Transition to psychosis associated with prefrontal and subcortical dysfunction in ultra high-risk individuals

Identifying neurobiological heterogeneity in clinical high-risk psychosis: a data-driven biotyping approach using resting-state functional connectivity

To explore the neurobiological heterogeneity within the Clinical High-Risk (CHR) for psychosis population, this study aimed to identify and characterize distinct neurobiological biotypes within CHR using features from resting-state functional networks. A total of 239 participants from the Shanghai At Risk for Psychosis (SHARP) program were enrolled, consisting of 151 CHR individuals and 88 matched healthy controls (HCs). Functional connectivity (FC) features that were correlated with symptom severity were subjected to the single-cell interpretation through multikernel learning (SIMLR) algorithm in order to identify latent homogeneous subgroups. The cognitive function, clinical symptoms, FC patterns, and correlation with neurotransmitter systems of biotype profiles were compared. Three distinct CHR biotypes were identified based on 646 significant ROI-ROI connectivity features, comprising 29.8%, 19.2%, and 51.0% of the CHR sample, respectively. Despite the absence of overall FC differences between CHR and HC groups, each CHR biotype demonstrated unique FC abnormalities. Biotype 1 displayed augmented somatomotor connection, Biotype 2 shown compromised working memory with heightened subcortical and network-specific connectivity, and Biotype 3, characterized by significant negative symptoms, revealed extensive connectivity reductions along with increased limbic-subcortical connectivity. The neurotransmitter correlates differed across biotypes. Biotype 2 revealed an inverse trend to Biotype 3, as increased neurotransmitter concentrations improved functional connectivity in Biotype 2 but reduced it in Biotype 3. The identification of CHR biotypes provides compelling evidence for the early manifestation of heterogeneity within the psychosis spectrum, suggesting that distinct pathophysiological mechanisms may underlie these subgroups.

EANM perspective on clinical PET and SPECT imaging in schizophrenia-spectrum disorders: a systematic review of longitudinal studies

PURPOSE

There is a need for biomarkers in psychiatry to improve diagnosis, prognosis and management, and with confirmed value in follow-up care. Radionuclide imaging, given its molecular imaging characteristics, is well-positioned for translation to the clinic. This systematic review lays the groundwork for integrating PET and SPECT imaging in the clinical management of schizophrenia-spectrum disorders.

METHODS

Systematic search of PubMed, Embase, Web of Science and Cochrane library databases was conducted from the earliest date available until February 2024. The focus was on longitudinal studies evaluating PET or SPECT imaging in individuals with a schizophrenia-spectrum or another psychotic disorders. Quality assessment was done using the Newcastle-Ottawa Scale (NOS), NIH scale for before-after studies and Cochrane Risk of Bias tool version 2 (Cochrane RoB2). Studies were further categorised into three groups: preclinical and diagnosis, predicting disease course or personalising treatment.

RESULTS

Fifty-six studies were included in the systematic review investigating in total 1329 patients over a median of 3 months. Over two-thirds used PET tracers, whereas the remaining studies employed SPECT tracers. The most frequently investigated system was dopaminergic transmission, followed by cerebral metabolism and blood flow. [18F]FDOPA demonstrated large effect size in predicting conversion of subjects at risk and treatment response. Additionally, treatment dosage could be optimised to reduce side effects using [123I]IBZM or [11C]raclopride.

CONCLUSION

Molecular imaging holds significant promise for real-life application in schizophrenia, with two particularly encouraging avenues being the prediction of conversion/response to antipsychotic medication and the improved management of antipsychotic dosage. Further longitudinal studies and clinical trials will be essential for validating both the clinical effectiveness and economic sustainability, as well as for exploring new applications.

