V22. EEG-vigilance and the autonomous nervous system in the prediction of antidepressant treatment: Findings from the iSPOT-D study

To overcome the limitations of the syndrome-based diagnostic routine in neuropsychiatric disorder and to provide biomarker-informed decisions for treatment, recently the Research Domain Criteria have been initialized [1] . They include separate criteria for autonomous and arousal systems. Based on findings of altered wakefulness-regulation and autonomous function in major depressive disorder (MDD), the goal of this study therefore was to investigate the predictive value for treatment outcome of central nervous system (CNS) and autonomous nervous system (ANS) arousal and their interaction in a large cohort of patients from the iSPOT-D trial that received either a selective-serotonin reuptake-inhibitor (SSRI) or a serotonin-norepinephrine-reuptake-inhibitor (SNRI). Methods CNS and ANS-arousal (defined by electroencephalogram vigilance and heart rate) and their change over time were assessed during rest. Differences of treatment outcome as defined by the decline of Hamilton Rating Scale for Depression-(HRSD) from baseline to week 8 after treatment initiation for the whole sample and for SSRI and SNRI groups separately were analysed using a binary logistic regression model and repeated measure analysis of variance (ANOVA). Results Responders and remitters were characterized by a steeper decline of CNS-arousal. Subgroup analysis showed that this effect was only present for the SSRI arm whereas SNRI responders showed a more pronounced increase of ANS-arousal. Further, SSRI responders showed a correlation between ANS and CNS measures, SSRI non-responders and the whole SNRI subgroup did not. Conclusions CNS and ANS-arousal during rest predict positive treatment outcome to antidepressant medication. The differences of CNS and ANS-profiles for SSRI or SNRI prediction are interpreted as neurophysiological traits that indicate responsiveness to different drug-classes rather than disorder specific aspects.