Centre for Youth Mental Health - Research Publications

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    Preventive interventions for individuals at ultra high risk for psychosis: An updated and extended meta-analysis
    Mei, C ; van der Gaag, M ; Nelson, B ; Smit, F ; Yuen, HP ; Berger, M ; Krcmar, M ; French, P ; Amminger, GP ; Bechdolf, A ; Cuijpers, P ; Yung, AR ; McGorry, PD (PERGAMON-ELSEVIER SCIENCE LTD, 2021-06)
    Intervention at the earliest illness stage, in ultra or clinical high-risk individuals, or indicated prevention, currently represents the most promising strategy to ameliorate, delay or prevent psychosis. We review the current state of evidence and conduct a broad-spectrum meta-analysis of various outcomes: transition to psychosis, attenuated positive and negative psychotic symptoms, mania, depression, anxiety, general psychopathology, symptom-related distress, functioning, quality of life, and treatment acceptability. 26 randomized controlled trials were included. Meta-analytically pooled interventions reduced transition rate (risk ratio [RR] = 0.57, 95%CI 0.41-0.81) and attenuated positive psychotic symptoms at 12-months (standardized mean difference = -0.15, 95%CI = -0.28--0.01). When stratified by intervention type (pharmacological, psychological), only the pooled effect of psychological interventions on transition rate was significant. Cognitive behavioral therapy (CBT) was associated with a reduction in incidence at 12-months (RR = 0.52, 95%CI = 0.33-0.82) and 18-48-months (RR = 0.60, 95%CI = 0.42-0.84), but not 6-months. Findings at 12-months and 18-48-months were robust in sensitivity and subgroup analyses. All other outcomes were non-significant. To date, effects of trialed treatments are specific to transition and, a lesser extent, attenuated positive symptoms, highlighting the future need to target other symptom domains and functional outcomes. Sound evidence supports CBT in reducing transition and the value of intervening at this illness stage. STUDY REGISTRATION: Research Registry ID: reviewregistry907.
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    The association between migrant status and transition in an ultra-high risk for psychosis population
    O'Donoghue, B ; Geros, H ; Sizer, H ; Addington, J ; Amminger, GP ; Beaden, CE ; Cadenhead, KS ; Cannon, TD ; Cornblatt, BA ; Berger, GE ; Chen, EYH ; de Haan, L ; Hartmann, JA ; Hickie, IB ; Ising, HK ; Lavoie, S ; Lin, A ; Markulev, C ; Mathalon, DH ; McGlashan, TH ; Mifsud, NG ; Mossaheb, N ; Nieman, DH ; Nordentoft, M ; Perkins, DO ; Riecher-Roessler, A ; Schaefer, MR ; Schloegelhofer, M ; Seidman, LJ ; Smesny, S ; Thompson, A ; Tsuang, MT ; van der Gaag, M ; Verma, S ; Walker, EF ; Wood, SJ ; Woods, SW ; Yuen, HP ; Yung, AR ; McGorry, PD ; Nelson, B (SPRINGER HEIDELBERG, 2021-06)
    PURPOSE: Migrant status is one of the most replicated and robust risk factors for developing a psychotic disorder. This study aimed to determine whether migrant status in people identified as Ultra-High Risk for Psychosis (UHR) was associated with risk of transitioning to a full-threshold psychotic disorder. METHODS: Hazard ratios for the risk of transition were calculated from five large UHR cohorts (n = 2166) and were used to conduct a meta-analysis using the generic inverse-variance method using a random-effects model. RESULTS: 2166 UHR young people, with a mean age of 19.1 years (SD ± 4.5) were included, of whom 221 (10.7%) were first-generation migrants. A total of 357 young people transitioned to psychosis over a median follow-up time of 417 days (I.Q.R.147-756 days), representing 17.0% of the cohort. The risk of transition to a full-threshold disorder was not increased for first-generation migrants, (HR = 1.08, 95% CI 0.62-1.89); however, there was a high level of heterogeneity between studies The hazard ratio for second-generation migrants to transition to a full-threshold psychotic disorder compared to the remainder of the native-born population was 1.03 (95% CI 0.70-1.51). CONCLUSIONS: This meta-analysis did not find a statistically significant association between migrant status and an increased risk for transition to a full-threshold psychotic disorder; however, several methodological issues could explain this finding. Further research should focus on examining the risk of specific migrant groups and also ensuring that migrant populations are adequately represented within UHR clinics.
