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Using structural-functional brain data fusion to explore adverse childhood experiences related PTSD.

Poster No:

2418 

Submission Type:

Abstract Submission 

Authors:

Richard Nkrumah1, Claudius Claudius von Schröder2, Traute Demirakca3, Lemye Zehirlioglu4, Sabine Vollstaedt-Klein5, Christian Schmahl6, Gabriele Ende7

Institutions:

1Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University, Mannheim, Select a State or Province, 2Department of Psychosomatic Medicine & Psychotherapy,Central Institute for Mental Health, Heidelberg, Mannheim, Baden württemberg, 3Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University, Mannheim, Germany, 4Dept. of Psychosomatic & Psychotherapy, Central Institute for Mental Health, Heidelberg University, Mannheim, Baden württemberg, 5Department of Addictive Behavior and Addiction Medicine, Central Institute for Mental Health, Heidel, Mannheim, Baden württemberg, 6Department of Psychosomatic Medicine & Psychotherapy,Central Institute for Mental Health, Heidelberg, Mannheim, Germany, 7Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University, Mannheim, Baden württemberg

First Author:

Richard Nkrumah  
Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University
Mannheim, Select a State or Province

Co-Author(s):

Claudius Claudius von Schröder  
Department of Psychosomatic Medicine & Psychotherapy,Central Institute for Mental Health, Heidelberg
Mannheim, Baden württemberg
Traute Demirakca  
Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University
Mannheim, Germany
Lemye Zehirlioglu  
Dept. of Psychosomatic & Psychotherapy, Central Institute for Mental Health, Heidelberg University
Mannheim, Baden württemberg
Sabine Vollstaedt-Klein  
Department of Addictive Behavior and Addiction Medicine, Central Institute for Mental Health, Heidel
Mannheim, Baden württemberg
Christian Schmahl  
Department of Psychosomatic Medicine & Psychotherapy,Central Institute for Mental Health, Heidelberg
Mannheim, Germany
Gabriele Ende  
Dept. of Neuroimaging, Central Institute for Mental Health, Heidelberg University
Mannheim, Baden württemberg

Introduction:

Identifying neuroimaging biomarkers associated with ACE-related posttraumatic stress disorder (PTSD) is an active area of psychotraumatology research. Neuroimaging studies have demonstrated widespread abnormalities in brain structure and function in PTSD1. Fusing functional and structural imaging informed sources has also grown in interest based on the recent advances in neuroimaging data acquisition and analysis. Specifically, data-driven joint connectivity matrix independent component analysis of both structural (SC) and functional connectivity (FC) has recently been explored in a healthy subject sample and shows a promising method for connectivity-based multimodal neuroimaging data fusion2. Additionally, most of the previous PTSD studies focused on only one specific modality or not specific trauma-related PTSD, and thus the relationship between these isolated structural and functional alterations in ACE-related PTSD individuals remains poorly understood3. . In this study, we performed joint connectivity matrix independent component analysis, in an ACE-related PTSD sample compared to ACE-exposed control. Based on the extant literature, we hypothesised that differences in fronto-parietal (FP) and salient (SN) networks differences between groups.

Methods:

