce therapeutic interventions to improve CC.
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Affiliation(s)
- R Maitra
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Tavistock and Portman NHS Foundation Trust, London, UK
| | - I L J Lemmers-Jansen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Clinical, Neuro and Developmental Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Institute for Brain and Behavior Amsterdam (iBBA), Amsterdam, Netherlands
| | - M Vooren
- Faculty of Behavioural and Movement Sciences, Educational Studies, Section Methods and Statistics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- LEARN! Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Amsterdam Center for Learning Analytics (ACLA), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lucy Vanes
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Timea Szentgyorgyi
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Charlotte Crisp
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Elias Mouchlianitis
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology, University of East London, London, UK
| | - S S Shergill
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Kent and Medway Medical School, University of Kent, Canterbury, UK
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2
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Chen J, Wei Y, Xue K, Han S, Li W, Zhou B, Cheng J. Abnormal effective connectivity of reward network in first-episode schizophrenia with auditory verbal hallucinations. J Psychiatr Res 2024; 171:207-214. [PMID: 38309210 DOI: 10.1016/j.jpsychires.2024.01.023] [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: 07/06/2023] [Revised: 12/02/2023] [Accepted: 01/15/2024] [Indexed: 02/05/2024]
Abstract
OBJECTIVE Auditory verbal hallucinations (AVHs) in schizophrenia is proved to be associated with dysfunction of mesolimbic-cortical circuits, especially during abnormal salient and internal verbal resource monitoring processing procedures. However, the information flow among areas involved in coordinated interaction implicated the pathophysiology of AVHs remains unclear. METHODS We used spectral dynamic causal modeling (DCM) to quantify connections among eight critical hubs of reward network in 86 first-episode drug-naïve schizophrenia patients with AVHs (AVH), 93 patients without AVHs (NAVH), and 88 matched normal controls (NC) using resting-state functional magnetic resonance imaging. Group-level connection coefficients, between-group differences and correlation analysis between image measures and symptoms were performed. RESULT DCM revealed weaker effective connectivity (EC) from right ventral striatum (RVS) to ventral tegmental area (VTA) in AVH compared to NAVH. AVH showed stronger EC from left anterior insula (AI) to RVS, stronger EC from RVS to anterior cingulate cortex (ACC), and stronger EC from VTA to posterior cingulate cortex (PCC) compared to NC. The correlation analysis results were mostly visible in the negative correlation between EC from right AI to ACC and positive sub-score, P1 sub-score, and P3 sub-score of PNASS in group-level. CONCLUSION These findings suggest that neural causal interactions between the reward network associated with AVHs are disrupted, expanding the evidence for potential neurobiological mechanisms of AVHs. Particularly, dopamine-dependent salience attribution and top-down monitoring impairments and compensatory effects of enhanced excitatory afferents to ACC, which may provide evidence for a therapeutic target based on direct in vivo of AVHs in schizophrenia.
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Affiliation(s)
- Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Kangkang Xue
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Wenbin Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China; Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, 450052, China.
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Hamzehpour L, Bohn T, Jaspers L, Grimm O. Exploring the link between functional connectivity of ventral tegmental area and physical fitness in schizophrenia and healthy controls. Eur Neuropsychopharmacol 2023; 76:77-86. [PMID: 37562082 DOI: 10.1016/j.euroneuro.2023.07.009] [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: 11/21/2022] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 08/12/2023]
Abstract
Decreased physical fitness and being overweight are highly prevalent in schizophrenia, represent a major risk factor for comorbid cardio-vascular diseases and decrease the life expectancy of the patients. Thus, it is important to understand the underlying mechanisms that link psychopathology and weight gain. We hypothesize that the dopaminergic reward system plays an important role in this. We analyzed the seed-based functional connectivity (FC) of the ventral tegmental area (VTA) in a group of schizophrenic patients (n=32) and age-, as well as gender-, matched healthy controls (n=27). We then correlated the resting-state results with physical fitness parameters, obtained in a fitness test, and psychopathology. The FC analysis revealed decreased functional connections between the VTA and the anterior cingulate cortex (ACC), as well as the dorsolateral prefrontal cortex, which negatively correlated with psychopathology, and increased FC between the VTA and the middle temporal gyrus in patients compared to healthy controls, which positively correlated with psychopathology. The decreased FC between the VTA and the ACC of the patient group further positively correlated with total body fat (p = .018, FDR-corr.) and negatively correlated with the overall physical fitness (p = .022). This study indicates a link between decreased physical fitness and higher body fat with functional dysconnectivity between the VTA and the ACC. These findings demonstrate that a dysregulated reward system might also be involved in comorbidities and could pave the way for future lifestyle therapy interventions.
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Affiliation(s)
- Lara Hamzehpour
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany; Goethe University Frankfurt, Faculty 15 Biological Sciences, Frankfurt am Main, Germany.
| | - Tamara Bohn
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
| | - Lucia Jaspers
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
| | - Oliver Grimm
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Heinrich-Hoffmann-Straße 10, 60528, Frankfurt am Main, Germany
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Cao H, Lencz T, Gallego JA, Rubio JM, John M, Barber AD, Birnbaum ML, Robinson DG, Malhotra AK. A Functional Connectome-Based Neural Signature for Individualized Prediction of Antipsychotic Response in First-Episode Psychosis. Am J Psychiatry 2023; 180:827-835. [PMID: 37644811 PMCID: PMC11104773 DOI: 10.1176/appi.ajp.20220719] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
OBJECTIVE Identification of robust biomarkers that predict individualized response to antipsychotic treatment at the early stage of psychotic disorders remains a challenge in precision psychiatry. The aim of this study was to investigate whether any functional connectome-based neural traits could serve as such a biomarker. METHODS In a discovery sample, 49 patients with first-episode psychosis received multi-paradigm fMRI scans at baseline and were clinically followed up for 12 weeks under antipsychotic monotherapies. Treatment response was evaluated at the individual level based on the psychosis score of the Brief Psychiatric Rating Scale. Cross-paradigm connectivity and connectome-based predictive modeling were employed to train a predictive model that uses baseline connectomic measures to predict individualized change rates of psychosis scores, with model performance evaluated as the Pearson correlations between the predicted change rates and the observed change rates, based on cross-validation. The model generalizability was further examined in an independent validation sample of 24 patients in a similar design. RESULTS The results revealed a paradigm-independent connectomic trait that significantly predicted individualized treatment outcome in both the discovery sample (predicted-versus-observed r=0.41) and the validation sample (predicted-versus-observed r=0.47, mean squared error=0.019). Features that positively predicted psychosis change rates primarily involved connections related to the cerebellar-cortical circuitry, and features that negatively predicted psychosis change rates were chiefly connections within the cortical cognitive systems. CONCLUSIONS This study discovers and validates a connectome-based functional signature as a promising early predictor for individualized response to antipsychotic treatment in first-episode psychosis, thus highlighting the potential clinical value of this biomarker in precision psychiatry.
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Affiliation(s)
- Hengyi Cao
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Todd Lencz
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Juan A Gallego
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Jose M Rubio
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Majnu John
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Anita D Barber
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Michael L Birnbaum
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Delbert G Robinson
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
| | - Anil K Malhotra
- Institute of Behavioral Sciences, Feinstein Institutes for Medical Research, Manhasset, N.Y. (all authors); Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, N.Y. (all authors); Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, N.Y. (all authors)
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5
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Dominicus LS, van Rijn L, van der A J, van der Spek R, Podzimek D, Begemann M, de Haan L, van der Pluijm M, Otte WM, Cahn W, Röder CH, Schnack HG, van Dellen E. fMRI connectivity as a biomarker of antipsychotic treatment response: A systematic review. Neuroimage Clin 2023; 40:103515. [PMID: 37797435 PMCID: PMC10568423 DOI: 10.1016/j.nicl.2023.103515] [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: 07/17/2023] [Revised: 08/31/2023] [Accepted: 09/22/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Antipsychotic drugs are the first-choice therapy for psychotic episodes, but antipsychotic treatment response (AP-R) is unpredictable and only becomes clear after weeks of therapy. A biomarker for AP-R is currently unavailable. We reviewed the evidence for the hypothesis that functional magnetic resonance imaging functional connectivity (fMRI-FC) is a predictor of AP-R or could serve as a biomarker for AP-R in psychosis. METHOD A systematic review of longitudinal fMRI studies examining the predictive performance and relationship between FC and AP-R was performed following PRISMA guidelines. Technical and clinical aspects were critically assessed for the retrieved studies. We addressed three questions: Q1) is baseline fMRI-FC related to subsequent AP-R; Q2) is AP-R related to a change in fMRI-FC; and Q3) can baseline fMRI-FC predict subsequent AP-R? RESULTS In total, 28 articles were included. Most studies were of good quality. fMRI-FC analysis pipelines included seed-based-, independent component- / canonical correlation analysis, network-based statistics, and graph-theoretical approaches. We found high heterogeneity in methodological approaches and results. For Q1 (N = 17) and Q2 (N = 18), the most consistent evidence was found for FC between the striatum and ventral attention network as a potential biomarker of AP-R. For Q3 (N = 9) accuracy's varied form 50 till 93%, and prediction models were based on FC between various brain regions. CONCLUSION The current fMRI-FC literature on AP-R is hampered by heterogeneity of methodological approaches. Methodological uniformity and further improvement of the reliability and validity of fMRI connectivity analysis is needed before fMRI-FC analysis can have a place in clinical applications of antipsychotic treatment.
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Affiliation(s)
- L S Dominicus
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - L van Rijn
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J van der A
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - R van der Spek
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - D Podzimek
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - M Begemann
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - L de Haan
- Department Early Psychosis, Academical Medical Centre of the University of Amsterdam, Amsterdam, Amsterdam, The Netherlands
| | - M van der Pluijm
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, The Netherlands; Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - W M Otte
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, and Utrecht University, Utrecht, The Netherlands
| | - W Cahn
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C H Röder
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - H G Schnack
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - E van Dellen
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; Department of Intensive Care Medicine and UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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6
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Guo LK, Su Y, Zhang YYN, Yu H, Lu Z, Li WQ, Yang YF, Xiao X, Yan H, Lu TL, Li J, Liao YD, Kang ZW, Wang LF, Li Y, Li M, Liu B, Huang HL, Lv LX, Yao Y, Tan YL, Breen G, Everall I, Wang HX, Huang Z, Zhang D, Yue WH. Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis. Mil Med Res 2023; 10:24. [PMID: 37269009 DOI: 10.1186/s40779-023-00459-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/05/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment. METHODS Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial (n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial (n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls (n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R2 for regression, and decision curve analysis. RESULTS Six risk genes for SCZ (LINC01795, DDHD2, SBNO1, KCNG2, SEMA7A, and RUFY1) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867-0.881), R2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R2 = 0.507]. CONCLUSIONS This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC-ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).
