Lesion-Network Mapping of Poststroke Depressive Symptoms: Evidence From Two Prospective Ischemic Stroke Cohorts

Abstract

Background: Poststroke depression affects up to one-third of stroke survivors, significantly impacting recovery and quality of life. However, its pathophysiology remains unclear.

Methods: We analyzed 2 independent, prospective ischemic stroke cohorts (PROSCIS-B [Prospective Cohort of Incident Stroke Berlin] and BAPTISe [Biomarkers and Perfusion-Training-Induced Changes After Stroke]; n=377) enrolled at the Charité Hospital, Germany, to identify brain regions and networks associated with depressive symptoms poststroke. Lesion-symptom mapping assessed associations between lesion location and depressive symptoms measured by the Center for Epidemiological Studies Depression Scale at 6 (BAPTISe) or 12 (PROSCIS-B) months poststroke. Lesion-network mapping evaluated lesion connectivity with brain networks. A mixed-effects model, including cohort as a random effect, assessed the relationship between network similarity (Pearson correlation) and Center for Epidemiological Studies Depression Scale scores. Dice coefficients (DC) quantified spatial overlap with canonical resting-state networks.

Results: Lesion-symptom mapping showed no significant associations between lesion location and depressive symptoms. In contrast, lesion-network mapping revealed that lesion connectivity to brain regions including the frontal pole, middle and inferior frontal gyri, inferior temporal gyrus, supramarginal gyrus, angular gyrus, frontal orbital cortex, and thalamus weakly correlated with Center for Epidemiological Studies Depression Scale scores (β, 11.4 [95%CI, 1.8-21.1]; P=0.02). These regions overlapped with the frontoparietal (DC=0.28), salience (DC=0.27), and default mode (DC=0.20) networks, as well as a published depression circuit (DC=0.43). However, these findings did not replicate across data sets.

Conclusions: Lesion location alone was not associated with poststroke depression. However, connectivity-based analyses implicated disruption of large-scale brain networks in the development of depressive symptoms. The failure to validate this association across data sets underscores the need for further studies with more comparable patient populations-particularly in terms of stroke severity and harmonized assessment time-points-to confirm these findings and their clinical relevance.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01363856. URL: https://www.clinicaltrials.gov; Unique identifier: NCT01954797.

Keywords: biomarkers; depression; quality of life; stroke; survivors.