A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS

Hannah Meijs, Helena Voetterl, Alexander T. Sack, Hanneke van Dijk, Bieke De Wilde, Jan Van Hecke, Peter Niemegeers, Evian Gordon, Jurjen J Luykx, Martijn Arns*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.
Original languageEnglish
Pages (from-to)7-16
Number of pages10
JournalEuropean Neuropsychopharmacology
Volume79
Early online date23 Nov 2023
DOIs
Publication statusPublished - Feb 2024

Keywords

  • EEG
  • LORETA
  • MDD
  • TMS
  • polygenic

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