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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: 1] [Impact Index Per Article: 1.0] [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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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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Martyn F, Nabulsi L, McPhilemy G, O'Donoghue S, Kilmartin L, Hallahan B, McDonald C, Cannon DM. Topological alteration is associated with non-dependent alcohol use in bipolar disorder. Brain Connect 2022; 12:823-834. [PMID: 35166131 DOI: 10.1089/brain.2021.0137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Structural alterations in cortical thickness and the microstructural organisation of white matter are independently associated with non-dependent alcohol consumption and bipolar disorder(BD). Identifying their interactive and network level effects on brain topology may identify the impact of alcohol on reward and emotion circuitry, and its contribution to relapse in BD. METHODS Thirty-four BD-I (DSM-IV-TR) and 38 healthy controls underwent T1 and diffusion-weighted MRI scanning, and the AUDIT-C to assess alcohol use. Connectomes comprised of 34 cortical and nine subcortical nodes bilaterally (Freesurfer v5.3) connected by fractional anisotropy-weighted edges derived from non-tensor based deterministic constrained spherical deconvolution tractography (ExploreDTI v4.8.6) underwent permutation-based topological analysis (NBS v1.2) and were examined for effects of alcohol use and diagnosis-by-alcohol use accounting for age, sex and diagnosis. RESULTS Alcohol was significantly related to a subnetwork, encompassing connections between fronto-limbic, basal ganglia and temporal nodes (Frange=5-8.4, p=0.031) and was not detected to have an effect on global brain integration or segregation. A portion of this network (18%), involving cortico-limbic and basal ganglia connections, was differentially impacted by alcohol in the BD relative to the control group (Frange=5-8.8, p=0.033), despite the groups' consuming similar amounts of alcohol (BD: mean±SD 4.95±3.0; HC 3.62±3.0, T=1.88, p=0.06). DISCUSSION Non-dependent alcohol use impacts brain architectural organization and connectivity within salience, reward, and affective circuitry. The relationship between alcohol use and topology of the network in BD suggests an interactive effect between specific biological vulnerability and alcohol use, which may explain susceptibility to increased risk of relapse in the disorder.
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Affiliation(s)
- Fiona Martyn
- National University of Ireland Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland.,National University of Ireland Galway, 8799, Psychology, Galway, Galway, Ireland;
| | - Leila Nabulsi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA 90292, Los Angeles, United States.,National University of Ireland Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
| | - Genevieve McPhilemy
- National University of Ireland Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
| | - Stefani O'Donoghue
- National University of Ireland Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
| | - Liam Kilmartin
- College of Engineering and Informatics, National University of Ireland Galway, H91 TK33 Galway Ireland, Republic of Ireland , Electrical & Electronic Eng, NUI Galway, Galway, Ireland;
| | - Brian Hallahan
- National University of Ireland Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
| | - Colm McDonald
- National University of Ireland - Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
| | - Dara M Cannon
- National University of Ireland - Galway, 8799, Centre for Neuroimaging, Cognition and Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, Galway, Galway, Ireland;
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Nabulsi L, McPhilemy G, Kilmartin L, O'Hora D, O'Donoghue S, Forcellini G, Najt P, Ambati S, Costello L, Byrne F, McLoughlin J, Hallahan B, McDonald C, Cannon DM. Bipolar Disorder and Gender Are Associated with Frontolimbic and Basal Ganglia Dysconnectivity: A Study of Topological Variance Using Network Analysis. Brain Connect 2019; 9:745-759. [PMID: 31591898 DOI: 10.1089/brain.2019.0667] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach. Connectivity matrices were constructed using 34 cortical and 9 subcortical bilateral nodes (Desikan-Killiany), and edges that were weighted by fractional anisotropy and streamline count derived from deterministic tractography using constrained spherical deconvolution. Whole-brain and rich-club connectivity alongside a permutation-based statistical approach was used to investigate topological variance in predominantly euthymic BD relative to healthy volunteers. BP patients (n = 40) demonstrated impairments across whole-brain topological arrangements (density, degree, and efficiency), and a dysconnected subnetwork involving limbic and basal ganglia relative to controls (n = 45). Increased rich-club connectivity was most evident in females with BD, with frontolimbic and parieto-occipital nodes not members of BD rich-club. Increased centrality in females relative to males was driven by basal ganglia and fronto-temporo-limbic nodes. Our subject-specific cortico-subcortical nontensor-based connectome map presents a neuroanatomical model of BD dysconnectivity that differentially involves communication within and between emotion-regulatory and reward-related subsystems. Moreover, the female brain positions more dependence on nodes belonging to these two differently specialized subsystems for communication relative to males, which may confer increased susceptibility to processes dependent on integration of emotion and reward-related information.
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Affiliation(s)
- 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
| | - 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
| | - Liam Kilmartin
- College of Engineering and Informatics, National University of Ireland Galway, Galway, Ireland
| | - Denis O'Hora
- School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Stefani O'Donoghue
- 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
| | - Giulia Forcellini
- 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.,Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Pablo Najt
- 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
| | - Srinath Ambati
- 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
| | - Laura Costello
- 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
| | - Fintan Byrne
- 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
| | - James McLoughlin
- 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
| | - 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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