Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

The self, neuroscience and psychosis study: Testing a neurophenomenological model of the onset of psychosis.

AIM: Basic self disturbance is a putative core vulnerability marker of schizophrenia spectrum disorders. The primary aims of the Self, Neuroscience and Psychosis (SNAP) study are to: (1) empirically test a previously described neurophenomenological self-disturbance model of psychosis by examining the relationship between specific clinical, neurocognitive, and neurophysiological variables in UHR patients, and (2) develop a prediction model using these neurophenomenological disturbances for persistence or deterioration of UHR symptoms at 12-month follow-up. METHODS: SNAP is a longitudinal observational study. Participants include 400 UHR individuals, 100 clinical controls with no attenuated psychotic symptoms, and 50 healthy controls. All participants complete baseline clinical and neurocognitive assessments and electroencephalography. The UHR sample are followed up for a total of 24 months, with clinical assessment completed every 6 months. RESULTS: This paper presents the protocol of the SNAP study, including background rationale, aims and hypotheses, design, and assessment procedures. CONCLUSIONS: The SNAP study will test whether neurophenomenological disturbances associated with basic self-disturbance predict persistence or intensification of UHR symptomatology over a 2-year follow up period, and how specific these disturbances are to a clinical population with attenuated psychotic symptoms. This may ultimately inform clinical care and pathoaetiological models of psychosis.

Affinity scores: An individual-centric fingerprinting framework for neuropsychiatric disorders.

Population-centric frameworks of biomarker identification for psychiatric disorders focus primarily on comparing averages between groups and assume that diagnostic groups are (1) mutually-exclusive, and (2) homogeneous. There is a paucity of individual-centric approaches capable of identifying individual-specific 'fingerprints' across multiple domains. To address this, we propose a novel framework, combining a range of biopsychosocial markers, including brain structure, cognition, and clinical markers, into higher-level 'fingerprints', capable of capturing intra-illness heterogeneity and inter-illness overlap. A multivariate framework was implemented to identify individualised patterns of brain structure, cognition and clinical markers based on affinity to other participants in the database. First, individual-level affinity scores defined each participant's "neighbourhood" across each measure based on variable-specific hop sizes. Next, diagnostic verification and classification algorithms were implemented based on multivariate affinity score profiles. To perform affinity-based classification, data were divided into training and test samples, and 5-fold nested cross-validation was performed on the training data. Affinity-based classification was compared to weighted K-nearest neighbours (KNN) classification. The framework was applied to the Australian Schizophrenia Research Bank (ASRB) dataset, which included data from individuals with chronic and treatment resistant schizophrenia and healthy controls. Individualised affinity scores provided a 'fingerprint' of brain structure, cognition, and clinical markers, which described the affinity of an individual to the representative groups in the dataset. Diagnostic verification capability was moderate to high depending on the choice of multivariate affinity metric. Affinity score-based classification achieved a high degree of accuracy in the training, nested cross-validation and prediction steps, and outperformed KNN classification in the training and test datasets. Affinity scores demonstrate utility in two keys ways: (1) Early and accurate diagnosis of neuropsychiatric disorders, whereby an individual can be grouped within a diagnostic category/ies that best matches their fingerprint, and (2) identification of biopsychosocial factors that most strongly characterise individuals/disorders, and which may be most amenable to intervention.

Cortico-cognition coupling in treatment resistant schizophrenia.

BACKGROUND: Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC). METHOD: Forty-one TRS patients (age 38.5 ± 9.1, 30 males (M)), and 45 HC (age 40.2 ± 10.6, 29 M) underwent 3T structural MRI. Volumes of 68 brain regions and seven variables from CANTAB covering memory and executive domains were included. Univariate group differences were assessed, followed by the MB-PLS-C analyses to identify group-specific multivariate patterns of cortico-cognitive coupling. Supplementary three-group analyses, which included 23 non-affected first-degree relatives (NAR), were also conducted. RESULTS: Univariate tests demonstrated that TRS patients showed impairments in all seven cognitive tasks and volume reductions in 12 cortical regions following Bonferroni correction. The MB-PLS-C analyses revealed two significant latent variables (LVs) explaining > 90% of the sum-of-squares variance. LV1 explained 78.86% of the sum-of-squares variance, describing a shared, widespread structure-cognitive pattern relevant to both TRS patients and HCs. In contrast, LV2 (13.47% of sum-of-squares variance explained) appeared specific to TRS and comprised a differential cortico-cognitive pattern including frontal and temporal lobes as well as paired associates learning (PAL) and intra-extra dimensional set shifting (IED). Three-group analyses also identified two significant LVs, with NARs more closely resembling healthy controls than TRS patients. CONCLUSIONS: MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.

Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness.

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.

Cognitive behavioral markers of neurodevelopmental trajectories in rodents.

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.

Investigation of structural brain correlates of neurological soft signs in individuals at ultra-high risk for psychosis.

Increased severity of neurological soft signs (NSS) in schizophrenia have been associated with abnormal brain morphology in cerebello-thalamo-cortical structures, but it is unclear whether similar structures underlie NSS prior to the onset of psychosis. The present study investigated the relationship between severity of NSS and grey matter volume (GMV) in individuals at ultra-high risk for psychosis (UHR) stratified for later conversion to psychosis. Structural T1-weighted MRI scans were obtained from 56 antipsychotic-naïve UHR individuals and 35 healthy controls (HC). The UHR individuals had follow-up data (mean follow-up: 5.2 years) to ascertain clinical outcome. Using whole-brain voxel-based morphometry, the relationship between NSS and GMV at baseline was assessed in UHR, HC, as well as individuals who later transitioned (UHR-P, n = 25) and did not transition (UHR-NP, n = 31) to psychosis. NSS total and subscale scores except motor coordination were significantly higher in UHR compared to HC. Higher signs were also found in UHR-P, but not UHR-NP. Total NSS was not associated with GMV in the whole sample or in each group. However, in UHR-P individuals, greater deficits in sensory integration was associated with lower GMV in the left cerebellum, right insula, and right middle frontal gyrus. In conclusion, NSS are present in UHR individuals, particularly those who later transitioned to a psychotic disorder. While these signs show little overall variation with GMV, the association of sensory integration deficits with lower GMV in UHR-P suggests that certain brain areas may be implicated in the development of specific neurological abnormalities in the psychosis prodrome.

Impaired olfactory ability associated with larger left hippocampus and rectus volumes at earliest stages of schizophrenia: A sign of neuroinflammation?

Impaired olfactory identification has been reported as a first sign of schizophrenia during the earliest stages of illness, including before illness onset. The aim of this study was to examine the relationship between volumes of these regions (amygdala, hippocampus, gyrus rectus and orbitofrontal cortex) and olfactory ability in three groups of participants: healthy control participants (Ctls), patients with first-episode schizophrenia (FE-Scz) and chronic schizophrenia patients (Scz). Exploratory analyses were performed in a sample of individuals at ultra-high risk (UHR) for psychosis in a co-submission paper (Masaoka et al., 2020). The relationship to brain structural measures was not apparent prior to psychosis onset, but was only evident following illness onset, with a different pattern of relationships apparent across illness stages (FE-Scz vs Scz). Path analysis found that lower olfactory ability was related to larger volumes of the left hippocampus and gyrus rectus in the FE-Scz group. We speculate that larger hippocampus and rectus in early schizophrenia are indicative of swelling, potentially caused by an active neurochemical or immunological process, such as inflammation or neurotoxicity, which is associated with impaired olfactory ability. The volumetric decreases in the chronic stage of Scz may be due to degeneration resulting from an active immune process and its resolution.

Evidence for Network-Based Cortical Thickness Reductions in Schizophrenia.

