Psychiatry - Research Publications

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    White matter pathology in schizophrenia
    Di Biase, MA ; Pantelis, C ; Zalesky, A ; Kubicki, M ; Shenton, ME (Springer Nature, 2020-01-01)
    Significant effort has been devoted to characterizing white matter pathology in patients with schizophrenia and its impact on brain connectivity (Samartzis et al., J Neuroimaging 24(2):101-10, 2014; Fusar-Poli et al., Neurosci Biobehav Rev 37(8):1680-91, 2013; Bora et al., Schizophr Res 127(1):46-57, 2011). This is particularly important in light of the disconnection hypothesis-a key etiological theory of schizophrenia suggesting that symptoms arise from a failure of integration between distinct brain regions (Friston, Schizophr Res 30(2):115-25, 1998). In this chapter, we focus on neuroimaging evidence demonstrating structural white matter alterations in schizophrenia. Key questions addressed include: what methods are sensitive to the pathophysiology of schizophrenia? What is the evidence that white matter pathology emerges prior to or near to the onset of psychosis? Is the trajectory of white matter pathology stable or, alternatively, a dynamic process, with progressive changes evident over the course of illness? What are the limitations of these studies? How does neuroimaging evidence relate to micro- and meso-structural white matter findings?.
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    Imaging of neuroinflammation in adult Niemann-Pick type C disease: a cross-sectional study
    Walterfang, M ; Di Biase, MA ; Cropley, VL ; Scott, AM ; O'Keefe, G ; Velakoulis, D ; Pathmaraj, K ; Ackermann, U ; Pantelis, C (American Academy of Neurology, 2020-04-21)
    Objective: To test the hypothesis that neuroinflammation is a key process in adult Niemann-Pick type C (NPC) disease, we undertook PET scanning utilizing a ligand binding activated microglia on 9 patients and 9 age- and sex-matched controls. Method: We scanned all participants with the PET radioligand 11C-(R)-PK-11195 and undertook structural MRI to measure gray matter volume and white matter fractional anisotropy (FA). Results: We found increased binding of 11C-(R)-PK-11195 in total white matter compared to controls (p < 0.01), but not in gray matter regions, and this did not correlate with illness severity or duration. Gray matter was reduced in the thalamus (p < 0.0001) in patients, who also showed widespread reductions in FA across the brain compared to controls (p < 0.001). A significant correlation between 11C-(R)-PK11195 binding and FA was shown (p = 0.002), driven by the NPC patient group. Conclusions: Our findings suggest that neuroinflammation—particularly in white matter—may underpin some structural and degenerative changes in patients with NPC.
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    Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort
    Lv, J ; Di Biase, M ; Cash, RFH ; Cocchi, L ; Cropley, VL ; Klauser, P ; Tian, Y ; Bayer, J ; Schmaal, L ; Cetin-Karayumak, S ; Rathi, Y ; Pasternak, O ; Bousman, C ; Pantelis, C ; Calamante, F ; Zalesky, A (SPRINGERNATURE, 2020-09-22)
    The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = -0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.