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Van Dyken PC, Yang K, Faria AV, Sawa A, MacKinley M, Khan AR, Palaniyappan L. Stable White Matter Structure in the First Three Years After Psychosis Onset. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2025; 5:100472. [PMID: 40231305 PMCID: PMC11994302 DOI: 10.1016/j.bpsgos.2025.100472] [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: 10/16/2024] [Revised: 02/08/2025] [Accepted: 02/11/2025] [Indexed: 04/16/2025] Open
Abstract
Background White matter alterations observed using diffusion weighted imaging have become a hallmark of chronic schizophrenia, but it is unclear when these changes arise over the course of the disease. Nearly all studies reported to date have been cross-sectional, so despite their large sample sizes, they cannot determine whether changes accumulate as a degenerative process or patients with preexisting white matter damage are predisposed to more chronic forms of schizophrenia. Methods We examined 160 scans comprising 2 years of annual follow-up data from 42 control participants and 28 patients with schizophrenia recruited in the first 2 years since their diagnosis, totaling 2 to 3 scans per participant. We also examined 6-month follow-up data obtained from an ultra-high field (7T) scanner (68 scans; n = 19 patients with first-episode schizophrenia, n = 15 control participants) as a validation dataset. A longitudinal model was used to compare the trajectory of diffusion tensor parameters in patients and control participants. Results Positive and negative symptom scores were correlated with diffusion parameters using region of interest-based approaches. No longitudinal differences between patients and control participants were observed for any diffusion tensor imaging parameter in either dataset. However, we did observe consistent associations between white matter alterations and negative symptoms in both datasets. Conclusions White matter does not appear to be susceptible to schizophrenia-linked degeneration in the early stages of disease, but preexisting pathology may be linked to disease severity.
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Affiliation(s)
- Peter C. Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Andreia V. Faria
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Akira Sawa
- Departments of Psychiatry, Neuroscience, Biomedical Engineering, Pharmacology, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, Ontario, Canada
| | - Ali R. Khan
- Robarts Research Institute, Western University, London, Ontario, Canada
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Western University, London, Ontario, Canada
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
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Elvira UKA, Rivero O, Postiguillo A, García-Marti G, Escarti MJ, Aguilar EJ, David-Lluesma J, Molto MD, Perez-Rando M, Nacher J. Altered volume of thalamic nuclei and genetic expression in first-episode psychotic patients, and their association with childhood adversity. Prog Neuropsychopharmacol Biol Psychiatry 2025; 139:111371. [PMID: 40250785 DOI: 10.1016/j.pnpbp.2025.111371] [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: 11/12/2024] [Revised: 03/21/2025] [Accepted: 04/15/2025] [Indexed: 04/20/2025]
Abstract
Childhood maltreatment is a significant risk factor for schizophrenia, and there are correlations between these adversities and thalamic gray matter density. The thalamus, a subcortical structure with various nuclei with specific connections, relays sensory information and participates in higher cognitive processes. Thalamic alterations are evident in psychotic disorders, and early-life adversities may affect its development, potentially contributing to psychosis. However, no evidence exists of volumetric alterations in thalamic nuclei in first-episode psychosis (FEP) patients related to early traumatic events. This study recruited 70 FEP patients and 68 age-matched healthy controls, who underwent 3 T structural MRI and clinical scales, including the Childhood Trauma Questionnaire (CTQ). The thalamus was analyzed for shape and segmented into nuclei to assess volume. Additionally, peripheral blood was analyzed for the expression of VCAN, CSGALNACT1, ST8SIA4, NRGN, SP4, and TOX genes, which are related to neuronal plasticity in the thalamus and psychosis. Results showed volumetric reductions in the whole thalamus and specific nuclei (lateral posterior, lateral geniculate, medial geniculate, ventrolateral, centromedian, anteroventral, mediodorsal, and pulvinar). The thalamus did not show shape alterations. A significant association was observed between physical neglect during childhood and the volume of the left thalamus and its anteroventral nucleus. Reduced expression of ST8SIA4 and SP4 genes was detected in FEP patients compared to healthy controls, with correlations between thalamic nuclei volumes and gene expression differing between groups. In conclusion, this study links thalamic nuclei volume with childhood adversities in FEP and highlights changes in ST8SIA4 and SP4 expression, correlating with thalamic nuclei volumes.
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Affiliation(s)
- Uriel K A Elvira
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain
| | - Olga Rivero
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain; Department of Genetics. Faculty of Biological Sciences, Universitat de València, Spain
| | - Alba Postiguillo
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain
| | - Gracian García-Marti
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Quironsalud Hospital, Valencia, Spain
| | - Maria Jose Escarti
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain; Servicio de Psiquiatría, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Eduardo J Aguilar
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain; Servicio de Psiquiatría, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Javier David-Lluesma
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain; CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain; Department of Genetics. Faculty of Biological Sciences, Universitat de València, Spain
| | - Maria Dolores Molto
- CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain; Department of Genetics. Faculty of Biological Sciences, Universitat de València, Spain
| | - Marta Perez-Rando
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain; CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain.
| | - Juan Nacher
- Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain; CIBERSAM, ISCIII Spanish National Network for Research in Mental Health, Madrid, Spain; Biomedical Research Institute of the Clinic Hospital of Valencia (INCLIVA), Valencia, Spain.