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Affiliation(s)
- Liang-Kun Guo
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yi Su
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Yu-Ya-Nan Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Hao Yu
- Department of Psychiatry, Jining Medical University, Jining, 272067, Shandong, China
| | - Zhe Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Wen-Qiang Li
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yong-Feng Yang
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Hao Yan
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Tian-Lan Lu
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Jun Li
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yun-Dan Liao
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Zhe-Wei Kang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Li-Fang Wang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China
| | - Yue Li
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hai-Liang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
| | - Lu-Xian Lv
- Henan Key Lab of Biological Psychiatry, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, 435001, Henan, China
| | - Yin Yao
- Department of Biostatistics and Computational Biology, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Yun-Long Tan
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, China
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Ian Everall
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, WC2R 2LS, UK
| | - Hong-Xing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Zhuo Huang
- State Key Laboratory of Natural and Biomimetic Drugs, Key Laboratory for Neuroscience for Ministry of Education, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, 100191, China.
| | - Dai Zhang
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
| | - Wei-Hua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health and Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder (2018RU006), Chinese Academy of Medical Sciences, Beijing, 100191, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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7
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Lu C, Zhu X, Feng Y, Ao W, Li J, Gao Z, Luo H, Chen M, Cai F, Zhan S, Li H, Sun W, Hu J. Atypical antipsychotics antagonize GABA A receptors in the ventral tegmental area GABA neurons to relieve psychotic behaviors. Mol Psychiatry 2023; 28:2107-2121. [PMID: 36754983 DOI: 10.1038/s41380-023-01982-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/19/2023] [Accepted: 01/24/2023] [Indexed: 02/10/2023]
Abstract
Psychosis is an abnormal mental condition that can cause patients to lose contact with reality. It is a common symptom of schizophrenia, bipolar disorder, sleep deprivation, and other mental disorders. Clinically, antipsychotic medications, such as olanzapine and clozapine, are very effective in treatment for psychosis. To investigate the neural circuit mechanism that is affected by antipsychotics and identify more selective therapeutic targets, we employed a strategy by using these effective antipsychotics to identify antipsychotic neural substrates. We observed that local injection of antipsychotics into the ventral tegmental area (VTA) could reverse the sensorimotor gating defects induced by MK-801 injection in mice. Using in vivo fiber photometry, electrophysiological techniques, and chemogenetics, we found that antipsychotics could activate VTA gamma-aminobutyric acid (GABA) neurons by blocking GABAA receptors. Moreover, we found that the VTAGABA nucleus accumbens (NAc) projection was crucially involved in such antipsychotic effects. In summary, our study identifies a novel therapeutic target for the treatment of psychosis and underscores the utility of a 'bedside-to-bench' approach for identifying neural circuits that influence psychotic disorders.
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Affiliation(s)
- Chen Lu
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 200031, Shanghai, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Xiaona Zhu
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
| | - Yifan Feng
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Weizhen Ao
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Jie Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200030, Shanghai, China
| | - Zilong Gao
- School of Life Sciences, Westlake University, 310024, Hangzhou, China
| | - Huoqing Luo
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Ming Chen
- Institutes of Brain Science, Fudan University, 200032, Shanghai, China
| | - Fang Cai
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Shulu Zhan
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Hongxia Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
| | - Wenzhi Sun
- Chinese Institute for Brain Research, 102206, Beijing, China.
- School of Basic Medical Sciences, Capital Medical University, 100069, Beijing, China.
| | - Ji Hu
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
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8
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Lahti AC. Discovery of early schizophrenia through neuroimaging. Psychiatry Res 2023; 322:114993. [PMID: 36773467 DOI: 10.1016/j.psychres.2022.114993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 11/22/2022] [Accepted: 11/27/2022] [Indexed: 11/29/2022]
Abstract
In order to understand the pathophysiology of schizophrenia we carried out a number of brain imaging studies in both medicated and unmedicated patients. In addition, to help unravel the pathophysiological mechanisms without the confound of prior exposure to antipsychotic medication or chronicity, we enrolled a large group of antipsychotic medication-naïve first episode psychosis patients at first treatment contact, and performed longitudinal multimodal neuroimaging studies over several months. In unmedicated patients we found both functional and structural connectivity alterations. Similarly, in medication-naïve patients we replicated many of our prior findings, suggesting that functional and structural connectivity alterations are core pathological features of the illness. We found that a longer duration of untreated psychosis, i.e. the time between first symptom onset and initial treatment contact, was associated with greater structural and functional connectivity abnormalities, which in turn was associated with worse subsequent clinical response to treatment. These results underscore the critical importance of early identification and treatment in patients with psychosis spectrum disorders.
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Affiliation(s)
- Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, Birmingham, AL, United States.
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9
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Brown NK, Roche JK, Farmer CB, Roberts RC. Evidence for upregulation of excitatory synaptic transmission in the substantia nigra in Schizophrenia: a postmortem ultrastructural study. J Neural Transm (Vienna) 2023; 130:561-573. [PMID: 36735096 DOI: 10.1007/s00702-023-02593-x] [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: 10/17/2022] [Accepted: 01/14/2023] [Indexed: 02/04/2023]
Abstract
The dopamine hypothesis of schizophrenia suggests that psychotic symptoms originate from dysregulation of dopaminergic activity, which may be controlled by upstream innervation. We hypothesized that we would find anatomical evidence for the hyperexcitability seen in the SN. We examined and quantified synaptic morphology, which correlates with function, in the postmortem substantia nigra (SN) from 15 schizophrenia and 12 normal subjects. Synapses were counted using stereological techniques and classified based on the morphology of the post-synaptic density (PSD) and the presence or absence of a presynaptic density. The density and proportion of excitatory synapses was higher in the schizophrenia group than in controls, while the proportion (but not density) of inhibitory synapses was lower. We also detected in the schizophrenia group an increase in density of synapses with a PSD of intermediate thickness, which may represent excitatory synapses. The density of synapses with presynaptic densities was similar in both groups. The density of synapses with mixed morphologies was higher in the schizophrenia group than in controls. The human SN contains atypical synaptic morphology. We found an excess amount and proportion of excitatory synapses in the SN in schizophrenia that could result in hyperactivity and drive the psychotic symptoms of schizophrenia. The sources of afferent excitatory inputs to the SN arise from the subthalamic nucleus, the pedunculopontine nucleus, and the ventral tegmental area (VTA), areas that could be the source of excess excitation. Synapses with mixed morphologies may represent inputs from the VTA, which release multiple transmitters.
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Affiliation(s)
- Nicole K Brown
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Sparks Center 835C, 1720 2nd Avenue South, Birmingham, AL, 35294, USA
| | - Joy K Roche
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Sparks Center 835C, 1720 2nd Avenue South, Birmingham, AL, 35294, USA
| | - Charlene B Farmer
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Sparks Center 835C, 1720 2nd Avenue South, Birmingham, AL, 35294, USA
| | - Rosalinda C Roberts
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Sparks Center 835C, 1720 2nd Avenue South, Birmingham, AL, 35294, USA.
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10
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Connectivity alterations of mesostriatal pathways in first episode psychosis. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:15. [PMID: 36918579 PMCID: PMC10014938 DOI: 10.1038/s41537-023-00339-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 02/24/2023] [Indexed: 03/15/2023]
Abstract
BACKGROUND AND HYPOTHESIS Pathogenic understanding of the psychotic disorders converges on regulation of dopaminergic signaling in mesostriatocortical pathways. Functional connectivity of the mesostriatal pathways may inform us of the neuronal networks involved. STUDY DESIGN This longitudinal study of first episode psychosis (FEP) (49 patients, 43 controls) employed seed-based functional connectivity analyses of fMRI data collected during a naturalistic movie stimulus. STUDY RESULTS We identified hypoconnectivity of the dorsal striatum with the midbrain, associated with antipsychotic medication dose in FEP, in comparison with the healthy control group. The midbrain regions that showed hypoconnectivity with the dorsal striatum also showed hypoconnectivity with cerebellar regions suggested to be involved in regulation of the mesostriatocortical dopaminergic pathways. None of the baseline hypoconnectivity detected was seen at follow-up. CONCLUSIONS These findings extend earlier resting state findings on mesostriatal connectivity in psychotic disorders and highlight the potential for cerebellar regulation of the mesostriatocortical pathways as a target of treatment trials.
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11
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Egerton A, Griffiths K, Casetta C, Deakin B, Drake R, Howes OD, Kassoumeri L, Khan S, Lankshear S, Lees J, Lewis S, Mikulskaya E, Millgate E, Oloyede E, Pollard R, Rich N, Segev A, Sendt KV, MacCabe JH. Anterior cingulate glutamate metabolites as a predictor of antipsychotic response in first episode psychosis: data from the STRATA collaboration. Neuropsychopharmacology 2023; 48:567-575. [PMID: 36456813 PMCID: PMC9852590 DOI: 10.1038/s41386-022-01508-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 11/07/2022] [Accepted: 11/09/2022] [Indexed: 12/03/2022]
Abstract
Elevated brain glutamate has been implicated in non-response to antipsychotic medication in schizophrenia. Biomarkers that can accurately predict antipsychotic non-response from the first episode of psychosis (FEP) could allow stratification of patients; for example, patients predicted not to respond to standard antipsychotics could be fast-tracked to clozapine. Using proton magnetic resonance spectroscopy (1H-MRS), we examined the ability of glutamate and Glx (glutamate plus glutamine) in the anterior cingulate cortex (ACC) and caudate to predict response to antipsychotic treatment. A total of 89 minimally medicated patients with FEP not meeting symptomatic criteria for remission were recruited across two study sites. 1H-MRS and clinical data were acquired at baseline, 2 and 6 weeks. Response was defined as >20% reduction in Positive and Negative Syndrome Scale (PANSS) Total score from baseline to 6 weeks. In the ACC, baseline glutamate and Glx were higher in Non-Responders and significantly predicted response (P < 0.02; n = 42). Overall accuracy was greatest for ACC Glx (69%) and increased to 75% when symptom severity at baseline was included in the model. Glutamate metabolites in the caudate were not associated with response, and there was no significant change in glutamate metabolites over time in either region. These results add to the evidence linking elevations in ACC glutamate metabolites to a poor antipsychotic response. They indicate that glutamate may have utility in predicting response during early treatment of first episode psychosis. Improvements in accuracy may be made by combining glutamate measures with other response biomarkers.
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Affiliation(s)
- Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK.
| | - Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Cecila Casetta
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Bill Deakin
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
| | - Richard Drake
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sobia Khan
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Steve Lankshear
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Jane Lees
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Shon Lewis
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Elena Mikulskaya
- Greater Manchester Mental Health NHS Foundation Trust Bury New Road, Prestwich, Manchester, M25 3BL, UK
- Division of Psychology and Mental Health, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Edward Millgate
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ebenezer Oloyede
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rebecca Pollard
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nathalie Rich
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Aviv Segev
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Kyra-Verena Sendt
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
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12
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Sabaroedin K, Tiego J, Fornito A. Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum. Biol Psychiatry 2023; 93:113-124. [PMID: 36253195 DOI: 10.1016/j.biopsych.2022.07.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 06/14/2022] [Accepted: 07/17/2022] [Indexed: 11/28/2022]
Abstract
Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.
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Affiliation(s)
- Kristina Sabaroedin
- Departments of Radiology and Paediatrics, Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Jeggan Tiego
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
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13
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Shi Y, Wang M, Xiao L, Gui L, Zheng W, Bai L, Su B, Li B, Xu Y, Pan W, Zhang J, Wang W. Potential therapeutic mechanism of deep brain stimulation of the nucleus accumbens in obsessive-compulsive disorder. Front Cell Neurosci 2023; 16:1057887. [PMID: 36687525 PMCID: PMC9845878 DOI: 10.3389/fncel.2022.1057887] [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: 09/30/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Deep brain stimulation (DBS) of the nucleus accumbens (NAc) (NAc-DBS) is an effective solution to refractory obsessive-compulsive disorder (OCD). However, evidence for the neurobiological mechanisms of OCD and the effect of NAc-DBS is still lacking. One hypothesis is that the electrophysiological activities in the NAc are modulated by DBS, and another hypothesis is that the activities of neurotransmitters in the NAc are influenced by DBS. To investigate these potential alterations, rats with quinpirole (QNP)- induced OCD were treated with DBS of the core part of NAc. Then, extracellular spikes (SPK) and local field potentials (LFP) in the NAc were recorded, and the levels of relevant neurotransmitters and related proteins were measured. Analysis of SPK revealed that the firing rate was decreased and the firing pattern was changed after NAc-DBS, and analysis of LFP showed that overall power spectral density (PSD) levels were reduced after NAc-DBS. Additionally, we found that the relative powers of the theta band, alpha band and beta band were increased in OCD status, while the relative powers of the delta band and gamma band were decreased. This pathological pattern of power distribution was reformed by NAc-DBS. Furthermore, we found that the local levels of monoamines [dopamine (DA) and serotonin (5-HT)] and amino acids [glutamate (Glu) and gamma-aminobutyric acid (GABA)] in the NAc were increased in OCD status, and that the expression of the two types of DA receptors in the NAc exhibited an opposite change. These abnormalities could be reversed by NAc-DBS. These findings provide a more comprehensive understanding about the function of the NAc in the pathophysiology of OCD and provide more detailed evidence for the potential effect of NAc-DBS.
