Differentiating Bipolar and Unipolar Depression in the Era of Precision Psychiatry

Abstract

Bipolar and unipolar depression share substantial clinical overlap, making differential diagnosis during depressive episodes particularly challenging.Because current diagnostic systems rely on the retrospective identification of manic or hypomanic episodes, many patients with bipolar disorder are initially misdiagnosed with major depressive disorder, resulting in delayed diagnosis, inappropriate antidepressant treatment, mood destabilization, and poorer outcomes.This review summarizes current evidence on clinical, biological, and digital approaches to differentiating bipolar from unipolar depression.Established clinical indicators-including early age at onset, recurrent depressive episodes, family history of bipolar disorder, mixed features, antidepressant-induced mood switching, and treatment resistanceremain central to diagnostic assessment.Emerging evidence from neuroimaging, electrophysiology, circadian rhythm evaluation, peripheral biomarkers, digital phenotyping, and machine-learning approaches suggests that multimodal integration may improve diagnostic precision.Although no single marker is suitable for routine clinical use, a longitudinal, probabilistic, and multimodal framework may facilitate earlier recognition of bipolarity and more personalized treatment strategies.