Complex Patterns of Altered White Matter Structural Connectivity within a 'subjective valuation network' in
Benjamin Maas1, Rachel Jones2, Christinia Johnson3
1School of Biomedical Engineering and Sciences, Virginia Tech-Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Background:
Treatment-resistant depression (TRD) poses a significant clinical challenge, demanding a deeper understanding of its neurobiological underpinnings to improve therapeutics. We examined white matter microstructure and structural connectivity in TRD, focusing on the 'subjective valuation network' (SVN), which captures motivated behavior, reward processing, and emotional regulation circuits commonly altered in depression. This allowed us to identify potential neuroimaging biomarkers associated with treatment resistance.
Methods:
Diffusion tensor imaging (DTI) data were acquired from a sample of age-and-gender balanced individuals with TRD (n=44; female = 24, male=11, non-binary/unchecked =7) and non-depressed controls (n=42; female=27, male =12, non-binary/unchecked=5). Tract-Based Spatial Statistics were used to compare whole-brain white matter integrity differences between groups. Probabilistic tractography was then used to assess fractional anisotropy (FA) and white matter structural connectivity within the SVN across groups. SVN was defined a priori based on converging functional connectivity studies and included key regions such as the ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), ventral striatum, and insula and their connecting white matter tracts. Additionally, correlations between clinical measures of depression severity and cognition and structural features of the network's white matter fibers (i.e. FA and structural connectivity) were explored.
Results:
Compared to non-depressed controls, individuals with TRD exhibited reduced FA within the left uncinate fasciculus, left inferior fronto-occipital fasciculus, and anterior cingulum, supporting widespread white matter integrity degradations in TRD. No correlations were found between FA and depression severity, suggesting a more specific association with anhedonic features. Whole-network measures of FA and structural connectivity of the SVN did not differ between groups. However, specific subcircuits' structural connectivity within the SVN differed between groups; namely, the white matter tracts connecting the insula-vmPFC, striatum-insula, and striatum-vmPFC. Hyperconnectivity emerged for patients with TRD for tracts connecting the insula-vmPFC and striatum-vmPFC region-pairs, with exhibited hypoconnectivity between the striatum-insula. Exploratory analyses for the TRD group indicated the subcircuits with altered structural connectivity within the SVN correlated with depressive severity. This indicates subcircuit network alterations may associate with greater difficulty experiencing pleasure - a core symptom of depression and a potential marker of treatment resistance.
Conclusions:
This study provides evidence for wide-spread disruption of white matter microstructure and altered structural connectivity within specific subcircuits of the SVN in TRD. These findings point to an intricate pattern of structural hyper-and-hypo-connectivity within the subcircuits of the SVN which may underlie the core symptoms of TRD. The altered structural connectivity within the SVN may contribute to the pathophysiology of TRD, especially concerning the motivational and emotional deficits associated with anhedonia. Future research employing multimodal neuroimaging techniques and longitudinal designs is warranted to further elucidate the functional consequences of these structural abnormalities and their potential as predictive biomarkers for personalized treatment interventions in TRD. Specifically, investigating how these white matter alterations change with successful treatment or targeted interventions aimed at improving anhedonia could inform more effective therapies for this challenging condition.
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