Amygdala Subnuclei Volume in Bipolar Spectrum Disorders: Insights From Diffusion-Based Subsegmentation and a High-Risk Design

Hum Brain Mapp. 2020 May 9. doi: 10.1002/hbm.25021. Online ahead of print.

Abstract

Amygdala abnormalities are widely documented in bipolar spectrum disorders (BSD). Amygdala volume typically is measured after BSD onset; thus, it is not known whether amygdala abnormalities predict BSD risk or relate to the disorder. Additionally, past literature often treated the amygdala as a homogeneous structure, and did not consider its distinct subnuclei and their differential connectivity to other brain regions. To address these issues, we used a behavioral high-risk design and diffusion-based subsegmentation to examine amygdala subnuclei among medication-free individuals with, and at risk for, BSD. The behavioral high-risk design (N = 114) included low-risk (N = 37), high-risk (N = 47), and BSD groups (N = 30). Diffusion-based subsegmentation of the amygdala was conducted to determine whether amygdala volume differences related to particular subnuclei. Individuals with a BSD diagnosis showed greater whole, bilateral amygdala volume compared to Low-Risk individuals. Examination of subnuclei revealed that the BSD group had larger volumes compared to the High-Risk group in both the left medial and central subnuclei, and showed larger volume in the right lateral subnucleus compared to the Low-Risk group. Within the BSD group, specific amygdala subnuclei volumes related to time since first episode onset and number of lifetime episodes. Taken together, whole amygdala volume analyses replicated past findings of enlargement in BSD, but did not detect abnormalities in the high-risk group. Examination of subnuclei volumes detected differences in volume between the high-risk and BSD groups that were missed in the whole amygdala volume. Results have implications for understanding amygdala abnormalities among individuals with, and at risk for, a BSD.

Keywords: amygdala; bipolar disorder; diffusion-based subsegmentation; gray matter volume; high-risk design; morphometry.