Predictive Biomarkers of Treatment Response in Major Depressive Disorder

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain’s electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Logistic regression modeling was used to predict treatment response, defined as at least a 50% improvement on the Beck’s Depression Inventory, in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). The results show that both age and baseline symptom severity were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance. These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies

EEG reveals that dextroamphetamine improves cognitive control through multiple processes in healthy participants

The poor translatability between preclinical and clinical drug trials has limited pro-cognitive therapeutic development. Future pro-cognitive drug trials should use translatable cross-species cognitive tasks with biomarkers (1) relevant to specific cognitive constructs, and (2) sensitive to drug treatment. Here, we used a difficulty-modulated variant of a cross-species cognitive control task with simultaneous electroencephalography (EEG) to identify neurophysiological biomarkers sensitive to the pro-cognitive effects of dextroamphetamine (d-amp) (10 or 20 mg) in healthy adults (n = 23), in a randomized, placebo-controlled, counterbalanced, double blind, within-subject study, conducted across three test days each separated by one week. D-amp boosted d-prime, sped reaction time, and increased frontal P3a amplitude to non-target correct rejections independent of task difficulty. Task difficulty did however, moderate d-amp effects on EEG during target performance. D-amp suppressed frontal theta power during easy target responses which negatively correlated with drug-induced improvement in hit rate while d-amp-induced changes in P3b amplitude during hard target trials strongly correlated with drug-induced improvement in hit rate. In summary, d-amp affected both behavioral and neurophysiological measures of cognitive control elements. Under low-demand, d-amp diminished cognitive control by suppressing theta, yet under high-demand it boosted control in concert with higher P3b amplitudes. These findings thus appear to reflect a gain-sharpening effect of d-amp: during high-demand processes were boosted while during low-demand processes were neglected. Future studies will use these neurophysiological measures of cognitive control as biomarkers to predict d-amp sensitivity in people with cognitive control deficits, including schizophrenia