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    Greater preference for eveningness is associated with negative symptoms in an ultra-high risk for psychosis sample
    Shetty, JJ ; Nicholas, C ; Nelson, B ; McGorry, PD ; Lavoie, S ; Markulev, C ; Schafer, MR ; Thompson, A ; Yuen, HP ; Yung, AR ; Nieman, DH ; de Haan, L ; Amminger, GP ; Hartmann, JA (WILEY, 2021-12)
    AIM: Investigating biological processes in at-risk individuals may help elucidate the aetiological mechanisms underlying psychosis development, refine prediction models and improve intervention strategies. This study examined the associations between sleep disturbances, chronotype, depressive and psychotic symptoms in individuals at ultra-high risk for psychosis. METHODS: A sample of 81 ultra-high risk patients completed clinical interviews and self-report assessments of chronotype and sleep during the Neurapro clinical trial. Mixed regression was used to investigate the cross-sectional associations between symptoms and sleep disturbances/chronotype. RESULTS: Sleep disturbances were significantly associated with increased depressive and attenuated positive psychotic symptoms. Greater preference for eveningness was significantly associated with increased negative symptoms, but not with depressive or attenuated positive psychotic symptoms. CONCLUSION: Sleep disturbances and chronotype may impact the emerging psychopathology experienced by ultra-high risk individuals. Further, the preliminary relationship observed between greater preference for eveningness and negative symptoms offers a unique opportunity to treat negative symptoms through chronobiological approaches.
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    Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing
    Sandini, C ; Zoller, D ; Schneider, M ; Tarun, A ; Armondo, M ; Nelson, B ; Amminger, PG ; Yuen, HP ; Markulev, C ; Schaffer, MR ; Mossaheb, N ; Schlogelhofer, M ; Smesny, S ; Hickie, IB ; Berger, GE ; Chen, EYH ; de Haan, L ; Nieman, DH ; Nordentoft, M ; Riecher-Rossler, A ; Verma, S ; Thompson, A ; Yung, AR ; McGorry, PD ; Van De Ville, D ; Eliez, S (eLIFE SCIENCES PUBL LTD, 2021-09-27)
    Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could significantly hinder our understanding of clinical pathways connecting individual symptoms. Network analysis techniques have emerged as alternative approaches that could help shed light on the complex dynamics of early psychopathology. The present study attempts to address the two main limitations that have in our opinion hindered the application of network approaches in the clinical setting. Firstly, we show that a multi-layer network analysis approach, can move beyond a static view of psychopathology, by providing an intuitive characterization of the role of specific symptoms in contributing to clinical trajectories over time. Secondly, we show that a Graph-Signal-Processing approach, can exploit knowledge of longitudinal interactions between symptoms, to predict clinical trajectories at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis. Novel network approaches can allow to embrace the dynamic complexity of early psychopathology and help pave the way towards a more a personalized approach to clinical care.
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    Characterization and Prediction of Clinical Pathways of Vulnerability to Psychosis through Graph Signal Processing
    Sandini, C ; Zöller, D ; Schneider, M ; Tarun, A ; Armando, M ; Nelson, B ; Nelson, B ; Mallawaarachchi, SR ; Amminger, P ; Farhall, J ; Bolt, L ; Yuen, HP ; Markulev, C ; Schäfer, M ; Mossaheb, N ; Schlögelhofer, M ; Smesny, S ; Hickie, I ; Berger, GE ; Chen, EYH ; de Haan, L ; Nieman, D ; Nordentoft, M ; Riecher-Rössler, A ; Verma, S ; Thompson, A ; Yung, AR ; Allott, K ; McGorry, P ; Van De Ville, D ; Eliez, S ( 2020)
    There is a growing recognition that psychiatric symptoms have the potential to causally interact with one another. Particularly in the earliest stages of psychopathology dynamic interactions between symptoms could contribute heterogeneous and cross-diagnostic clinical evolutions. Current clinical approaches attempt to merge clinical manifestations that co-occur across subjects and could therefore significantly hinder our understanding of clinical pathways connecting individual symptoms. Network approaches have the potential to shed light on the complex dynamics of early psychopathology. In the present manuscript we attempt to address 2 main limitations that have in our opinion hindered the application of network approaches in the clinical setting. The first limitation is that network analyses have mostly been applied to cross-sectional data, yielding results that often lack the intuitive interpretability of simpler categorical or dimensional approaches. Here we propose an approach based on multi-layer network analysis that offers an intuitive low-dimensional characterization of longitudinal pathways involved in the evolution of psychopathology, while conserving high-dimensional information on the role of specific symptoms. The second limitation is that network analyses typically characterize symptom connectivity at the level of a population, whereas clinical practice deals with symptom severity at the level of the individual. Here we propose an approach based on graph signal processing that exploits knowledge of network interactions between symptoms to predict longitudinal clinical evolution at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis.
