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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Cross-diagnostic genetic organization of clinical readouts corresponds to distributed cortical profiles
Han Gao1, Hui Xun1, Jing Zhang1
1Department of Cell Biology and Molecular Medicine, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, 561113, China.
Abstract:
Psychiatric disorders share common-variant liability, and the Psychiatric Genomics Consortium has identified five correlated cross-disorder genetic dimensions derived from diagnoses. Whether these dimensions also organize heterogeneous clinical observations and their cortical associations remains unclear. We used F1-F5, together with hierarchical p, as external coordinates for 37 genetically informative clinical readouts and integrated them with structural-imaging GWAS. Thirty-one readouts showed multidimensional profiles, although Internalizing was strongest for most. Racing thoughts illustrated this organization, spanning four dimensions and showing, in a separate imaging analysis, a bounded association with right frontal-pole gray-matter volume. Broad psychopathology, several clinical readouts, and distributed cortical regions converged on a common pattern: inverse associations with cortical surface area. Beyond individual regions, readouts with more similar five-coordinate profiles also had more similarly shaped cortical association maps across 34 regions. We then asked whether coordinate-based projections could recover the collective cortical organization without using the observed readout-cortex cells in their construction. They recovered part of this organization and preserved part of its pairwise geometry. Hierarchical p also corresponded with parts of these fields. Together, these findings suggest that diagnosis-derived genetic structure provides a bridge between heterogeneous clinical readouts and distributed cortical morphology, without reducing either to single diagnoses or single brain regions.
