Mapping the Interplay Between Hormones, Neurotransmitters, and Brain Energy Dynamics in Aging Women
Poster No:
929
Submission Type:
Abstract Submission
Authors:
Ceren Tozlu1, Louisa Schilling2, Parker Singleton3, Keith Jamison1, Laura Pritschet3, Emily Jacobs4, Amy Kuceyeski1
Institutions:
1Weill Cornell Medicine & Cornell University, Ithaca, NY, 2Weill Cornell Medicine, NYC, NY, 3University of Pennsylvania, Philadelphia, PA, 4University of California, Santa Barbara, Santa Barbara, CA
First Author:
Co-Author(s):
Introduction:
Sex hormones and neurotransmitter/receptor density play an important yet not fully understood role in shaping how the brain's structural and functional architecture evolve across the lifespan [1,2,3]. Network Control Theory (NCT) [4] is one tool that can be used to investigate how the brain's structural connectivity architecture constrains its dynamic functional activation. NCT begins by identifying commonly recurring states of brain activity and then uses the brain's structural connectivity networks to identify the minimum transition energy (TE) required to transition between these states. NCT has previously been applied in disease [5] and health [6,7], for example, to identify changes across developing populations [8] and to identify sex-specific differences in brain activity dynamics of youth with a family history of substance use disorder [9]. However, no study to date has applied NCT in aging women to investigate how TE is related to female hormone levels and to further shed light on which neurotransmitter/receptors may be central to this relationship.
Methods:
Four hundred and four females (age: 60.05 ± 15.74) from the Human Connectome Project-Aging (HCP-A) dataset [10] were used. First, k-means was applied to the regional functional MRI (fMRI) time series to identify commonly recurring dynamic brain states. The time series were analyzed using regional averages of 68 cortical and 18 subcortex/cerebellum FreeSurfer-based regions; structural connectivity matrices were extracted using diffusion MRI. Second, NCT was applied to calculate the minimum energy required to transition between each pair of dynamic brain states. Global TE was calculated as the average of the pairwise TEs between dynamic states. Linear models were used to investigate the association of global, regional, and network-level TE with hormones such as estradiol, Luteinizing Hormone (LH), and Follicle-Stimulating Hormone (FSH). Interaction terms between age and hormones, age and framewise displacement (FD), and hormones and FD were included. Neurotransmitter/receptor density maps [11] were correlated with regional coefficients representing the relationship between hormones and TE to investigate how microstructural architecture may perhaps underlie NCT-based brain dynamics. Spearman's correlation was used to identify the correlation between the neurotransmitter/receptor maps and the estimates of the hormones as well as hormone and age interaction from the linear models. The p-values were corrected for multiple comparisons with the Benjamini & Hochberg method.
Results:
Recurrent brain states included visual (VIS), default mode (DMN), and somatomotor (SOM) networks with high (+) and low-amplitude activity (-). Estradiol was negatively associated with global TE while the interaction between estradiol and age was positive. This indicates that as age increases, the negative relationship between estradiol and global TE diminishes (Figure 1). Increased estradiol and decreased FSH were associated with decreased TE in FP networks. Moreover, the interaction between estradiol and TE in the FP was negative, while between FSH and TE was positive, indicating these associations are age-dependent (Figure 1). The regions that showed strong associations between their TE and hormones were enriched in serotonin, GABA, acetylcholine, and glutamate neurotransmitters/receptors (Figure 2).
·Figure 1
·Figure 2
Conclusions:
Our findings highlight that the association between estradiol and the brain's energetic landscape is age-dependent. Hormones are linked to shifts in the brain's dynamic activity landscape, with neurotransmitter and receptor density perhaps playing a role in how hormones mediate this dynamic activity. Understanding how hormonal changes during life stages such as puberty, pregnancy, postpartum, and menopause impact brain dynamics is crucial for advancing female-specific healthcare and developing targeted interventions to support women's brain health across the lifespan.
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Keywords:
FUNCTIONAL MRI
Modeling
Neurotransmitter
RECEPTORS
Other - Network Control Theory, Aging, Women's Health
1|2Indicates the priority used for review
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[9] Sex-specific differences in brain activity dynamics of youth with a family history of substance use disorder Louisa Schilling, S Parker Singleton, Ceren Tozlu, Marie Hédo, Qingyu Zhao, Kilian M Pohl, Keith Jamison, Amy Kuceyeski. bioRxiv 2024
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