Psychiatry - Research Publications

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    Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness
    Wannan, CMJ ; Bartholomeusz, CF ; Pantelis, C ; Di Biase, MA ; Syeda, WT ; Chakravarty, MM ; Bousman, CA ; Everall, IP ; McGorry, PD ; Zalesky, A ; Cropley, VL (SPRINGER HEIDELBERG, 2022-09-01)
    Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.
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    Brain charts for the human lifespan (vol 604, pg 525, 2022)
    Bethlehem, RAI ; Seidlitz, J ; White, SR ; Vogel, JW ; Anderson, KM ; Adamson, C ; Adler, S ; Alexopoulos, GS ; Anagnostou, E ; Areces-Gonzalez, A ; Astle, DE ; Auyeung, B ; Ayub, M ; Bae, J ; Ball, G ; Baron-Cohen, S ; Beare, R ; Bedford, SA ; Benegal, V ; Beyer, F ; Blangero, J ; Blesa Cabez, M ; Boardman, JP ; Borzage, M ; Bosch-Bayard, JF ; Bourke, N ; Calhoun, VD ; Chakravarty, MM ; Chen, C ; Chertavian, C ; Chetelat, G ; Chong, YS ; Cole, JH ; Corvin, A ; Costantino, M ; Courchesne, E ; Crivello, F ; Cropley, VL ; Crosbie, J ; Crossley, N ; Delarue, M ; Delorme, R ; Desrivieres, S ; Devenyi, GA ; Di Biase, MA ; Dolan, R ; Donald, KA ; Donohoe, G ; Dunlop, K ; Edwards, AD ; Elison, JT ; Ellis, CT ; Elman, JA ; Eyler, L ; Fair, DA ; Feczko, E ; Fletcher, PC ; Fonagy, P ; Franz, CE ; Galan-Garcia, L ; Gholipour, A ; Giedd, J ; Gilmore, JH ; Glahn, DC ; Goodyer, IM ; Grant, PE ; Groenewold, NA ; Gunning, FM ; Gur, RE ; Gur, RC ; Hammill, CF ; Hansson, O ; Hedden, T ; Heinz, A ; Henson, RN ; Heuer, K ; Hoare, J ; Holla, B ; Holmes, AJ ; Holt, R ; Huang, H ; Im, K ; Ipser, J ; Jack, CR ; Jackowski, AP ; Jia, T ; Johnson, KA ; Jones, PB ; Jones, DT ; Kahn, RS ; Karlsson, H ; Karlsson, L ; Kawashima, R ; Kelley, EA ; Kern, S ; Kim, KW ; Kitzbichler, MG ; Kremen, WS ; Lalonde, F ; Landeau, B ; Lee, S ; Lerch, J ; Lewis, JD ; Li, J ; Liao, W ; Liston, C ; Lombardo, MV ; Lv, J ; Lynch, C ; Mallard, TT ; Marcelis, M ; Markello, RD ; Mathias, SR ; Mazoyer, B ; McGuire, P ; Meaney, MJ ; Mechelli, A ; Medic, N ; Misic, B ; Morgan, SE ; Mothersill, D ; Nigg, J ; Ong, MQW ; Ortinau, C ; Ossenkoppele, R ; Ouyang, M ; Palaniyappan, L ; Paly, L ; Pan, PM ; Pantelis, C ; Park, MM ; Paus, T ; Pausova, Z ; Paz-Linares, D ; Pichet Binette, A ; Pierce, K ; Qian, X ; Qiu, J ; Qiu, A ; Raznahan, A ; Rittman, T ; Rodrigue, A ; Rollins, CK ; Romero-Garcia, R ; Ronan, L ; Rosenberg, MD ; Rowitch, DH ; Salum, GA ; Satterthwaite, TD ; Schaare, HL ; Schachar, RJ ; Schultz, AP ; Schumann, G ; Scholl, M ; Sharp, D ; Shinohara, RT ; Skoog, I ; Smyser, CD ; Sperling, RA ; Stein, DJ ; Stolicyn, A ; Suckling, J ; Sullivan, G ; Taki, Y ; Thyreau, B ; Toro, R ; Traut, N ; Tsvetanov, KA ; Turk-Browne, NB ; Tuulari, JJ ; Tzourio, C ; Vachon-Presseau, E ; Valdes-Sosa, MJ ; Valdes-Sosa, PA ; Valk, SL ; van Amelsvoort, T ; Vandekar, SN ; Vasung, L ; Victoria, LW ; Villeneuve, S ; Villringer, A ; Vertes, PE ; Wagstyl, K ; Wang, YS ; Warfield, SK ; Warrier, V ; Westman, E ; Westwater, ML ; Whalley, HC ; Witte, AV ; Yang, N ; Yeo, B ; Yun, H ; Zalesky, A ; Zar, HJ ; Zettergren, A ; Zhou, JH ; Ziauddeen, H ; Zugman, A ; Zuo, XN ; Bullmore, ET ; Alexander-Bloch, AF (NATURE PORTFOLIO, 2022-10-13)
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    Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia
    Di Biase, MA ; Geaghan, MP ; Reay, WR ; Seidlitz, J ; Weickert, CS ; Pebay, A ; Green, MJ ; Quide, Y ; Atkins, JR ; Coleman, MJ ; Bouix, S ; Knyazhanskaya, EE ; Lyall, AE ; Pasternak, O ; Kubicki, M ; Rathi, Y ; Visco, A ; Gaunnac, M ; Lv, J ; Mesholam-Gately, R ; Lewandowski, KE ; Holt, DJ ; Keshavan, MS ; Pantelis, C ; Ongur, D ; Breier, A ; Cairns, MJ ; Shenton, ME ; Zalesky, A (SPRINGERNATURE, 2022-04)