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Affiliation(s)
- Yifeng Shi
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mengqi Wang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Linglong Xiao
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Luolan Gui
- Laboratory of Clinical Proteomics and Metabolomics, Frontiers Science Center for Disease-Related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Institutes for Systems Genetics, Sichuan University, Chengdu, Sichuan, China
| | - Wen Zheng
- Laboratory of Clinical Proteomics and Metabolomics, Frontiers Science Center for Disease-Related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Institutes for Systems Genetics, Sichuan University, Chengdu, Sichuan, China
| | - Lin Bai
- Histology and Imaging Platform, Core Facilities of West China Hospital, Sichuan University, Chengdu, Sichuan, China,Key Laboratory of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bo Su
- Histology and Imaging Platform, Core Facilities of West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bin Li
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yangyang Xu
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Pan
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jie Zhang
- Histology and Imaging Platform, Core Facilities of West China Hospital, Sichuan University, Chengdu, Sichuan, China,Key Laboratory of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Wang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China,*Correspondence: Wei Wang,
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14
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Lencz T, Moyett A, Argyelan M, Barber AD, Cholewa J, Birnbaum ML, Gallego JA, John M, Szeszko PR, Robinson DG, Malhotra AK. Frontal lobe fALFF measured from resting-state fMRI as a prognostic biomarker in first-episode psychosis. Neuropsychopharmacology 2022; 47:2245-2251. [PMID: 36198875 PMCID: PMC9630308 DOI: 10.1038/s41386-022-01470-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/05/2022] [Accepted: 09/21/2022] [Indexed: 11/09/2022]
Abstract
Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The goal of the present study was to test whether the fractional amplitude of low-frequency fluctuations (fALFF), as measured from baseline resting-state fMRI data, can serve as a potential biomarker of treatment response to antipsychotics. Patients in the first episode of psychosis (n = 126) were enrolled in two prospective studies employing second-generation antipsychotics (risperidone or aripiprazole). Patients were scanned at the initiation of treatment on a 3T MRI scanner (Study 1, GE Signa HDx, n = 74; Study 2, Siemens Prisma, n = 52). Voxelwise fALFF derived from baseline resting-state fMRI scans served as the primary measure of interest, providing a hypothesis-free (as opposed to region-of-interest) search for regions of the brain that might be predictive of response. At baseline, patients who would later meet strict criteria for clinical response (defined as two consecutive ratings of much or very much improved on the CGI, as well as a rating of ≤3 on psychosis-related items of the BPRS-A) demonstrated significantly greater baseline fALFF in bilateral orbitofrontal cortex compared to non-responders. Thus, spontaneous activity in orbitofrontal cortex may serve as a prognostic biomarker of antipsychotic treatment.
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Affiliation(s)
- Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA.
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA.
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA.
| | - Ashley Moyett
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
| | - Miklos Argyelan
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Anita D Barber
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - John Cholewa
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
| | - Michael L Birnbaum
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Juan A Gallego
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Majnu John
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
- Department of Mathematics, Hofstra University, Hempstead, NY, 11549, USA
| | - Philip R Szeszko
- James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Delbert G Robinson
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Anil K Malhotra
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
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15
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Marino M, Spironelli C, Mantini D, Craven AR, Ersland L, Angrilli A, Hugdahl K. Default mode network alterations underlie auditory verbal hallucinations in schizophrenia. J Psychiatr Res 2022; 155:24-32. [PMID: 35981441 DOI: 10.1016/j.jpsychires.2022.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/08/2022] [Accepted: 08/04/2022] [Indexed: 10/31/2022]
Abstract
Although alterations of the default mode network (DMN) in schizophrenia (SZ) have been largely investigated, less research has been carried out on DMN alterations in different sub-phenotypes of this disorder. The aim of this pilot study was to compare DMN features among SZ patients with and without auditory verbal hallucinations (AVH). Three groups of 17 participants each were considered: patients with hallucinations (AVH-SZ), patients without hallucinations (nAVH-SZ) and age-matched healthy controls (HC). The DMN spatial pattern was similar between the nAVH-SZ and HC, but the comparison between these two groups and the AVH-SZ group revealed alterations in the left Angular Gyrus (lAG) node of the DMN. Using a novel approach based on normalized fractional Amplitude of Low-Frequency Fluctuations (fALFF), the AVH-SZ subgroup showed altered spectral activity in the DMN compared with the other two groups, especially in the lower-frequency bands (0.017-0.04 Hz). Significant positive correlations were found for both SZ groups collapsed, and for the nAVH-SZ group alone between delusional scores (PANSS-P1) and slow fALFF bands of the DMN. Narrowing the analysis to the ROI centered on the lAG, significant correlations were found in the AVH-SZ group for hallucination scores (PANSS-P3) and Slow-5 and Slow-4 (both positive), and Slow-3 (negative) fALFF bands. Our results reveal the central role of the lAG in relation to hallucinations, an important cortical area connecting auditory cortex with several hubs (including frontal linguistic centers) and involved in auditory process monitoring.
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Affiliation(s)
- Marco Marino
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium; IRCCS San Camillo Hospital, Venice, Italy.
| | - Chiara Spironelli
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy.
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway; Division of Psychiatry and NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway
| | - Lars Ersland
- Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Alessandro Angrilli
- Department of General Psychology, University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy
| | - Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; Division of Psychiatry and NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
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16
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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: 7.0] [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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17
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Kowalski J, Styła R. Visual worry in patients with schizophrenia. J Psychiatr Res 2022; 153:116-124. [PMID: 35810601 DOI: 10.1016/j.jpsychires.2022.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 06/22/2022] [Accepted: 07/01/2022] [Indexed: 10/17/2022]
Abstract
OBJECTIVE Worrying is a pervasive transdiagnostic symptom in schizophrenia. It is most often associated in the literature with verbal modality due to many studies of its presence in generalised anxiety disorder. The current study aimed to elucidate worry in different sensory modalities, visual and verbal, in individuals with schizophrenia. METHOD We tested persons with schizophrenia (n = 92) and healthy controls (n = 138) in a cross-sectional design. We used questionnaires of visual and verbal worry (original Worry Modality Questionnaire), trait worry (Penn State Worry Questionnaire) and general psychopathology symptoms (General Functioning Questionnaire-58 and Brief Psychiatric Rating Scale). RESULTS Both visual and verbal worry were associated with psychotic, anxiety and general symptoms of psychopathology in both groups with medium to large effect sizes. Regression analyses indicated that visual worry was a single significant predictor of positive psychotic symptoms in a model with verbal and trait worry, both in clinical and control groups (β's of 0.49 and 0.38, respectively). Visual worry was also a superior predictor of anxiety and general psychopathology severity (β's of 0.34 and 0.37, respectively) than verbal worry (β's of 0.03 and -0.02, respectively), under control of trait worry, in the schizophrenia group. We also proposed two indices of worry modality dominance and analysed profiles of dominating worry modality in both groups. CONCLUSIONS Our study is the first to demonstrate that visual worry might be of specific importance for understanding psychotic and general psychopathology symptoms in persons with schizophrenia.
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Affiliation(s)
- Joachim Kowalski
- Experimental Psychopathology Laboratory, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland.
| | - Rafał Styła
- Faculty of Psychology, University of Warsaw, Warsaw, Poland
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18
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Lu C, Feng Y, Li H, Gao Z, Zhu X, Hu J. A preclinical study of deep brain stimulation in the ventral tegmental area for alleviating positive psychotic-like behaviors in mice. Front Hum Neurosci 2022; 16:945912. [PMID: 36034113 PMCID: PMC9399924 DOI: 10.3389/fnhum.2022.945912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) is a clinical intervention for the treatment of movement disorders. It has also been applied to the treatment of psychiatric disorders such as depression, anorexia nervosa, obsessive-compulsive disorder, and schizophrenia. Psychiatric disorders including schizophrenia, bipolar disorder, and major depression can lead to psychosis, which can cause patients to lose touch with reality. The ventral tegmental area (VTA), located near the midline of the midbrain, is an important region involved in psychosis. However, the clinical application of electrical stimulation of the VTA to treat psychotic diseases has been limited, and related mechanisms have not been thoroughly studied. In the present study, hyperlocomotion and stereotyped behaviors of the mice were employed to mimic and evaluate the positive-psychotic-like behaviors. We attempted to treat positive psychotic-like behaviors by electrically stimulating the VTA in mice and exploring the neural mechanisms behind behavioral effects. Local field potential recording and in vivo fiber photometry to observe the behavioral effects and changes in neural activities caused by DBS in the VTA of mice. Optogenetic techniques were used to verify the neural mechanisms underlying the behavioral effects induced by DBS. Our results showed that electrical stimulation of the VTA activates local gamma-aminobutyric acid (GABA) neurons, and dopamine (DA) neurons, reduces hyperlocomotion, and relieves stereotyped behaviors induced by MK-801 (dizocilpine) injection. The results of optogenetic manipulation showed that the activation of the VTA GABA neurons, but not DA neurons, is involved in the alleviation of hyperlocomotion and stereotyped behaviors. We visualized changes in the activity of specific types in specific brain areas induced by DBS, and explored the neural mechanism of DBS in alleviating positive psychotic-like behaviors. This preclinical study not only proposes new technical means of exploring the mechanism of DBS, but also provides experimental justification for the clinical treatment of psychotic diseases by electrical stimulation of the VTA.
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Affiliation(s)
- Chen Lu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yifan Feng
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
| | - Hongxia Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zilong Gao
- School of Life Sciences, Westlake University, Hangzhou, China
| | - Xiaona Zhu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
- *Correspondence: Ji Hu Xiaona Zhu
| | - Ji Hu
- School of Life Science and Technology, Shanghai Tech University, Shanghai, China
- *Correspondence: Ji Hu Xiaona Zhu
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19
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Bracht T, Mertse N, Walther S, Lüdi K, Breit S, Federspiel A, Wiest R, Denier N. Link between structural connectivity of the medial forebrain bundle, functional connectivity of the ventral tegmental area, and anhedonia in unipolar depression. Neuroimage Clin 2022; 34:102961. [PMID: 35152053 PMCID: PMC8844724 DOI: 10.1016/j.nicl.2022.102961] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/10/2022] [Accepted: 02/06/2022] [Indexed: 12/17/2022]
Abstract
Tract volume and number of tracts are reduced in the left slMFB. Those microstructural alterations are related to depression severity and anhedonia. There is increased VTA-PFC functional connectivity in depression. Those increases are more pronounced in patients with severe anhedonia. Our results extend pathophysiological models of anhedonia in depression.
The ventral tegmental area (VTA), nucleus accumbens (NAcc), and prefrontal cortex (PFC) are essential for experiencing pleasure and initiating motivated behaviour. The VTA, NAcc, and PFC are connected through the medial forebrain bundle (MFB). In humans, two branches have been described: an infero-medial branch (imMFB) and a supero-lateral branch (slMFB). This study aimed to explore the associations between structural connectivity of the MFB, functional connectivity (FC) of the VTA, anhedonia, and depression severity in patients with depression. Fifty-six patients with unipolar depression and 22 healthy controls matched for age, sex, and handedness were recruited at the University Hospital of Psychiatry and Psychotherapy in Bern, Switzerland. Diffusion-weighted imaging and resting-state functional magnetic resonance imaging scans were acquired. Using manual tractography, the imMFB and slMFB were reconstructed bilaterally for each participant. Seed-based resting-state FC was computed from the VTA to the PFC. Hedonic tone was assessed using the Fawcett-Clark Pleasure Scale. We identified reduced tract volume and reduced number of tracts in the left slMFB. There was an increase in FC between the VTA and right medial PFC in patients with depression. Depression severity was associated with reduced tract volume and fewer tracts in the left slMFB. Reduced hedonic tone was associated with reduced tract volume. Conversely, reduced hedonic tone was associated with increased FC between the VTA and the PFC. In conclusion, our results suggest reduced structural connectivity of the slMFB in patients with depression. Increases in FC between the VTA and PFC may be associated with anhedonia or compensatory hyperactivity.