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    Functional Connectivity in Antipsychotic-Treated and Antipsychotic-Naive Patients With First-Episode Psychosis and Low Risk of Self-harm or Aggression A Secondary Analysis of a Randomized Clinical Trial
    Chopra, S ; Francey, SM ; O'Donoghue, B ; Sabaroedin, K ; Arnatkeviciute, A ; Cropley, V ; Nelson, B ; Graham, J ; Baldwin, L ; Tahtalian, S ; Yuen, HP ; Allott, K ; Alvarez-Jimenez, M ; Harrigan, S ; Pantelis, C ; Wood, SJ ; McGorry, P ; Fornito, A (AMER MEDICAL ASSOC, 2021-09)
    IMPORTANCE: Altered functional connectivity (FC) is a common finding in resting-state functional magnetic resonance imaging (rs-fMRI) studies of people with psychosis, yet how FC disturbances evolve in the early stages of illness, and how antipsychotic treatment influences these disturbances, remains unknown. OBJECTIVE: To investigate longitudinal FC changes in antipsychotic-naive and antipsychotic-treated patients with first-episode psychosis (FEP). DESIGN, SETTING, AND PARTICIPANTS: This secondary analysis of a triple-blind, randomized clinical trial was conducted over a 5-year recruitment period between April 2008 and December 2016 with 59 antipsychotic-naive patients with FEP receiving either a second-generation antipsychotic or a placebo pill over a treatment period of 6 months. Participants were required to have low suicidality and aggression, to have a duration of untreated psychosis of less than 6 months, and to be living in stable accommodations with social support. Both FEP groups received intensive psychosocial therapy. A healthy control group was also recruited. Participants completed rs-fMRI scans at baseline, 3 months, and 12 months. Data were analyzed from May 2019 to August 2020. INTERVENTIONS: Resting-state functional MRI was used to probe brain FC. Patients received either a second-generation antipsychotic or a matched placebo tablet. Both patient groups received a manualized psychosocial intervention. MAIN OUTCOMES AND MEASURES: The primary outcomes of this analysis were to investigate (1) FC differences between patients and controls at baseline; (2) FC changes in medicated and unmedicated patients between baseline and 3 months; and (3) associations between longitudinal FC changes and clinical outcomes. An additional aim was to investigate long-term FC changes at 12 months after baseline. These outcomes were not preregistered. RESULTS: Data were analyzed for 59 patients (antipsychotic medication plus psychosocial treatment: 28 [47.5%]; mean [SD] age, 19.5 [3.0] years; 15 men [53.6%]; placebo plus psychosocial treatment: 31 [52.5%]; mean [SD] age, 18.8 [2.7]; 16 men [51.6%]) and 27 control individuals (mean [SD] age, 21.9 [1.9] years). At baseline, patients showed widespread functional dysconnectivity compared with controls, with reductions predominantly affecting interactions between the default mode network, limbic systems, and the rest of the brain. From baseline to 3 months, patients receiving placebo showed increased FC principally within the same systems; some of these changes correlated with improved clinical outcomes (canonical correlation analysis R = 0.901; familywise error-corrected P = .005). Antipsychotic exposure was associated with increased FC primarily between the thalamus and the rest of the brain. CONCLUSIONS AND RELEVANCE: In this secondary analysis of a clinical trial, antipsychotic-naive patients with FEP showed widespread functional dysconnectivity at baseline, followed by an early normalization of default mode network and cortical limbic dysfunction in patients receiving placebo and psychosocial intervention. Antipsychotic exposure was associated with FC changes concentrated on thalamocortical networks. TRIAL REGISTRATION: ACTRN12607000608460.
