Gamma-band qEEG biomarkers as trait indicators in depression

Identifying trait biomarkers that reflect vulnerability to major depressive disorder (MDD), independent of acute symptom fluctuations, is critical for advancing early detection and personalized treatment. Quantitative electroencephalography (qEEG) offers a non-invasive, cost-effective method for assessing neural oscillations as potential trait markers.

To determine whether resting-state qEEG band power differs at baseline between recurrent and non-recurrent MDD patients and healthy controls (HCs), and whether these differences remain stable over repeated measurements.

Eighty-five outpatients with MDD (59 recurrent, 26 non-recurrent) and 67 HCs underwent three qEEG recordings: baseline (T0), mid-treatment (T1), and follow-up (T2) within approximately thirty months. One-way ANOVA, controlling for age and gender, compared baseline absolute qEEG power across groups. Bands showing significant differences were further examined using repeated-measures ANCOVA, adjusting for demographic and clinical covariates. Pearson correlations assessed associations between qEEG power and concurrent depression and anxiety severity.

At baseline, absolute gamma power was significantly lower in both recurrent and non-recurrent MDD groups than in HCs across widespread regions. Other frequency bands showed no consistent group differences. Across repeated measures, gamma power remained stable with the most robust stability observed in midline-posterior regions. No significant correlations were found between gamma power and depression or anxiety severity.

The persistence of reduced gamma activity across sessions supports its candidacy as a trait biomarker for MDD, with limited region-specific state sensitivity. qEEG-based markers hold promises for enhancing diagnostic precision and guiding individualized interventions.