OBJECTIVE: Cortical thickness reductions in schizophrenia are irregularly distributed across multiple loci. The authors hypothesized that cortical connectivity networks would explain the distribution of cortical thickness reductions across the cortex, and, specifically, that cortico-cortical connectivity between loci with these reductions would be exceptionally strong and form an interconnected network. This hypothesis was tested in three cross-sectional schizophrenia cohorts: first-episode psychosis, chronic schizophrenia, and treatment-resistant schizophrenia. METHODS: Structural brain images were acquired for 70 patients with first-episode psychosis, 153 patients with chronic schizophrenia, and 47 patients with treatment-resistant schizophrenia and in matching healthy control groups (N=57, N=168, and N=54, respectively). Cortical thickness was compared between the patient and respective control groups at 148 regions spanning the cortex. Structural connectivity strength between pairs of cortical regions was quantified with structural covariance analysis. Connectivity strength between regions with cortical thickness reductions was compared with connectivity strength between 5,000 sets of randomly chosen regions to establish whether regions with reductions were interconnected more strongly than would be expected by chance. RESULTS: Significant (false discovery rate corrected) and widespread cortical thickness reductions were found in the chronic schizophrenia (79 regions) and treatment-resistant schizophrenia (106 regions) groups, with more circumscribed reductions in the first-episode psychosis group (34 regions). Cortical thickness reductions with the largest effect sizes were found in frontal, temporal, cingulate, and insular regions. In all cohorts, both the patient and healthy control groups showed significantly increased structural covariance between regions with cortical thickness reductions compared with randomly selected regions. CONCLUSIONS: Brain network architecture can explain the irregular topographic distribution of cortical thickness reductions in schizophrenia. This finding, replicated in three distinct schizophrenia cohorts, suggests that the effect is robust and independent of illness stage.

Hippocampal subfields and visuospatial associative memory across stages of schizophrenia-spectrum disorder.

BACKGROUND: While previous studies have identified relationships between hippocampal volumes and memory performance in schizophrenia, these relationships are not apparent in healthy individuals. Further, few studies have examined the role of hippocampal subfields in illness-related memory deficits, and no study has examined potential differences across varying illness stages. The current study aimed to investigate whether individuals with early and established psychosis exhibited differential relationships between visuospatial associative memory and hippocampal subfield volumes. METHODS: Measurements of visuospatial associative memory performance and grey matter volume were obtained from 52 individuals with a chronic schizophrenia-spectrum disorder, 28 youth with recent-onset psychosis, 52 older healthy controls, and 28 younger healthy controls. RESULTS: Both chronic and recent-onset patients had impaired visuospatial associative memory performance, however, only chronic patients showed hippocampal subfield volume loss. Both chronic and recent-onset patients demonstrated relationships between visuospatial associative memory performance and hippocampal subfield volumes in the CA4/dentate gyrus and the stratum that were not observed in older healthy controls. There were no group by volume interactions when chronic and recent-onset patients were compared. CONCLUSIONS: The current study extends the findings of previous studies by identifying particular hippocampal subfields, including the hippocampal stratum layers and the dentate gyrus, that appear to be related to visuospatial associative memory ability in individuals with both chronic and first-episode psychosis.

Risk and resilience brain networks in treatment-resistant schizophrenia.

BACKGROUND: Genes, molecules and neural circuits that are associated with, or confer risk to developing schizophrenia have been studied and mapped. It is hypothesized that certain neural systems may counterbalance familial risk of schizophrenia, and thus confer resilience to developing the disorder. This study sought to identify resting-state functional brain connectivity (rs-FC) representing putative risk or resilience endophenotypes in schizophrenia. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed in 42 individuals with treatment resistant schizophrenia (TRS), 16 unaffected first-degree family members (UFM) and 42 healthy controls. Whole-brain rs-FC networks were mapped for each individual and analysed graph theoretically to identify network markers associated with schizophrenia risk or resilience. RESULTS: The ~900 functional connections showing between-group differences were operationalized as conferring: i) resilience, ii) risk, or iii) precipitating risk and/or illness effects. Approximately 95% of connections belonged to the latter two categories, with substantially fewer connections associated with resilience. Schizophrenia risk primarily involved reduced frontal and occipital rs-FC, with patients showing additional reduced frontal and temporal rs-FC. Functional brain networks were characterized by greater local efficiency in UFM, compared to TRS and controls. CONCLUSIONS: TRS and UFM share frontal and occipital rs-FC deficits, representing a 'risk' endophenotype. Additional reductions in frontal and temporal rs-FC appear to be associated with risk that precipitates psychosis in vulnerable individuals, or may be due to other illness-related effects, such as medication. Functional brain networks are more topologically resilient in UFM compared to TRS, which may protect UFM from psychosis onset despite familial liability.