Differential contributions of functional and structural connectivity to chronic stress symptoms
Poster No:
1514
Submission Type:
Abstract Submission
Authors:
David O'Connor1, Charbel Gharios2, Mandy Van Leent1, Helena Chang1, Shady Abohashem2, Michael Osborne2, Cheuk Tang1, Audrey Kaufman1, Philip Robson1, Sarayu Ramachandran1, Claudia Calcagno1, Venkatesh Mani1, Maria Giovanna Trivieri1, Antonia Seligowski2, Sharon Dekel2, Willem Mulder3, James Murrough1, Lisa Shin4, Ahmed Tawakol2, Zahi Fayad1
Institutions:
1Icahn School of Medicine at Mount Sinai, New York, NY, 2Massachusetts General Hospital, Boston, MA, 3Radboud University Medical Center, Nijmegen, Netherlands, 4Tufts University, Boston, MA
First Author:
Co-Author(s):
Introduction:
Chronic stress is a long-standing health concern. Its effects are particularly evident in post-traumatic stress disorder (PTSD). PTSD symptoms include intrusive recollections of traumatic events, hypervigilance, and elevated physiological arousal. Individuals with chronic stress have poorer health outcomes overall. In this study we investigate the effects of chronic stress on the brain using functional and structural MRI connectivity estimates.
Methods:
MR imaging of the brain was performed in 70 participants (19 with PTSD, 35 Trauma-exposed controls without PTSD, and 16 Healthy controls). Task (face-matching, (Hariri et al., 2000; Swartz et al., 2015)) and resting state fMRI (rs-fMRI), diffusion MRI and T1 images were collected. Questionnaire data were collected to assess chronic stress, resilience, anxiety, and trauma, including the Perceived Stress Scale (PSS), Conor Davidson Resilience Scale (CDRISC), State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA), and PTSD checklist for DSM-5 (PCL-5). MR data were preprocessed using Freesurfer, fMRIPrep and QSIPrep (Cieslak et al., 2021; Esteban et al., 2019; Fischl, 2012). Functional (task and rs-fMRI) and structural connectivity matrices were generated using the Shen 368 atlas. The network-based statistic (NBS) was used to identify functional and structural connections which discriminate participants with PTSD and controls (Zalesky et al., 2010). NBS was run for varying t value thresholds from 0.5 up to 4. Functional and structural network mean connectivity, within each of the respective discriminating networks, were then related to questionnaire summary scores using linear regression, with adjustment age and sex. The cross-modality generalization of the connections was also assessed. The functional task connections which successfully discriminated subgroups were applied to the rs-fMRI data, and structural data, and then in each case related to the set of four questionnaires. The structural connections which successfully discriminated subgroups was then applied to each set of functional data and similarly related to the questionnaires.
Results:
A task-based functional network of 92 edges was found at t = 3.5, p = 0.063 (Figure 1, panel A), which discriminated PTSD subjects from controls. A structural network of 238 edges was also found at t = 3, p = 0.078, Figure 1, panel B. For rs- fMRI, no discriminating network was found. The mean connectivity of the task fMRI network and structural network were negatively associated with CDRISC scores, and positively associated with the PSS, PCL, and STICSA. Figure 2 shows a table of beta values and confidence intervals. The brain regions most represented in the task network were the left fusiform gyrus, secondary visual areas, primary motor area, cerebellum, and frontal eye fields. This result likely reflects differences in how the task was processed, with individuals with PTSD documented as having disrupted visual processing (Mueller-Pfeiffer et al., 2013). The brain regions most represented in the structural network were the left and right amygdala, pars orbitalis, insula, and secondary visual area. The amygdala is a classical feature in structural findings in PTSD (Logue et al., 2018). The results of the cross-modality comparisons are also shown in Figure 2, where the structural network could be applied to the task data, and the task network to the rest data, with some success.
·Figure 1
·Figure 2
Conclusions:
We were able to find functional and structural connectivity networks which are sensitive to commonly used scales for assessing resilience, stress, trauma, and anxiety. The results suggests that task fMRI is more salient than rest, as is the structural data. There was some concordance between task and structural data in the features extracted. These results highlight the benefit of multimodal approaches to investigating brain-behavior relationships.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
Keywords:
Data analysis
Psychiatric
Other - PTSD
1|2Indicates the priority used for review
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