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Faghiri A, Yang K, Faria A, Ishizuka K, Sawa A, Adali T, Calhoun V. Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study. Netw Neurosci 2024; 8:734-761. [PMID: 39355435 PMCID: PMC11349031 DOI: 10.1162/netn_a_00372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 03/06/2024] [Indexed: 10/03/2024] Open
Abstract
Representing data using time-resolved networks is valuable for analyzing functional data of the human brain. One commonly used method for constructing time-resolved networks from data is sliding window Pearson correlation (SWPC). One major limitation of SWPC is that it applies a high-pass filter to the activity time series. Therefore, if we select a short window (desirable to estimate rapid changes in connectivity), we will remove important low-frequency information. Here, we propose an approach based on single sideband modulation (SSB) in communication theory. This allows us to select shorter windows to capture rapid changes in the time-resolved functional network connectivity (trFNC). We use simulation and real resting-state functional magnetic resonance imaging (fMRI) data to demonstrate the superior performance of SSB+SWPC compared to SWPC. We also compare the recurring trFNC patterns between individuals with the first episode of psychosis (FEP) and typical controls (TC) and show that FEPs stay more in states that show weaker connectivity across the whole brain. A result exclusive to SSB+SWPC is that TCs stay more in a state with negative connectivity between subcortical and cortical regions. Based on all the results, we argue that SSB+SWPC is more sensitive for capturing temporal variation in trFNC.
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Affiliation(s)
- Ashkan Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andreia Faria
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Koko Ishizuka
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akira Sawa
- Departments of Psychiatry, Neuroscience, Biomedical Engineering, Genetic Medicine, and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Tülay Adali
- Deptartment of CSEE, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Vince Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Wang Y, Ouyang L, Fan L, Zheng W, Li Z, Tang J, Yuan L, Li C, Jin K, Liu W, Chen X, He Y, Ma X. Functional and structural abnormalities of thalamus in individuals at early stage of schizophrenia. Schizophr Res 2024; 271:292-299. [PMID: 39079406 DOI: 10.1016/j.schres.2024.07.045] [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: 09/23/2023] [Revised: 07/17/2024] [Accepted: 07/20/2024] [Indexed: 09/11/2024]
Abstract
BACKGROUND Thalamic abnormalities in schizophrenia are recognized, alongside cognitive deficits. However, the current findings about these abnormalities during the prodromal period remain relatively few and inconsistent. This study applied multimodal methods to explore the alterations in thalamic function and structure and their relationship with cognitive function in first-episode schizophrenia (FES) patients and ultra-high-risk (UHR) individuals, aiming to affirm the thalamus's role in schizophrenia development and cognitive deficits. METHODS 75 FES patients, 60 UHR individuals, and 60 healthy controls (HC) were recruited. Among the three groups, gray matter volume (GMV) and functional connectivity (FC) were evaluated to reflect the structural and functional abnormalities in the thalamus. Pearson correlation was used to calculate the association between these abnormalities and cognitive impairments. RESULTS No significant difference in GMV of the thalamus was found among the abovementioned three groups. Compared with HC individuals, FES patients had decreased thalamocortical FC mostly in the thalamocortical triple network, including the default mode network (DMN), salience network (SN), and executive control network (ECN). UHR individuals had similar but milder dysconnectivity as the FES group. Furthermore, FC between the left thalamus and right putamen was significantly correlated with execution speed and attention in the FES group. CONCLUSIONS Our findings revealed decreased thalamocortical FC associated with cognitive deficits in FES and UHR subjects. This improves our understanding of the functional alterations in thalamus in prodromal stage of schizophrenia and the related factors of the cognitive impairment of the disease. TRIAL REGISTRATION ClinicalTrials.govNCT03965598; https://clinicaltrials.gov/ct2/show/NCT03965598.
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Affiliation(s)
- Yujue Wang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Lijun Ouyang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Lejia Fan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Wenxiao Zheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinsong Tang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Liu Yuan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Ke Jin
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Weiqing Liu
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China; Laboratory for Molecular Mechanisms of Brain Development, Center for Brain Science (CBS), RIKEN, Wako, Saitama, Japan
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; China National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China; Institute of Mental Health, Changsha, Hunan, China; Hunan Medical Center for Mental Health, Changsha, Hunan, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; China National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China; Institute of Mental Health, Changsha, Hunan, China; Hunan Medical Center for Mental Health, Changsha, Hunan, China.
| | - Xiaoqian Ma
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; China National Technology Institute on Mental Disorders, Changsha, Hunan, China; Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, Hunan, China; Institute of Mental Health, Changsha, Hunan, China; Hunan Medical Center for Mental Health, Changsha, Hunan, China.
