Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis.
Leila NabulsiGenevieve McPhilemyStefani O'DonoghueDara M CannonLiam KilmartinDenis O'HoraSamuel SarrazinCyril PouponMarc-Antoine D'AlbisAmelia VersaceMarine DelavestJulia LinkeMichèle WessaMary L PhillipsJosselin HouenouColm McDonaldPublished in: Cerebral cortex (New York, N.Y. : 1991) (2021)
Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.
Keyphrases
- bipolar disorder
- cross sectional
- major depressive disorder
- magnetic resonance imaging
- diffusion weighted
- resting state
- white matter
- contrast enhanced
- functional connectivity
- depressive symptoms
- squamous cell carcinoma
- multiple sclerosis
- autism spectrum disorder
- magnetic resonance
- radiation therapy
- electronic health record
- network analysis
- deep learning
- brain injury
- machine learning
- sentinel lymph node
- data analysis