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Affiliation(s)
- Tobias Bracht
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
| | - Nicolas Mertse
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Karin Lüdi
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Sigrid Breit
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Andrea Federspiel
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Roland Wiest
- Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Niklaus Denier
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
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20
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Sabaroedin K, Razi A, Chopra S, Tran N, Pozaruk A, Chen Z, Finlay A, Nelson B, Allott K, Alvarez-Jimenez M, Graham J, Yuen HP, Harrigan S, Cropley V, Sharma S, Saluja B, Williams R, Pantelis C, Wood SJ, O’Donoghue B, Francey S, McGorry P, Aquino K, Fornito A. Frontostriatothalamic effective connectivity and dopaminergic function in the psychosis continuum. Brain 2022; 146:372-386. [PMID: 35094052 PMCID: PMC9825436 DOI: 10.1093/brain/awac018] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 01/12/2023] Open
Abstract
Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.
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Affiliation(s)
- Kristina Sabaroedin
- Correspondence to: Kristina Sabaroedin Turner Institute for Brain and Mental Health 770 Blackburn Road, Clayton, Victoria 3168, Australia E-mail:
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia,Wellcome Centre for Human Neuroimaging, University College, London WC1N 3AR, UK
| | - Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Nancy Tran
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Andrii Pozaruk
- Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Amy Finlay
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Hok P Yuen
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Susy Harrigan
- Department of Social Work, Monash University, Victoria 3800, Australia,Melbourne School of Population and Global Health, The University of Melbourne, Parkville. Victoria 3010, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, Victoria 3010, Australia
| | - Sujit Sharma
- Monash Health, Dandenong, Victoria 3175, Australia
| | | | - Rob Williams
- The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, Victoria 3010, Australia,The Florey Institute for Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Stephen J Wood
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia,School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Shona Francey
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Patrick McGorry
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Kevin Aquino
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
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21
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Present and future antipsychotic drugs: a systematic review of the putative mechanisms of action for efficacy and a critical appraisal under a translational perspective. Pharmacol Res 2022; 176:106078. [PMID: 35026403 DOI: 10.1016/j.phrs.2022.106078] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/23/2021] [Accepted: 01/07/2022] [Indexed: 01/10/2023]
Abstract
Antipsychotics represent the mainstay of schizophrenia pharmacological therapy, and their role has been expanded in the last years to mood disorders treatment. Although introduced in 1952, many years of research were required before an accurate picture of how antipsychotics work began to emerge. Despite the well-recognized characterization of antipsychotics in typical and atypical based on their liability to induce motor adverse events, their main action at dopamine D2R to elicit the "anti-psychotic" effect, as well as the multimodal action at other classes of receptors, their effects on intracellular mechanisms starting with receptor occupancy is still not completely understood. Significant lines of evidence converge on the impact of these compounds on multiple molecular signaling pathways implicated in the regulation of early genes and growth factors, dendritic spine shape, brain inflammation, and immune response, tuning overall the function and architecture of the synapse. Here we present, based on PRISMA approach, a comprehensive and systematic review of the above mechanisms under a translational perspective to disentangle those intracellular actions and signaling that may underline clinically relevant effects and represent potential targets for further innovative strategies in antipsychotic therapy.
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22
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Schulz J, Zimmermann J, Sorg C, Menegaux A, Brandl F. Magnetic resonance imaging of the dopamine system in schizophrenia - A scoping review. Front Psychiatry 2022; 13:925476. [PMID: 36203848 PMCID: PMC9530597 DOI: 10.3389/fpsyt.2022.925476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 07/08/2022] [Indexed: 11/30/2022] Open
Abstract
For decades, aberrant dopamine transmission has been proposed to play a central role in schizophrenia pathophysiology. These theories are supported by human in vivo molecular imaging studies of dopamine transmission, particularly positron emission tomography. However, there are several downsides to such approaches, for example limited spatial resolution or restriction of the measurement to synaptic processes of dopaminergic neurons. To overcome these limitations and to measure complementary aspects of dopamine transmission, magnetic resonance imaging (MRI)-based approaches investigating the macrostructure, metabolism, and connectivity of dopaminergic nuclei, i.e., substantia nigra pars compacta and ventral tegmental area, can be employed. In this scoping review, we focus on four dopamine MRI methods that have been employed in patients with schizophrenia so far: neuromelanin MRI, which is thought to measure long-term dopamine function in dopaminergic nuclei; morphometric MRI, which is assumed to measure the volume of dopaminergic nuclei; diffusion MRI, which is assumed to measure fiber-based structural connectivity of dopaminergic nuclei; and resting-state blood-oxygenation-level-dependent functional MRI, which is thought to measure functional connectivity of dopaminergic nuclei based on correlated blood oxygenation fluctuations. For each method, we describe the underlying signal, outcome measures, and downsides. We present the current state of research in schizophrenia and compare it to other disorders with either similar (psychotic) symptoms, i.e., bipolar disorder and major depressive disorder, or dopaminergic abnormalities, i.e., substance use disorder and Parkinson's disease. Finally, we discuss overarching issues and outline future research questions.
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Affiliation(s)
- Julia Schulz
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Juliana Zimmermann
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
| | - Aurore Menegaux
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Felix Brandl
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM-NIC Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
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23
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Overbeek G, Gawne TJ, Reid MA, Kraguljac NV, Lahti AC. A multimodal neuroimaging study investigating resting-state connectivity, glutamate and GABA at 7 T in first-episode psychosis. J Psychiatry Neurosci 2021; 46:E702-E710. [PMID: 34933941 PMCID: PMC8695527 DOI: 10.1503/jpn.210107] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 10/05/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The major excitatory and inhibitory neurometabolites in the brain, glutamate and γ-aminobutyric acid (GABA), respectively, are related to the functional MRI signal. Disruption of resting-state functional MRI signals has been reported in psychosis spectrum disorders, but few studies have investigated the role of these metabolites in this context. METHODS We included 19 patients with first-episode psychosis and 21 healthy controls in this combined magnetic resonance spectroscopy (MRS) and resting-state functional connectivity study. All imaging was performed on a Siemens Magnetom 7 T MRI scanner. Both the MRS voxel and the seed for functional connectivity analysis were located in the dorsal anterior cingulate cortex (ACC). We used multiple regressions to test for an interaction between ACC brain connectivity, diagnosis and neurometabolites. RESULTS ACC brain connectivity was altered in first-episode psychosis. The relationship between ACC glutamate and ACC functional connectivity differed between patients with first-episode psychosis and healthy controls in the precuneus, retrosplenial cortex, supramarginal gyrus and angular gyrus. As well, the relationship between ACC GABA and ACC functional connectivity differed between groups in the caudate, putamen and supramarginal gyrus. LIMITATIONS We used a small sample size. As well, although they were not chronically medicated, all participants were medicated during the study. CONCLUSION We demonstrated a link between the major excitatory and inhibitory brain metabolites and resting-state functional connectivity in healthy participants, as well as an alteration in this relationship in patients with first-episode psychosis. Combining data from different imaging modalities may help our mechanistic understanding of the relationship between major neurometabolites and brain network dynamics, and shed light on the pathophysiology of first-episode psychosis.
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Affiliation(s)
- Gregory Overbeek
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Timothy J Gawne
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Meredith A Reid
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Nina V Kraguljac
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
| | - Adrienne C Lahti
- From the Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham (Overbeek, Kraguljac, Lahti); the Department of Optometry and Vision Science, University of Alabama at Birmingham (Gawne); and the Department of Electrical and Computer Engineering, Auburn University, Auburn AL (Reid)
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24
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Resting-state functional connectivity predictors of treatment response in schizophrenia - A systematic review and meta-analysis. Schizophr Res 2021; 237:153-165. [PMID: 34534947 DOI: 10.1016/j.schres.2021.09.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/18/2021] [Accepted: 09/06/2021] [Indexed: 11/21/2022]
Abstract
We aimed to systematically synthesize and quantify the utility of pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI) in predicting antipsychotic response in schizophrenia. We searched the PubMed/MEDLINE database for studies that examined the magnitude of association between baseline rs-fMRI assessment and subsequent response to antipsychotic treatment in persons with schizophrenia. We also performed meta-analyses for quantifying the magnitude and accuracy of predicting response defined continuously and categorically. Data from 22 datasets examining 1280 individuals identified striatal and default mode network functional segregation and integration metrics as consistent determinants of treatment response. The pooled correlation coefficient for predicting improvement in total symptoms measured continuously was ~0.47 (12 datasets; 95% CI: 0.35 to 0.59). The pooled odds ratio of predicting categorically defined treatment response was 12.66 (nine datasets; 95% CI: 7.91-20.29), with 81% sensitivity and 76% specificity. rs-fMRI holds promise as a predictive biomarker of antipsychotic treatment response in schizophrenia. Future efforts need to focus on refining feature characterization to improve prediction accuracy, validate prediction models, and evaluate their implementation in clinical practice.
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25
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Ueno F, Iwata Y, Nakajima S, Caravaggio F, Rubio JM, Horga G, Cassidy CM, Torres-Carmona E, de Luca V, Tsugawa S, Honda S, Moriguchi S, Noda Y, Gerretsen P, Graff-Guerrero A. Neuromelanin accumulation in patients with schizophrenia: A systematic review and meta-analysis. Neurosci Biobehav Rev 2021; 132:1205-1213. [PMID: 34718049 PMCID: PMC9059704 DOI: 10.1016/j.neubiorev.2021.10.028] [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: 09/16/2021] [Revised: 10/21/2021] [Accepted: 10/24/2021] [Indexed: 11/25/2022]
Abstract
Although schizophrenia is associated with increased presynaptic dopamine function in the striatum, it remains unclear if neuromelanin levels, which are thought to serve as a biomarker for midbrain dopamine neuron function, are increased in patients with schizophrenia. We conducted a systematic review and meta-analysis of magnetic resonance imaging (MRI) and postmortem studies comparing neuromelanin (NM) levels between patients with schizophrenia and healthy controls (HCs). Standard mean differences were calculated to assess group differences in NM accumulation levels between patients with schizophrenia and HCs. This study included 7 articles in total. Five studies employed NM-sensitive MRI (NM-MRI) and two were postmortem brain studies. The patient group (n = 163) showed higher NM levels in the substantia nigra (SN) than HCs (n = 228) in both the analysis of the seven studies and the subgroup analysis of the 5 NM-MRI studies. This analysis suggest increased NM levels in the SN may be a potential biomarker for stratifying schizophrenia, warranting further research that accounts for the heterogeneity of this disorder.
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Affiliation(s)
- Fumihiko Ueno
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi, Faculty of Medicine, Yamanashi, Japan
| | - Shinichiro Nakajima
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
| | - Fernando Caravaggio
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Jose M Rubio
- Barbara and Donald Zucker School of Medicine at Hofstra University - Northwell Health, Hempstead, NY, USA; Institute of Behavioral Science, Feinstein Institutes of Medical Research, Manhasset, NY, USA; Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Guillermo Horga
- Department of Psychiatry, Columbia University, New York, NY, USA; Division of Translational Imaging, New York State Psychiatric Institute, New York, NY, USA
| | - Clifford M Cassidy
- The Royal's Institute of Mental Health Research Affiliated with the University of Ottawa, Ottawa, Ontario, Canada
| | - Edgardo Torres-Carmona
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Vincenzo de Luca
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Sho Moriguchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Philip Gerretsen
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada.