Neuropsychological performances and brain perfusion patterns in patients with first episode psychosis

Abnormalities in cognition are a pronounced feature in primary psychotic disorders and may appear long before the manifestation of the first-episode psychosis (FEP). Although brain functional changes may precede structural alterations, brain perfusion patterns in FEP and most importantly their correlations with cognition remain poorly understood. In the present study we assessed neurocognitive functions and regional cerebral blood flow (rCBF) in 53 patients with a diagnosis of FEP. A special emphasis was placed on the assessment of basic executive functions. Cerebral perfusion patterns were measured by SPECT rCBF scintigraphy in cerebral lobes bilaterally and Brodmann Areas (BAs). Patients showed impairments in long-term verbal memory, processing speed/response latency and executive cognition. Pathological perfusion was prominent in the limbic lobes bilaterally. BAs with the largest hypoperfusion, were the subgenual area (BA25) and hippocampal areas (BA 28 and 36). The left temporal lobe was also hypoperfused, and specifically the inferior temporal gyrus (BA 20), the left middle (BA 21) and superior (BA 22) temporal gyrus, and the temporal pole (BA 38). Hypoperfusion was limited in the frontal regions, although specific BAs displayed pathological perfusion (i.e., BA 24). Cerebral lobe perfusion was not correlated with compromised cognitive abilities.

Aberrant brain language network in schizophrenia spectrum disorder: a systematic review of its relation to language signs beyond symptoms

Background

Language disturbances are a core feature of schizophrenia, often studied as a formal thought disorder. The neurobiology of language in schizophrenia has been addressed within the same framework, that language and thought are equivalents considering symptoms and not signs. This review aims to systematically examine published peer-reviewed studies that employed neuroimaging techniques to investigate aberrant brain-language networks in individuals with schizophrenia in relation to linguistic signs.

Methods

We employed a language model for automatic data extraction. We selected our studies according to the PRISMA recommendations, and we conducted the quality assessment of the selected studies according to the STROBE guidance.

Results

We analyzed the findings from 37 studies, categorizing them based on patient characteristics, brain measures, and language task types. The inferior frontal gyrus (IFG) and superior temporal gyrus (STG) exhibited the most significant differences among these studies and paradigms.

Conclusions

We propose guidelines for future research in this field based on our analysis. It is crucial to investigate larger networks involved in language processing, and language models with brain metrics must be integrated to enhance our understanding of the relationship between language and brain abnormalities in schizophrenia.

Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin

Abnormalities in functional brain networks (functional connectome) are increasingly implicated in people at Clinical High Risk for Psychosis (CHR-P). Intranasal oxytocin, a potential novel treatment for the CHR-P state, modulates network topology in healthy individuals. However, its connectomic effects in people at CHR-P remain unknown. Forty-seven men (30 CHR-P and 17 healthy controls) received acute challenges of both intranasal oxytocin 40 IU and placebo in two parallel randomised, double-blind, placebo-controlled cross-over studies which had similar but not identical designs. Multi-echo resting-state fMRI data was acquired at approximately 1 h post-dosing. Using a graph theoretical approach, the effects of group (CHR-P vs healthy control), treatment (oxytocin vs placebo) and respective interactions were tested on graph metrics describing the topology of the functional connectome. Group effects were observed in 12 regions (all pFDR < 0.05) most localised to the frontoparietal network. Treatment effects were found in 7 regions (all pFDR < 0.05) predominantly within the ventral attention network. Our major finding was that many effects of oxytocin on network topology differ across CHR-P and healthy individuals, with significant interaction effects observed in numerous subcortical regions strongly implicated in psychosis onset, such as the thalamus, pallidum and nucleus accumbens, and cortical regions which localised primarily to the default mode network (12 regions, all pFDR < 0.05). Collectively, our findings provide new insights on aberrant functional brain network organisation associated with psychosis risk and demonstrate, for the first time, that oxytocin modulates network topology in brain regions implicated in the pathophysiology of psychosis in a clinical status (CHR-P vs healthy control) specific manner.

Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering

BACKGROUND

Similarities among schizophrenia (SZ), schizoaffective disorder (SAD) and bipolar disorder (BP) including clinical phenotypes, brain alterations and risk genes, make it challenging to perform reliable separation among them. However, previous subtype identification that transcend traditional diagnostic boundaries were based on group-level neuroimaging features, ignoring individual-level inferences.

METHODS

455 psychoses (178 SZs, 134 SADs and 143 BPs), their first-degree relatives (N = 453) and healthy controls (HCs, N = 220) were collected from Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP I) consortium. Individualized covariance structural differential networks (ICSDNs) were constructed for each patient and multi-site clustering was used to identify psychosis subtypes. Group differences between subtypes in clinical phenotypes and voxel-wise fractional amplitude of low frequency fluctuation (fALFF) were calculated, as well as between the corresponding relatives.