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Jensen KM, Calhoun VD, Fu Z, Yang K, Faria AV, Ishizuka K, Sawa A, Andrés-Camazón P, Coffman BA, Seebold D, Turner JA, Salisbury DF, Iraji A. A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry. Neuroimage Clin 2024; 41:103584. [PMID: 38422833 PMCID: PMC10944191 DOI: 10.1016/j.nicl.2024.103584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 01/31/2024] [Accepted: 02/25/2024] [Indexed: 03/02/2024]
Abstract
Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.
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Affiliation(s)
- Kyle M Jensen
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA.
| | - Vince D Calhoun
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Zening Fu
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
| | - Kun Yang
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andreia V Faria
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Koko Ishizuka
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Pablo Andrés-Camazón
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA; Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, Madrid, Spain
| | - Brian A Coffman
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dylan Seebold
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jessica A Turner
- Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Dean F Salisbury
- University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Armin Iraji
- Georgia State University, Atlanta, GA, USA; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Atlanta, GA, USA
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Van Dyken PC, MacKinley M, Khan AR, Palaniyappan L. Cortical Network Disruption Is Minimal in Early Stages of Psychosis. SCHIZOPHRENIA BULLETIN OPEN 2024; 5:sgae010. [PMID: 39144115 PMCID: PMC11207789 DOI: 10.1093/schizbullopen/sgae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Background and Hypothesis Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness. Study Design Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset. Study Results Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics. Conclusions The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.
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Affiliation(s)
- Peter C Van Dyken
- Neuroscience Graduate Program, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Michael MacKinley
- Lawson Health Research Institute, London Health Sciences Centre, London, ON, Canada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, London, ON, Canada
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
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Mihaljevic M, Nagpal A, Etyemez S, Narita Z, Ross A, Schaub R, Cascella NG, Coughlin JM, Nestadt G, Nucifora FC, Sedlak TW, Calhoun VD, Faria AV, Yang K, Sawa A. Neuroimaging alterations and relapse in early-stage psychosis. J Psychiatry Neurosci 2024; 49:E135-E142. [PMID: 38569725 PMCID: PMC10980532 DOI: 10.1503/jpn.230115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 01/22/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Recent reports have indicated that symptom exacerbation after a period of improvement, referred to as relapse, in early-stage psychosis could result in brain changes and poor disease outcomes. We hypothesized that substantial neuroimaging alterations may exist among patients who experience relapse in early-stage psychosis. METHODS We studied patients with psychosis within 2 years after the first psychotic event and healthy controls. We divided patients into 2 groups, namely those who did not experience relapse between disease onset and the magnetic resonance imaging (MRI) scan (no-relapse group) and those who did experience relapse between these 2 timings (relapse group). We analyzed 3003 functional connectivity estimates between 78 regions of interest (ROIs) derived from resting-state functional MRI data by adjusting for demographic and clinical confounding factors. RESULTS We studied 85 patients, incuding 54 in the relapse group and 31 in the no-relapse group, along with 94 healthy controls. We observed significant differences in 47 functional connectivity estimates between the relapse and control groups after multiple comparison corrections, whereas no differences were found between the no-relapse and control groups. Most of these pathological signatures (64%) involved the thalamus. The Jonckheere-Terpstra test indicated that all 47 functional connectivity changes had a significant cross-group progression from controls to patients in the no-relapse group to patients in the relapse group. LIMITATIONS Longitudinal studies are needed to further validate the involvement and pathological importance of the thalamus in relapse. CONCLUSION We observed pathological differences in neuronal connectivity associated with relapse in early-stage psychosis, which are more specifically associated with the thalamus. Our study implies the importance of considering neurobiological mechanisms associated with relapse in the trajectory of psychotic disorders.
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Affiliation(s)
- Marina Mihaljevic
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Anisha Nagpal
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Semra Etyemez
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Zui Narita
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Anna Ross
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Rebecca Schaub
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Nicola G Cascella
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Jennifer M Coughlin
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Gerald Nestadt
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Frederik C Nucifora
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Thomas W Sedlak
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Vince D Calhoun
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Andreia V Faria
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Kun Yang
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
| | - Akira Sawa
- Departments of Psychiatry (Mihaljevic, Nagpal, Etyemez, Narita, Ross, Schaub, Cascella, Coughlin, Nestadt, Nucifora, Sedlak, Yang, Sawa), Radiology and Radiological Sciences (Faria), Neuroscience (Sawa), Biomedical Engineering (Sawa), Phamarchology (Sawa), and Genetic Medicine (Sawa), Johns Hopkins University School of Medicine; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md. (Sawa); Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Ga. (Calhoun)
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8
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Alahmadi A, Al-Ghamdi J, Tayeb HO. The hidden link: Investigating functional connectivity of rarely explored sub-regions of thalamus and superior temporal gyrus in Schizophrenia. Transl Neurosci 2024; 15:20220356. [PMID: 39669226 PMCID: PMC11635424 DOI: 10.1515/tnsci-2022-0356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 09/05/2024] [Accepted: 09/17/2024] [Indexed: 12/14/2024] Open
Abstract
Functional magnetic resonance imaging (fMRI) stands as a pivotal tool in advancing our comprehension of Schizophrenia, offering insights into functional segregations and integrations. Previous investigations employing either task-based or resting-state fMRI primarily focused on large main regions of interest (ROI), revealing the thalamus and superior temporal gyrus (STG) as prominently affected areas. Recent studies, however, unveiled the cytoarchitectural intricacies within these regions, prompting a more nuanced exploration. In this study, resting-state fMRI was conducted on 72 schizophrenic patients and 74 healthy controls to discern whether distinct thalamic nuclei and STG sub-regions exhibit varied functional integrational connectivity to main networks and to identify the most affected sub-regions in Schizophrenia. Employing seed-based analysis, six sub-ROIs - four in the thalamus and two in the STG - were selected. Our findings unveiled heightened positive functional connectivity in Schizophrenic patients, particularly toward the anterior STG (aSTG) and posterior STG (pSTG). Notably, positive connectivity emerged between the medial division of mediodorsal thalamic nuclei (MDm) and the visual network, while increased functional connectivity linked the ventral lateral nucleus of the thalamus with aSTG. This accentuated functional connectivity potentially influences these sub-regions, contributing to dysfunctions and manifesting symptoms such as language and learning difficulties alongside hallucinations. This study underscores the importance of delineating sub-regional dynamics to enhance our understanding of the nuanced neural alterations in Schizophrenia, paving the way for more targeted interventions and therapeutic approaches.