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Increased Homotopic Connectivity in the Prefrontal Cortex Modulated by Olanzapine Predicts Therapeutic Efficacy in Patients with Schizophrenia. Neural Plast 2021; 2021:9954547. [PMID: 34512748 PMCID: PMC8429031 DOI: 10.1155/2021/9954547] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 08/08/2021] [Accepted: 08/18/2021] [Indexed: 11/18/2022] Open
Abstract
Background Previous studies have revealed the abnormalities in homotopic connectivity in schizophrenia. However, the relationship of these deficits to antipsychotic treatment in schizophrenia remains unclear. This study explored the effects of antipsychotic therapy on brain homotopic connectivity and whether the homotopic connectivity of these regions might predict individual treatment response in schizophrenic patients. Methods A total of 21 schizophrenic patients and 20 healthy controls were scanned by the resting-state functional magnetic resonance imaging. The patients received olanzapine treatment and were scanned at two time points. Voxel-mirrored homotopic connectivity (VMHC) and pattern classification techniques were applied to analyze the imaging data. Results Schizophrenic patients presented significantly decreased VMHC in the temporal and inferior frontal gyri, medial prefrontal cortex (MPFC), and motor and low-level sensory processing regions (including the fusiform gyrus and cerebellum lobule VI) relative to healthy controls. The VMHC in the superior/middle MPFC was significantly increased in the patients after eight weeks of treatment. Support vector regression (SVR) analyses revealed that VMHC in the superior/middle MPFC at baseline can predict the symptomatic improvement of the positive and negative syndrome scale after eight weeks of treatment. Conclusions This study demonstrated that olanzapine treatment may normalize decreased homotopic connectivity in the superior/middle MPFC in schizophrenic patients. The VMHC in the superior/middle MPFC may predict individual response for antipsychotic therapy. The findings of this study conduce to the comprehension of the therapy effects of antipsychotic medications on homotopic connectivity in schizophrenia.
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Cui LB, Zhang YJ, Lu HL, Liu L, Zhang HJ, Fu YF, Wu XS, Xu YQ, Li XS, Qiao YT, Qin W, Yin H, Cao F. Thalamus Radiomics-Based Disease Identification and Prediction of Early Treatment Response for Schizophrenia. Front Neurosci 2021; 15:682777. [PMID: 34290581 PMCID: PMC8289251 DOI: 10.3389/fnins.2021.682777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 05/31/2021] [Indexed: 12/15/2022] Open
Abstract
Background Emerging evidence suggests structural and functional disruptions of the thalamus in schizophrenia, but whether thalamus abnormalities are able to be used for disease identification and prediction of early treatment response in schizophrenia remains to be determined. This study aims at developing and validating a method of disease identification and prediction of treatment response by multi-dimensional thalamic features derived from magnetic resonance imaging in schizophrenia patients using radiomics approaches. Methods A total of 390 subjects, including patients with schizophrenia and healthy controls, participated in this study, among which 109 out of 191 patients had clinical characteristics of early outcome (61 responders and 48 non-responders). Thalamus-based radiomics features were extracted and selected. The diagnostic and predictive capacity of multi-dimensional thalamic features was evaluated using radiomics approach. Results Using radiomics features, the classifier accurately discriminated patients from healthy controls, with an accuracy of 68%. The features were further confirmed in prediction and random forest of treatment response, with an accuracy of 75%. Conclusion Our study demonstrates a radiomics approach by multiple thalamic features to identify schizophrenia and predict early treatment response. Thalamus-based classification could be promising to apply in schizophrenia definition and treatment selection.
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Affiliation(s)
- Long-Biao Cui
- The Second Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
| | - Ya-Juan Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Hong-Liang Lu
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Lin Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, China.,Peking University Sixth Hospital/Institute of Mental Health and Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Hai-Jun Zhang
- Department of Clinical Aerospace Medicine, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yong-Qiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao-Sa Li
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yu-Ting Qiao
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Feng Cao
- The Second Medical Center, Chinese PLA General Hospital, Beijing, China
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Xi YB, Guo F, Liu WM, Fu YF, Li JM, Wang HN, Chen FL, Cui LB, Zhu YQ, Li C, Kang XW, Li BJ, Yin H. Triple network hypothesis-related disrupted connections in schizophrenia: A spectral dynamic causal modeling analysis with functional magnetic resonance imaging. Schizophr Res 2021; 233:89-96. [PMID: 34246865 DOI: 10.1016/j.schres.2021.06.024] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 04/15/2021] [Accepted: 06/21/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients. METHODS We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS). RESULTS We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS. CONCLUSIONS Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.
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Affiliation(s)
- Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Wen-Ming Liu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Jia-Ming Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fu-Lin Chen
- College of Life Sciences, Northwest University, Taibai North Rd 229, Xi'an, Shaanxi, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi, China; The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yuan-Qiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Xiao-Wei Kang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Bao-Juan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
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Gangadin SS, Cahn W, Scheewe TW, Hulshoff Pol HE, Bossong MG. Reduced resting state functional connectivity in the hippocampus-midbrain-striatum network of schizophrenia patients. J Psychiatr Res 2021; 138:83-88. [PMID: 33836433 DOI: 10.1016/j.jpsychires.2021.03.041] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 02/22/2021] [Accepted: 03/19/2021] [Indexed: 11/17/2022]
Abstract
Contemporary preclinical models suggest that abnormal functioning of a brain network consisting of the hippocampus, midbrain and striatum plays a critical role in the pathophysiology of schizophrenia. Previous neuroimaging studies examined individual aspects of this model in schizophrenia patients and individuals at clinical high risk for psychosis. However, this exact preclinical brain network has not been translated to human neuroimaging studies with schizophrenia patients and therefore it is currently unknown how functioning of this network is altered in patients. Here we investigated resting state functional connectivity in the hippocampus-midbrain-striatum network of schizophrenia patients, using functional Magnetic Resonance Imaging. Based on preclinical models, a network of functionally validated brain regions comprising the anterior subiculum (SUB), limbic striatum (LS), ventral tegmental area (VTA) and associative striatum (AS) was examined in 47 schizophrenia patients and 51 healthy controls. Schizophrenia patients demonstrated significantly lower functional connectivity in this hippocampus-midbrain-striatum network compared with healthy controls (p = 0.036). Particular reductions in connectivity were found between the SUB and LS (0.002 ± 0.315 and 0.116 ± 0.224, p = 0.040) and between the VTA and AS (0.230 ± 0.268 and 0.356 ± 0.285, p = 0.026). In patients, functional connectivity was not significantly associated with positive, negative or general symptom scores. Reduced connectivity is consistent with the concept of functional brain dysconnectivity as a key feature of the disorder. Our results support the notion that functioning of the hippocampus-midbrain-striatum network is significantly altered in the pathophysiology of schizophrenia.
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Affiliation(s)
- Shiral S Gangadin
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Section of Neuropsychiatry, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Thomas W Scheewe
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Matthijs G Bossong
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands.
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Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging Biomarkers in Schizophrenia. Am J Psychiatry 2021; 178:509-521. [PMID: 33397140 PMCID: PMC8222104 DOI: 10.1176/appi.ajp.2020.20030340] [Citation(s) in RCA: 108] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.
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Affiliation(s)
- Nina V. Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL,Corresponding Author: Nina Vanessa Kraguljac, MD, Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, SC 501, 1720 7th Ave S, Birmingham, AL 35294-0017, 205-996-7171,
| | - William M. McDonald
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | - Alik S. Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Carolyn I. Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA,Veterans Affairs Palo Alto Health Care System, Palo Alto, CA
| | - Mauricio Tohen
- Department of Psychiatry and Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Charles B. Nemeroff
- Department of Psychiatry, University of Texas Dell Medical School, Austin, TX
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A potential biomarker for treatment stratification in psychosis: evaluation of an [ 18F] FDOPA PET imaging approach. Neuropsychopharmacology 2021; 46:1122-1132. [PMID: 32961543 PMCID: PMC8115068 DOI: 10.1038/s41386-020-00866-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/27/2020] [Accepted: 08/19/2020] [Indexed: 12/25/2022]
Abstract
[18F]FDOPA PET imaging has shown dopaminergic function indexed as Kicer differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [18F]FDOPA PET approaches had good test-rest reproducibility across striatal regions (Kicer ICC: 0.68-0.94, SUVRc ICC: 0.76-0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach: Kicer = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (Kicer: ~50%, SUVRc: 40-60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [18F]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of ~£3400 (equivalent to $4232 USD) per patient. These findings indicate [18F]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.
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32
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de la Cruz F, Wagner G, Schumann A, Suttkus S, Güllmar D, Reichenbach JR, Bär KJ. Interrelations between dopamine and serotonin producing sites and regions of the default mode network. Hum Brain Mapp 2021; 42:811-823. [PMID: 33128416 PMCID: PMC7814772 DOI: 10.1002/hbm.25264] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 10/05/2020] [Accepted: 10/14/2020] [Indexed: 12/13/2022] Open
Abstract
Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.
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Affiliation(s)
- Feliberto de la Cruz
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Germany
| | - Andy Schumann
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Stefanie Suttkus
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
| | - Daniel Güllmar
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Germany
| | - Karl-Jürgen Bär
- Lab for Autonomic Neuroscience, Imaging and Cognition (LANIC), Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Germany
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Intermittent theta burst stimulation for negative symptoms of schizophrenia-A double-blind, sham-controlled pilot study. NPJ SCHIZOPHRENIA 2021; 7:10. [PMID: 33580032 PMCID: PMC7880987 DOI: 10.1038/s41537-021-00138-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 12/22/2020] [Indexed: 12/16/2022]
Abstract
Optimal noninvasive brain stimulation parameters for the treatment of negative symptoms of schizophrenia remain unclear. Here, we aimed to investigate the clinical and biological effects of intermittent theta burst transcranial magnetic stimulation (iTBS) in patients with treatment-resistant negative symptoms of schizophrenia (NCT00875498). In a randomized sham-controlled 2-arm study, 22 patients with schizophrenia and treatment-resistant negative symptoms received 20 sessions of either active (n = 12) or sham (n = 10) iTBS. Sessions were delivered twice a day on 10 consecutive working days. Negative symptom severity was assessed 5 times using the Scale for the Assessment of Negative Symptoms (SANS): before iTBS, after iTBS, and 1, 3, and 6 months after iTBS. As a secondary objective, we explored the acute effects of iTBS on functional connectivity of the left dorsolateral prefrontal cortex (DLPFC) using seed-based resting-state functional connectivity MRI (rsFC fMRI) images acquired before and after iTBS. Active iTBS over the left DLPFC significantly decreased negative symptoms severity compared to sham iTBS (F(3,60) = 3.321, p = 0.026). Post hoc analyses revealed that the difference between groups was significant 6 months after the end of stimulation sessions. Neuroimaging revealed an increase in rsFC between the left DLPFC and a brain region encompassing the right lateral occipital cortex and right angular gyrus and a right midbrain region that may encompass dopamine neuron cell bodies. Thus, iTBS over the left DLPFC can alleviate negative symptoms of schizophrenia. The effect might be driven by significant modulation of dopamine transmission.
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Barone A, Signoriello S, Latte G, Vellucci L, Giordano G, Avagliano C, Buonaguro EF, Marmo F, Tomasetti C, Iasevoli F, de Bartolomeis A. Modulation of glutamatergic functional connectivity by a prototypical antipsychotic: Translational inference from a postsynaptic density immediate-early gene-based network analysis. Behav Brain Res 2021; 404:113160. [PMID: 33577880 DOI: 10.1016/j.bbr.2021.113160] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 01/30/2021] [Accepted: 01/31/2021] [Indexed: 10/22/2022]
Abstract
BACKGROUND Although extensively studied, the effect of antipsychotics is not completely understood at a network level. We tested the hypothesis that acute administration of haloperidol would modulate functional connectivity of brain regions relevant to schizophrenia pathophysiology. To assess putative changes in brain network properties and regional interactivity, we studied the expression of Homer1a, an Immediate Early Gene (IEG) demonstrated to be induced by antipsychotic administration and coding for a protein involved in glutamatergic synapses remodeling. METHODS Sprague-Dawley rats (n = 26) assigned to vehicle (VEH; NaCl 0.9%) or haloperidol (HAL; 0.8 mg/kg) were included in the network analysis. Homer1a mRNA induction was evaluated by in situ hybridization. Signal intensity analysis was performed in 33 Regions of Interest (ROIs) in the cortex, the caudate putamen, and the nucleus accumbens. A signal correlation analysis was performed, computing all possible pairwise Pearson correlations among ROIs in the two groups. Two networks were generated for HAL and VEH groups, and their properties and topography were explored. RESULTS VEH and HAL networks showed qualitative differences in global efficiency and clustering coefficient. The HAL network showed enhanced interactivity between cortical and striatal regions, and within caudate putamen subdivisions. On the other hand, it exhibited reduced inter-correlations between cingulate cortex and anterior insula and caudate putamen and nucleus accumbens. Moreover, haloperidol was able to modulate centrality of crucial functional hubs. These preclinical results corroborate and expand the clinical evidence that antipsychotics may modulate specific brain network properties and disease-related circuits' interactivity.