RESULTS

Two psychosis subtypes were identified with increased whole brain structural covariance, with decreased connectivity between amygdala-hippocampus and temporal-occipital cortex in subtype I (S-I) compared to subtype II (S-II), which was replicated under different clustering methods, number of edges and across datasets (B-SNIP II) and different brain atlases. S-I had higher emotional-related symptoms than S-II and showed significant fALFF decrease in temporal and occipital cortex, while S-II was more similar to HC. This pattern was consistently validated on relatives of S-I and S-II in both fALFF and clinical symptoms.

CONCLUSIONS

These findings reconcile categorical and dimensional perspectives of psychosis neurobiological heterogeneity, indicating that relatives of S-I might have greater predisposition in developing psychosis, while relatives of S-II are more likely to be healthy. This study contributes to the development of neuroimaging informed diagnostic classifications within psychosis spectrum.

Regional Vulnerability Indices in Youth With Persistent and Distressing Psychoticlike Experiences

Importance

Distressing and persistent psychoticlike experiences (PLEs) in youth are associated with greater odds of developing psychiatric conditions in adulthood. Despite this risk, it is unclear whether early PLEs show similar brain patterns compared with adults with psychiatric and neurologic conditions.

Objective

To examine the degree to which persistent and distressing PLEs exhibit neural metrics that show similarity to adults with chronic psychiatric and neurologic conditions.

Design, Setting, and Participants

This cohort study used Adolescent Brain Cognitive Development (ABCD) Study examining the persistence and distress associated with PLEs across the first 3 waves of data with baseline structural magnetic resonance imaging data. Analyzed data were collected between September 1, 2016, and September 27, 2021. Children were recruited from 21 research sites across the US.

Exposures

Psychoticlike experiences were assessed using the Prodromal Questionnaire-Brief Child Version, and participants were categorized into groups based on the persistence and distress associated with PLEs.

Main Outcomes and Measures

Cortical and subcortical regional vulnerability indices (RVIs) were created by quantifying the similarity of participants' baseline neuroimaging measures to the expected patterns found in adult neuropsychiatric samples. The PLE groups were compared on the following RVI cortical and subcortical metrics: schizophrenia spectrum disorders, bipolar disorder, major depressive disorder, Parkinson disease, Alzheimer disease, and metabolic diseases.

Results

Analyses examined PLE groups created from 8242 children in the ABCD sample (52.5% male; mean [SD] age, 9.93 [0.63] years; and 56.3% White), including persistent distressing PLEs (n = 329), transient distressing PLEs (n = 396), persistent nondistressing PLEs (n = 234), transient nondistressing PLEs (n = 390), and low distressing PLEs (n = 6893) groups. Participants with persistent or transient distressing PLEs broadly showed increased subcortical RVI scores across most RVI metrics, with persistent distressing PLEs additionally showing increased scores for cortical RVI metrics. The greatest effect sizes were found for persistent distressing PLEs with cortical RVI-schizophrenia spectrum disorders (β estimate, 1.055; 95% CI, 0.326-1.786) and RVI-Alzheimer disease (β estimate, 2.473; 95% CI, 0.930-4.018).

Conclusions and Relevance

In this cohort study of ABCD participants, the findings suggest that especially the persistent distressing PLEs in children were associated with neural metrics resembling those observed in adults with severe psychiatric and neurologic conditions. These findings support the potential use of brain-based risk scores for early identification and precision medicine approaches in the assessment of PLEs.

Clinical high risk for psychosis syndrome is associated with reduced neural responding to unpleasant images

Deficits in emotion processing are core features of psychotic disorders. Electrophysiology research in schizophrenia suggests deficits in sustained engagement with emotional content (indexed by the late positive potential [LPP]) may contribute to emotion processing impairments. Despite similar behavioral emotion processing dysfunction in those at clinical high risk (CHR) for psychosis, limited research has examined neural mechanisms of impaired emotion processing in the high-risk period, where research can inform risk models. To examine mechanisms of emotion processing deficits in those at CHR for psychosis, the present study used a passive viewing task to elicit the LPP in response to emotionally engaging and neutral stimuli in 28 CHR and 32 control participants (60% female). Relative to controls, CHR participants showed reduced LPP amplitude when viewing unpleasant images (d = 0.75, p = .005) but similar LPP amplitude in response to both neutral (d = 0.35, p = .19) and pleasant images (d = 0.31, p = .24). This pattern suggests that individuals at CHR for psychosis exhibit a deficit in sustained engagement with unpleasant stimuli. Clinical and trait questionnaires were administered to examine potential exploratory explanations for group differences in LPP amplitude. Consistent with evidence suggesting LPP amplitude reflects engagement of approach/avoidance motivational systems, greater LPP amplitude was associated with greater trait-level behavioral avoidance in control participants (r = .42, p = .032) but not CHR participants (r = -.21, p = .40). Together, the present research is consistent with LPP studies in psychosis and implicates reduced sustained engagement with emotional content in the high-risk period. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Review of Major Social Determinants of Health in Schizophrenia-Spectrum Psychotic Disorders: III. Biology

