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    Genetic Influences on Cost-Efficient Organization of Human Cortical Functional Networks
    Fornito, A ; Zalesky, A ; Bassett, DS ; Meunier, D ; Ellison-Wright, I ; Yuecel, M ; Wood, SJ ; Shaw, K ; O'Connor, J ; Nertney, D ; Mowry, BJ ; Pantelis, C ; Bullmore, ET (SOC NEUROSCIENCE, 2011-03-02)
    The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09-0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.
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    Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
    Mullins, N ; Forstner, AJ ; O'Connell, KS ; Coombes, B ; Coleman, JR ; Qiao, Z ; Als, TD ; Bigdeli, TB ; Borte, S ; Bryois, J ; Charney, AW ; Drange, OK ; Gandal, MJ ; Hagenaars, SP ; Ikeda, M ; Kamitaki, N ; Kim, M ; Krebs, K ; Panagiotaropoulou, G ; Schilder, BM ; Sloofman, LG ; Steinberg, S ; Trubetskoy, V ; Winsvold, BS ; Won, H-H ; Abramova, L ; Adorjan, K ; Agerbo, E ; Al Eissa, M ; Albani, D ; Alliey-Rodriguez, N ; Anjorin, A ; Antilla, V ; Antoniou, A ; Awasthi, S ; Baek, JH ; Baekvad-Hansen, M ; Bass, N ; Bauer, M ; Beins, EC ; Bergen, SE ; Birner, A ; Pedersen, CB ; Boen, E ; Boks, MP ; Bosch, R ; Brum, M ; Brumpton, BM ; Brunkhorst-Kanaan, N ; Budde, M ; Bybjerg-Grauholm, J ; Byerley, W ; Cairns, M ; Casas, M ; Cervantes, P ; Clarke, T-K ; Cruceanu, C ; Cuellar-Barboza, A ; Cunningham, J ; Curtis, D ; Czerski, PM ; Dale, AM ; Dalkner, N ; David, FS ; Degenhardt, F ; Djurovic, S ; Dobbyn, AL ; Douzenis, A ; Elvsashagen, T ; Escott-Price, V ; Ferrier, IN ; Fiorentino, A ; Foroud, TM ; Forty, L ; Frank, J ; Frei, O ; Freimer, NB ; Frisen, L ; Gade, K ; Garnham, J ; Gelernter, J ; Pedersen, MG ; Gizer, IR ; Gordon, SD ; Gordon-Smith, K ; Greenwood, TA ; Grove, J ; Guzman-Parra, J ; Ha, K ; Haraldsson, M ; Hautzinger, M ; Heilbronner, U ; Hellgren, D ; Herms, S ; Hoffmann, P ; Holmans, PA ; Huckins, L ; Jamain, S ; Johnson, JS ; Kalman, JL ; Kamatani, Y ; Kennedy, JL ; Kittel-Schneider, S ; Knowles, JA ; Kogevinas, M ; Koromina, M ; Kranz, TM ; Kranzler, HR ; Kubo, M ; Kupka, R ; Kushner, SA ; Lavebratt, C ; Lawrence, J ; Leber, M ; Lee, H-J ; Lee, PH ; Levy, SE ; Lewis, C ; Liao, C ; Lucae, S ; Lundberg, M ; MacIntyre, DJ ; Maier, W ; Maihofer, A ; Malaspina, D ; Maratou, E ; Martinsson, L ; Mattheisen, M ; McCarroll, SA ; McGregor, NW ; McGuffin, P ; McKay, JD ; Medeiros, H ; Medland, SE ; Millischer, V ; Montgomery, GW ; Moran, JL ; Morris, DW ; Muhleisen, TW ; O'Brien, N ; O'Donovan, C ; Loohuis, LMO ; Oruc, L ; Papiol, S ; Pardinas, AF ; Perry, A ; Pfennig, A ; Porichi, E ; Potash, JB ; Quested, D ; Raj, T ; Rapaport, MH ; DePaulo, JR ; Regeer, EJ ; Rice, JP ; Rivas, F ; Rivera, M ; Roth, J ; Roussos, P ; Ruderfer, DM ; Sanchez-Mora, C ; Schulte, EC ; Senner, F ; Sharp, S ; Shilling, PD ; Sigurdsson, E ; Sirignano, L ; Slaney, C ; Smeland, OB ; Sobell, JL ; Hansen, CS ; Artigas, MS ; Spijker, AT ; Stein, DJ ; Strauss, JS ; Swiatkowska, B ; Terao, C ; Thorgeirsson, TE ; Toma, C ; Tooney, P ; Tsermpini, E-E ; Vawter, MP ; Vedder, H ; Walters, JTR ; Witt, SH ; Xi, S ; Xu, W ; Yang, JMK ; Young, AH ; Young, H ; Zandi, PP ; Zhou, H ; Zillich, L ; Adolfsson, R ; Agartz, I ; Alda, M ; Alfredsson, L ; Babadjanova, G ; Backlund, L ; Baune, BT ; Bellivier, F ; Bengesser, S ; Berrettini, WH ; Blackwood, DHR ; Boehnke, M ; Borglum, AD ; Breen, G ; Carr, VJ ; Catts, S ; Corvin, A ; Craddock, N ; Dannlowski, U ; Dikeos, D ; Esko, T ; Etain, B ; Ferentinos, P ; Frye, M ; Fullerton, JM ; Gawlik, M ; Gershon, ES ; Goes, F ; Green, MJ ; Grigoroiu-Serbanescu, M ; Hauser, J ; Henskens, F ; Hillert, J ; Hong, KS ; Hougaard, DM ; Hultman, CM ; Hveem, K ; Iwata, N ; Jablensky, A ; Jones, I ; Jones, LA ; Kahn, RS ; Kelsoe, JR ; Kirov, G ; Landen, M ; Leboyer, M ; Lewis, CM ; Li, QS ; Lissowska, J ; Lochner, C ; Loughland, C ; Martin, NG ; Mathews, CA ; Mayoral, F ; McElroy, SL ; McIntosh, AM ; McMahon, FJ ; Melle, I ; Michie, P ; Milani, L ; Mitchell, PB ; Morken, G ; Mors, O ; Mortensen, PB ; Mowry, B ; Muller-Myhsok, B ; Myers, RM ; Neale, BM ; Nievergelt, CM ; Nordentoft, M ; Nothen, MM ; ODonovan, MC ; Oedegaard, KJ ; Olsson, T ; Owen, MJ ; Paciga, SA ; Pantelis, C ; Pato, C ; Pato, MT ; Patrinos, GP ; Perlis, RH ; Posthuma, D ; Ramos-Quiroga, JA ; Reif, A ; Reininghaus, EZ ; Ribases, M ; Rietschel, M ; Ripke, S ; Rouleau, GA ; Saito, T ; Schall, U ; Schalling, M ; Schofield, PR ; Schulze, TG ; Scott, LJ ; Scott, RJ ; Serretti, A ; Weickert, CS ; Smoller, JW ; Stefansson, H ; Stefansson, K ; Stordal, E ; Streit, F ; Sullivan, PF ; Turecki, G ; Vaaler, AE ; Vieta, E ; Vincent, JB ; Waldman, ID ; Weickert, TW ; Werge, T ; Wray, NR ; Zwart, J ; Biernacka, JM ; Nurnberger, J ; Cichon, S ; Edenberg, HJ ; Stahl, EA ; McQuillin, A ; Di Florio, A ; Ophoff, RA ; Andreassen, OA (NATURE PORTFOLIO, 2021-06)
    Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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    Cortical and Subcortical Neuroanatomical Signatures of Schizotypy in 2,952 Individuals Assessed in a Worldwide ENIGMA Study
    Kirschner, M ; Hodzic-Santor, B ; Antoniades, M ; Nenadic, I ; Kircher, T ; Krug, A ; Fornito, A ; Arnatkeviciute, A ; Dannlowski, U ; DeRosse, P ; Baune, BT ; Green, M ; Quide, Y ; Pantelis, C ; Chan, R ; Ettinger, U ; Debbane, M ; Derome, M ; Gaser, C ; Besteher, B ; Diederen, K ; Spencer, TJ ; Fletcher, P ; Roessler, W ; Kumari, V ; Park, H ; Lemmers-Jansen, I ; Gilleen, J ; Allen, P ; Marsman, J-B ; Lebedeva, I ; Kaiser, S ; Fett, A-K ; Sommer, I ; Lariviere, S ; Bernhardt, BC ; Dagher, A ; van Erp, TGM ; Turner, JA ; Thompson, PM ; Aleman, A (ELSEVIER SCIENCE INC, 2021-05-01)
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    Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach