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Affiliation(s)
- Adnan Alahmadi
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
| | - Jamaan Al-Ghamdi
- Radiologic Sciences Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Haythum O. Tayeb
- Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
- Faculty of Medicine in Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia
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9
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Gengeç Benli Ş. Classification of First-Episode Psychosis with EEG Signals: ciSSA and Machine Learning Approach. Biomedicines 2023; 11:3223. [PMID: 38137444 PMCID: PMC10741114 DOI: 10.3390/biomedicines11123223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/21/2023] [Accepted: 11/23/2023] [Indexed: 12/24/2023] Open
Abstract
First-episode psychosis (FEP) typically marks the onset of severe psychiatric disorders and represents a critical period in the field of mental health. The early diagnosis of this condition is essential for timely intervention and improved clinical outcomes. In this study, the classification of FEP was investigated using the analysis of electroencephalography (EEG) signals and circulant spectrum analysis (ciSSA) sub-band signals. FEP poses a significant diagnostic challenge in the realm of mental health, and it is aimed at introducing a novel and effective approach for early diagnosis. To achieve this, the LASSO method was utilized to select the most significant features derived from entropy, frequency, and statistical-based characteristics obtained from ciSSA sub-band signals, as well as their hybrid combinations. Subsequently, a high-performance classification model has been developed using machine learning techniques, including ensemble, support vector machine (SVM), and artificial neural network (ANN) methods. The results of this study demonstrated that the hybrid features extracted from EEG signals' ciSSA sub-bands, in combination with the SVM method, achieved a high level of performance, with an area under curve (AUC) of 0.9893, an accuracy of 96.23%, a sensitivity of 0.966, a specificity of 0.956, a precision of 0.9667, and an F1 score of 0.9666. This has revealed the effectiveness of the ciSSA-based method for classifying FEP from EEG signals.
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Affiliation(s)
- Şerife Gengeç Benli
- Department of Biomedical Engineering, Faculty of Engineering, Erciyes University, Kayseri 38280, Turkey
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10
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Porter A, Fei S, Damme KSF, Nusslock R, Gratton C, Mittal VA. A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis. Mol Psychiatry 2023; 28:3278-3292. [PMID: 37563277 PMCID: PMC10618094 DOI: 10.1038/s41380-023-02195-9] [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: 10/03/2022] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Psychotic disorders are characterized by structural and functional abnormalities in brain networks. Neuroimaging techniques map and characterize such abnormalities using unique features (e.g., structural integrity, coactivation). However, it is unclear if a specific method, or a combination of modalities, is particularly effective in identifying differences in brain networks of someone with a psychotic disorder. METHODS A systematic meta-analysis evaluated machine learning classification of schizophrenia spectrum disorders in comparison to healthy control participants using various neuroimaging modalities (i.e., T1-weighted imaging (T1), diffusion tensor imaging (DTI), resting state functional connectivity (rs-FC), or some combination (multimodal)). Criteria for manuscript inclusion included whole-brain analyses and cross-validation to provide a complete picture regarding the predictive ability of large-scale brain systems in psychosis. For this meta-analysis, we searched Ovid MEDLINE, PubMed, PsychInfo, Google Scholar, and Web of Science published between inception and March 13th 2023. Prediction results were averaged for studies using the same dataset, but parallel analyses were run that included studies with pooled sample across many datasets. We assessed bias through funnel plot asymmetry. A bivariate regression model determined whether differences in imaging modality, demographics, and preprocessing methods moderated classification. Separate models were run for studies with internal prediction (via cross-validation) and external prediction. RESULTS 93 studies were identified for quantitative review (30 T1, 9 DTI, 40 rs-FC, and 14 multimodal). As a whole, all modalities reliably differentiated those with schizophrenia spectrum disorders from controls (OR = 2.64 (95%CI = 2.33 to 2.95)). However, classification was relatively similar across modalities: no differences were seen across modalities in the classification of independent internal data, and a small advantage was seen for rs-FC studies relative to T1 studies in classification in external datasets. We found large amounts of heterogeneity across results resulting in significant signs of bias in funnel plots and Egger's tests. Results remained similar, however, when studies were restricted to those with less heterogeneity, with continued small advantages for rs-FC relative to structural measures. Notably, in all cases, no significant differences were seen between multimodal and unimodal approaches, with rs-FC and unimodal studies reporting largely overlapping classification performance. Differences in demographics and analysis or denoising were not associated with changes in classification scores. CONCLUSIONS The results of this study suggest that neuroimaging approaches have promise in the classification of psychosis. Interestingly, at present most modalities perform similarly in the classification of psychosis, with slight advantages for rs-FC relative to structural modalities in some specific cases. Notably, results differed substantially across studies, with suggestions of biased effect sizes, particularly highlighting the need for more studies using external prediction and large sample sizes. Adopting more rigorous and systematized standards will add significant value toward understanding and treating this critical population.
