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A data-driven transdiagnostic analysis of white matter integrity in young adults with major psychiatric disorders
Journal article   Peer reviewed

A data-driven transdiagnostic analysis of white matter integrity in young adults with major psychiatric disorders

Daniel F Hermens, Sean N Hatton, Django White, Rico S C Lee, Adam J Guastella, Elizabeth M Scott, Sharon L Naismith, Ian B Hickie and Jim Lagopoulos
Progress in Neuro-Psychopharmacology and Biological Psychiatry, Vol.89, pp.73-83
2019
DOI: https://doi.org/10.1016/j.pnpbp.2018.08.032
Appears in  Thompson Institute Research Collection
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https://doi.org/10.1016/j.pnpbp.2018.08.032View
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Abstract

anxiety disorders cluster analysis diffusion tensor imaging fractional anisotropy mood disorders psychotic disorders Youth mental health Neuroimaging Thompson Institute Special Collection UniSC Diversity Area - Disability and Inclusion UniSC Diversity Area - Life Stages
Diffusion tensor imaging (DTI) has been utilized to index white matter (WM) integrity in the major psychiatric disorders. However, the findings within and across such disorders have been mixed. Given this, transdiagnostic sampling with data-driven statistical approaches may lead to new and better insights about the clinical and functional factors associated with WM abnormalities. Thus, we undertook a cross-sectional DTI study of 401 young adult (18-30 years old) outpatients with a major psychiatric (depressive, bipolar, psychotic, or anxiety) disorder and 61 healthy controls. Participants also completed self-report questionnaires and underwent neuropsychological assessment. Fractional anisotropy (FA) as well as axial (AD) and radial (RD) diffusivity was determined via a whole brain voxel-wise approach (tract-based spatial statistics). Hierarchical cluster analysis was performed on FA scores in patients only, obtained from 20 major WM tracts (that is, association, projection and commissural fibers). The three cluster groups derived were distinguished by have consistently increased or decreased FA scores across all tracts. Compared to controls, the largest cluster (N = 177) showed significantly increased FA in 55% of tracts, the second cluster (N = 169) demonstrated decreased FA (in 90% of tracts) and the final cluster (N = 55) exhibited the most increased FA (in 95% of tracts). Importantly, the distribution of primary diagnosis did not significantly differ among the three clusters. Furthermore, the clusters showed comparable functional, clinical and neuropsychological measures, with the exception of alcohol use, medication status and verbal fluency. Overall, this study provides evidence that among young adults with a major psychiatric disorder there are subgroups with either abnormally high or low FA and that either pattern is associated with suboptimal functioning. Importantly, these neuroimaging-based subgroups appear despite diagnostic and clinical factors, suggesting differential treatment strategies are warranted.

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