    Lalousis, PA ; Wood, SJ ; Schmaal, L ; Chisholm, K ; Griffiths, S ; Reniers, R ; Bertolino, A ; Borgwardt, S ; Brambilla, P ; Kambeitz, J ; Lencer, R ; Pantelis, C ; Ruhrmann, S ; Salokangas, RKR ; Schultze-Lutter, F ; Bonivento, C ; Dwyer, DB ; Ferro, A ; Haidl, T ; Rosen, M ; Schmidt, A ; Meisenzahl, E ; Koutsouleris, N ; Upthegrove, R (Elsevier BV, 2021-05)
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    Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis An ENIGMA Working Group Mega-analysis
    Jalbrzikowski, M ; Hayes, RA ; Wood, SJ ; Nordholm, D ; Zhou, JH ; Fusar-Poli, P ; Uhlhaas, PJ ; Takahashi, T ; Sugranyes, G ; Kwak, YB ; Mathalon, DH ; Katagiri, N ; Hooker, CI ; Smigielski, L ; Colibazzi, T ; Via, E ; Tang, J ; Koike, S ; Rasser, PE ; Michel, C ; Lebedeva, I ; Hegelstad, WTV ; de la Fuente-Sandoval, C ; Waltz, JA ; Mizrahi, R ; Corcoran, CM ; Resch, F ; Tamnes, CK ; Haas, SS ; Lemmers-Jansen, ILJ ; Agartz, I ; Allen, P ; Amminger, GP ; Andreassen, OA ; Atkinson, K ; Bachman, P ; Baeza, I ; Baldwin, H ; Bartholomeusz, CF ; Borgwardt, S ; Catalano, S ; Chee, MWL ; Chen, X ; Cho, KIK ; Cooper, RE ; Cropley, VL ; Dolz, M ; Ebdrup, BH ; Fortea, A ; Glenthoj, LB ; Glenthoj, BY ; de Haan, L ; Hamilton, HK ; Harris, MA ; Haut, KM ; He, Y ; Heekeren, K ; Heinz, A ; Hubl, D ; Hwang, WJ ; Kaess, M ; Kasai, K ; Kim, M ; Kindler, J ; Klaunig, MJ ; Koppel, A ; Kristensen, TD ; Kwon, JS ; Lawrie, SM ; Lee, J ; Leon-Ortiz, P ; Lin, A ; Loewy, RL ; Ma, X ; McGorry, P ; McGuire, P ; Mizuno, M ; Moller, P ; Moncada-Habib, T ; Munoz-Samons, D ; Nelson, B ; Nemoto, T ; Nordentoft, M ; Omelchenko, MA ; Oppedal, K ; Ouyang, L ; Pantelis, C ; Pariente, JC ; Raghava, JM ; Reyes-Madrigal, F ; Roach, BJ ; Rossberg, JI ; Rossler, W ; Salisbury, DF ; Sasabayashi, D ; Schall, U ; Schiffman, J ; Schlagenhauf, F ; Schmidt, A ; Sorensen, ME ; Suzuki, M ; Theodoridou, A ; Tomyshev, AS ; Tor, J ; Vaernes, TG ; Velakoulis, D ; Venegoni, GD ; Vinogradov, S ; Wenneberg, C ; Westlye, LT ; Yamasue, H ; Yuan, L ; Yung, AR ; van Amelsvoort, TAMJ ; Turner, JA ; van Erp, TGM ; Thompson, PM ; Hernaus, D (AMER MEDICAL ASSOC, 2021-07)
    IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001). CONCLUSIONS AND RELEVANCE: This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.
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    Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach
    Lalousis, PA ; Wood, SJ ; Schmaal, L ; Chisholm, K ; Griffiths, SL ; Reniers, RLEP ; Bertolino, A ; Borgwardt, S ; Brambilla, P ; Kambeitz, J ; Lencer, R ; Pantelis, C ; Ruhrmann, S ; Salokangas, RKR ; Schultze-Lutter, F ; Bonivento, C ; Dwyer, D ; Ferro, A ; Haidl, T ; Rosen, M ; Schmidt, A ; Meisenzahl, E ; Koutsouleris, N ; Upthegrove, R (OXFORD UNIV PRESS, 2021-07)
    Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.