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Affiliation(s)
- Alexis Porter
- Department of Psychology, Northwestern University, Evanston, IL, USA.
| | - Sihan Fei
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Katherine S F Damme
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, IL, USA
| | - Robin Nusslock
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Caterina Gratton
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, IL, USA
- Department of Psychiatry, Northwestern University, Chicago, IL, USA
- Medical Social Sciences, Northwestern University, Chicago, IL, USA
- Institute for Policy Research, Northwestern University, Chicago, IL, USA
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11
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Chen F, Mihaljevic M, Hou Z, Li Y, Lu H, Mori S, Sawa A, Faria AV. Relation between white matter integrity, perfusion, and processing speed in early-stage schizophrenia. J Psychiatr Res 2023; 163:166-171. [PMID: 37210835 DOI: 10.1016/j.jpsychires.2023.05.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 05/23/2023]
Abstract
OBJECTIVE Cerebral blood flow (CBF) plays a critical role in the maintenance of neuronal integrity, and CBF alterations have been linked to deleterious white matter changes. Several studies report CBF and white matter structural alterations individually. However, whether and how these pathological changes relate to each other remains elusive. By using our cohort of individuals with early-stage schizophrenia, we investigated the relationship between CBF and white matter structure. METHOD We studied 51 early-stage schizophrenia patients and age- and sex-matched healthy controls. We investigated the relationship among tissue structure (assessed with diffusion weighted imaging), perfusion (accessed by pseudo-continuous arterial labeling imaging), and neuropsychological indices (focusing on processing speed). We focused on the corpus callosum, due to its major role in associative functions and directness on revealing the architecture of a major white matter bundle. We performed mediation analysis to identify the possible mechanism underlay the relationship among cognition and white matter integrity and perfusion. RESULTS The CBF and the fractional anisotropy (FA) were inversely correlated in the corpus callosum of early-stage schizophrenia patients. While CBF negatively correlated with processing speed, FA correlated positively with this cognitive measure. These results were not observed in controls. Mediation analysis revealed that the effect of FA on processing speed was mediated via the CBF. CONCLUSIONS We provide evidence of a relationship between brain perfusion and white matter integrity in the corpus callosum in early-stage schizophrenia. These findings may shed the light on underlying metabolic support for structural changes with cognitive impact in schizophrenia.
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Affiliation(s)
- Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Marina Mihaljevic
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhipeng Hou
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Yang Li
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, 570311, China
| | - Hanzhang Lu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Akira Sawa
- Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, The Whiting School of Engineering, Baltimore, MD, USA; Department of Mental Health, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andreia V Faria
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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12
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Etyemez S, Narita Z, Mihaljevic M, Coughlin JM, Nestadt G, Nucifora FC, Sedlak TW, Cascella NG, Batt FD, Hua J, Faria A, Ishizuka K, Kamath V, Yang K, Sawa A. Brain regions associated with olfactory dysfunction in first episode psychosis patients. World J Biol Psychiatry 2023; 24:178-186. [PMID: 35678361 PMCID: PMC10503825 DOI: 10.1080/15622975.2022.2082526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 03/03/2022] [Accepted: 03/24/2022] [Indexed: 10/18/2022]
Abstract
OBJECTIVES Olfactory dysfunction is reproducibly reported in psychotic disorders, particularly in association with negative symptoms. The superior frontal gyrus (SFG) has been frequently studied in patients with psychotic disorders, in particular with their associations with negative symptoms. The relationship between olfactory functions and brain structure has been studied in healthy controls (HCs). Nevertheless, the studies with patients with psychotic disorders are limited. Here we report the olfactory-brain relationship in a first episode psychosis (FEP) cohort through both hypothesis-driven (centred on the SFG) and data-driven approaches. METHODS Using data from 88 HCs and 76 FEP patients, we evaluated the correlation between olfactory functions and structural/resting-state functional magnetic resonance imaging (MRI) data. RESULTS We found a significant correlation between the left SFG volume and odour discrimination in FEP patients, but not in HCs. We also observed a significant correlation between rs-fMRI connectivity involving the left SFG and odour discrimination in FEP patients, but not in HCs. The data-driven approach didn't observe any significant correlations, possibly due to insufficient statistical power. CONCLUSION The left SFG may be a promising brain region in the context of olfactory dysfunction and negative symptoms in FEP.