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Affiliation(s)
- Annarita Barone
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Simona Signoriello
- Medical Statistics Unit, University of Campania "Luigi Vanvitelli", 80138, Naples, Italy
| | - Gianmarco Latte
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Licia Vellucci
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Giuseppe Giordano
- Department of Social and Political Studies, University of Salerno, 84084, Fisciano, SA, Italy
| | - Camilla Avagliano
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Elisabetta F Buonaguro
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Federica Marmo
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Carmine Tomasetti
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Felice Iasevoli
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy
| | - Andrea de Bartolomeis
- Laboratory of Molecular and Translational Psychiatry and Unit of Treatment Resistant Psychosis, Section of Psychiatry, Department of Neuroscience, Reproductive Science, and Odontostomatology, University of Naples Federico II, 80131, Napoli, Italy.
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35
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Rubio JM, Malhotra AK, Kane JM. Towards a framework to develop neuroimaging biomarkers of relapse in schizophrenia. Behav Brain Res 2021; 402:113099. [PMID: 33417996 DOI: 10.1016/j.bbr.2020.113099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 12/16/2020] [Accepted: 12/27/2020] [Indexed: 12/31/2022]
Abstract
Schizophrenia is a chronic disorder that often requires long-term relapse-prevention treatment. This treatment is effective for most individuals, yet approximately 20-30 % of them may still relapse despite confirmed adherence. Alternatively, for about 15 % it may be safe to discontinue medications over the long term, but since there are no means to identify who those individuals will be, the recommendation is that all individuals receive long-term relapse-prevention treatment with antipsychotic maintenance. Thus, the current approach to prevent relapse in schizophrenia may be suboptimal for over one third of individuals, either by being insufficient to protect against relapse, or by unnecessarily exposing them to medication side effects. There is great need to identify biomarkers of relapse in schizophrenia to stratify treatment according to the risk and develop therapeutics targeting its pathophysiology. In order to develop a line of research that meets those needs, it is necessary to create a framework by identifying the challenges to this type of study as well as potential areas for biomarker identification and development. In this manuscript we review the literature to create such a framework.
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Affiliation(s)
- Jose M Rubio
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA.
| | - Anil K Malhotra
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
| | - John M Kane
- The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA; Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA; The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA
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36
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Kraguljac NV, Lahti AC. Neuroimaging as a Window Into the Pathophysiological Mechanisms of Schizophrenia. Front Psychiatry 2021; 12:613764. [PMID: 33776813 PMCID: PMC7991588 DOI: 10.3389/fpsyt.2021.613764] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 02/15/2021] [Indexed: 12/16/2022] Open
Abstract
Schizophrenia is a complex neuropsychiatric disorder with a diverse clinical phenotype that has a substantial personal and public health burden. To advance the mechanistic understanding of the illness, neuroimaging can be utilized to capture different aspects of brain pathology in vivo, including brain structural integrity deficits, functional dysconnectivity, and altered neurotransmitter systems. In this review, we consider a number of key scientific questions relevant in the context of neuroimaging studies aimed at unraveling the pathophysiology of schizophrenia and take the opportunity to reflect on our progress toward advancing the mechanistic understanding of the illness. Our data is congruent with the idea that the brain is fundamentally affected in the illness, where widespread structural gray and white matter involvement, functionally abnormal cortical and subcortical information processing, and neurometabolic dysregulation are present in patients. Importantly, certain brain circuits appear preferentially affected and subtle abnormalities are already evident in first episode psychosis patients. We also demonstrated that brain circuitry alterations are clinically relevant by showing that these pathological signatures can be leveraged for predicting subsequent response to antipsychotic treatment. Interestingly, dopamine D2 receptor blockers alleviate neural abnormalities to some extent. Taken together, it is highly unlikely that the pathogenesis of schizophrenia is uniform, it is more plausible that there may be multiple different etiologies that converge to the behavioral phenotype of schizophrenia. Our data underscore that mechanistically oriented neuroimaging studies must take non-specific factors such as antipsychotic drug exposure or illness chronicity into consideration when interpreting disease signatures, as a clear characterization of primary pathophysiological processes is an imperative prerequisite for rational drug development and for alleviating disease burden in our patients.
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Affiliation(s)
- Nina Vanessa Kraguljac
- Neuroimaging and Translational Research Laboratory, Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Adrienne Carol Lahti
- Neuroimaging and Translational Research Laboratory, Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
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Lin X, Deng J, Dong G, Li S, Wu P, Sun H, Liu L, Shi J, Fan Y, Lu L, Li P. Effects of Chronic Pharmacological Treatment on Functional Brain Network Connectivity in Patients with Schizophrenia. Psychiatry Res 2021; 295:113338. [PMID: 32768152 DOI: 10.1016/j.psychres.2020.113338] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 07/19/2020] [Accepted: 07/26/2020] [Indexed: 12/19/2022]
Abstract
Schizophrenia is characterized by the dysfunction of various brain networks. Previous studies suggested that pharmacological treatments for schizophrenia induce functional changes in localized brain regions. However, the effects of antipsychotic treatments on brain networks associated with symptom improvement are still elusive. The elucidation of antipsychotic-induced functional brain changes is essential for the development of biologically informed treatment strategies. Forty-five healthy controls and 44 patients with schizophrenia underwent resting-state fMRI scans at baseline. The patients underwent a second scan after 6 weeks of antipsychotic treatment. At baseline, patients exhibited a significant decrease in functional connectivity of the cingulate gyrus in the default mode network compared to healthy controls, and this decrease was negatively correlated with symptom severity. Clinical improvements were observed after 6 weeks treatment, accompanied by an increase in functional connectivity of the cingulate gyrus in the default mode network and the inferior parietal lobule in the executive control network. The changes in functional connectivity of the inferior parietal lobule were significantly correlated with symptom improvement. These longitudinal neuroimaging findings suggest that schizophrenia might be an outcome of the disruption of the optimal balance of brain networks, and reestablishing this balance through antipsychotic treatment may result in clinical symptom improvement.
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Affiliation(s)
- Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jiahui Deng
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Guangheng Dong
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, China
| | - Suxia Li
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Ping Wu
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Lin Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China; National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China.
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, Key Laboratory of Mental Health, Ministry of Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
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38
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Wang Y, Jiang Y, Su W, Xu L, Wei Y, Tang Y, Zhang T, Tang X, Hu Y, Cui H, Wang J, Yao D, Luo C, Wang J. Temporal Dynamics in Degree Centrality of Brain Functional Connectome in First-Episode Schizophrenia with Different Short-Term Treatment Responses: A Longitudinal Study. Neuropsychiatr Dis Treat 2021; 17:1505-1516. [PMID: 34079256 PMCID: PMC8166279 DOI: 10.2147/ndt.s305117] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/14/2021] [Indexed: 11/23/2022] Open
Abstract
PURPOSE This study investigated temporal dynamics in degree centrality (DC) of the brain functional connectome in first-episode schizophrenia with different short-term treatment responses. METHODS A total of 127 first-episode patients (FEPs) with schizophrenia and 133 healthy controls (HCs) were recruited in this study. All subjects underwent resting-state functional magnetic resonance imaging. FEPs were scanned at baseline (pretreatment) and at follow-up (posttreatment), while HCs were scanned only at baseline. The patients were exposed to naturalistic antipsychotic treatment for 12 weeks, and classified as schizophrenia responders (SRs) or nonresponders (NRs). Voxel-wise dynamic DC analyses were conducted among the SRs (n=75), NRs (n=52), and HCs (n=133) to assess temporal variability in functional connectivity across the entire neuronal network. RESULTS The SRs and NRs showed dissimilar dynamic DC at baseline, with differences mainly involving the temporal lobe. Different DC alteration was observed in the left fusiform gyrus, right fusiform gyrus, left middle cingulate cortex, and left superior parietal gyrus in the SRs and NRs pre- and posttreatment. SRs group and NRs presented opposite changing patterns of dynamic DC in particular regions of the brain. CONCLUSION These findings indicate that dynamic DC abnormalities exist in unmedicated patients with schizophrenia. The NRs differed from the SRs in dynamic DC not only at baseline but in the characteristics of changes before and after treatment as well. Our study may contribute to understanding pathophysiology in schizophrenia with different treatment responses.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Wenjun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yanyan Wei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Xiaochen Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Yegang Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Huiru Cui
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Jinhong Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People's Republic of China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, 200031, People's Republic of China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
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39
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Correll CU, Demyttenaere K, Fagiolini A, Hajak G, Pallanti S, Racagni G, Singh S. Cariprazine in the management of negative symptoms of schizophrenia: state of the art and future perspectives. FUTURE NEUROLOGY 2020. [DOI: 10.2217/fnl-2020-0012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
In schizophrenia, dopaminergic hyperactivity in the mesolimbic regions, or possibly even selectively so in the dorsal striatum, seems to cause the emergence of psychotic symptoms, whereas dopaminergic hypoactivity in cortical regions underlies the negative symptoms and cognitive deficits. Managing the negative symptoms is a major current challenge in the treatment of schizophrenia with a dearth of novel modalities to address this clinical issue. Cariprazine is a novel second-generation antipsychotic that specifically targets the D3 receptor mainly associated to negative symptoms. The review summarizes the main issues regarding negative symptom management and the role of cariprazine treatment.
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Affiliation(s)
- Christoph U Correll
- Department of Psychiatry Research, The Zucker Hillside Hospital, 75–59 263rd Street Glen Oaks, NY 11004, USA
- Department of Psychiatry & Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
- Department of Child & Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Koen Demyttenaere
- University Psychiatric Center KU Leuven, Campus Gasthuisberg & University of Leuven, Psychiatry Research Group, Department of Neurosciences, Faculty of Medicine, Herestraat 49, Leuven 3000, Belgium
| | - Andrea Fagiolini
- Department of Molecular Medicine, University of Siena School of Medicine, Siena 53100, Italy
| | - Göran Hajak
- Department of Psychiatry, Psychosomatic Medicine & Psychotherapy, Sozialstiftung Bamberg, St.-Getreustrasse 18, Bamberg 96049, Germany
| | | | - Giorgio Racagni
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Via G. Balzaretti 9, Milano 20123, Italy
| | - Swaran Singh
- Mental Health & Wellbeing, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
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40
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Dazzan P, Lawrence AJ, Reinders AATS, Egerton A, van Haren NEM, Merritt K, Barker GJ, Perez-Iglesias R, Sendt KV, Demjaha A, Nam KW, Sommer IE, Pantelis C, Wolfgang Fleischhacker W, van Rossum IW, Galderisi S, Mucci A, Drake R, Lewis S, Weiser M, Martinez Diaz-Caneja CM, Janssen J, Diaz-Marsa M, Rodríguez-Jimenez R, Arango C, Baandrup L, Broberg B, Rostrup E, Ebdrup BH, Glenthøj B, Kahn RS, McGuire P. Symptom Remission and Brain Cortical Networks at First Clinical Presentation of Psychosis: The OPTiMiSE Study. Schizophr Bull 2020; 47:444-455. [PMID: 33057670 PMCID: PMC7965060 DOI: 10.1093/schbul/sbaa115] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, that may be particularly prominent, already at illness onset, in those more likely to have poorer symptom remission following treatment with the first antipsychotic. The identification of strong neuroanatomical markers of symptom remission could thus facilitate stratification and individualized treatment of patients with schizophrenia. We used magnetic resonance imaging at baseline to examine brain regional and network correlates of subsequent symptomatic remission in 167 medication-naïve or minimally treated patients with first-episode schizophrenia, schizophreniform disorder, or schizoaffective disorder entering a three-phase trial, at seven sites. Patients in remission at the end of each phase were randomized to treatment as usual, with or without an adjunctive psycho-social intervention for medication adherence. The final follow-up visit was at 74 weeks. A total of 108 patients (70%) were in remission at Week 4, 85 (55%) at Week 22, and 97 (63%) at Week 74. We found no baseline regional differences in volumes, cortical thickness, surface area, or local gyrification between patients who did or did not achieved remission at any time point. However, patients not in remission at Week 74, at baseline showed reduced structural connectivity across frontal, anterior cingulate, and insular cortices. A similar pattern was evident in patients not in remission at Week 4 and Week 22, although not significantly. Lack of symptom remission in first-episode psychosis is not associated with regional brain alterations at illness onset. Instead, when the illness becomes a stable entity, its association with the altered organization of cortical gyrification becomes more defined.
