Altered Functional Gradient Organization in Adolescents with Symptoms of Depression and Anxiety
Poster No:
2040
Submission Type:
Abstract Submission
Authors:
Clare Shaffer1, Jiahe Zhang1, Keara Greene1, Randy Auerbach2, Diego Pizzagali3,4, Stefan Hofmann5, Anastasia Yendiki3,6, Lisa Feldman-Barrett1,3,6, Susan Whitfield Gabrieli1,7, Yuta Katsumi3,6
Institutions:
1Northeastern University, Boston, MA, 2Columbia University, New York City, NY, 3Harvard Medical School, Boston, MA, 4McLean Hospital, Belmont, MA, 5Philipps-University, Marburg, Hesse, 6Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, 7Massachusetts Institute of Technology, Cambridge, MA
First Author:
Co-Author(s):
Anastasia Yendiki
Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA
Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA
Lisa Feldman-Barrett
Northeastern University|Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA|Boston, MA
Northeastern University|Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA|Boston, MA
Susan Whitfield Gabrieli
Northeastern University|Massachusetts Institute of Technology
Boston, MA|Cambridge, MA
Northeastern University|Massachusetts Institute of Technology
Boston, MA|Cambridge, MA
Yuta Katsumi
Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA
Harvard Medical School|Athinoula A. Martinos Center for Biomedical Imaging
Boston, MA|Boston, MA
Introduction:
Functional gradient mapping represents high dimensional brain features in a lower dimensional space and has been leveraged in exploring brain-behavior relationships in clinical samples. Despite this progress, recent studies characterizing alterations in major functional connectivity gradients in mood disorder patients are primarily based on adults. Here, we addressed this gap in the literature by investigating the functional architecture of the cerebral cortex in a sample of adolescents with mood disorders, with a hypothesis that the severity of depression and anxiety symptoms would be associated with alterations in functional connectivity gradient organization.
Methods:
Two hundred and four participants aged 14-17 years old (134 female) completed a resting state functional MRI (fMRI) scan and mood symptom questionnaires. Of the 204 participants, 141 presented with an active mood disorder diagnosis, whereas 63 were healthy controls. Symptom severity was assessed using the Revised Child Anxiety and Depression Scale (RCADS). fMRI data were preprocessed and denoised in the CONN toolbox. We used diffusion map embedding to derive cortical gradients of intrinsic functional connectivity, representing a set of dimensions along which the similarity of connectivity profiles is organized. We focused on the three most dominant gradients of intrinsic functional connectivity (Figure 1A). Relationships between individual-level vertex-wise gradient values and RCADS scores were assessed using multiple linear regression controlling for participant age, sex, and head motion (Figure 1B). We then performed a series of post-hoc seed-based connectivity-behavior analyses using the resulting significant clusters from each gradient as seeds (Figure 1C). Statistical significance of all analyses was assessed using FSL PALM.
Results:
Higher RCADS scores were associated with more positive Gradient 1 values in cortical areas that are part of the somatomotor network (r = .26, p < .001), suggesting a compression of this gradient from its somatomotor end linked to more severe symptoms. Our post-hoc analysis using seed-based connectivity (SBC) revealed that this compression was driven by stronger connectivity between the somatomotor seed and association networks related to more severe symptoms. Higher RCADS scores were also associated with more positive Gradient 2 values in the visual network (r = .27, p <.001), suggesting an expansion of the gradient from the visual network end. This was further supported by our SBC results showing weaker connectivity between a visual network seed and clusters in the somatomotor network related to more severe symptoms, which anchors this gradient at the opposite end. Higher RCADS scores were also associated with more negative Gradient 2 values from several regions in the salience network (e.g., insula, mid-cingulate cortex) (r = -.32, p < .001), suggesting reorganization of its connectivity along this gradient. Our SBC analysis identified a salience network seed exhibiting stronger connectivity with the somatomotor network linked to more severe symptoms, suggesting greater affiliation with the somatomotor end of this gradient. Finally, higher RCADS scores were correlated with more negative Gradient 3 values in the default mode and somatomotor networks (r = -.30, p < .001), consistent with a compression of this gradient from this end. Our SBC results supported this interpretation, revealing stronger connectivity between a default mode network seed (anterior temporal lobe) and the attentional networks linked to more severe symptoms.
Conclusions:
These findings identify the robust cross-sectional associations between intrinsic functional connectivity gradients and the severity of depression and anxiety symptoms in a clinical adolescent sample. These results may point to the role of functional connectivity gradients as a useful imaging biomarker for disorder prognostication and outcome monitoring in this population.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Task-Independent and Resting-State Analysis 1
Keywords:
Affective Disorders
FUNCTIONAL MRI
Psychiatric Disorders
Other - Functional gradients; Adolescents; Depression
1|2Indicates the priority used for review
Provide references using author date format
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