Author:
Metzak Paul D.,Shakeel Mohammed K.,Long Xiangyu,Lasby Mike,Souza Roberto,Bray Signe,Goldstein Benjamin I.,MacQueen Glenda,Wang JianLi,Kennedy Sidney H.,Addington Jean,Lebel Catherine
Abstract
Abstract
Background
Identifying early biomarkers of serious mental illness (SMI)—such as changes in brain structure and function—can aid in early diagnosis and treatment. Whole brain structural and functional connectomes were investigated in youth at risk for SMI.
Methods
Participants were classified as healthy controls (HC; n = 33), familial risk for serious mental illness (stage 0; n = 31), mild symptoms (stage 1a; n = 37), attenuated syndromes (stage 1b; n = 61), or discrete disorder (transition; n = 9) based on clinical assessments. Imaging data was collected from two sites. Graph-theory based analysis was performed on the connectivity matrix constructed from whole-brain white matter fibers derived from constrained spherical deconvolution of the diffusion tensor imaging (DTI) scans, and from the correlations between brain regions measured with resting state functional magnetic resonance imaging (fMRI) data.
Results
Linear mixed effects analysis and analysis of covariance revealed no significant differences between groups in global or nodal metrics after correction for multiple comparisons. A follow up machine learning analysis broadly supported the findings. Several non-overlapping frontal and temporal network differences were identified in the structural and functional connectomes before corrections.
Conclusions
Results suggest significant brain connectome changes in youth at transdiagnostic risk may not be evident before illness onset.
Funder
Fondation Brain Canada
Mathison Centre for Mental Health Research and Education
Publisher
Springer Science and Business Media LLC
Subject
Psychiatry and Mental health
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