Serum multi-biomarkers for predicting relapse in patients with depressive disorders under psychopharmacotherapy

Abstract

Background: Effective predictive biomarkers for depression relapse remain elusive. This study examined the association of a multi-modal serum biomarker panel with relapse among outpatients with depressive disorders under psychopharmacotherapy, utilizing a naturalistic 24-month prospective design. Methods: atients were recruited from a University hospital in South Korea between March 2012 and April 2017. At baseline, 14 serum biomarkers along with socio-demographic and clinical characteristics were assessed in 1094 patients. Following initial antidepressant monotherapy, patients who responded (Hamilton Depression Rating Scale [HAMD] ≤ 14) at the 12-week mark (N = 823) were monitored for relapse (HAMD >14) every three months up to 24 months (N = 710). Logistic regression models, adjusted for relevant covariates, were used to evaluate predictive biomarkers of relapse. Results: The combined scores of four serum biomarkers (cortisol, high-sensitivity C-reactive protein, tumor necrosis factor-alpha, and brain-derived neurotrophic factor) showed a significant and graded association with depression relapse (P-value <0.001), even after adjustments. Conclusions: The application of a combined multi-serum biomarker panel could significantly enhance the predictability of depression relapse. Further validation of these biomarkers in diverse populations and settings is warranted to confirm their utility in clinical practice. © 2025 Elsevier Inc.