Sex- and Obesity-related Differences in Amygdala Subnuclei Apportionment Exist during Preadolescence
Poster No:
1254
Submission Type:
Abstract Submission
Authors:
L. Nate Overholtzer1, J. Max Landa1, Jade Li1, Jessica Morrel2, Hedyeh Ahmadi1, Megan Herting1
Institutions:
1University of Southern California, Los Angeles, CA, 2University of Southern California, Los Angles, CA
First Author:
Co-Author(s):
Introduction:
The amygdala is a subcortical limbic system structure critical for emotional processing, sensory perception, decision-making, and appetitive behaviors (Baxter and Murray, 2002; Izadi and Radahmadi, 2022). Neuroanatomical and imaging techniques demonstrate the amygdala can be cytoarchitecturally, genetically, and functionally divided into distinct subnuclei (Ou et al. 2023). Using the novel CIT168 atlas, 9 subnuclei can be assessed in vivo: lateral (LA), dorsal and intermediate basolateral (BLDI), basomedial nucleus (BM), central (CEN), cortical and medial (CMN), basolateral ventral and paralaminar subdivision (BLVPL), amygdala transition areas (ATA), amygdalostriatal transition area (ASTA), anterior amygdala area (AAA), and other non-classified amygdala areas (OTHER) (Pauli, et al., 2018; Tyszka and Pauli, 2016). Prior research in a group of about 400 adolescents spanning ages 10-17 years old indicated sex-related differences but no effects of obesity in amygdala subnuclei apportionment (Campbell et al. 2021). The current study aims to characterize the relationship between (1) obesity and (2) sex differences with proportional amygdala subnuclei volumes in a large, diverse sample of preadolescents.
Methods:
We utilized cross-sectional Siemens Prisma MRI data from 4,155 participants aged 9-10 (Males: 55.4%, Females: 44.6%) from 12 sites of the Adolescent Brain Cognitive Development (ABCD®) Study. B-spline bivariate symmetric normalization (SyN) diffeomorphic registration algorithm from ANTs version 2.2.0 was adapted for image registration of T1w and T2w participant images to the high-resolution CIT168 probabilistic atlas (Figure 1). We measured the probabilistic volumes of 9 subnuclei and calculated the relative volume fraction (RVF) for each subnuclei as the proportion of subnuclei volume relative to the total hemispheric amygdala volume. We excluded participants with an intra-amygdala contrast to noise-ratio (CNR) less than 1.0 in either hemisphere (Campbell, et. al, 2021). Multilevel modeling was employed to examine the effect of (1) BMIz and (2) sex on subnuclei RVFs while adjusting for covariates (i.e., pubertal status, handedness, race/ethnicity, household income, parental education) and study site. Standardized beta coefficients and confidence intervals are reported; P-values were FDR corrected and p-FDRs < 0.05 were considered statistically significant.
Results:
For BMIz, we observed a significant association between obesity and RVFs, including a smaller LA as well as larger BM, CMN, and ATA (all p-FDRs ≤ 0.05, Figure 2a). Also, we saw an association obesity with smaller BLDI RVF in the right amygdala (p-FDRs = 0.03), which trended towards significance in the left amygdala (p-FDR = 0.06, Figure 2a). In both hemispheres, we saw significant sex differences, with smaller RVFs of the BLVPL and ATA, but larger RVFs of the CEN and CMN, in female as compared to male preadolescents (all p-FDR < 0.05, Figure 2b). Sex differences were also noted in some additional left hemisphere subnuclei, with smaller RVFs of LA and OTHER, but larger RVFs of ASTA and BM, in females (all p-FDR < 0.05, Figure 2b).
Conclusions:
In a large, diverse sample of preadolescents, we were able to identify distinct associations between obesity and sex in amygdala subnuclei apportionment. This research expands upon prior work (Campbell et al., 2021) in identifying sex differences in additional subnuclei and expands upon obesity-related differences in amygdala subnuclei previously found in a small sample of youth 8-22 years of age (Kim et al., 2020). Given that several subnuclei have been implicated in reward learning and homeostatic regulation of eating behavior, additional research could contextualize how these findings influence self-regulation during preadolescence.
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Image Registration and Computational Anatomy
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures 2
Keywords:
Development
Limbic Systems
Morphometrics
MRI
STRUCTURAL MRI
Sub-Cortical
Other - Amygdala
1|2Indicates the priority used for review
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