Limbic network damage in bipolar disorder
Poster No:
449
Submission Type:
Abstract Submission
Authors:
Matteo Martino1, Chun-Hung Yeh2, Hsiang-Yuan Lin3, Rung-Yu Tseng2, Elham Dabiri1, Benedetta Conio4, Mario Amore4, Jean-François Mangin5, Paola Magioncalda1
Institutions:
1Taipei Medical University, Taipei, Taiwan, 2Chang Gung University, Taoyuan, Taiwan, 3University of Toronto, Toronto, Ontario, Canada, 4University of Genoa, Genoa, Italy, 5Université Paris-Saclay, Gif-sur-Yvette, France
First Author:
Co-Author(s):
Introduction:
Understanding the neurobiology of bipolar disorder (BD) represents a major challenge for neuroscience and psychiatry. This work aimed to investigate the spatial and temporal pattern of the brain's white matter (WM) alteration and its relationship with intrinsic brain activity in BD, to better define the role of WM damage in the pathophysiology of the disorder.
Methods:
Multimodal magnetic resonance imaging (MRI) data were collected in 67 BD patients (during the manic, depressive, or euthymic phases) and 125 healthy controls (HC) at baseline (T1), and in a subsample of 33 BD (during an illness phase different from T1) and 23 HC after a follow-up period (T2).
In a first step, (1) we investigated the alterations in WM microstructure in BD. The fixel-based analysis (FBA) of diffusion MRI data was performed (using MRtrix3). FBA metrics were computed, including: fiber density (FD), measuring the microscopic density of fiber bundles; fiber-bundle cross-section (FC), measuring the macroscopic volume of fiber bundles; and fiber density and cross-section (FDC), combining FD and FC. The statistical analysis of whole-brain fixel-wise metrics was conducted based on a general linear model (GLM) in conjunction with the connectivity-based fixel enhancement approach. (1a) FBA metrics were compared between HC and BD using two-sample t-tests at T1. Next, (1b) the longitudinal change of FBA metrics over time and across the phases of illness were characterized from T1 to T2.
Then, (2) we investigated the relationship of WM alterations with intrinsic brain connectivity in BD. Regional homogeneity (ReHo) and seed-based voxel-wise functional connectivity were calculated from resting-state functional MRI data. (2a) The altered FBA metrics were entered into whole-brain voxel-wise regression analyses with ReHo data at T1. Then, (2b) ReHo was extracted from the resulting clusters and entered into an ANCOVA comparing BD vs. HC. Additionally, (2c) a whole-brain voxel-wise functional connectivity analysis was performed using as regions of interest the clusters identified in the previous analyses and entered into one-sample t-tests within the HC group. Subsequently, (2d) ReHo was extracted from the clusters resulting from the functional connectivity analysis and entered into an ANCOVA to compare BD vs. HC. Finally, (2e) ReHo in the clusters resulting from all the previous analyses was compared longitudinally between T1 and T2 in BD and HC, by performing a repeated measures ANOVA and testing the group by time interaction.
Covariates included sex, age, and head motion. For each GLM, a p-value <0.05, corrected for family-wise error, was set.
In a first step, (1) we investigated the alterations in WM microstructure in BD. The fixel-based analysis (FBA) of diffusion MRI data was performed (using MRtrix3). FBA metrics were computed, including: fiber density (FD), measuring the microscopic density of fiber bundles; fiber-bundle cross-section (FC), measuring the macroscopic volume of fiber bundles; and fiber density and cross-section (FDC), combining FD and FC. The statistical analysis of whole-brain fixel-wise metrics was conducted based on a general linear model (GLM) in conjunction with the connectivity-based fixel enhancement approach. (1a) FBA metrics were compared between HC and BD using two-sample t-tests at T1. Next, (1b) the longitudinal change of FBA metrics over time and across the phases of illness were characterized from T1 to T2.
Then, (2) we investigated the relationship of WM alterations with intrinsic brain connectivity in BD. Regional homogeneity (ReHo) and seed-based voxel-wise functional connectivity were calculated from resting-state functional MRI data. (2a) The altered FBA metrics were entered into whole-brain voxel-wise regression analyses with ReHo data at T1. Then, (2b) ReHo was extracted from the resulting clusters and entered into an ANCOVA comparing BD vs. HC. Additionally, (2c) a whole-brain voxel-wise functional connectivity analysis was performed using as regions of interest the clusters identified in the previous analyses and entered into one-sample t-tests within the HC group. Subsequently, (2d) ReHo was extracted from the clusters resulting from the functional connectivity analysis and entered into an ANCOVA to compare BD vs. HC. Finally, (2e) ReHo in the clusters resulting from all the previous analyses was compared longitudinally between T1 and T2 in BD and HC, by performing a repeated measures ANOVA and testing the group by time interaction.
Covariates included sex, age, and head motion. For each GLM, a p-value <0.05, corrected for family-wise error, was set.
Results:
(1) BD was associated with WM alterations in a definite set of tracts. (1a) At T1, FD and/or FC were reduced in the fornix, cingulum, inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), corticospinal tract (CST), and corpus callosum (CC). (1b) These alterations were stable over time and across the phases of illness. See Figure 1.
(2) WM deficits in the fornix were specifically associated with a reconfiguration of the functional architecture of intrinsic brain activity. (2a) At T1, the FD in the fornix showed a negative correlation with ReHo in the thalamus (encompassing associative nuclei) and midbrain (including the raphe nuclei). (2b) ReHo in the fornix-related thalamic/midbrain cluster was increased in BD. (2c) The fornix-related thalamic/midbrain cluster showed positive functional connectivity with fronto-temporal cortical areas primarily belonging to the default-mode network (DMN). (2d) ReHo in these fronto-temporal areas was reduced in BD. (2e) These alterations were stable over time and across the phases of illness. See Figure 2.
(2) WM deficits in the fornix were specifically associated with a reconfiguration of the functional architecture of intrinsic brain activity. (2a) At T1, the FD in the fornix showed a negative correlation with ReHo in the thalamus (encompassing associative nuclei) and midbrain (including the raphe nuclei). (2b) ReHo in the fornix-related thalamic/midbrain cluster was increased in BD. (2c) The fornix-related thalamic/midbrain cluster showed positive functional connectivity with fronto-temporal cortical areas primarily belonging to the default-mode network (DMN). (2d) ReHo in these fronto-temporal areas was reduced in BD. (2e) These alterations were stable over time and across the phases of illness. See Figure 2.
·Figure 1
·Figure 2
Conclusions:
These results suggest that a trait WM damage to the limbic tracts, like the fornix, which destabilizes the DMN activity represents a core alteration in BD, supporting and updating the recently proposed unified model of the pathophysiology of BD.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Task-Independent and Resting-State Analysis 2
Keywords:
Affective Disorders
FUNCTIONAL MRI
Psychiatric Disorders
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
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Provide references using APA citation style.
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