Neurobiological signatures of anxiety and depression in resting-state functional magnetic resonance imaging

Abstract

Background: There is increasing interest in using neurobiological measures to inform psychiatric nosology. It is unclear at the present time whether anxiety and depression are neurobiologically distinct or similar processes. It is also unknown if the best way to examine these disorders neurobiologically is by contrasting categorical definitions or by examining symptom dimensions.

Methods: A cross-sectional neuroimaging study was conducted of patients with generalized anxiety disorder (GAD), major depressive disorder (MDD), comorbid GAD and MDD (GAD/MDD), or neither GAD nor MDD (control subjects). There were 90 participants, all medication-free (17 GAD, 12 MDD, 23 GAD/MDD, and 38 control subjects). Diagnosis/category and dimensions/symptoms were assessed to determine the best fit for neurobiological data. Symptoms included general distress, common to anxiety and depression, and anxiety-specific (anxious arousal) or depression-specific (anhedonia) symptoms. Low-frequency (.008-.1 Hz) signal amplitude and functional connectivity analyses of resting-state functional magnetic resonance imaging data focused on a priori cortical and subcortical regions of interest.

Results: Support was found for effects of diagnosis above and beyond effects related to symptom levels as well as for effects of symptom levels above and beyond effects of diagnostic categories. The specific dimensional factors of general distress and anxious arousal as well as a diagnosis of MDD explained unique proportions of variance in signal amplitude or functional connectivity.

Conclusions: Using resting-state functional magnetic resonance imaging, our data show that a single conceptual model alone (i.e., categorical diagnoses or symptom dimensions) provides an incomplete mapping of psychopathology to neurobiology. Instead, the data support an additive model that best captures abnormal neural patterns in patients with anxiety and depression.

Keywords: Anhedonia; Anxiety; Depression; Neuroimaging; Resting state; fMRI.

Figure 1

Brain image depicts surface reconstructions of regions of interest (ROIs) used in functional connectivity and intrinsic signal amplitude analyses. DLPFC=dorsolateral prefrontal cortex, dACC=dorsal anterior cingulate cortex, sgACC=subgenual anterior cingulate cortex, mPFC=medial prefrontal cortex, FIC=fronto-insular cortex, VS=ventral striatum.

Figure 2

Distribution of the dimensional Mood and Anxiety Symptom Questionnaire (MASQ) subscale scores across each of the diagnostic categories.

Figure 3

Signal amplitude results from models of only categorical, dimensional, or both categorical and dimensional models of anxiety and depression for all participants, plotting estimated marginal means and their standard errors. For the categorical model, (A) a specific effect of GAD on limbic/paralimbic signal amplitude was found. For the dimensional only model, there was a significant positive relationship between the broad symptom of general distress and limbic/paralimbic signal amplitude (B) that remained significant in the combined categorical and dimensional model (C) after accounting for other symptoms and diagnostic categories. In the combined model, a main effect of MDD was driven by overall lower signal amplitudes for MDD patients compared to individuals without MDD (D).

Figure 4

Functional connectivity results from models of only categorical, dimensional, or both categorical and dimensional models of anxiety and depression for all participants, plotting estimated marginal means and their standard errors. (A) For the dimensional model, there was a significant relationship between anxious arousal and connectivity with the sgACC/ventral striatum that was again significant in the combined categorical and dimensional model (B). In the combined model, MDD was associated with reduced sgACC/VS connectivity and increased amygdala-subcortical connectivity.