BACKGROUND

Social determinants of health (SDoHs) are nonmedical factors that significantly impact health and longevity. We found no published reviews on the biology of SDoHs in schizophrenia-spectrum psychotic disorders (SSPD).

STUDY DESIGN

We present an overview of pathophysiological mechanisms and neurobiological processes plausibly involved in the effects of major SDoHs on clinical outcomes in SSPD.

STUDY RESULTS

This review of the biology of SDoHs focuses on early-life adversities, poverty, social disconnection, discrimination including racism, migration, disadvantaged neighborhoods, and food insecurity. These factors interact with psychological and biological factors to increase the risk and worsen the course and prognosis of schizophrenia. Published studies on the topic are limited by cross-sectional design, variable clinical and biomarker assessments, heterogeneous methods, and a lack of control for confounding variables. Drawing on preclinical and clinical studies, we propose a biological framework to consider the likely pathogenesis. Putative systemic pathophysiological processes include epigenetics, allostatic load, accelerated aging with inflammation (inflammaging), and the microbiome. These processes affect neural structures, brain function, neurochemistry, and neuroplasticity, impacting the development of psychosis, quality of life, cognitive impairment, physical comorbidities, and premature mortality. Our model provides a framework for research that could lead to developing specific strategies for prevention and treatment of the risk factors and biological processes, thereby improving the quality of life and increasing the longevity of people with SSPD.

CONCLUSIONS

Biology of SDoHs in SSPD is an exciting area of research that points to innovative multidisciplinary team science for improving the course and prognosis of these serious psychiatric disorders.

A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk

The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.

Parsing neurobiological heterogeneity of the clinical high-risk state for psychosis: A pseudo-continuous arterial spin labelling study

Introduction

The impact of the clinical high-risk for psychosis (CHR-P) construct is dependent on accurately predicting outcomes. Individuals with brief limited intermittent psychotic symptoms (BLIPS) have higher risk of developing a first episode of psychosis (FEP) compared to individuals with attenuated psychotic symptoms (APS). Supplementing subgroup stratification with information from candidate biomarkers based on neurobiological parameters, such as resting-state, regional cerebral blood flow (rCBF), may help refine risk estimates. Based on previous evidence, we hypothesized that individuals with BLIPS would exhibit increased rCBF compared to APS in key regions linked to dopaminergic pathways.

Methods

Data from four studies were combined using ComBat (to account for between-study differences) to analyse rCBF in 150 age- and sex-matched subjects (n = 30 healthy controls [HCs], n = 80 APS, n = 20 BLIPS and n = 20 FEP). Global gray matter (GM) rCBF was examined in addition to region-of-interest (ROI) analyses in bilateral/left/right frontal cortex, hippocampus and striatum. Group differences were assessed using general linear models: (i) alone; (ii) with global GM rCBF as a covariate; (iii) with global GM rCBF and smoking status as covariates. Significance was set at p < 0.05.

Results

Whole-brain voxel-wise analyses and Bayesian ROI analyses were also conducted. No significant group differences were found in global [F(3,143) = 1,41, p = 0.24], bilateral frontal cortex [F(3,143) = 1.01, p = 0.39], hippocampus [F(3,143) = 0.63, p = 0.60] or striatum [F(3,143) = 0.52, p = 0.57] rCBF. Similar null findings were observed in lateralized ROIs (p > 0.05). All results were robust to addition of covariates (p > 0.05). No significant clusters were identified in whole-brain voxel-wise analyses (p > 0.05FWE). Weak-to-moderate evidence was found for an absence of rCBF differences between APS and BLIPS in Bayesian ROI analyses.

