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Gencheva TM, Valkov BV, Kandilarova SS, Maes MHJ, Stoyanov DS. Diagnostic value of structural, functional and effective connectivity in bipolar disorder. Acta Psychiatr Scand 2024. [PMID: 39137928 DOI: 10.1111/acps.13742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 08/15/2024]
Abstract
INTRODUCTION The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS. RESULTS A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria. DISCUSSION Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.
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Affiliation(s)
| | - Bozhidar V Valkov
- Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Sevdalina S Kandilarova
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
| | - Michael H J Maes
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
| | - Drozdstoy S Stoyanov
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
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Xie Y, Li C, Guan M, Zhang T, Ma C, Wang Z, Ma Z, Wang H, Fang P. Low-frequency rTMS induces modifications in cortical structural connectivity - functional connectivity coupling in schizophrenia patients with auditory verbal hallucinations. Hum Brain Mapp 2024; 45:e26614. [PMID: 38375980 PMCID: PMC10878014 DOI: 10.1002/hbm.26614] [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: 08/17/2023] [Revised: 01/09/2024] [Accepted: 01/19/2024] [Indexed: 02/21/2024] Open
Abstract
Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC-FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC-FC coupling compared to healthy controls. Notably, SC-FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC-FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC-FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low-frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.
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Affiliation(s)
- Yuanjun Xie
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Chenxi Li
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Muzhen Guan
- Department of Mental HealthXi'an Medical CollegeXi'anChina
| | - Tian Zhang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Chaozong Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Zhongheng Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Zhujing Ma
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
| | - Huaning Wang
- Department of Psychiatry, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Peng Fang
- Military Medical Psychology SchoolFourth Military Medical UniversityXi'anChina
- Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent PerceptionXi'anChina
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Levi PT, Chopra S, Pang JC, Holmes A, Gajwani M, Sassenberg TA, DeYoung CG, Fornito A. The effect of using group-averaged or individualized brain parcellations when investigating connectome dysfunction in psychosis. Netw Neurosci 2023; 7:1228-1247. [PMID: 38144692 PMCID: PMC10631788 DOI: 10.1162/netn_a_00329] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 06/27/2023] [Indexed: 12/26/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) is widely used to investigate functional coupling (FC) disturbances in a range of clinical disorders. Most analyses performed to date have used group-based parcellations for defining regions of interest (ROIs), in which a single parcellation is applied to each brain. This approach neglects individual differences in brain functional organization and may inaccurately delineate the true borders of functional regions. These inaccuracies could inflate or underestimate group differences in case-control analyses. We investigated how individual differences in brain organization influence group comparisons of FC using psychosis as a case study, drawing on fMRI data in 121 early psychosis patients and 57 controls. We defined FC networks using either a group-based parcellation or an individually tailored variant of the same parcellation. Individualized parcellations yielded more functionally homogeneous ROIs than did group-based parcellations. At the level of individual connections, case-control FC differences were widespread, but the group-based parcellation identified approximately 7.7% more connections as dysfunctional than the individualized parcellation. When considering differences at the level of functional networks, the results from both parcellations converged. Our results suggest that a substantial fraction of dysconnectivity previously observed in psychosis may be driven by the parcellation method, rather than by a pathophysiological process related to psychosis.
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Affiliation(s)
- Priscila T. Levi
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Sidhant Chopra
- Department of Psychology, Yale University, New Haven, CT, USA
| | - James C. Pang
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Alexander Holmes
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Mehul Gajwani
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | | | - Colin G. DeYoung
- Department of Psychology, University of Minnesota, Minnesota, MN, USA
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
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Nabulsi L, Chandio BQ, Dhinagar N, Laltoo E, McPhilemy G, Martyn FM, Hallahan B, McDonald C, Thompson PM, Cannon DM. Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-7. [PMID: 38083303 DOI: 10.1109/embc40787.2023.10339964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN)-a recently developed analytic approach for tractography-to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls.Clinical Relevance- BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.
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Nabulsi L, Chandio BQ, Dhinagar N, Laltoo E, McPhilemy G, Martyn FM, Hallahan B, McDonald C, Thompson PM, Cannon DM. Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531585. [PMID: 36945403 PMCID: PMC10028925 DOI: 10.1101/2023.03.07.531585] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN), a recently developed analytic approach for tractography, to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean Fractional Anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls. BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.
