Identifying Connectome-based Neuroimaging Biomarkers Associated with Behavioral Changes in An Animal Model of Depression: An Exploratory Analysis — The Association Specialists
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Identifying Connectome-based Neuroimaging Biomarkers Associated with Behavioral Changes in An Animal Model of Depression: An Exploratory Analysis (21471)

Twain Dai 1 2 , Shannon Algar 3 , Michael Small 3 , Jennifer Rodger 1 2
  1. School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
  2. Perron Institute for Neurological and Translational Science, Perth, WA, Australia
  3. The Complex Systems Group, Department of Mathematics and Statistics, The University of Western Australia, Crawley, WA, Australia

Background: Traditional analyses to identify resting-state functional MRI (rs-fMRI) biomarkers for depression have relied on uncovering group-level patterns in cross-sectional data. This approach fails to adequately capture individual behavioral and neurobiological variability in core symptoms (anxiety and psychomotor disturbance). Therefore, the present study aimed to identify rs-fMRI biomarkers associated with the development of anxiety-related behaviors and locomotion disturbance following chronic restraint stress (CRS) at an individual level in rats.

Methods: 96 male Sprague Dawley rats underwent two sessions of MRI and behavioral tests, before and after CRS. Behaviors were assessed with elevated plus maze and forced swimming test. Hierarchical clustering was applied to construct functional clusters of the brain. Ridge-regularized partial correlation was used to compute connectivity between each pair of functional clusters. Regression was employed to identify rs-fMRI biomarkers associated with behavioral changes following CRS.

Results: Following CRS, alteration of functional connectivity between the salience-orbitofrontal and lateral-temporal cortical cluster was associated with anxiety-related behaviors. Connectivity changes in the hippocampal-cortical and default mode-somatomotor clusters with the lateral-temporal cortical cluster were associated with locomotor disturbance. High individual variability was presented in these functional alterations. 

Conclusions: The present study is the first to identify connectome-based biomarkers in the brain associated with anxiety and psychomotor disturbance using an animal model of depression. It provides another piece of evidence supporting the idea that biomarker research would benefit from shifting the focus from group to individual level. Our results shed light on biomarkers to aid diagnosis and treatment of depression in humans.