The aim of this study was to investigate if biomarkers in QEEG, genetic and neuropsychological measures are suitable for the prediction of antidepressant treatment outcome in depression. Twenty-five patients diagnosed with major depressive disorder were assessed twice, pretreatment and at 8-wk follow-up, on a variety of QEEG and neuropsychological tasks. Additionally, cheek swab samples were collected to assess genetic predictors of treatment outcome. The primary outcome measure was the absolute decrease on the HAM-D rating scale. Regression models were built in order to investigate which markers contribute most to the decrease in absolute HAM-D scores. Patients who had a better clinical outcome were characterized by a decrease in the amplitude of the Auditory Oddball N1 at baseline. The 'Met/Met' variant of the COMT gene was the best genetic predictor of treatment outcome. Impaired verbal memory performance was the best cognitive predictor. Raised frontal Theta power was the best EEG predictor of change in HAM-D scores. A tentative integrative model showed that a combination of N1 amplitude at Pz and verbal memory performance accounted for the largest part of the explained variance. These markers may serve as new biomarkers suitable for the prediction of antidepressant treatment outcome.
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