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Affiliation(s)
- Leila Nabulsi
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, 90292 USA
| | - Bramsh Q Chandio
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, 90292 USA
| | - Nikhil Dhinagar
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, 90292 USA
| | - Emily Laltoo
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, 90292 USA
| | - Genevieve McPhilemy
- Clinical Neuroimaging Lab, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, University of Galway, Galway, Ireland
| | - Fiona M Martyn
- Clinical Neuroimaging Lab, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, University of Galway, Galway, Ireland
| | - Brian Hallahan
- Clinical Neuroimaging Lab, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, University of Galway, Galway, Ireland
| | - Colm McDonald
- Clinical Neuroimaging Lab, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, University of Galway, Galway, Ireland
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, University of Southern California, Marina del Rey, CA, 90292 USA
| | - Dara M Cannon
- Clinical Neuroimaging Lab, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, University of Galway, Galway, Ireland
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Associations of leptin and corticostriatal connectivity in bipolar disorder. Sci Rep 2022; 12:21898. [PMID: 36535988 PMCID: PMC9763246 DOI: 10.1038/s41598-022-26233-8] [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: 07/27/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Bipolar disorder (BD) and metabolic disturbance represent a chronic state of low-grade inflammation and corticostriatal circuitry alterations. Herein, we aimed to investigate whether plasma leptin, an adipokine that plays a key role in the interplay of metabolism and inflammation, is associated with corticostriatal connectivity in patients with BD. Twenty-eight BD I patients, 36 BD II patients and 66 healthy controls were enrolled and completed the Hamilton Depression Rating Scale, the Young Mania Rating Scale, and the Recent Life Change Questionnaire. Fasting plasma leptin and C-reactive protein (CRP) levels were measured, and corticostriatal connectivity was examined using functional magnetic resonance imaging (fMRI). The relationships between leptin, CRP and body mass index (BMI) identified in the controls and BD II patients were absent in the BD I patients. We did not find a significant group difference in the leptin level; nevertheless, the negative correlation between leptin level and corticostriatal connectivity (ventrolateral prefrontal cortex and inferior temporal gyrus) observed in the healthy controls was absent in the BD patients. The disproportionate increase in leptin level with increasing BMI in BD indicated a potential inflammatory role of white adipose tissue in BD. Furthermore, higher CRP levels in BD I patients might induce leptin resistance. Collectively, our results implied vulnerability to inflammatory and metabolic diseases in patients with BD, especially BD I.
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Liang J, Huang W, Guo H, Wu W, Li X, Xu C, Xie G, Chen W. Differences of resting fMRI and cognitive function between drug-naïve bipolar disorder and schizophrenia. BMC Psychiatry 2022; 22:654. [PMID: 36271368 PMCID: PMC9587563 DOI: 10.1186/s12888-022-04301-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 09/13/2022] [Accepted: 10/10/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) and schizophrenia (SC) have many similarities in clinical manifestations. The acute phase of BD has psychotic symptoms, while SC also has emotional symptoms during the onset, which suggests that there is some uncertainty in distinguishing BD and SC through clinical symptoms. AIM To explore the characteristics of brain functional activities and cognitive impairment between BD and SC. METHODS Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test was performed on patients in drug-naïve BD and SC (50 subjects in each group), and resting-state functional magnetic resonance imaging (rs-fMRI) scanning was performed meanwhile. Rs-fMRI data were routinely preprocessed, and the value of the fractional amplitude of low-frequency fluctuation (fALFF) was calculated. Then each part of the scores of the RBANS and the characteristics of brain function activities were compared between the two groups. Finally used Pearson correlation to analyze the correlation between cognition and brain function. RESULTS (1) Compared with BD group, all parts of RBANS scores in SC group decreased; (2) The left inferior occipital gyrus (IOG, peak coordinates - 30, -87, -15; t = 4.78, voxel size = 31, Alphasim correction) and the right superior temporal gyrus (STG, peak coordinates 51, -12, 0; t = 5.08, voxel size = 17, AlphaSim correction) were the brain areas with significant difference in fALFF values between BD and SC. Compared with SC group, the fALFF values of the left IOG and the right STG in BD group were increased (p < 0.05); (3) Pearson correlation analysis showed that the visuospatial construction score was positively correlated with the fALFF values of the left IOG and the right STG (rleft IOG = 0.304, p = 0.003; rright STG = 0.340, p = 0.001); The delayed memory (figure recall) score was positively correlated with the fALFF value of the left IOG (rleft IOG = 0.207, p = 0.044). DISCUSSION The cognitive impairment of SC was more serious than BD. The abnormal activities of the left IOG and the right STG may be the core brain region to distinguish BD and SC, and are closely related to cognitive impairment, which provide neuroimaging basis for clinical differential diagnosis and explore the pathological mechanism of cognitive impairment.
