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Functional network characteristics in anxiety- and mania-based subgroups of bipolar I disorder
Adriana P C Hermans1, Dennis J L G Schutter2, Richard A I Bethlehem3
1Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Dr. Molewaterplein 60, 3015 GJ Rotterdam, The Netherlands.
Background:
Bipolar disorder I (BD-I) is a heterogeneous disorder with a high prevalence of comorbid anxiety. The aim of this study was to investigate whether anxiety and mania symptoms define distinct subgroups within BD-I and to explore potential differences in functional network characteristics between these subgroups.
Methods:
Subgroups were identified using scores from clinical anxiety and mania scales. After dimension reduction of these scores, data-driven clustering analysis with cross-validation was employed to reveal the existence of subgroups. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were pre-processed using fMRIPrep. After parcellation and network construction, global and regional graph theoretical measures were calculated per subgroup.
Results:
Clustering results revealed that, based on anxiety symptomatology, subjects fell into two distinct subgroups, whereas mania symptoms divided subjects into four unique subgroups. These subgroups varied notably on several symptom scales. Network assortativity was significantly associated with anxiety subgroups. Post-hoc pairwise comparisons did not reveal significant global functional network differences between the anxiety subgroups or between mania subgroups. Regional network differences between clinical subgroups were especially apparent for strength and degree in the temporal and frontal lobes.
Limitations:
Small sample size of some subgroups is a limitation of this study as is the categorical rather than continuous representation of anxiety and mania symptoms.
Conclusions:
BD-I populations may be stratified into robust subgroups based on anxiety and mania symptoms, showing differences in functional network connectivity. Our findings highlight new avenues of research for investigating heterogeneity in psychiatric populations.
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