▎ACHIEVEMENTS

Prof. Po-Hsiu Kuo of NTU’s Department of Public Health and Institute of Epidemiological and Preventive Medicine participated in a groundbreaking global research collaboration with the Psychiatric Genomics Consortium. This study conducted the largest multi-ancestry genomic analysis of bipolar disorder to date. The study findings were published in Nature (January 22, 2025).

Bipolar disorder is a chronic mood disorder that significantly impacts one’s quality of life and functional ability, with an increased risk of suicide. It is clinically heterogeneous, with two main subtypes: bipolar disorder type I (BD-I) and type II (BD-II). BD-I involves both manic and depressive episodes, while BD-II includes hypomania and depression. On average, it takes eight years to make an accurate diagnosis, and much about the biology of the condition remains unknown.

This study analyzed genomic data from 2.9 million participants with a diversity of ancestries, including European, East Asian, African American, and Latino populations. Researchers examined over 6.7 million common genetic variants, drawing from more than 158,000 individuals diagnosed with bipolar disorder. They identified 298 genomic regions containing DNA variants linked to an increased risk of the condition—more than four times the number found in previous studies. Using advanced techniques like fine-mapping and variant-to-gene mapping, the team pinpointed 36 genes likely involved in bipolar disorder. The study also highlighted genetic differences in bipolar disorder across clinical, community-based, and self-reported samples, showing the influence of how data is collected and the varying prevalence of BD-I and BD-II.

The findings revealed that the genetic signals associated with bipolar disorder are linked to specific brain cell types, particularly GABAergic interneurons and medium spiny neurons in the prefrontal cortex and hippocampus. Interestingly, the study also found that cells in the intestine and pancreas might be involved, though further research is needed to explore these connections. This research opens the way to better treatments, earlier interventions, and precision medicine approaches, ultimately helping clinicians make more well-informed, individualized decisions for patients.