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    Cognitive functioning throughout adulthood and illness stages in individuals with psychotic disorders and their unaffected siblings
    Velthorst, E ; Mollon, J ; Murray, RM ; de Haan, L ; Germeys, IM ; Glahn, DC ; Arango, C ; van der Ven, E ; Di Forti, M ; Bernardo, M ; Guloksuz, S ; Delespaul, P ; Mezquida, G ; Amoretti, S ; Bobes, J ; Saiz, PA ; Garcia-Portilla, MP ; Santos, JL ; Jimenez-Lopez, E ; Sanjuan, J ; Aguilar, EJ ; Arrojo, M ; Carracedo, A ; Lopez, G ; Gonzalez-Penas, J ; Parellada, M ; Atbasoglu, C ; Saka, MC ; Ucok, A ; Alptekin, K ; Akdede, B ; Binbay, T ; Altinyazar, V ; Ulas, H ; Yalincetin, B ; Gumus-Akay, G ; Beyaz, BC ; Soygur, H ; Cankurtaran, ES ; Kaymak, SU ; Maric, NP ; Mihaljevic, MM ; Petrovic, SA ; Mirjanic, T ; Del-Ben, CM ; Ferraro, L ; Gayer-Anderson, C ; Jones, PB ; Jongsma, HE ; Kirkbride, JB ; La Cascia, C ; Lasalvia, A ; Tosato, S ; Llorca, P-M ; Menezes, PR ; Morgan, C ; Quattrone, D ; Menchetti, M ; Selten, J-P ; Szoke, A ; Tarricone, I ; Tortelli, A ; McGuire, P ; Valmaggia, L ; Kempton, MJ ; van der Gaag, M ; Riecher-Rossler, A ; Bressan, RA ; Barrantes-Vidal, N ; Nelson, B ; McGorry, P ; Pantelis, C ; Krebs, M-O ; Ruhrmann, S ; Sachs, G ; Rutten, BPF ; van Os, J ; Alizadeh, BZ ; van Amelsvoort, T ; Bartels-Velthuis, AA ; Bruggeman, R ; van Beveren, NJ ; Luykx, JJ ; Cahn, W ; Simons, CJP ; Kahn, RS ; Schirmbeck, F ; van Winkel, R ; Reichenberg, A (SPRINGERNATURE, 2021-08)
    Important questions remain about the profile of cognitive impairment in psychotic disorders across adulthood and illness stages. The age-associated profile of familial impairments also remains unclear, as well as the effect of factors, such as symptoms, functioning, and medication. Using cross-sectional data from the EU-GEI and GROUP studies, comprising 8455 participants aged 18 to 65, we examined cognitive functioning across adulthood in patients with psychotic disorders (n = 2883), and their unaffected siblings (n = 2271), compared to controls (n = 3301). An abbreviated WAIS-III measured verbal knowledge, working memory, visuospatial processing, processing speed, and IQ. Patients showed medium to large deficits across all functions (ES range = -0.45 to -0.73, p < 0.001), while siblings showed small deficits on IQ, verbal knowledge, and working memory (ES = -0.14 to -0.33, p < 0.001). Magnitude of impairment was not associated with participant age, such that the size of impairment in older and younger patients did not significantly differ. However, first-episode patients performed worse than prodromal patients (ES range = -0.88 to -0.60, p < 0.001). Adjusting for cannabis use, symptom severity, and global functioning attenuated impairments in siblings, while deficits in patients remained statistically significant, albeit reduced by half (ES range = -0.13 to -0.38, p < 0.01). Antipsychotic medication also accounted for around half of the impairment in patients (ES range = -0.21 to -0.43, p < 0.01). Deficits in verbal knowledge, and working memory may specifically index familial, i.e., shared genetic and/or shared environmental, liability for psychotic disorders. Nevertheless, potentially modifiable illness-related factors account for a significant portion of the cognitive impairment in psychotic disorders.
