Poster No:
1678
Submission Type:
Late-Breaking Abstract Submission
Authors:
Farai Mberi1,2, Emmanuel Nwosu1,2, Haitao Chen3,4, Thabang Serakge1,2, Claudia Buss5,6, Elysia Davis7,8, Catherine Demers7,9, Kirsten Donald2,10, A. David Edwards11, John Gilmore12, Benjamin Hankin13, Xiaowei Ou14,15,16,17, Kim Pilyoung7, Jerod Rasmussen6, Dan Stein1,2,18, Heather Zar10,19, Paul Thompson20, Ann Alex21,22, Wei Gao3, Rebecca Knickmeyer21,23, Nynke Groenewold1,2, Jonathan Ipser1,2
Institutions:
1Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa, 2Neuroscience Institute, University of Cape Town, Cape Town, South Africa, 3Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 4Department of Bioengineering, University of California at Los Angeles, Los Angeles, CA, 5Charité – Universitätsmedizin Berlin, Institute of Medical Psychology, Berlin, Germany, 6Department of Pediatrics, Development, Health and Disease Research Program University of California, Irvine, CA, 7Department of Psychology, University of Denver, Denver, CO, 8Department of Pediatrics, University of California-Irvine, Irvine, CA, 9Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, 10Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa, 11Research Department of Early Life Imaging, Biomedical Engineering and Imaging, King's College London, London, United Kingdom, 12Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 13Department of Psychology, University of Illinois-Urbana-Champaign, Urbana–Champaign, IL, 14Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, Little Rock, AR, 15Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Little Rock, AR, 16Arkansas Children’s Nutrition Center, Little Rock, AR, 17Arkansas Children’s Research Institute, Little Rock, AR, 18South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Cape Town, South Africa, 19South African Medical Research Council (SAMRC) Unit on Child & Adolescent Health, Cape Town, South Africa, 20Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, USC, Marina del Rey, CA, 21Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, 22Department of Neuroscience and Experimental Therapeutics, Texas A&M Health Science 16 Center, College of Medicine, Bryan, TX, 23Department of Pediatrics and Human Development, Michigan State University, East Lansing, MI
First Author:
Farai Mberi
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
Co-Author(s):
Emmanuel Nwosu
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
Haitao Chen
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center|Department of Bioengineering, University of California at Los Angeles
Los Angeles, CA|Los Angeles, CA
Thabang Serakge
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
Claudia Buss
Charité – Universitätsmedizin Berlin, Institute of Medical Psychology|Department of Pediatrics, Development, Health and Disease Research Program University of California
Berlin, Germany|Irvine, CA
Elysia Davis
Department of Psychology, University of Denver|Department of Pediatrics, University of California-Irvine
Denver, CO|Irvine, CA
Catherine Demers
Department of Psychology, University of Denver|Department of Psychiatry, University of Colorado Anschutz Medical Campus
Denver, CO|Aurora, CO
Kirsten Donald
Neuroscience Institute, University of Cape Town|Department of Paediatrics and Child Health, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
A. David Edwards
Research Department of Early Life Imaging, Biomedical Engineering and Imaging, King's College London
London, United Kingdom
John Gilmore
Department of Psychiatry, University of North Carolina at Chapel Hill
Chapel Hill, NC
Benjamin Hankin
Department of Psychology, University of Illinois-Urbana-Champaign
Urbana–Champaign, IL
Xiaowei Ou
Department of Radiology, University of Arkansas for Medical Sciences, Little Rock|Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock|Arkansas Children’s Nutrition Center|Arkansas Children’s Research Institute
Little Rock, AR|Little Rock, AR|Little Rock, AR|Little Rock, AR
Kim Pilyoung
Department of Psychology, University of Denver
Denver, CO
Jerod Rasmussen
Department of Pediatrics, Development, Health and Disease Research Program University of California
Irvine, CA
Dan Stein
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town|South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders
Cape Town, South Africa|Cape Town, South Africa|Cape Town, South Africa
Heather Zar
Department of Paediatrics and Child Health, University of Cape Town|South African Medical Research Council (SAMRC) Unit on Child & Adolescent Health
Cape Town, South Africa|Cape Town, South Africa
Paul Thompson
Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, USC
Marina del Rey, CA
Ann Alex
Institute for Quantitative Health Sciences and Engineering, Michigan State University|Department of Neuroscience and Experimental Therapeutics, Texas A&M Health Science 16 Center, College of Medicine
East Lansing, MI|Bryan, TX
Wei Gao
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center
Los Angeles, CA
Rebecca Knickmeyer
Institute for Quantitative Health Sciences and Engineering, Michigan State University|Department of Pediatrics and Human Development, Michigan State University
East Lansing, MI|East Lansing, MI
Nynke Groenewold
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
Jonathan Ipser
Department of Psychiatry and Mental Health, University of Cape Town|Neuroscience Institute, University of Cape Town
Cape Town, South Africa|Cape Town, South Africa
Late Breaking Reviewer(s):
Jaehee Kim
Duksung Women's University
Seoul, 서울특별시
Rosanna Olsen
Rotman Research Institute, Baycrest Academy for Research and Education
Toronto, Ontario
Introduction:
Antenatal maternal depression (AMD) affects 7-20% of pregnant women. Literature investigating functional brain alterations in neonates exposed to AMD converges to implicate the involvement of regions within the extended salience network (ESN), including the amygdala (AMG), anterior insula (aINS), and dorsal anterior cingulate cortex (dACC). However, functional connectivity findings related to these regions remain inconsistent, likely due to methodological differences, including a focus on AMG-prefrontal connectivity (Posner, 2016; Qiu, 2015), and network approaches that do not allow for a detailed assessment of pairwise connectivity between ESN nodes (Na, 2023; Rotem-Kohavi, 2019). Leveraging data pooled from different sites in the ENIGMA-ORIGINS database, this study aims to characterize AMD-associated functional connectivity (FC) alterations within the extended salience network, in a larger, more diverse sample.
