Neural signatures of emotional biases predict clinical outcomes in difficult-to-treat depression

TY - JOUR

T1 - Neural signatures of emotional biases predict clinical outcomes in difficult-to-treat depression

AU - Fennema, Diede

AU - Barker, Gareth J

AU - O'Daly, Owen

AU - Godlewska, Beata R

AU - Carr, Ewan

AU - Goldsmith, Kimberley

AU - Young, Allan H

AU - Moll, Jorge

AU - Zahn, Roland

N1 - © The Author(s) 2024.

PY - 2024

Y1 - 2024

N2 - BACKGROUND: Neural predictors underlying variability in depression outcomes are poorly understood. Functional MRI measures of subgenual cortex connectivity, self-blaming and negative perceptual biases have shown prognostic potential in treatment-naïve, medication-free and fully remitting forms of major depressive disorder (MDD). However, their role in more chronic, difficult-to-treat forms of MDD is unknown.METHODS: Forty-five participants (n = 38 meeting minimum data quality thresholds) fulfilled criteria for difficult-to-treat MDD. Clinical outcome was determined by computing percentage change at follow-up from baseline (four months) on the self-reported Quick Inventory of Depressive Symptomatology (16-item). Baseline measures included self-blame-selective connectivity of the right superior anterior temporal lobe with an a priori Brodmann Area 25 region-of-interest, blood-oxygen-level-dependent a priori bilateral amygdala activation for subliminal sad vs happy faces, and resting-state connectivity of the subgenual cortex with an a priori defined ventrolateral prefrontal cortex/insula region-of-interest. FINDINGS: A linear regression model showed that baseline severity of depressive symptoms explained 3% of the variance in outcomes at follow-up ( F[3,34] = .33, p = .81). In contrast, our three pre-registered neural measures combined, explained 32% of the variance in clinical outcomes ( F[4,33] = 3.86, p = .01). CONCLUSION: These findings corroborate the pathophysiological relevance of neural signatures of emotional biases and their potential as predictors of outcomes in difficult-to-treat depression.

AB - BACKGROUND: Neural predictors underlying variability in depression outcomes are poorly understood. Functional MRI measures of subgenual cortex connectivity, self-blaming and negative perceptual biases have shown prognostic potential in treatment-naïve, medication-free and fully remitting forms of major depressive disorder (MDD). However, their role in more chronic, difficult-to-treat forms of MDD is unknown.METHODS: Forty-five participants (n = 38 meeting minimum data quality thresholds) fulfilled criteria for difficult-to-treat MDD. Clinical outcome was determined by computing percentage change at follow-up from baseline (four months) on the self-reported Quick Inventory of Depressive Symptomatology (16-item). Baseline measures included self-blame-selective connectivity of the right superior anterior temporal lobe with an a priori Brodmann Area 25 region-of-interest, blood-oxygen-level-dependent a priori bilateral amygdala activation for subliminal sad vs happy faces, and resting-state connectivity of the subgenual cortex with an a priori defined ventrolateral prefrontal cortex/insula region-of-interest. FINDINGS: A linear regression model showed that baseline severity of depressive symptoms explained 3% of the variance in outcomes at follow-up ( F[3,34] = .33, p = .81). In contrast, our three pre-registered neural measures combined, explained 32% of the variance in clinical outcomes ( F[4,33] = 3.86, p = .01). CONCLUSION: These findings corroborate the pathophysiological relevance of neural signatures of emotional biases and their potential as predictors of outcomes in difficult-to-treat depression.

KW - depression

KW - prediction

KW - fMRI

KW - prognosis

KW - difficult-to-treat

U2 - 10.1017/dep.2024.6

DO - 10.1017/dep.2024.6

M3 - Article

C2 - 40028885

SN - 2976-9000

VL - 1

SP - e21

JO - Research Directions: Depression

JF - Research Directions: Depression

ER -