Abstract
Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Highlights
Bipolar disorder (BD) is a severe chronic mental illness that affects ~1% of the general population [1]
This model is mainly supported by results from functional magnetic resonance imaging (MRI) studies demonstrating that emotional instability in this disorder might be underpinned by abnormal connectivity between frontal and limbic regions [5, 6]
Metaanalyses based on whole-brain data have revealed lower fractional anisotropy (FA), a metric derived from diffusion tensor imaging (DTI) known to be positively correlated with the directionality and coherence of white matter bundles [17], in patients with BD near the parahippocampal gyrus, subgenual cingulate cortex [18], temporo-parietal junction and cingulum [19]
Summary
Bipolar disorder (BD) is a severe chronic mental illness that affects ~1% of the general population [1]. Neural models of BD suggest a role of fronto-limbic dysconnectivity in the emergence of mood symptoms of BD [3, 4] This model is mainly supported by results from functional MRI (fMRI) studies demonstrating that emotional instability in this disorder might be underpinned by abnormal connectivity between frontal and limbic regions [5, 6]. The ENIGMA consortium presents a framework to identify generalizable biomarkers, by analyzing large samples with a harmonized processing pipeline—a strategy that has already identified widespread cortical alterations and specific subcortical volumetric abnormalities in patients with BD [23, 24]. We analyzed DTI data from the ENIGMA-BD working group with the objectives of (i) identifying reliable generalizable WM abnormalities in BD using mega- and meta- analytics; (ii) testing if clinical characteristics modulate WM microstructure using mega- analytics. We expected more pronounced alterations (i.e., larger FA differences with respect to healthy controls) in WM microstructure in patients with a more severe course of illness, and a significant association with psychotropic medication
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