Comorbid anxiety: A challenge to the dysconnection syndrome hypothesis of major depressive disorder?
Poster No:
407
Submission Type:
Abstract Submission
Authors:
Marius Gruber1, Jan Schulte2, Elisabeth J. Leehr2, Susanne Meinert2, Dominik Grotegerd2, Igor Nenadić3, Tilo Kircher3, Udo Dannlowski2, Jonathan Repple1
Institutions:
1Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt, Germany, 2Institute for Translational Psychiatry, University of Münster, Münster, Germany, 3Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
First Author:
Marius Gruber
Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt
Frankfurt, Germany
Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt
Frankfurt, Germany
Co-Author(s):
Jonathan Repple
Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt
Frankfurt, Germany
Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt
Frankfurt, Germany
Introduction:
Viewing psychiatric disorders as dysconnection syndromes, that is, disorders characterized by structural brain dysconnectivity, has a long-standing tradition in psychiatric neuroimaging research (Geschwind, 1965; van den Heuvel & Sporns, 2019), especially in the context of schizophrenia (Friston & Frith, 1995; Weinberger, 1993). Based on findings of reduced structural connectivity, this notion was extended to major depressive disorder (MDD) in recent studies as well (Li et al., 2018; Repple et al., 2020). However, these studies did not thoroughly investigate the role of comorbid disorders in such patterns of structural dysconnectivity. This is a crucial research gap given the high rate of comorbidity in mental disorders and, in particular, comorbid anxiety disorders in MDD (Kalin, 2020). Here, we investigated the structural connectivity patterns observed in MDD with and without comorbid anxiety disorder.
Methods:
The sample included n=781 individuals with a lifetime diagnosis of MDD and n=906 healthy controls from the ongoing Marburg-Münster Affective Disorders Cohort Study (MACS). MDD patients were classified into MDD patients, who had at least one lifetime diagnosis of an anxiety disorder (n=249), and MDD patients without any diagnoses of anxiety disorders (n=532). Diagnoses of psychiatric disorders or the lack thereof were established by trained personnel using the Structured Clinical Interview for DSM-IV (SCID-IV). The individual structural brain networks from all participants were reconstructed using data from structural and diffusion-weighted MRI. The network-based statistic (NBS) toolbox was applied to these structural brain networks to evaluate network-level differences in structural brain connectivity among the three groups. Additionally, using a more continuous approach, transdiagnostic analyses were conducted to explore the relationship between levels of state or trait anxiety and structural connectivity across the three groups.
Results:
NBS revealed differences in structural brain connectivity between all three groups (NBS primary threshold F = 4.0, pFWE < 0.05). Post-hoc tests demonstrated decreased structural connectivity in MDD patients without comorbid anxiety disorder and increased structural connectivity in MDD patients with comorbid anxiety disorder relative to healthy controls (Cohen's d = -0.30, and Cohen's d = 0.42, respectively). Robustness checks validated that these findings are not driven by sex effects, non-linear age effects, outliers in structural connectivity, or group differences in head motion or gray matter volume. Given this unexpected finding, we conducted additional analyses to explore whole-brain patterns of structural connectivity. Nodal analyses revealed that structural hypoconnectivity was less prevalent in MDD patients with comorbid anxiety disorder compared to MDD patients without comorbid anxiety disorder, while hyperconnectivity was more widespread in MDD patients with comorbid anxiety disorder than in MDD patients without comorbid anxiety disorder (ꭕ²=4.67, p=0.031). Transdiagnostic analyses suggested that increases in both state and trait anxiety were associated with increased structural connectivity across all three groups (state anxiety: pη²=0.047, pFWE=0.007; trait anxiety: pη=0.046, pFWE=0.049).
·Subnetwork of white matter tracts identified in diagnosis-based NBS analysis
·Results from nodal analysis on whole-brain distribution of connectome alterations
Conclusions:
We found a pattern of hyperconnectivity rather than hypoconnectivity in the structural connectome of MDD patients with comorbid anxiety disorder. Importantly, transdiagnostic analyses revealed that this pattern of structural hyperconnectivity extended to individuals with subclinical levels of anxious symptomatology and is even detectable in healthy controls with subclinical levels of anxiety. These results challenge the broad applicability of the dysconnection syndrome hypothesis to MDD patients. They underscore the importance of symptom-based investigations of brain alterations, especially in mental disorders that occur in comorbidity with each other.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Novel Imaging Acquisition Methods:
Diffusion MRI 2
Keywords:
Affective Disorders
Anxiety
White Matter
1|2Indicates the priority used for review
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Geschwind, N. (1965). Disconnexion syndromes in animals and man. Brain, 88(2), 237–237.
Kalin, N. H. (2020). The Critical Relationship Between Anxiety and Depression. American Journal of Psychiatry, 177(5), 365–367. https://doi.org/10.1176/appi.ajp.2020.20030305
Li, B.-J., et al. (2018). A brain network model for depression: From symptom understanding to disease intervention. CNS Neuroscience & Therapeutics, 24(11), 1004–1019. https://doi.org/10.1111/cns.12998
Repple, J., et al. (2020). Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder. Molecular Psychiatry, 25(7), 1550–1558. https://doi.org/10.1038/s41380-019-0603-1
van den Heuvel, M. P., et al. (2019). A cross-disorder connectome landscape of brain dysconnectivity. Nature Reviews. Neuroscience, 20(7), 435–446. https://doi.org/10.1038/s41583-019-0177-6
Weinberger, D. R. (1993). A connectionist approach to the prefrontal cortex. The Journal of Neuropsychiatry and Clinical Neurosciences, 5(3), 241–253. https://doi.org/10.1176/jnp.5.3.241