Conclusion

On this evidence, APS and BLIPS are unlikely to be neurobiologically distinct. Due to this and the weak-to-moderate evidence for the null hypothesis, future research should investigate larger samples of APS and BLIPS through collaboration across large-scale international consortia.

Psychotic disorders as a framework for precision psychiatry

People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.

The substantia nigra in the pathology of schizophrenia: A review on post-mortem and molecular imaging findings

Dysregulation of striatal dopamine is considered to be an important driver of pathophysiological processes in schizophrenia. Despite being one of the main origins of dopaminergic input to the striatum, the (dys)functioning of the substantia nigra (SN) has been relatively understudied in schizophrenia. Hence, this paper aims to review different molecular aspects of nigral functioning in patients with schizophrenia compared to healthy controls by integrating post-mortem and molecular imaging studies. We found evidence for hyperdopaminergic functioning in the SN of patients with schizophrenia (i.e. increased AADC activity in antipsychotic-free/-naïve patients and elevated neuromelanin accumulation). Reduced GABAergic inhibition (i.e. decreased density of GABAergic synapses, lower VGAT mRNA levels and lower mRNA levels for GABA_A receptor subunits), excessive glutamatergic excitation (i.e. increased NR1 and Glur5 mRNA levels and a reduced number of astrocytes), and several other disturbances implicating the SN (i.e. immune functioning and copper concentrations) could potentially underlie this nigral hyperactivity and associated striatal hyperdopaminergic functioning in schizophrenia. These results highlight the importance of the SN in schizophrenia pathology and suggest that some aspects of molecular functioning in the SN could potentially be used as treatment targets or biomarkers.

Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.

Animal Models of Relevance to the Schizophrenia Prodrome

Patients with schizophrenia often undergo a prodromal phase prior to diagnosis. Given the absence of significant therapeutic improvements, attention has recently shifted to the possibility of intervention during this early stage to delay or diminish symptom severity or even prevent onset. Unfortunately, the 20 or so trials of intervention to date have not been successful in either preventing onset or improving long-term outcomes in subjects who are at risk of developing schizophrenia. One reason may be that the biological pathways an effective intervention must target are not static. The prodromal phase typically occurs during late adolescence, a period during which a number of brain circuits and structures are still maturing. We propose that developing a deeper understanding of which circuits/processes and brain structures are still maturing at this time and which processes drive the transition to schizophrenia will take us a step closer to developing better prophylactic interventions. Fortunately, such knowledge is now emerging from clinical studies, complemented by work in animal models. Our task here is to describe what would constitute an appropriate animal model to study and to potentially intervene in such processes. Such a model would allow invasive analysis of the cellular and molecular substrates of the progressive neurobiology that defines the schizophrenia prodrome and hopefully offer valuable insights into potential prophylactic targets.

Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence

Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject's clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.

Further evidence that antipsychotic medication does not prevent long-term psychosis in higher-risk individuals

OBJECTIVE

Although existing guidelines have discouraged use of antipsychotics for general clinical high-risk (CHR) individuals, it is unclear if antipsychotics can prevent psychosis in higher-risk population. We aimed to study the comparative real-world effectiveness of antipsychotic treatments for preventing psychosis in higher-risk CHR individuals.

METHODS

A total of 300 CHR individuals were identified using the structured interview for prodromal syndromes (SIPS) and followed the participants for 3 years. In total, 228(76.0%) individuals completed baseline assessments using the NAPLS-2 risk calculator (NAPLS-2-RC), and 210(92.1%) completed the follow-up. The sample was further stratified according to risk level. "Higher-risk" was defined based on the NAPLS-2-RC risk score (≥ 20%) and SIPS positive symptom total scores (≥ 10). The main outcome was conversion to psychosis and poor functional outcomes, defined as a global assessment of function (GAF) score lower than 60 at follow-up.

RESULTS

In higher-risk CHR individuals, we found no significant difference in the rate of conversion to psychosis or poor functional outcomes between the antipsychotic and no-antipsychotic groups. Low-risk individuals treated with antipsychotic drugs were more likely exhibit poor functional outcomes compared with the no-antipsychotics group(NAPLS-2-RC estimated risk: χ² = 8.330, p = 0.004; Positive symptom severity: χ² = 12.997, p < 0.001). No significant effective factors were identified for prevention of the conversion to psychosis; conversely, CHR individuals who were treated with high dose antipsychotics (olanzapine, aripiprazole) showed a significantly increased risk of poor functional outcomes.