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Affiliation(s)
- Jiaquan Liang
- Department of Psychiatry, The Third People's Hospital of Foshan, Guangdong, People's Republic of China. .,Center on Translational Neuroscience, Minzu University of China, Beijing, People's Republic of China.
| | - Wei Huang
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Huagui Guo
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Weibin Wu
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Xiaoling Li
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Caixia Xu
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Guojun Xie
- Department of Psychiatry, The Third People’s Hospital of Foshan, Guangdong, People’s Republic of China
| | - Wensheng Chen
- Department of Psychiatry, The Third People's Hospital of Foshan, Guangdong, People's Republic of China.
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Altered dynamic amplitude of low-frequency fluctuation between bipolar type I and type II in the depressive state. Neuroimage Clin 2022; 36:103184. [PMID: 36095891 PMCID: PMC9472068 DOI: 10.1016/j.nicl.2022.103184] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Bipolar disorder is a chronic and highly recurrent mental disorder that can be classified as bipolar type I (BD I) and bipolar type II (BD II). BD II is sometimes taken as a milder form of BD I or even doubted as an independent subtype. However, the fact that symptoms and severity differ in patients with BD I and BD II suggests different pathophysiologies and underlying neurobiological mechanisms. In this study, we aimed to explore the shared and unique functional abnormalities between subtypes. METHODS The dynamic amplitude of low-frequency fluctuation (dALFF) was performed to compare 31 patients with BD I, 32 with BD II, and 79 healthy controls (HCs). Global dALFF was calculated using sliding-window analysis. Group differences in dALFF among the 3 groups were compared using analysis of covariance (ANCOVA), with covariates of age, sex, years of education, and mean FD, and Bonferroni correction was applied for post hoc analysis. Pearson and Spearman's correlations were conducted between clusters with significant differences and clinical features in the BD I and BD II groups, after which false error rate (FDR) was used for correction. RESULTS We found a significant decrease in dALFF values in BD patients compared with HCs in the following brain regions: the bilateral-side inferior frontal gyrus (including the triangular, orbital, and opercular parts), inferior temporal gyrus, the medial part of the superior frontal gyrus, middle frontal gyrus, anterior cingulum, insula gyrus, lingual gyrus, calcarine gyrus, precuneus gyrus, cuneus gyrus, left-side precentral gyrus, postcentral gyrus, inferior parietal gyrus, superior temporal pole gyrus, middle temporal gyrus, middle occipital gyrus, superior occipital gyrus and right-side fusiform gyrus, parahippocampal gyrus, hippocampus, middle cingulum, orbital part of the medial frontal gyrus and superior frontal gyrus. Unique alterations in BD I were observed in the right-side supramarginal gyrus and postcentral gyrus. In addition, dALFF values in BD II were significantly higher than those in BD I in the right superior temporal gyrus and middle temporal gyrus. The variables of dALFF correlated with clinical characteristics differently according to the subtypes, but no correlations survived after FDR correction. LIMITATIONS Our study was cross-sectional. Most of our patients were on medication, and the sample was limited. CONCLUSIONS Our findings demonstrated neurobiological characteristics of BD subtypes, providing evidence for BD II as an independent existence, which could be the underlying explanation for the specific symptoms and/or severity and point to potential biomarkers for the differential diagnosis of bipolar subtypes.