Methods:
We conducted a mega-analysis of resting-state functional MRI (rs-fMRI) data from 743 neonates (127 AMD-exposed and 617 healthy controls, aged 0–6 months, 53 % females) across 8 sites. Data were preprocessed using FSL and AFNI, with steps including motion correction, registration, bandpass filtering (0.01–0.10 Hz), scrubbing, nuisance signal regression, and global signal regression. ComBat harmonization (Pomponio, 2020) was applied to FC matrices, and connectomes for regions constituting the ESN were defined using neonatal functional parcellations (Shi, 2018). Multivariate modeling (3dMVM) was used to assess between-group connectivity differences at the network level, followed by post hoc tests to identify pairwise connections driving network effects. Analyses were adjusted for age, sex, and scan site (Chen, 2014).
Results:
Our analysis implicated significant differences in connectivity between AMD-exposed and unexposed neonates for the AMG, aINS, and ACC, core nodes of the ESN (χ2 = 8.18, p = 0.004) (Fig. 1.a). These findings align with earlier studies suggesting disrupted FC within the ESN in neonates exposed to antenatal maternal depression (AMD). Specifically, across all 8 sites, decreased FC was identified between the right ACC and right AMG (β = 0.073; p = 0.015), right aINS and right AMG (β = 0.069; p = 0.047), right aINS and left aINS (β = 0.073; p = 0.017), and left aINS and left AMG (β = 0.085; p = 0.005). Analyses of the AMD-exposure-by-site interactions reveal strong effects (χ2 = 5.96, p = 0.015).
Conclusions:
This study represents the first large-scale mega-analysis of functional brain alterations in young infants exposed to AMD, providing compelling evidence of disrupted connectivity within the extended salience network (ESN). The findings highlight AMD-associated perturbations in connectivity of the right AMG with two core regions of the canonical salience network (rINS and ACC). Notably, these regions have been identified as hub nodes in prior literature (Rotem-Kohavi, 2019). This finding provides a critical starting point for understanding the neurodevelopmental consequences of AMD exposure in early life. Future directions include extending the investigation from the ESN to connectivity with prefrontal regions, to capture AMD-associated disruption of top-down emotion regulation pathways, as well as whole brain FC analyses to further elucidate the broader impact of AMD on early brain development.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Emotion, Motivation and Social Neuroscience:
Emotional Perception
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling
Multivariate Approaches 2
Task-Independent and Resting-State Analysis 1
Keywords:
FUNCTIONAL MRI
Multivariate
PEDIATRIC
Psychiatric Disorders
Other - Antenatal Maternal Depression, Mega-analysis, Extended salience network, Harmonization
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
AFNI
FSL
Provide references using APA citation style.
Chen, G. (2014). Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model. NeuroImage, 99, 571–588.
Na, X. (2023). Associations between mother’s depressive symptoms during pregnancy and newborn’s brain functional connectivity. Cerebral Cortex, 33(14), 8980–8989.
Pomponio, R. (2020). Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage, 208.
Posner, J. (2016). Alterations in amygdala-prefrontal circuits in infants exposed to prenatal maternal depression. Translational Psychiatry, 6(11), 935-935.
Qiu, A. (2015). Prenatal maternal depression alters amygdala functional connectivity in 6-month-old infants. Translational Psychiatry, 5(2), e508-e508.
Rifkin-Graboi, A. (2013). Prenatal maternal depression associates with microstructure of right amygdala in neonates at birth. Biological Psychiatry, 74(11), 837–844.
Rotem-Kohavi, N. (2019). Hub distribution of the brain functional networks of newborns prenatally exposed to maternal depression and SSRI antidepressants. Depression and Anxiety, 36(8), 753–765.
Shi, F. (2018). Functional Brain Parcellations of the Infant Brain and the Associated Developmental Trends. Cerebral Cortex (New York, N.Y. : 1991), 28(4), 1358–1368.
No