CONCLUSIONS

In CHR individuals, antipsychotic treatment should be provided with caution because of the risk of poor functional outcomes. Further, antipsychotic treatment does not appear to prevent onset of psychosis in real-world settings.

Neurometabolic patterns of an "at risk for mental disorders" syndrome involve abnormalities in the thalamus and anterior midcingulate cortex

BACKGROUND

The ultra-high risk (UHR) paradigm allows the investigation of individuals at increased risk of developing psychotic or other mental disorders with the aim of making prevention and early intervention as specific as possible in terms of the individual outcome.

METHODS

Single-session ¹H-/³¹P-Chemical Shift Imaging of thalamus, prefrontal (DLPFC) and anterior midcingulate (aMCC) cortices was applied to 69 UHR patients for psychosis and 61 matched healthy controls. N-acetylaspartate (NAA), glutamate/glutamine complex (Glx), energy (PCr, ATP) and phospholipid metabolites were assessed, analysed by ANOVA (or ANCOVA [with covariates]) and correlated with symptomatology (SCL-90R).

RESULTS

The thalamus showed decreased NAA, inversely correlated with self-rated aggressiveness, as well as increased PCr, and altered phospholipid breakdown. While the aMCC showed a pattern of NAA decrease and PCr increase, the DLPFC showed PCr increase only in the close-to-psychosis patient subgroup. There were no specific findings in transition patients.

CONCLUSION

The results do not support the notion of a specific pre-psychotic neurometabolic pattern, but likely reflect correlates of an "at risk for mental disorders syndrome". This includes disturbed neuronal (mitochondrial) metabolism in the thalamus and aMCC, with emphasis on left-sided structures, and altered PL remodeling across structures.

Frontostriatothalamic effective connectivity and dopaminergic function in the psychosis continuum

Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.

Early Detection and Prevention of Schizophrenic Psychosis-A Review

Psychotic disorders often run a chronic course and are associated with a considerable emotional and social impact for patients and their relatives. Therefore, early recognition, combined with the possibility of preventive intervention, is urgently warranted since the duration of untreated psychosis (DUP) significantly determines the further course of the disease. In addition to established diagnostic tools, neurobiological factors in the development of schizophrenic psychoses are increasingly being investigated. It is shown that numerous molecular alterations already exist before the clinical onset of the disease. As schizophrenic psychoses are not elicited by a single mutation in the deoxyribonucleic acid (DNA) sequence, epigenetics likely constitute the missing link between environmental influences and disease development and could potentially serve as a biomarker. The results from transcriptomic and proteomic studies point to a dysregulated immune system, likely evoked by epigenetic alterations. Despite the increasing knowledge of the neurobiological mechanisms involved in the development of psychotic disorders, further research efforts with large population-based study designs are needed to identify suitable biomarkers. In conclusion, a combination of blood examinations, functional imaging techniques, electroencephalography (EEG) investigations and polygenic risk scores should be considered as the basis for predicting how subjects will transition into manifest psychosis.

Adverse clinical outcomes in people at clinical high-risk for psychosis related to altered interactions between hippocampal activity and glutamatergic function

Preclinical rodent models suggest that psychosis involves alterations in the activity and glutamatergic function in the hippocampus, driving dopamine activity through projections to the striatum. The extent to which this model applies to the onset of psychosis in clinical subjects is unclear. We assessed whether interactions between hippocampal glutamatergic function and activity/striatal connectivity are associated with adverse clinical outcomes in people at clinical high-risk (CHR) for psychosis. We measured functional Magnetic Resonance Imaging of hippocampal activation/connectivity, and 1H-Magnetic Resonance Spectroscopy of hippocampal glutamatergic metabolites in 75 CHR participants and 31 healthy volunteers. At follow-up, 12 CHR participants had transitioned to psychosis and 63 had not. Within the clinical high-risk cohort, at follow-up, 35 and 17 participants had a poor or a good functional outcome, respectively. The onset of psychosis (ppeakFWE = 0.003, t = 4.4, z = 4.19) and a poor functional outcome (ppeakFWE < 0.001, t = 5.52, z = 4.81 and ppeakFWE < 0.001, t = 5.25, z = 4.62) were associated with a negative correlation between the hippocampal activation and hippocampal Glx concentration at baseline. In addition, there was a negative association between hippocampal Glx concentration and hippocampo-striatal connectivity (ppeakFWE = 0.016, t = 3.73, z = 3.39, ppeakFWE = 0.014, t = 3.78, z = 3.42, ppeakFWE = 0.011, t = 4.45, z = 3.91, ppeakFWE = 0.003, t = 4.92, z = 4.23) in the total CHR sample, not seen in healthy volunteers. As predicted by preclinical models, adverse clinical outcomes in people at risk for psychosis are associated with altered interactions between hippocampal activity and glutamatergic function.