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Digiovanni A, Ajdinaj P, Russo M, Sensi SL, Onofrj M, Thomas A. Bipolar spectrum disorders in neurologic disorders. Front Psychiatry 2022; 13:1046471. [PMID: 36620667 PMCID: PMC9811836 DOI: 10.3389/fpsyt.2022.1046471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
Psychiatric symptoms frequently predate or complicate neurological disorders, such as neurodegenerative diseases. Symptoms of bipolar spectrum disorders (BSD), like mood, behavioral, and psychotic alterations, are known to occur - individually or as a syndromic cluster - in Parkinson's disease and in the behavioral variant of frontotemporal dementia (FTD). Nonetheless, due to shared pathophysiological mechanisms, or genetic predisposition, several other neurological disorders show significant, yet neglected, clinical and biological overlaps with BSD like neuroinflammation, ion channel dysfunctions, neurotransmission imbalance, or neurodegeneration. BSD pathophysiology is still largely unclear, but large-scale network dysfunctions are known to participate in the onset of mood disorders and psychotic symptoms. Thus, functional alterations can unleash BSD symptoms years before the evidence of an organic disease of the central nervous system. The aim of our narrative review was to illustrate the numerous intersections between BSD and neurological disorders from a clinical-biological point of view and the underlying predisposing factors, to guide future diagnostic and therapeutical research in the field.
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Affiliation(s)
- Anna Digiovanni
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Paola Ajdinaj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Astrid Thomas
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
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Zhang L, Wu H, Zhang A, Bai T, Ji GJ, Tian Y, Wang K. Aberrant brain network topology in the frontoparietal-limbic circuit in bipolar disorder: a graph-theory study. Eur Arch Psychiatry Clin Neurosci 2021; 271:1379-1391. [PMID: 33386961 DOI: 10.1007/s00406-020-01219-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 12/02/2020] [Indexed: 12/21/2022]
Abstract
Characterizing the properties of brain networks across mood states seen in bipolar disorder (BP) can provide a deeper insight into the mechanisms involved in this type of affective disorder. In this study, graph theoretical methods were used to examine global, modular and nodal brain network topology in the resting state using functional magnetic resonance imaging data acquired from 95 participants, including those with bipolar depression (BPD; n = 30) and bipolar mania (BPM; n = 39) and healthy control (HC) subjects (n = 26). The threshold value of the individual subjects' connectivity matrix varied from 0.15 to 0.30 with steps of 0.01. We found that: (1) at the global level, BP patients showed a significantly increased global efficiency and synchronization and a decreased path length; (2) at the nodal level, BP patients showed impaired nodal parameters, predominantly within the frontoparietal and limbic sub-network; (3) at the module level, BP patients were characterized by denser FCs (edges) between Module III (the front-parietal system) and Module V (limbic/paralimbic systems); (4) at the nodal level, the BPD and BPM groups showed state-specific differences in the orbital part of the left superior-frontal gyrus, right putamen, right parahippocampal gyrus and left fusiform gyrus. These results revealed abnormalities in topological organization in the whole brain, especially in the frontoparietal-limbic circuit in both BPD and BPM. These deficits may reflect the pathophysiological processes occurring in BP. In addition, state-specific regional nodal alterations in BP could potentially provide biomarkers of conversion across different mood states.
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Affiliation(s)
- Li Zhang
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Huiling Wu
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Aiguo Zhang
- Anhui Mental Health Center, Hefei, Anhui Province, China
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
| | - Gong-Jun Ji
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, 230022, China
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui Province, China.
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, 230022, China.
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, 230022, China.