    Brain morphology differs markedly between individuals with schizophrenia, but the cellular and genetic basis of this heterogeneity is poorly understood. Here, we sought to determine whether cortical thickness (CTh) heterogeneity in schizophrenia relates to interregional variation in distinct neural cell types, as inferred from established gene expression data and person-specific genomic variation. This study comprised 1849 participants in total, including a discovery (140 cases and 1267 controls) and a validation cohort (335 cases and 185 controls). To characterize CTh heterogeneity, normative ranges were established for 34 cortical regions and the extent of deviation from these ranges was measured for each individual with schizophrenia. CTh deviations were explained by interregional gene expression levels of five out of seven neural cell types examined: (1) astrocytes; (2) endothelial cells; (3) oligodendrocyte progenitor cells (OPCs); (4) excitatory neurons; and (5) inhibitory neurons. Regional alignment between CTh alterations with cell type transcriptional maps distinguished broad patient subtypes, which were validated against genomic data drawn from the same individuals. In a predominantly neuronal/endothelial subtype (22% of patients), CTh deviations covaried with polygenic risk for schizophrenia (sczPRS) calculated specifically from genes marking neuronal and endothelial cells (r = -0.40, p = 0.010). Whereas, in a predominantly glia/OPC subtype (43% of patients), CTh deviations covaried with sczPRS calculated from glia and OPC-linked genes (r = -0.30, p = 0.028). This multi-scale analysis of genomic, transcriptomic, and brain phenotypic data may indicate that CTh heterogeneity in schizophrenia relates to inter-individual variation in cell-type specific functions. Decomposing heterogeneity in relation to cortical cell types enables prioritization of schizophrenia subsets for future disease modeling efforts.
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    Large-Scale Evidence for an Association Between Peripheral Inflammation and White Matter Free Water in Schizophrenia and Healthy Individuals
    Di Biase, MA ; Zalesky, A ; Cetin-Karayumak, S ; Rathi, Y ; Lv, J ; Boerrigter, D ; North, H ; Tooney, P ; Pantelis, C ; Pasternak, O ; Shannon Weickert, C ; Cropley, VL (Oxford University Press (OUP), 2021-03-01)
    INTRODUCTION: Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aimed to establish a link between peripheral markers of inflammation and FW in brain white matter. METHODS: All data were obtained from the Australian Schizophrenia Research Bank (ASRB) across 5 Australian states and territories. We first tested for the presence of peripheral cytokine deregulation in schizophrenia, using a large sample (N = 1143) comprising the ASRB. We next determined the extent to which individual variation in 8 circulating pro-/anti-inflammatory cytokines related to FW in brain white matter, imaged in a subset (n = 308) of patients and controls. RESULTS: Patients with schizophrenia showed reduced interleukin-2 (IL-2) (t = -3.56, P = .0004) and IL-12(p70) (t = -2.84, P = .005) and increased IL-6 (t = 3.56, P = .0004), IL-8 (t = 3.8, P = .0002), and TNFα (t = 4.30, P < .0001). Higher proinflammatory signaling of IL-6 (t = 3.4, P = .0007) and TNFα (t = 2.7, P = .0007) was associated with higher FW levels in white matter. The reciprocal increases in serum cytokines and FW were spatially widespread in patients encompassing most major fibers; conversely, in controls, the relationship was confined to the anterior corpus callosum and thalamic radiations. No relationships were observed with alternative dMRI measures, including the fractional anisotropy and tissue-related FA. CONCLUSIONS: We report widespread deregulation of cytokines in schizophrenia and identify inflammation as a putative mechanism underlying increases in brain FW levels.
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    Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure
    Ye, H ; Zalesky, A ; Lv, J ; Loi, SM ; Cetin-Karayumak, S ; Rathi, Y ; Tian, Y ; Pantelis, C ; Di Biase, MA (Oxford University Press (OUP), 2021-03-08)
    INTRODUCTION: Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. METHODS: A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. RESULTS: Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). CONCLUSION: Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.
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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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    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, 2021-07)
    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.