Divergent effects of family history of substance use disorder on brain dynamics in females and males
Poster No:
333
Submission Type:
Abstract Submission
Authors:
Louisa Schilling1, S. Parker Singleton2, Marie Hedo3, Ceren Tozlu4, Keith Jamison5, Amy Kuceyeski6
Institutions:
1Weill Cornell, brooklyn, NY, 2University of Pennsylvania, Philadelphia, PA, 3Cornell University, Ithaca, NY, 4Weill Cornell Medicine, NYC, NY, 5Weill Cornell Medicine, New York, NY, 6Cornell, Ithaca, NY
First Author:
Co-Author(s):
Introduction:
An individual's risk of substance use disorder (SUD) is shaped by a complex interplay of potent biosocial factors. Current neurodevelopmental models posit vulnerability to SUD in youth is due to an overactive reward system and reduced inhibitory control (Heitzeg et al., 2015). Having a family history of SUD is a particularly strong risk factor, yet few studies have explored its impact on brain function and structure prior to substance exposure (Bogdan et al., 2023). Herein, we utilized a network control theory (NCT) approach to quantify sex-specific differences in brain activity dynamics and structural connectivity in youth with and without a family history of SUD, drawn from a large cohort of substance-naïve youth from the Adolescent Brain Cognitive Development Study (ABCD) (Casey et al., 2018).
Methods:
We analyzed a subset of 1894 youth (54% females, age 9-11) from the baseline assessment of the ABCD study. Subjects with 1+ parent and/or 2+ grandparents with SUD and subjects with no parental nor grandparental SUD were categorized as FH+ and FH-, respectively. We analyzed pre-processed rsfMRI and structural connectivity data as described in Ooi et al., 2022. We analyzed group differences in brain function and structure using two NCT approaches. First, we looked at group differences in rsfMRI data using a group-average structural connectome (SC). Following previous work (Singleton et al., 2022 & Cornblath et al., 2020), we performed k-means clustering (k=4) of brain activity into recurring brain states parcellated into 86 regions derived from FreeSurfer (68 cortical +18 subcortical). We calculated the energy required to transition from a given state to every other state, or transition energy (TE), for each of nine functional networks (Yeo et al., 2011; Gu et al., 2015). We next explored group differences in structural connectivity by using individual SC's to calculate the TE for transitions between canonical states of the Yeo 7-networks (i.e., binary states with 1's assigned to brain regions belonging to each network and 0's elsewhere for all subjects) parcellated into 68 cortical regions (Singleton et al., 2023). We performed ANCOVA models to determine the effect of the interaction between sex and FH of SUD on TE, controlling for sex, age, puberty, race, income, parental education, parental mental illness, in utero substance exposure, MRI model and framewise displacement. All reported p-values underwent FDR correction.
Results:
For our analysis using subject-specific brain states and average SC, we identified k=4 states and named them based on their cosine similarity of its high and low-amplitude activity to a priori resting-state networks: DMN+/-, VIS+/- (Yeo et al., 2011). Our findings reveal sex-specific differences in the effect of FH of SUD on network energy dynamics such that TE is higher in the DMN network of FH+ females and lower in the attentional (DAT and VAT) networks of FH+ males, compared to their same-sex, FH- counterparts (Fig 1). Using canonical brain states and individual SC, we found FH-by-sex effects in transitions to the VAT state driven by lower TE in FH+ compared to FH- males (Fig 2). FH+ females revealed higher TE in transitions from VIS to LIM and FPN states. Across males and females, there was a pattern of asymmetric differences in top-down and bottom-up TE such that bottom-up transitions required more TE and top-down required less TE in FH+ compared to FH- individuals.
·Figure 1. Network-level transition energy differences in family history of SUD vary by sex.
·Figure 2. Structural connectivity-derived differences in males and females with family history of SUD.
Conclusions:
The present results suggest a family history of SUD endows an asymmetry of energetic demand in bottom-up and top-down transitions which manifests in both the structural connectome and functional activity dynamics of the brain. This may alter reward saliency and inhibitory control in a sex-specific manner, offering insights for personalized intervention strategies that address distinct cognitive mechanisms predisposing male and female adolescents to SUD.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Emotion, Motivation and Social Neuroscience:
Reward and Punishment
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Addictions
Computational Neuroscience
Development
FUNCTIONAL MRI
Modeling
PEDIATRIC
Preprint
Psychiatric Disorders
Statistical Methods
STRUCTURAL MRI
1|2Indicates the priority used for review
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Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., ... & Dale, A. M. (2018). The adolescent brain cognitive development (ABCD) study: imaging acquisition across 21 sites. Developmental cognitive neuroscience, 32, 43-54.
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Ooi, L. Q. R. et al. Comparison of individualized behavioral predictions across anatomical, diffusion and functional connectivity MRI. NeuroImage 263, 119636, DOI: 10.1016/j.neuroimage.2022.119636 (2022).
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Singleton, S. P., Velidi, P., Schilling, L., Luppi, A. I., Jamison, K., Parkes, L., & Kuceyeski, A. (2023). Altered structural connectivity and functional brain dynamics in individuals with heavy alcohol use. bioRxiv.
Yeo, BT Thomas, et al. (2011). "The organization of the human cerebral cortex estimated by intrinsic functional connectivity." Journal of neurophysiology.