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    Omega-3 fatty acids and neurocognitive ability in young people at ultra-high risk for psychosis
    McLaverty, A ; Allott, KA ; Berger, M ; Hester, R ; McGorry, PD ; Nelson, B ; Markulev, C ; Yuen, HP ; Schaefer, MR ; Mossaheb, N ; Schloegelhofer, M ; Smesny, S ; Hickie, IB ; Berger, GE ; Chen, EYH ; de Haan, L ; Nieman, DH ; Nordentoft, M ; Riecher-Roessler, A ; Verma, S ; Thompson, A ; Yung, AR ; Amminger, GP (WILEY, 2021-08)
    BACKGROUND: Neurocognitive impairments are core early features of psychosis and are observed in those at ultra-high risk (UHR) for psychosis. The aim of the present study was to explore whether neurocognition is associated with polyunsaturated fatty acids (PUFAs), as has been observed in other clinical populations. METHOD: Erythrocyte levels of total omega-3-and omega-6 PUFAs the omega-3/omega-6 ratio, were measured in 265 UHR individuals. Six domains of neurocognition as well a Composite Score, were assessed using the Brief Assessment of Cognition in Schizophrenia. Pearson's correlations were used to assess the relationship between PUFAs and neurocognition. All analyses were controlled for tobacco smoking. RESULTS: Verbal Fluency correlated positively with eicosapentaenoic acid (P = .024) and alpha-linolenic acid (P = .01), and negatively with docosahexanoic acid (P = .007) and Working Memory positively correlated with omega-3/omega-6 ratio (P = .007). CONCLUSIONS: The current results provide support for a relationship between Verbal Fluency and omega-3 PUFAs in UHR. Further investigation is required to elucidate whether these biomarkers are useful as risk markers or in understanding the biological underpinning of neurocognitive impairment in this population.
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    Prediction of clinical outcomes beyond psychosis in theultra-highrisk for psychosis population
    Polari, A ; Yuen, HP ; Amminger, P ; Berger, G ; Chen, E ; deHaan, L ; Hartmann, J ; Markulev, C ; McGorry, P ; Nieman, D ; Nordentoft, M ; Riecher-Roessler, A ; Smesny, S ; Stratford, J ; Verma, S ; Yung, A ; Lavoie, S ; Nelson, B (WILEY, 2021-06)
    AIM: Several prediction models have been introduced to identify young people at greatest risk of transitioning to psychosis. To date, none has examined the possibility of developing a clinical prediction model of outcomes other than transition. The aims of this study were to examine the association between baseline clinical predictors and outcomes including, but not limited to, transition to psychosis in young people at risk for psychosis, and to develop a prediction model for these outcomes. METHODS: Several evidence-based variables previously associated with transition to psychosis and some important clinical comorbidities experienced by ultra-high risk (UHR) individuals were identified in 202 UHR individuals. Secondary analysis of the Neurapro clinical trial were conducted to investigate the associations between these variables and favourable (remission and recovery) or unfavourable (transition to psychosis, no remission, any recurrence and relapse) clinical outcomes. Logistic regression, best subset selection, Akaike Information Criterion and receiver operating characteristic curves were used to seek the best prediction model for clinical outcomes from all combinations of possible predictors. RESULTS: When considered individually, only higher general psychopathology levels (P = .023) was associated with the unfavourable outcomes. Prediction models suggest that general psychopathology and functioning are predictive of unfavourable outcomes. CONCLUSION: The predictive performance of the resulting models was modest and further research is needed. Nonetheless, when designing early intervention centres aiming to support individuals in the early phases of a mental disorder, the proper assessment of general psychopathology and functioning should be considered in order to inform interventions and length of care provided.
