Recent advances in the genetic architecture of bipolar disorder and its clinical implications: a narrative review

Purpose: Bipolar disorder (BD) is a highly heritable psychiatric condition characterized by recurrent alternations between manic and depressive episodes. This review summarizes recent advances in understanding the genetic architecture of BD, spanning early heritability and candidate gene studies through genome-wide and sequencing-based discoveries, and discusses the potential clinical implications of these findings.Current concepts: Family and twin studies have established the substantial heritability of BD, whereas early candidate gene approaches focusing on neurotransmitter and circadian pathways demonstrated limited reproducibility. In contrast, large-scale genome-wide association studies have identified numerous common risk variants implicating synaptic signaling, calcium channel function, and neurodevelopmental processes. Complementary exome and whole-genome sequencing studies have further uncovered rare variants and structural alterations contributing to disease risk. Epigenome-wide association studies additionally reveal how genetic variants interact with DNA methylation and chromatin accessibility to regulate transcription. Emerging multi-ancestry research, including studies involving Korean cohorts, has expanded understanding of both shared and population-specific loci. Functionally, BD risk genes converge on biological networks involved in neurotransmission, ion channel regulation, neurodevelopment, circadian rhythm regulation, and immune-inflammatory pathways.Discussion and conclusion: Despite these genomic advances, translation into routine clinical practice remains limited. Integrating genetic findings with multi-omics data and detailed clinical phenotypes may improve diagnostic precision, enhance prediction of treatment response (e.g., lithium efficacy and adverse drug reactions), and support the development of personalized psychiatry. Future research should prioritize cross-ancestry analyses, functional validation, and causal inference frameworks to bridge the gap between genetic discovery and clinical application.