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Updated: Sep 10, 2026

Developing a Rat Model for Bipolar Disorder
Published on: May 2, 2025
Association of Polygenic Risk Score for Suicidal Behavior With Ventral Prefrontal Morphology in Bipolar Disorder
Noa Katz Shroitman1, Daniel F Levey1, Brian Pittman1
1Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA.
Background:
Bipolar disorder (BD) studies consistently implicate the ventral prefrontal cortex (VPFC) in association with suicidal behaviors. A suicidal behavior polygenic risk score (PRS) can now be computed to test whether elevated genetic risk for suicidal behavior is associated with variation in VPFC gray matter and/or suicidal behavior history.
Methods:
We explored relationships among a PRS previously associated with suicidal behavior, VPFC morphology, and suicidal behavior in 376 individuals of European ancestry (mean age 30y; 57% female): 225 with BD (76 suicide attempters (SAs), 149 non-suicide attempters (NSAs)) and 151 healthy control individuals (HCs). We calculated PRS and performed magnetic resonance imaging to assess VPFC (inferior frontal gyrus (IFG) and orbitofrontal cortex) cortical thickness and surface area. Associations were examined among PRS, diagnosis, suicide attempt history, and brain measures.
Results:
Among individuals with BD, those with higher PRS showed decreased right VPFC surface area, primarily due to IFG reductions (p < 0.01). A significant group (SA, NSA, HC)-by-PRS interaction was observed for right IFG cortical surface area (p < 0.05); NSAs with high vs. low PRS had significantly smaller right IFG surface area. The mean PRS was highest for SAs, then NSAs, and lowest for HCs; however, differences did not reach significance.
Conclusions:
These findings suggest this suicide PRS may reflect genetic mechanisms influencing IFG differences in BD. Given the modest sample size, replication of these preliminary findings in large-scale diverse cohorts is required to determine whether including this PRS and/or the corresponding IFG values could improve multimodal BD suicidal behavior prediction algorithms.
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