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    Differentiating the effect of antipsychotic medication and illness on brain volume reductions in first-episode psychosis: A Longitudinal, Randomised, Triple-blind, Placebo-controlled MRI Study
    Chopra, S ; Fornito, A ; Francey, SM ; O'Donoghue, B ; Cropley, V ; Nelson, B ; Graham, J ; Baldwin, L ; Tahtalian, S ; Yuen, HP ; Allott, K ; Alvarez-Jimenez, M ; Harrigan, S ; Sabaroedin, K ; Pantelis, C ; Wood, SJ ; McGorry, P (SPRINGERNATURE, 2021-07)
    Changes in brain volume are a common finding in Magnetic Resonance Imaging (MRI) studies of people with psychosis and numerous longitudinal studies suggest that volume deficits progress with illness duration. However, a major unresolved question concerns whether these changes are driven by the underlying illness or represent iatrogenic effects of antipsychotic medication. In this study, 62 antipsychotic-naïve patients with first-episode psychosis (FEP) received either a second-generation antipsychotic (risperidone or paliperidone) or a placebo pill over a treatment period of 6 months. Both FEP groups received intensive psychosocial therapy. A healthy control group (n = 27) was also recruited. Structural MRI scans were obtained at baseline, 3 months and 12 months. Our primary aim was to differentiate illness-related brain volume changes from medication-related changes within the first 3 months of treatment. We secondarily investigated long-term effects at the 12-month timepoint. From baseline to 3 months, we observed a significant group x time interaction in the pallidum (p < 0.05 FWE-corrected), such that patients receiving antipsychotic medication showed increased volume, patients on placebo showed decreased volume, and healthy controls showed no change. Across the entire patient sample, a greater increase in pallidal grey matter volume over 3 months was associated with a greater reduction in symptom severity. Our findings indicate that psychotic illness and antipsychotic exposure exert distinct and spatially distributed effects on brain volume. Our results align with prior work in suggesting that the therapeutic efficacy of antipsychotic medications may be primarily mediated through their effects on the basal ganglia.
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    S166. EFFECTIVE CONNECTIVITY OF FRONTOSTRIATAL SYSTEMS IN FIRST-EPISODE PSYCHOSIS
    Sabaroedin, K ; Razi, A ; Aquino, K ; Chopra, S ; Finlay, A ; Nelson, B ; Allott, K ; Alvarez-Jimenez, M ; Graham, J ; Baldwin, L ; Tahtalian, S ; Yuen, HP ; Harrigan, S ; Cropley, V ; Pantelis, C ; Wood, S ; O’Donoghue, B ; Francey, S ; McGorry, P ; Fornito, A (Oxford University Press (OUP), 2020-05-18)
    Abstract Background Neuroimaging studies have found dysconnectivity of frontostriatal circuits across a broad spectrum of psychotic symptoms. However, it is unknown whether dysconnectivity within frontostriatal circuits originates from disrupted bottom-up or top-down control signaling within these systems. Here, we used dynamic causal modelling (DCM) to examine the effective connectivity of frontostriatal systems in first-episode psychosis (FEP). Methods A total of 55 FEP patients (26 males; mean [SD] age = 19.24 [2.89]) and 24 healthy controls (15 males; mean [SD] age = 21.83 [1.93]) underwent a resting-state functional magnetic resonance imaging protocol. Biologically plausible connections between eight left hemisphere regions encompassing the dorsal and ventral frontostriatal systems were modelled using spectral DCM. The regions comprise dorsolateral prefrontal cortex, ventromedial prefrontal cortex, anterior hippocampus, amygdala, dorsal caudate, nucleus accumbens, thalamus, and the midbrain. Effective connectivity between groups were assessed using a parametric Bayesian model. Associations between effective connectivity parameters and positive symptoms, measured by the Brief Psychiatric Rating Scale positive subscale, was assessed in the patient group in a separate Bayesian general linear model. Results DCM shows evidence for differences in effective connectivity between patients and healthy controls, namely in the bottom-down connections distributed in the frontostriatal system encompassing the hippocampus, amygdala, striatum, and midbrain. Compared to healthy controls, patients also demonstrated increased disinhibition of the midbrain. In patients, positive symptoms are associated with increased top-down connections to the midbrain. Outgoing connection from the midbrain to the nucleus accumbens is also increased in association with positive symptoms. Discussion Aberrant top-down connectivity in the frontostriatal system in patients is consistent with top-down dysregulation of dopamine function in FEP, as dopaminergic activity in the midbrain is proposed to be under the control of higher brain areas. In patients, increased self-inhibition of the midbrain, as well as symptom associations in both ingoing and outgoing connections of this region, are congruous with hyperactivity of the midbrain as proposed by the dopamine dysregulation hypothesis. Here, we demonstrate that mathematical models of brain imaging signals can be used to identify the key disruptions driving brain circuit dysfunction, identifying new targets for treatment.