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Affiliation(s)
- Semra Etyemez
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Zui Narita
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Marina Mihaljevic
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jennifer M. Coughlin
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Gerald Nestadt
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Frederick C. Nucifora
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Thomas W. Sedlak
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Nicola G. Cascella
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Finn-Davis Batt
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jun Hua
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Andreia Faria
- Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Koko Ishizuka
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Vidyulata Kamath
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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13
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Dabiri M, Dehghani Firouzabadi F, Yang K, Barker PB, Lee RR, Yousem DM. Neuroimaging in schizophrenia: A review article. Front Neurosci 2022; 16:1042814. [PMID: 36458043 PMCID: PMC9706110 DOI: 10.3389/fnins.2022.1042814] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/28/2022] [Indexed: 11/16/2022] Open
Abstract
In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.
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Affiliation(s)
- Mona Dabiri
- Department of Radiology, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Kun Yang
- Department of Psychiatry, Molecular Psychiatry Program, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Roland R. Lee
- Department of Radiology, UCSD/VA Medical Center, San Diego, CA, United States
| | - David M. Yousem
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
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14
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Kim WS, Shen J, Tsogt U, Odkhuu S, Chung YC. Altered thalamic subregion functional networks in patients with treatment-resistant schizophrenia. World J Psychiatry 2022; 12:693-707. [PMID: 35663295 PMCID: PMC9150031 DOI: 10.5498/wjp.v12.i5.693] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/25/2021] [Accepted: 04/04/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The thalamus plays a key role in filtering information and has extensive interconnectivity with other brain regions. A large body of evidence points to impaired functional connectivity (FC) of the thalamocortical pathway in schizophrenia. However, the functional network of the thalamic subregions has not been investigated in patients with treatment-resistant schizophrenia (TRS).
AIM To identify the neural mechanisms underlying TRS, we investigated FC of thalamic sub-regions with cortical networks and voxels, and the associations of this FC with clinical symptoms. We hypothesized that the FC of thalamic sub-regions with cortical networks and voxels would differ between TRS patients and HCs.
METHODS In total, 50 patients with TRS and 61 healthy controls (HCs) matched for age, sex, and education underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical evaluation. Based on the rs-fMRI data, we conducted a FC analysis between thalamic subregions and cortical functional networks and voxels, and within thalamic subregions and cortical functional networks, in the patients with TRS. A functional parcellation atlas was used to segment the thalamus into nine subregions. Correlations between altered FC and TRS symptoms were explored.
RESULTS We found differences in FC within thalamic subregions and cortical functional networks between patients with TRS and HCs. In addition, increased FC was observed between thalamic subregions and the sensorimotor cortex, frontal medial cortex, and lingual gyrus. These abnormalities were associated with the pathophysiology of TRS.
CONCLUSION Our findings suggest that disrupted FC within thalamic subregions and cortical functional networks, and within the thalamocortical pathway, has potential as a marker for TRS. Our findings also improve our understanding of the relationship between the thalamocortical pathway and TRS symptoms.
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Affiliation(s)
- Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University, Jeon-ju 54907, South Korea
| | - Jie Shen
- Department of Psychiatry, Jeonbuk National University, Jeon-ju 54907, South Korea
| | - Uyanga Tsogt
- Department of Psychiatry, Jeonbuk National University, Jeon-ju 54907, South Korea
| | - Soyolsaikhan Odkhuu
- Department of Psychiatry, Jeonbuk National University, Jeon-ju 54907, South Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Jeon-ju 54907, South Korea
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15
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Jaaro-Peled H, Landek-Salgado MA, Cascella NG, Nucifora FC, Coughlin JM, Nestadt G, Sedlak TW, Lavoie J, De Silva S, Lee S, Tajinda K, Hiyama H, Ishizuka K, Yang K, Sawa A. Sex-specific involvement of the Notch-JAG pathway in social recognition. Transl Psychiatry 2022; 12:99. [PMID: 35273151 PMCID: PMC8913639 DOI: 10.1038/s41398-022-01867-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 02/12/2022] [Accepted: 02/24/2022] [Indexed: 12/18/2022] Open
Abstract
Under the hypothesis that olfactory neural epithelium gene expression profiles may be useful to look for disease-relevant neuronal signatures, we examined microarray gene expression in olfactory neuronal cells and underscored Notch-JAG pathway molecules in association with schizophrenia (SZ). The microarray profiling study underscored JAG1 as the most promising candidate. Combined with further validation with real-time PCR, downregulation of NOTCH1 was statistically significant. Accordingly, we reverse-translated the significant finding from a surrogate tissue for neurons, and studied the behavioral profile of Notch1+/- mice. We found a specific impairment in social novelty recognition, whereas other behaviors, such as sociability, novel object recognition and olfaction of social odors, were normal. This social novelty recognition deficit was male-specific and was rescued by rapamycin treatment. Based on the results from the animal model, we next tested whether patients with psychosis might have male-specific alterations in social cognition in association with the expression of NOTCH1 or JAG1. In our first episode psychosis cohort, we observed a specific correlation between the expression of JAG1 and a face processing measure only in male patients. The expression of JAG1 was not correlated with any other cognitive and symptomatic scales in all subjects. Together, although we acknowledge the pioneering and exploratory nature, the present work that combines both human and animal studies in a reciprocal manner suggests a novel role for the Notch-JAG pathway in a behavioral dimension(s) related to social cognition in psychotic disorders in a male-specific manner.