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Affiliation(s)
- Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,To whom correspondence should be addressed; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London SE5 8AF, UK; tel: +44 0207-848-0700, fax: +44 (0)207 848 0287, e-mail:
| | - Andrew J Lawrence
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Antje A T S Reinders
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK
| | - Alice Egerton
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Sophia Children’s Hospital, Rotterdam, The Netherlands,Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Kate Merritt
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Gareth J Barker
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Rocio Perez-Iglesias
- Early Intervention in Psychosis Service, Department of Psychiatry, Hospital Universitario Marques de Valdecilla, Santander, Spain
| | - Kyra-Verena Sendt
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Arsime Demjaha
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Kie W Nam
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Iris E Sommer
- Department of Biomedical Sciences of Cells and Systems, Rijksuniversiteit Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - W Wolfgang Fleischhacker
- Medical University of Innsbruck, Department of Psychiatry, Psychotherapy and Psychosomatics, Division of Psychiatry I, Innsbruck, Austria
| | - Inge Winter van Rossum
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Richard Drake
- Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Manchester, UK,Greater Manchester Mental Health Foundation Trust, Manchester, UK,Manchester Academic Health Sciences Centre, Manchester, UK
| | - Shon Lewis
- Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Manchester, UK,Greater Manchester Mental Health Foundation Trust, Manchester, UK,Manchester Academic Health Sciences Centre, Manchester, UK
| | - Mark Weiser
- Department of Psychiatry, Sheba Medical Center, Tel Aviv, Israel,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Covadonga M Martinez Diaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañon, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense Madrid, Madrid, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañon, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense Madrid, Madrid, Spain
| | - Marina Diaz-Marsa
- Department of Psychiatry, Instituto de Investigación Sanitaria Hospital Clínico San Carlos; CIBERSAM; Universidad Complutense Madrid, Madrid, Spain
| | - Roberto Rodríguez-Jimenez
- Department of Psychiatry, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12); CIBERSAM; Universidad Complutense Madrid, Madrid, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañon, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense Madrid, Madrid, Spain
| | - Lone Baandrup
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Brian Broberg
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bjørn H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Birte Glenthøj
- Center for Neuropsychiatric Schizophrenia Research, CNSR, and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Copenhagen, Denmark,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rene S Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Philip McGuire
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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41
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Li Q, Cao X, Liu S, Li Z, Wang Y, Cheng L, Yang C, Xu Y. Dynamic Alterations of Amplitude of Low-Frequency Fluctuations in Patients With Drug-Naïve First-Episode Early Onset Schizophrenia. Front Neurosci 2020; 14:901. [PMID: 33122982 PMCID: PMC7573348 DOI: 10.3389/fnins.2020.00901] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 08/03/2020] [Indexed: 12/26/2022] Open
Abstract
Abnormalities in static neural activity have been widely reported in early onset schizophrenia (EOS). However, dynamic brain activity alterations over time in EOS are unclear. Here, we investigated whether temporal dynamic changes in spontaneous neural activity are influenced by EOS. A total of 78 drug-naïve first-episode patients with EOS and 90 healthy controls (HCs) were enrolled in this study. Dynamic amplitude of low-frequency fluctuations (dALFF) was performed to examine the abnormal time-varying local neural activity in EOS. Furthermore, we investigated the relationships between abnormalities in dALFF variability and clinical characteristics in EOS patients. Compared to HCs, EOS patients showed significantly decreased dALFF variability in the bilateral precuneus, right superior marginal gyrus, right post-central gyrus and increased dALFF in the right middle temporal gyrus (MTG). Moreover, increased dALFF variability in MTG was negatively associated with negative symptoms in EOS. Our findings reveal increased dynamic local neural activity in higher order networks of the cortex, suggesting that enhanced spontaneous brain activity may be a predominant neural marker for brain maturation. In addition, decreased dALFF variability in the default mode network (DMN) and limbic system may reflect unusually dynamic neural activity. This dysfunctional brain activity could distinguish between patients and HCs and deepen our understanding of the pathophysiological mechanisms of EOS.
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Affiliation(s)
- Qiang Li
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Xiaohua Cao
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Zexuan Li
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Yanfang Wang
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Long Cheng
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Chengxiang Yang
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Yong Xu
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China.,Department of Mental Health, Shanxi Medical University, Taiyuan, China
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42
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Fritze S, Thieme CE, Kubera KM, Northoff G, Schmitgen MM, Wolf RC, Hirjak D. Brainstem alterations contribute to catatonia in schizophrenia spectrum disorders. Schizophr Res 2020; 224:82-87. [PMID: 33046340 DOI: 10.1016/j.schres.2020.09.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 09/20/2020] [Accepted: 09/26/2020] [Indexed: 01/19/2023]
Abstract
Catatonia is a severe psychomotor syndrome that frequently occurs in patients with schizophrenia spectrum disorders (SSD). Accumulating neuroimaging evidence suggests orbitofrontal, frontoparietal and cerebellar network dysfunction in catatonia. Very little is known about contributions of brainstem regions (as part of the dopaminergic-based subcortical-cortical motor circuit) to catatonia in SSD patients. Here, we used structural magnetic resonance imaging (MRI) at 3 T to examine volumes of brainstem regions in catatonic SSD patients compared to non-catatonic SSD patients. Catatonia severity was measured with the Northoff Catatonia Rating Scale (NCRS). The segmentation of the brainstem in order to investigate the volumes of medulla oblongata, pons, superior cerebellar pedunculus, and midbrain was carried out using FreeSurfer vers. 6.0. Catatonic patients (NCRS total score ≥ 3; at least 1 point in the three different symptom categories; i.e., motor, behavioral, and affective; n = 30) had significantly smaller midbrain volumes (p = 0.004, Bonferroni corr.) when compared to non-catatonic patients (NCRS total score = 0; n = 29). In catatonic patients, significant correlations were detected between NCRS motor scores and whole brainstem (p = 0.015, Bonferroni corr.) volumes. These results support a neuromechanistically important role of brainstem structures in catatonia in SSD, particularly in motor symptom expression.
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Affiliation(s)
- Stefan Fritze
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Cristina E Thieme
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Mike M Schmitgen
- Center for Psychosocial Medicine, Department of General Psychiatry, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Robert C Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
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43
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Nakamura Y, Okada N, Koshiyama D, Kamiya K, Abe O, Kunimatsu A, Okanoya K, Kasai K, Koike S. Differences in Functional Connectivity Networks Related to the Midbrain Dopaminergic System-Related Area in Various Psychiatric Disorders. Schizophr Bull 2020; 46:1239-1248. [PMID: 31901932 PMCID: PMC7505191 DOI: 10.1093/schbul/sbz121] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Disruptions in the dopamine system have been observed in psychiatric disorders. Since dopamine is mainly produced in the ventral tegmental area (VTA), elucidating the differences in the VTA neural network across psychiatric disorders would facilitate a greater understanding of the pathophysiological mechanisms underlying these disorders. However, no study has compared VTA-seed-based functional connectivity across psychiatric disorders. Therefore, we conducted a resting-state functional magnetic resonance imaging (rs-fMRI) study to perform a seed-based fMRI analysis, using the VTA as a seed. METHODS We included participants with major depressive disorder (MDD; n = 45), schizophrenia (n = 32), and bipolar disorder (BPD; n = 30), along with healthy control participants (n = 46) who were matched for age, gender, and handedness. RESULTS The results showed that patients with MDD and BPD had altered VTA-related connectivity in the superior frontal gyrus, frontal pole regions, hippocampus, cerebellum, and posterior cingulate cortex. Some of these differences in connectivity were also found between affective disorders and schizophrenia; however, there were no differences between the schizophrenia and control groups. Connectivity between the VTA and the hippocampus was correlated with positive symptoms in the schizophrenia group. The connectivity was not associated with medication dose, and the results remained significant after controlling for dose. CONCLUSIONS The results suggest that altered brain functional connectivity related to VTA networks could be associated with the distinctive pathophysiologies of psychiatric disorders, especially affective disorders.
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Affiliation(s)
- Yuko Nakamura
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
| | - Daisuke Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akira Kunimatsu
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Radiology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Kazuo Okanoya
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Kiyoto Kasai
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Shinsuke Koike
- Center for Integrative Science of Human Behavior, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science at the University of Tokyo, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
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44
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van Dellen E, Börner C, Schutte M, van Montfort S, Abramovic L, Boks MP, Cahn W, van Haren N, Mandl R, Stam CJ, Sommer I. Functional brain networks in the schizophrenia spectrum and bipolar disorder with psychosis. NPJ SCHIZOPHRENIA 2020; 6:22. [PMID: 32879316 PMCID: PMC7468123 DOI: 10.1038/s41537-020-00111-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 06/23/2020] [Indexed: 12/22/2022]
Abstract
Psychotic experiences have been proposed to lie on a spectrum, ranging from subclinical experiences to treatment-resistant schizophrenia. We aimed to characterize functional connectivity and brain network characteristics in relation to the schizophrenia spectrum and bipolar disorder with psychosis to disentangle neural correlates to psychosis. Additionally, we studied antipsychotic medication and lithium effects on network characteristics. We analyzed functional connectivity strength and network topology in 487 resting-state functional MRI scans of individuals with schizophrenia spectrum disorder (SCZ), bipolar disorder with a history of psychotic experiences (BD), treatment-naïve subclinical psychosis (SCP), and healthy controls (HC). Since differences in connectivity strength may confound group comparisons of brain network topology, we analyzed characteristics of the minimum spanning tree (MST), a relatively unbiased backbone of the network. SCZ and SCP subjects had a lower connectivity strength than BD and HC individuals but showed no differences in network topology. In contrast, BD patients showed a less integrated network topology but no disturbances in connectivity strength. No differences in outcome measures were found between SCP and SCZ, or between BD patients that used antipsychotic medication or lithium and those that did not. We conclude that functional networks in patients prone to psychosis have different signatures for chronic SCZ patients and SCP compared to euthymic BD patients, with a limited role for medication. Connectivity strength effects may have confounded previous studies, as no functional network alterations were found in SCZ after strict correction for connectivity strength.