- Department of Medical Psychology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
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McPhilemy G, Nabulsi L, Kilmartin L, Whittaker JR, Martyn FM, Hallahan B, McDonald C, Murphy K, Cannon DM. Resting-State Network Patterns Underlying Cognitive Function in Bipolar Disorder: A Graph Theoretical Analysis. Brain Connect 2020; 10:355-367. [PMID: 32458698 DOI: 10.1089/brain.2019.0709] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Background: Synchronous and antisynchronous activity between neural elements at rest reflects the physiological processes underlying complex cognitive ability. Regional and pairwise connectivity investigations suggest that perturbations in these activity patterns may relate to widespread cognitive impairments seen in bipolar disorder (BD). Here we take a network-based perspective to more meaningfully capture interactions among distributed brain regions compared to focal measurements and examine network-cognition relationships across a range of commonly affected cognitive domains in BD in relation to healthy controls. Methods: Resting-state networks were constructed as matrices of correlation coefficients between regionally averaged resting-state time series from 86 cortical/subcortical brain regions (FreeSurferv5.3.0). Cognitive performance measured using the Wechsler Adult Intelligence Scale, Cambridge Automated Neuropsychological Test Battery (CANTAB), and Reading the Mind in the Eyes tests was examined in relation to whole-brain connectivity measures and patterns of connectivity using a permutation-based statistical approach. Results: Faster response times in controls (n = 49) related to synchronous activity between frontal, parietal, cingulate, temporal, and occipital regions, while a similar response times in BD (n = 35) related to antisynchronous activity between regions of this subnetwork. Across all subjects, antisynchronous activity between the frontal, parietal, temporal, occipital, cingulate, insula, and amygdala regions related to improved memory performance. No resting-state subnetworks related to intelligence, executive function, short-term memory, or social cognition performance in the overall sample or in a manner that would explain deficits in these facets in BD. Conclusions: Our results demonstrate alterations in the intrinsic connectivity patterns underlying response timing in BD that are not specific to performance or errors on the same tasks. Across all individuals, no strong effects of resting-state global topology on cognition are found, while distinct functional networks supporting episodic and spatial memory highlight intrinsic inhibitory influences present in the resting state that facilitate memory processing. Impact Statement Regional and pairwise-connectivity investigations suggest altered interactions between brain areas may contribute to impairments in cognition that are observed in bipolar disorder. However, the distributed nature of these interactions across the brain remains poorly understood. Using recent advances in network neuroscience, we examine functional connectivity patterns associated with multiple cognitive domains in individuals with and without bipolar disorder. We discover distinct patterns of connectivity underlying response-timing performance uniquely in bipolar disorder and, independent of diagnosis, inhibitory interactions that relate to memory performance.
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Affiliation(s)
- Genevieve McPhilemy
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Liam Kilmartin
- College of Science and Engineering, National University of Ireland Galway, Galway, Republic of Ireland
| | - Joseph R Whittaker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Fiona M Martyn
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Brian Hallahan
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Dara M Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, Ireland
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Averill LA, Fouda S, Murrough JW, Abdallah CG. Chronic stress pathology and ketamine-induced alterations in functional connectivity in major depressive disorder: An abridged review of the clinical evidence. ADVANCES IN PHARMACOLOGY 2020; 89:163-194. [PMID: 32616206 DOI: 10.1016/bs.apha.2020.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
A paradigm shift in the conceptualization of the neurobiology of depression and the serendipitous discovery of ketamine's rapid-acting antidepressant (RAAD) effects has ushered in a new era of innovative research and novel drug development. Since the initial discovery of ketamine's RAAD effects, multiple studies have supported its short-term efficacy for fast-tracked improvements in treatment-resistant depression. Evidence from MRI studies have repeatedly demonstrated functional connectivity alterations in stress- and trauma-related disorders suggesting this may be a viable biomarker of chronic stress pathology (CSP). Human mechanistic studies further support this by coupling functional connectivity to ketamine's RAAD effects including connectivity to glutamate neurotransmission, ketamine to normalized connectivity, and these advantageous normalizations to symptom improvement/ketamine response. This review provides an abridged discussion of the suspected neurobiological underpinnings of ketamine's RAAD effects, highlighting ketamine-induced alterations in prefrontal, striatal, and anterior cingulate cortex functional connectivity in major depressive disorder. We present a model of CSP underscoring the role of synaptic loss and dysconnectivity and discuss how ketamine may be used both as (1) a treatment to restore and normalize these stress-induced neural alterations and (2) a tool to study potential biomarkers of CSP and treatment response. We conclude by noting challenges and future directions including heterogeneity, sex differences, the role of early life stress, and the need for proliferation of new methods, paradigms, and tools that will optimize signal and allow analyses at different levels of complexity, according to the needs of the question at hand, perhaps by thinking hierarchically about both clinical and biological phenotypes.
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Affiliation(s)
- Lynnette A Averill
- Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States.
| | - Samar Fouda
- Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - James W Murrough
- Department of Psychiatry, Depression and Anxiety Center for Discovery and Treatment, Icahn School of Medicine of Mount Sinai, New York, NY, United States; Department of Neuroscience, Icahn School of Medicine of Mount Sinai, New York, NY, United States
| | - Chadi G Abdallah
- Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
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