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    Multimodal prognosis of negative symptom severity in individuals at increased risk of developing psychosis
    Hauke, DJ ; Schmidt, A ; Studerus, E ; Andreou, C ; Riecher-Roessler, A ; Radua, J ; Kambeitz, J ; Ruef, A ; Dwyer, DB ; Kambeitz-Ilankovic, L ; Lichtenstein, T ; Sanfelici, R ; Penzel, N ; Haas, SS ; Antonucci, LA ; Lalousis, PA ; Chisholm, K ; Schultze-Lutter, F ; Ruhrmann, S ; Hietala, J ; Brambilla, P ; Koutsouleris, N ; Meisenzahl, E ; Pantelis, C ; Rosen, M ; Salokangas, RKR ; Upthegrove, R ; Wood, SJ ; Borgwardt, S (SPRINGERNATURE, 2021-05-24)
    Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models' ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40-64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.
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    Cognitive behavioral markers of neurodevelopmental trajectories in rodents
    Choy, KHC ; Luo, JK ; Wannan, CMJ ; Laskaris, L ; Merritt, A ; Syeda, WT ; Sexton, PM ; Christopoulos, A ; Pantelis, C ; Nithianantharajah, J (SPRINGERNATURE, 2021-10-30)
    Between adolescence and adulthood, the brain critically undergoes maturation and refinement of synaptic and neural circuits that shape cognitive processing. Adolescence also represents a vulnerable period for the onset of symptoms in neurodevelopmental psychiatric disorders. Despite the wide use of rodent models to unravel neurobiological mechanisms underlying neurodevelopmental disorders, there is a surprising paucity of rigorous studies focusing on normal cognitive-developmental trajectories in such models. Here, we sought to behaviorally capture maturational changes in cognitive trajectories during adolescence and into adulthood in male and female mice using distinct behavioral paradigms. C57 BL/6J mice (4.5, 6, and 12 weeks of age) were assessed on three behavioral paradigms: drug-induced locomotor hyperactivity, prepulse inhibition, and a novel validated version of a visuospatial paired-associate learning touchscreen task. We show that the normal maturational trajectories of behavioral performance on these paradigms are dissociable. Responses in drug-induced locomotor hyperactivity and prepulse inhibition both displayed a 'U-shaped' developmental trajectory; lower during mid-adolescence relative to early adolescence and adulthood. In contrast, visuospatial learning and memory, memory retention, and response times indicative of motivational processing progressively improved with age. Our study offers a framework to investigate how insults at different developmental stages might perturb normal trajectories in cognitive development. We provide a brain maturational approach to understand resilience factors of brain plasticity in the face of adversity and to examine pharmacological and non-pharmacological interventions directed at ameliorating or rescuing perturbed trajectories in neurodevelopmental and neuropsychiatric disorders.
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    Brain change trajectories that differentiate the major psychoses
    Liberg, B ; Rahm, C ; Panayiotou, A ; Pantelis, C (WILEY, 2016-07)
    BACKGROUND: Bipolar disorder and schizophrenia are highly heritable, often chronic and debilitating psychotic disorders that can be difficult to differentiate clinically. Their brain phenotypes appear to overlap in both cross-sectional and longitudinal structural neuroimaging studies, with some evidence to suggest areas of differentiation with differing trajectories. The aim of this review was to investigate the notion that longitudinal trajectories of alterations in brain structure could differentiate the two disorders. DESIGN: Narrative review. We searched MEDLINE and Web of Science databases in May 2016 for studies that used structural magnetic resonance imaging to investigate longitudinal between-group differences in bipolar disorder and schizophrenia. Ten studies met inclusion criteria, namely longitudinal structural magnetic resonance studies comparing bipolar disorder (or affective psychosis) and schizophrenia within the same study. RESULTS: Our review of these studies implicates illness-specific trajectories of morphological change in total grey matter volume, and in regions of the frontal, temporal and cingulate cortices. The findings in schizophrenia suggest a trajectory involving progressive grey matter loss confined to fronto-temporal cortical regions. Preliminary findings identify a similar but less severely impacted trajectory in a number of regions in bipolar disorder, however, bipolar disorder is also characterized by differential involvement across cingulate subregions. CONCLUSION: The small number of available studies must be interpreted with caution but provide initial evidence supporting the notion that bipolar disorder and schizophrenia have differential longitudinal trajectories that are influenced by brain maturation.