Early Life Adversity and Deviations in Normative Brain Structure: An ENIGMA Mega-Analysis
Poster No:
1865
Submission Type:
Abstract Submission
Authors:
Haley Wang1, Zhen-Qi Liu2, Lauren Salminen3, Laura Han4, Elena Pozzi5, Priyanka Sigar1, ENIGMA MDD Working Group6, ENIGMA PTSD Working Group6, Sophia Frangou7, Paul Thompson3, Rajendra Morey8, Jennifer Stevens9, Lianne Schmaal5, Tiffany Ho1
Institutions:
1University of California, Los Angeles, Los Angeles, CA, 2Montreal Neurological Institute, Montreal, Quebec, 3University of Southern California, Los Angeles, CA, 4Amsterdam UMC, Amsterdam, Noord-Holland, 5The University of Melbourne, Parkville, Victoria, 6USC, Los Angeles, CA, 7Icahn School of Medicine at Mount Sinai, New York, NY, 8Duke University, Durham, NC, 9Emory University, Atlanta, GA
First Author:
Co-Author(s):
Introduction:
Early life adversity (ELA), encompassing abuse and neglect, affects more than two-thirds of the general population and substantially increases risk for stress-related psychopathology, including major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). While neuroanatomical abnormalities are frequently observed in both MDD and PTSD, the extent to which these alterations are attributable to ELA exposure remains uncertain.
Methods:
We analyzed ELA and structural MRI data from 3,711 participants (1,389 patients [872 MDD, 517 PTSD] and 2,322 healthy controls) across 25 international cohorts from the ENIGMA MDD and PTSD Working Groups (mean age 33±12.98 years; 59.82% female). Using the Childhood Trauma Questionnaire, we calculated separate composite scores for abuse (emotional, physical, and sexual) and neglect (emotional and physical) subscales. Leveraging normative modeling based on an independent reference population of 37,407 healthy individuals, we quantified deviation scores in subcortical volumes, cortical thickness, and surface area, evaluating transdiagnostic associations between ELA and brain deviation scores separately within each sex across three age groups: pediatric (≤18 years), young adult (>18 and <35 years), and older adult (≥35 years).
Results:
We observed heterogeneous effects of ELA on brain deviation scores that varied by exposure type, age, and sex, with the strongest effects emerging in young adult females. In this group, childhood abuse was associated with widespread alterations in volumes of the hippocampus and pallidum and cortical thickness of medial temporal and frontal regions (|r|=.12-.18, q<.01), while childhood neglect was associated with larger surface area of frontal and temporal pole regions (r=.19-.21, q<.01). Notably, no significant associations were observed in the pediatric cohort, and effects were most pronounced in association cortices showing protracted developmental trajectories. These patterns remained robust after controlling for diagnosis, site effects, and clinical variables.
·Surface area results (Fig 3) not included due to figure number limitation of the abstract.
Conclusions:
Our findings support incubation models of ELA, suggesting that the neurobiological consequences of early adversity may not manifest immediately but rather emerge more prominently during young adulthood, particularly in females. This work highlights the importance of considering age- and sex-specific effects when studying the impact of early adversity on brain development and emphasizes the potential value of targeted interventions during young adulthood, especially for females with histories of childhood trauma.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism)
Lifespan Development:
Early life, Adolescence, Aging 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Subcortical Structures
Novel Imaging Acquisition Methods:
Anatomical MRI 1
Keywords:
Affective Disorders
Development
Morphometrics
MRI
Psychiatric Disorders
STRUCTURAL MRI
Trauma
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.
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.
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.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
2. Gee, D. G., & Cohodes, E. M. (2023). Leveraging the developmental neuroscience of caregiving to promote resilience among youth exposed to adversity. Development and Psychopathology, 1–18. https://doi.org/10.1017/S0954579423001128
3. Colich, N. L., Rosen, M. L., Williams, E. S., & McLaughlin, K. A. (2020). Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis. Psychological Bulletin, 146(9), 721–764. https://doi.org/10.1037/bul0000270
4. Smith, K. E., & Pollak, S. D. (2021). Rethinking Concepts and Categories for Understanding the Neurodevelopmental Effects of Childhood Adversity. Perspectives on Psychological Science: A Journal of the Association for Psychological Science, 16(1), 67–93. https://doi.org/10.1177/1745691620920725
5. Holz, N. E., Zabihi, M., Kia, S. M., Monninger, M., Aggensteiner, P.-M., Siehl, S., Floris, D. L., Bokde, A. L. W., Desrivières, S., Flor, H., Grigis, A., Garavan, H., Gowland, P., Heinz, A., Brühl, R., Martinot, J.-L., Martinot, M.-L. P., Orfanos, D. P., Paus, T., … Marquand, A. F. (2023). A stable and replicable neural signature of lifespan adversity in the adult brain. Nature Neuroscience, 26(9), 1603–1612. https://doi.org/10.1038/s41593-023-01410-8
6. Pomponio, R., Erus, G., Habes, M., Doshi, J., Srinivasan, D., Mamourian, E., Bashyam, V., Nasrallah, I. M., Satterthwaite, T. D., Fan, Y., Launer, L. J., Masters, C. L., Maruff, P., Zhuo, C., Völzke, H., Johnson, S. C., Fripp, J., Koutsouleris, N., Wolf, D. H., … Davatzikos, C. (2020). Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage, 208, 116450. https://doi.org/10.1016/j.neuroimage.2019.116
7. Ge, R., Yu, Y., Qi, Y. X., Fan, Y.-N., Chen, S., Gao, C., Haas, S. S., New, F., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Buckner, R., Caseras, X., Crivello, F., Crone, E. A., Erk, S., Fisher, S. E., Franke, B., Glahn, D. C., … ENIGMA Lifespan Working Group. (2024). Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation. The Lancet. Digital Health, 6(3), e211–e221. https://doi.org/10.1016/S2589-7500(23)0025