A total of 119 participants with any form of ACE were included in this study. Participants completed the Childhood Trauma Questionnaire (CTQ), the Structured Clinical Interview for DSM-5 (SCID-II), and the Life Event Checklist (LEC) for PTSD to ascertain the severity of ACE exposure, lifetime PTSD diagnosis, and the presence of other possible events associated with PTSD. PTSD=70, ACE severity (i.e. CTQtotal, PTSD=72.59, noPTSD=51.80), age (PTSD=31.67, noPTSD=29.22), sex (PTSD=64F, noPTSD=37F), and overall trauma load (PTSD=2.33, noPTSD=2.04) were computed. T1-weighted images were acquired, preprocessed, parcellated, and segmented into cortical and subcortical nodes. Diffusion and resting-state fMRI data were also collected and preprocessed, and SC and FC were retrieved using cmp3. The SC measure included individual measures of normalised fibre density and the number of fibres between nodes, while the FC measure included negative and positive correlation measures between nodes. All connectivity matrices were controlled for age, sex, ACE severity and trauma load and then normalised by rescaling the range of the data to a [0, 1] interval. Data-driven PCA/ICA was performed using a joint connectivity matrix that was obtained by fusing individual subjects by SC & FC measures data (Fig.1) using FIT. Finally, a shared mixing matrix between the four connectivity matrices was produced by taking an average of independent components (IC) computed over 10 runs, and a t-test was performed on shared weighted matrix data to identify components that were significantly different between groups. Conversely, the two previously reported brain networks in ACE/PTSD literature were then explored in the components that showed significant results.
Supporting Image: fig1.jpg
 

Results:

After correcting for multiple comparisons using Bonferroni, the joint mixing coefficient matrix for component 9 was significantly different between groups (p < 0.001, Figure 2A). Figure 2B shows the difference in the SC & FC measures between the noPTSD vs PTSD group from component 9. Overall, compared to the no-PTSD group, the PTSD group had reduced SC & FC measures in both SN & FP.
Supporting Image: fig2.jpg
 

Conclusions:

Using a joint connectivity matrix independent component analysis, we identified networks previously reported in literature to be statistically significant between ACE-exposed PTSD compared to ACE-exposed controls. Our findings in the salience network and frontal parietal network, which include regions such as the superior parietal lobe, extend the literature on the effect of PTSD on the brain, especially in regions involved in communication, social behaviour, self-awareness and attentional functioning7,8.

Modeling and Analysis Methods:

Connectivity (eg. functional, effective, structural) 2

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

White Matter Anatomy, Fiber Pathways and Connectivity

Novel Imaging Acquisition Methods:

Multi-Modal Imaging 1

Keywords:

Psychiatric Disorders

1|2Indicates the priority used for review

Provide references using author date format

1. McLaughlin, K. A., Koenen, K. C., Bromet, E. J., Karam, E. G., Liu, H., Petukhova, M., … Kessler, R. C. (2017). Childhood adversities and post-traumatic stress disorder: Evidence for stress sensitisation in the World Mental Health Surveys
2. Wu, L., & Calhoun, V. (2023). Joint connectivity matrix independent component analysis: Auto‐linking of structural and functional connectivities.
3. McLaughlin, K. A., Weissman, D., & Bitrán, D. (2019). Childhood Adversity and Neural Development: A Systematic Review.
4. Tourbier, S., Rue-Queralt, J., Glomb, K., Aleman-Gomez, Y., Mullier, E., Griffa, A., … Hagmann, P. (2022). Connectome Mapper 3: A Flexible and Open-Source Pipeline Software for Multiscale Multimodal Human Connectome Mapping.
5. The FIT Documentation Team (2020). Fusion ICA (FIT). Retrieved from https://trends-public-website-fileshare.s3.amazonaws.com/public_website_files/software/fit/docs/v2.0e_FIT_Manual.pdf
6. Khalilullah, K. M. I., Agcaoglu, O., Sui, J., Adali, T., Duda, M., & Calhoun, V. D. (2023). Multimodal fusion of multiple rest fMRI networks and MRI gray matter via parallel multilink joint ICA reveals highly significant function/structure coupling in Alzheimer’s disease.
7. Nkrumah, R. O., Schröder, C. von, Demirakca, T., Schmahl, C., & Ende, G. (2023). Cortical volume alteration in the superior parietal region mediates the relation between the childhood abuse and PTSD avoidance symptoms: a complementary multimodal neuroimaging study
8. Cardenas, V. A., Samuelson, K., Lenoci, M., Studholme, C., Neylan, T. C., Marmar, C. R., … Weiner, M. W. (2011). Changes in brain anatomy during the course of posttraumatic stress disorder.