Inflammation-based Precision Medicine for Depression: From Biomarkers to Clinical Application

Major depressive disorder (MDD) is clinically and biologically heterogeneous, and immune-inflammatory dysregulation has emerged as a central pathophysiological axis.Single inflammatory markers, however, offer only modest predictive accuracy, motivating integrative biomarker strategies.This review synthesizes international meta-analyses, prospective cohorts, and mechanistic studies together with the Korean MAKE BETTER and K-DEPACS/EsDEPACS programs, organizing the evidence into four complementary streams.High-sensitivity C-reactive protein, interleukin (IL)-6, tumor necrosis factor-, and IL-1 are consistently elevated in MDD but with modest effect sizes.Their predictive value strengthens when stratified by psychosocial moderators such as stressful life events, childhood maltreatment, anxiety, functional status, and employment, which concentrate or unmask marker effects on remission, relapse, and suicidality.Pairing inflammatory markers with monoaminergic, neurotrophic, hypothalamic-pituitary-adrenal, and metabolic-nutritional biomarkers further refines prediction by mirroring the multi-system architecture of the disorder.Multi-biomarker panels raise the area under the receiver operating characteristic curve from approximately 0.58 to 0.65-0.67 for remission, and to 0.74-0.76with multi-omics machine learning, with odds ratios for high-versus low-risk strata ranging from 6 to over 50 across diagnosis, treatment response, and suicidality.These findings converge with 2025 proposals to designate an inflammatory MDD subtype as a future Diagnostic and Statistical Manual of Mental Disorders, sixth edition specifier and with the immuno-metabolic depression phenotype, supporting a biomarker-guided precision-medicine framework.Priorities include international multi-omics validation, standardized assays, and decision-support tools that jointly model biomarkers with psychosocial context.