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Affiliation(s)
- Hanna Jaaro-Peled
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Melissa A Landek-Salgado
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Nicola G Cascella
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Frederick C Nucifora
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Jennifer M Coughlin
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Gerald Nestadt
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Thomas W Sedlak
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Joelle Lavoie
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Sarah De Silva
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Somin Lee
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Katsunori Tajinda
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Hideki Hiyama
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Koko Ishizuka
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
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16
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Buchsbaum MS, Mitelman SA, Christian BT, Merrill BM, Buchsbaum BR, Mitelman D, Mukherjee J, Lehrer DS. Four-modality imaging of unmedicated subjects with schizophrenia: 18F-fluorodeoxyglucose and 18F-fallypride PET, diffusion tensor imaging, and MRI. Psychiatry Res Neuroimaging 2022; 320:111428. [PMID: 34954446 DOI: 10.1016/j.pscychresns.2021.111428] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/14/2021] [Accepted: 12/16/2021] [Indexed: 12/28/2022]
Abstract
Diminished prefrontal function, dopaminergic abnormalities in the striatum and thalamus, reductions in white matter integrity and frontotemporal gray matter deficits are the most replicated findings in schizophrenia. We used four imaging modalities (18F-fluorodeoxyglucose and 18F-fallypride PET, diffusion tensor imaging, structural MRI) in 19 healthy and 25 schizophrenia subjects to assess the relationship between functional (dopamine D2/D3 receptor binding potential, glucose metabolic rate) and structural (fractional anisotropy, MRI) correlates of schizophrenia and their additive diagnostic prediction potential. Multivariate ANOVA was used to compare structural and functional image sets for identification of schizophrenia. Integration of data from all four modalities yielded better predictive power than less inclusive combinations, specifically in the thalamus, left dorsolateral prefrontal and temporal regions. Among the modalities, fractional anisotropy showed highest discrimination in white matter whereas 18F-fallypride binding showed highest discrimination in gray matter. Structural and functional modalities displayed comparable discriminative power but different topography, with higher sensitivity of structural modalities in the left prefrontal region. Combination of functional and structural imaging modalities with inclusion of both gray and white matter appears most effective in diagnostic discrimination. The highest sensitivity of 18F-fallypride PET to gray matter changes in schizophrenia supports the primacy of dopaminergic abnormalities in its pathophysiology.
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Affiliation(s)
- Monte S Buchsbaum
- Departments of Psychiatry and Radiology, University of California, Irvine and San Diego, 11388 Sorrento Valley Road, San Diego, CA 92121, United States
| | - Serge A Mitelman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States; Department of Psychiatry, Division of Child and Adolescent Psychiatry, Elmhurst Hospital Center, 79-01 Broadway, Elmhurst, NY 11373, United States.
| | - Bradley T Christian
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, 1500 Highland Avenue, Room T231, Madison, WI 53705, United States
| | - Brian M Merrill
- Department of Psychiatry, Boonshoft School of Medicine, Wright State University, East Medical Plaza, Dayton, OH 45408, United States
| | - Bradley R Buchsbaum
- The Rotman Research Institute, Baycrest Centre for Geriatric Care and Department of Psychiatry, University of Toronto, 3560 Bathurst St., Toronto, Ontario, Canada, M6A 2E1
| | - Danielle Mitelman
- The Arnold & Marie Schwartz College of Pharmacy and Health Sciences, Long Island University, 75 Dekalb Avenue, Brooklyn, NY 11201, United States
| | - Jogeshwar Mukherjee
- Department of Radiological Sciences, Preclinical Imaging, University of California, Irvine School of Medicine, Irvine, CA 92697
| | - Douglas S Lehrer
- Department of Psychiatry, Boonshoft School of Medicine, Wright State University, East Medical Plaza, Dayton, OH 45408, United States
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17
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Walther S, Lefebvre S, Conring F, Gangl N, Nadesalingam N, Alexaki D, Wüthrich F, Rüter M, Viher PV, Federspiel A, Wiest R, Stegmayer K. Limbic links to paranoia: increased resting-state functional connectivity between amygdala, hippocampus and orbitofrontal cortex in schizophrenia patients with paranoia. Eur Arch Psychiatry Clin Neurosci 2022; 272:1021-1032. [PMID: 34636951 PMCID: PMC9388427 DOI: 10.1007/s00406-021-01337-w] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/22/2021] [Indexed: 11/24/2022]
Abstract
Paranoia is a frequent and highly distressing experience in psychosis. Models of paranoia suggest limbic circuit pathology. Here, we tested whether resting-state functional connectivity (rs-fc) in the limbic circuit was altered in schizophrenia patients with current paranoia. We collected MRI scans in 165 subjects including 89 patients with schizophrenia spectrum disorders (schizophrenia, schizoaffective disorder, brief psychotic disorder, schizophreniform disorder) and 76 healthy controls. Paranoia was assessed using a Positive And Negative Syndrome Scale composite score. We tested rs-fc between bilateral nucleus accumbens, hippocampus, amygdala and orbitofrontal cortex between groups and as a function of paranoia severity. Patients with paranoia had increased connectivity between hippocampus and amygdala compared to patients without paranoia. Likewise, paranoia severity was linked to increased connectivity between hippocampus and amygdala. Furthermore, paranoia was associated with increased connectivity between orbitofrontal and medial prefrontal cortex. In addition, patients with paranoia had increased functional connectivity within the frontal hubs of the default mode network compared to healthy controls. These results demonstrate that current paranoia is linked to aberrant connectivity within the core limbic circuit and prefrontal cortex reflecting amplified threat processing and impaired emotion regulation. Future studies will need to explore the association between limbic hyperactivity, paranoid ideation and perceived stress.