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Affiliation(s)
- Edwin van Dellen
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
- Department of Intensive Care Medicine and UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Corinna Börner
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Maya Schutte
- University of Groningen, Department of Neuroscience, University Medical Center Groningen, Groningen, The Netherlands
| | - Simone van Montfort
- Department of Intensive Care Medicine and UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Lucija Abramovic
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marco P Boks
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Neeltje van Haren
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands
| | - René Mandl
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Iris Sommer
- University of Groningen, Department of Neuroscience, University Medical Center Groningen, Groningen, The Netherlands
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
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45
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Herms EN, Bishop JR, Okuneye VT, Tamminga CA, Keshavan MS, Pearlson GD, Clementz BA, McDowell JE, Ivleva EI, Gershon ES, Sweeney JA, Keedy SK. No connectivity alterations for striatum, default mode, or salience network in association with self-reported antipsychotic medication dose in a large chronic patient group. Schizophr Res 2020; 223:359-360. [PMID: 32624351 PMCID: PMC8082971 DOI: 10.1016/j.schres.2020.06.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/01/2020] [Accepted: 06/18/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Emma N. Herms
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Jeffrey R. Bishop
- Departments of Pharmacy and Psychiatry, University of Minnesota, Minneapolis, MN, United States
| | - Victoria T. Okuneye
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Carol A. Tamminga
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - Matcheri S. Keshavan
- Department of Psychiatry, Beth Israel Deaconness Medical Center and Harvard Medical School, Boston, MA, United States
| | - Godfrey D. Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, United States; Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - Brett A. Clementz
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Jennifer E. McDowell
- Department of Psychology and Neuroscience, University of Georgia, Athens, GA, United States
| | - Elena I. Ivleva
- Department of Psychiatry, UT-Southwestern Medical Center, Dallas, TX, United States
| | - Elliot S. Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
| | - Sarah K. Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
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46
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Miao Q, Pu C, Wang Z, Yan CG, Shi C, Cao Q, Wang X, Cheng Z, Han X, Yang L, Lai Y, Yuan Y, Ma H, Li K, Hong N, Yu X. Influence of More Than 5 Years of Continuous Exposure to Antipsychotics on Cerebral Functional Connectivity of Chronic Schizophrenia. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2020; 65:463-472. [PMID: 32027178 PMCID: PMC7298577 DOI: 10.1177/0706743720904815] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE To explore the effect of long-term antipsychotics use on the strength of functional connectivity (FC) in the brains of patients with chronic schizophrenia. METHOD We collected resting-state functional magnetic resonance imaging from 15 patients with continuously treated chronic schizophrenia (TCS), 19 patients with minimally TCS (MTCS), and 20 healthy controls (HCs). Then, we evaluated and compared the whole-brain FC strength (FCS; including full-range, short-range, and long-range FCS) among patients with TCS, MTCS, and HCs. RESULTS Patients with TCS and MTCS showed reduced full-/short-range FC compared with the HCs. No significant differences in the whole-brain FCS (including full-range, short-range, and long-range FCS) or clinical characteristics were identified between patients with TCS and MTCS. Additionally, the FCS in the right fusiform gyrus, right inferior temporal gyrus, and right inferior occipital gyrus negatively correlated with the duration of illness and positively correlated with onset age across all patients with chronic schizophrenia. CONCLUSIONS Regardless of the long-term use of antipsychotics, patients with chronic schizophrenia show decreased FC compared with healthy individuals. For some patients with chronic schizophrenia, the influence of long-term and minimal/short-term antipsychotic exposure on resting-state FC was similar. The decreased full- and short-range FCS in the right fusiform gyrus, right inferior temporal gyrus, and right inferior occipital gyrus may be an ongoing pathological process that is not altered by antipsychotic interventions in patients with chronic schizophrenia. Large-sample, long-term follow-up studies are still needed for further exploration.
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Affiliation(s)
- Qi Miao
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Chengcheng Pu
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Zhijiang Wang
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.,Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Chuan Shi
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Qingjiu Cao
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Xijin Wang
- The First Psychiatric Hospital of Harbin, Heilongjiang, China
| | - Zhang Cheng
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Xue Han
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Lei Yang
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Yunyao Lai
- Department of Radiology, People's Hospital, Peking University, Beijing, China
| | - Yanbo Yuan
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Hong Ma
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
| | - Keqing Li
- The Sixth People's Hospital of Hebei Province, Baoding, China
| | - Nan Hong
- Department of Radiology, People's Hospital, Peking University, Beijing, China
| | - Xin Yu
- Peking University Sixth Hospital, Beijing, China.,Peking University Institute of Mental Health, Beijing, China.,NHC Key Laboratory of Mental Health, Peking University, Beijing, China.,National Clinical Research Center for Mental Health Disorders, Peking University Sixth Hospital, Beijing, China
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47
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Mabry SJ, McCollum LA, Farmer CB, Bloom ES, Roberts RC. Evidence for altered excitatory and inhibitory tone in the post-mortem substantia nigra in schizophrenia. World J Biol Psychiatry 2020; 21:339-356. [PMID: 31062628 PMCID: PMC6891153 DOI: 10.1080/15622975.2019.1615638] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Objectives: The substantia nigra (SN) receives glutamatergic and GABAergic inputs that regulate dopaminergic neuronal activity. Imaging studies have shown hyperactivity of the SN in schizophrenia (SZ) patients. We examined neurochemically defined inputs to the SN, synaptic density, and neuromelanin content that might contribute to or reflect this hyperexcitability.Methods: Glutamatergic axon terminals were identified by the immunohistochemical localisation of vGLUT1 and vGLUT2; GABA inputs were identified by the immunohistochemical localisation of GAD67. Neuromelanin granules are visible in unstained sections and thus were assessed in unstained sections. Optical densitometry was measured to assess the density of vGLUT1, vGLUT2 or GAD67 immunolabelled axon terminals and neuromelanin granules. Electron microscopy was used to quantify synaptic and mitochondrial density.Results: Compared to controls, SZ subjects had nonsignificant trends toward a decrease in vGLUT1, and an increase in both vGLUT2 and GAD67. vGLUT1 was negatively correlated with GAD67 in normal controls (NCs) and positively correlated in SZ subjects. A correlation of coefficient analysis showed a significant difference between the negative correlation in NCs and the positive correlation in SZ subjects. Frequency histograms showed the distribution of neuromelanin density was different in SZ subjects compared to NCs. Synaptic density data showed a decrease in inhibitory synapses in SZ subjects. Mitochondrial density was normal in SZ subjects.Conclusions: Synaptic density alterations and the lack of a positive correlation between GAD67 and vGLUT1 could contribute to hyperactivity in the SN.
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Affiliation(s)
| | | | | | | | - Rosalinda C. Roberts
- Corresponding author: Rosalinda C. Roberts, PhD, 865D Sparks Center, 1720 7th Ave. South, University of Alabama at Birmingham, Birmingham, AL, 35294, Tel. 205-996-9373,
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48
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Seah C, Brennand KJ. If there is not one cure for schizophrenia, there may be many. NPJ SCHIZOPHRENIA 2020; 6:11. [PMID: 32313122 PMCID: PMC7170875 DOI: 10.1038/s41537-020-0101-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 02/28/2020] [Indexed: 11/24/2022]
Affiliation(s)
- Carina Seah
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kristen J Brennand
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. .,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. .,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. .,Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. .,Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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49
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Kim D, Moussa‐Tooks AB, Bolbecker AR, Apthorp D, Newman SD, O'Donnell BF, Hetrick WP. Cerebellar-cortical dysconnectivity in resting-state associated with sensorimotor tasks in schizophrenia. Hum Brain Mapp 2020; 41:3119-3132. [PMID: 32250008 PMCID: PMC7336143 DOI: 10.1002/hbm.25002] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/15/2020] [Accepted: 03/25/2020] [Indexed: 12/11/2022] Open
Abstract
Abnormalities of cerebellar function have been implicated in the pathophysiology of schizophrenia. Since the cerebellum has afferent and efferent projections to diverse brain regions, abnormalities in cerebellar lobules could affect functional connectivity with multiple functional systems in the brain. Prior studies, however, have not examined the relationship of individual cerebellar lobules with motor and nonmotor resting‐state functional networks. We evaluated these relationships using resting‐state fMRI in 30 patients with a schizophrenia‐spectrum disorder and 37 healthy comparison participants. For connectivity analyses, the cerebellum was parcellated into 18 lobular and vermal regions, and functional connectivity of each lobule to 10 major functional networks in the cerebrum was evaluated. The relationship between functional connectivity measures and behavioral performance on sensorimotor tasks (i.e., finger‐tapping and postural sway) was also examined. We found cerebellar–cortical hyperconnectivity in schizophrenia, which was predominantly associated with Crus I, Crus II, lobule IX, and lobule X. Specifically, abnormal cerebellar connectivity was found to the cerebral ventral attention, motor, and auditory networks. This cerebellar–cortical connectivity in the resting‐state was differentially associated with sensorimotor task‐based behavioral measures in schizophrenia and healthy comparison participants—that is, dissociation with motor network and association with nonmotor network in schizophrenia. These findings suggest that functional association between individual cerebellar lobules and the ventral attentional, motor, and auditory networks is particularly affected in schizophrenia. They are also consistent with dysconnectivity models of schizophrenia suggesting cerebellar contributions to a broad range of sensorimotor and cognitive operations.
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Affiliation(s)
- Dae‐Jin Kim
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
| | - Alexandra B. Moussa‐Tooks
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
- Program in NeuroscienceIndiana UniversityBloomingtonIndianaUSA
| | - Amanda R. Bolbecker
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| | - Deborah Apthorp
- School of Psychology, Faculty of Medicine and HealthUniversity of New EnglandArmidaleNew South WalesAustralia
- Research School of Computer Science, College of Engineering and Computer ScienceAustralian National UniversityCanberraAustralian Capital TerritoryAustralia
| | - Sharlene D. Newman
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
- Program in NeuroscienceIndiana UniversityBloomingtonIndianaUSA
| | - Brian F. O'Donnell
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
- Program in NeuroscienceIndiana UniversityBloomingtonIndianaUSA
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| | - William P. Hetrick
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
- Program in NeuroscienceIndiana UniversityBloomingtonIndianaUSA
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
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50
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Duan X, Hu M, Huang X, Dong X, Zong X, He C, Xiao J, Tang J, Chen X, Chen H. Effects of risperidone monotherapy on the default-mode network in antipsychotic-naïve first-episode schizophrenia: Posteromedial cortex heterogeneity and relationship with the symptom improvements. Schizophr Res 2020; 218:201-208. [PMID: 31954611 DOI: 10.1016/j.schres.2020.01.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 10/23/2019] [Accepted: 01/06/2020] [Indexed: 12/12/2022]
Abstract
The default mode network (DMN) has been consistently detected abnormally in schizophrenia. However, the effects of antipsychotics on this network are still under debate, and inconsistent findings may be due to the functional heterogeneity within the DMN, especially in the component regions of the posteromedial cortex (PMC). Here, we conducted a longitudinal research on the resting-state functional connectivity of the PMC subdivisions on 33 treatment-naive first-episode patients with schizophrenia at baseline and after 8 weeks of risperidone treatment through resting-state functional magnetic resonance imaging. At baseline, the patients demonstrated decreased connectivity of the three PMC seeds with several brain regions (target regions) compared with healthy controls. We then tested the effect of antipsychotic treatment on the functional connectivity between the three seeds and the target regions. We found that, one of the three seeds encompassed in PMC, namely, posterior cingulate cortex (PCC), was observed to have increased functional connectivity with the bilateral thalamus and the left lingual gyrus (LG). On the contrary, the functional connectivity between the target regions and the two remaining seeds, namely, the retrosplenial cortex and precuneus, was unaffected by risperidone treatment. Correlation analysis revealed a positive correlation between longitudinal change of PCC-LG connectivity and symptom improvement. These findings indicated the heterogeneity of the PMC in response to antipsychotic treatment and suggested the role of PCC as a treatment biomarker for schizophrenia.
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Affiliation(s)
- Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Maolin Hu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China; Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, Hunan, PR China; Division of Molecular Imaging and Neuropathology, Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Xinyue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Xia Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China; Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, Hunan, PR China; Division of Molecular Imaging and Neuropathology, Columbia University and New York State Psychiatric Institute, New York, NY, USA
| | - Changchun He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Jinsong Tang
- Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, Hunan, PR China; Mental Health Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Changsha, Hunan, PR China
| | - Xiaogang Chen
- Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, Hunan, PR China; Mental Health Institute of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center on Mental Disorders (Xiangya), China National Technology Institute on Mental Disorders, Changsha, Hunan, PR China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, PR China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China.
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