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Affiliation(s)
- Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Stephanie Lefebvre
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
| | - Frauke Conring
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Nicole Gangl
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Niluja Nadesalingam
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Danai Alexaki
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Florian Wüthrich
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Maximilian Rüter
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Petra V. Viher
- 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, Inselspital, University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
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18
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Avigdor BE, Yang K, Shinder I, Orsburn BC, Rais R, Kano SI, Sawa A, Pevsner J. Characterization of antipsychotic medications, amino acid signatures, and platelet-activating factor in first-episode psychosis. Biomark Neuropsychiatry 2021. [DOI: 10.1016/j.bionps.2021.100045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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19
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Thalamic connectivity system across psychiatric disorders: Current status and clinical implications. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:332-340. [PMID: 36324665 PMCID: PMC9616255 DOI: 10.1016/j.bpsgos.2021.09.008] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 09/23/2021] [Accepted: 09/25/2021] [Indexed: 12/20/2022] Open
Abstract
The thalamic connectivity system, with the thalamus as the central node, enables transmission of the brain’s neural computations via extensive connections to cortical, subcortical, and cerebellar regions. Emerging reports suggest deficits in this system across multiple psychiatric disorders, making it a unique network of high translational and transdiagnostic utility in mapping neural alterations that potentially contribute to symptoms and disturbances in psychiatric patients. However, despite considerable research effort, it is still debated how this system contributes to psychiatric disorders. This review characterizes current knowledge regarding thalamic connectivity system deficits in psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder, across multiple levels of the system. We identify the presence of common and distinct patterns of deficits in the thalamic connectivity system in major psychiatric disorders and assess their nature and characteristics. Specifically, this review assembles evidence for the hypotheses of 1) thalamic microstructure, particularly in the mediodorsal nucleus, as a state marker of psychosis; 2) thalamo-prefrontal connectivity as a trait marker of psychosis; and 3) thalamo-somatosensory/parietal connectivity as a possible marker of general psychiatric illness. Furthermore, possible mechanisms contributing to thalamocortical dysconnectivity are explored. We discuss current views on the contributions of cerebellar-thalamic connectivity to the thalamic connectivity system and propose future studies to examine its effects at multiple levels, from the molecular (e.g., glutamatergic) to the behavioral (e.g., cognition), to gain a deeper understanding of the mechanisms that underlie the disturbances observed in psychiatric disorders.
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20
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Wang D, Zhuo K, Sun Y, Xiang Q, Guo X, Wang J, Xu Y, Liu D, Li Y. Middle temporal corpus callosum impairment as a predictor of eight-week treatment outcome of drug-naïve first-episode psychosis patients: A pilot longitudinal study. Schizophr Res 2021; 232:95-97. [PMID: 34029947 DOI: 10.1016/j.schres.2021.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 05/01/2021] [Accepted: 05/02/2021] [Indexed: 11/19/2022]
Affiliation(s)
- Danni Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Kaiming Zhuo
- First-episode Schizophrenia and Early Psychosis Program, Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yu Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Zhejiang 310052, China; Department of Radiology, the Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Zhejiang 310052, China
| | - Qiong Xiang
- First-episode Schizophrenia and Early Psychosis Program, Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xiaoyun Guo
- First-episode Schizophrenia and Early Psychosis Program, Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jinhong Wang
- Department of Medical Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yifeng Xu
- First-episode Schizophrenia and Early Psychosis Program, Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Institute of Mental Health, Fudan University, Shanghai 200030, China
| | - Dengtang Liu
- First-episode Schizophrenia and Early Psychosis Program, Division of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China; Institute of Mental Health, Fudan University, Shanghai 200030, China.
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
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