Neural Correlates of Aberrant Salience and Source Monitoring in Schizophrenia and At-Risk Mental States-A Systematic Review of fMRI Studies

Cognitive biases are an important factor contributing to the development and symptom severity of psychosis. Despite the fact that various cognitive biases are contributing to psychosis, they are rarely investigated together. In the current systematic review, we aimed at investigating specific and shared functional neural correlates of two important cognitive biases: aberrant salience and source monitoring. We conducted a systematic search of fMRI studies of said cognitive biases. Eight studies on aberrant salience and eleven studies on source monitoring were included in the review. We critically discussed behavioural and neuroimaging findings concerning cognitive biases. Various brain regions are associated with aberrant salience and source monitoring in individuals with schizophrenia and the risk of psychosis. The ventral striatum and insula contribute to aberrant salience. The medial prefrontal cortex, superior and middle temporal gyrus contribute to source monitoring. The anterior cingulate cortex and hippocampus contribute to both cognitive biases, constituting a neural overlap. Our review indicates that aberrant salience and source monitoring may share neural mechanisms, suggesting their joint role in producing disrupted external attributions of perceptual and cognitive experiences, thus elucidating their role in positive symptoms of psychosis. Account bridging mechanisms of these two biases is discussed. Further studies are warranted.

Biomarker Profiles in Psychosis Risk Groups Within Unaffected Relatives Based on Familiality and Age

Investigating biomarkers in unaffected relatives (UR) of individuals with psychotic disorders has already proven productive in research on psychosis neurobiology. However, there is considerable heterogeneity among UR based on features linked to psychosis vulnerability. Here, using the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) dataset, we examined cognitive and neurophysiologic biomarkers in first-degree UR of psychosis probands, stratified by 2 widely used risk factors: familiality status of the respective proband (the presence or absence of a first- or second-degree relative with a history of psychotic disorder) and age (within or older than the common age range for developing psychosis). We investigated biomarkers that best differentiate the above specific risk subgroups. Additionally, we examined the relationship of biomarkers with Polygenic Risk Scores for Schizophrenia (PRSSCZ) in a subsample of Caucasian probands and healthy controls (HC). Our results demonstrate that the Brief Assessment of Cognition in Schizophrenia (BACS) score, antisaccade error (ASE) factor, and stop-signal task (SST) factor best differentiate UR (n = 169) from HC (n = 137) (P = .013). Biomarker profiles of UR of familial (n = 82) and non-familial (n = 83) probands were not significantly different. Furthermore, ASE and SST factors best differentiated younger UR (age ≤ 30) (n = 59) from older UR (n = 110) and HC from both age groups (age ≤ 30 years, n=49; age > 30 years, n = 88) (P < .001). In addition, BACS (r = -0.175, P = .006) and ASE factor (r = 0.188, P = .006) showed associations with PRSSCZ. Taken together, our findings indicate that cognitive biomarkers-"top-down inhibition" impairments in particular-may be of critical importance as indicators of psychosis vulnerability.

Computerized Assessment of Psychosis Risk

Early detection and intervention with young people at clinical high risk (CHR) for psychosis is critical for prevention efforts focused on altering the trajectory of psychosis. Early CHR research largely focused on validating clinical interviews for detecting at-risk individuals; however, this approach has limitations related to: (1) specificity (i.e., only 20% of CHR individuals convert to psychosis) and (2) the expertise and training needed to administer these interviews is limited. The purpose of our study is to develop the computerized assessment of psychosis risk (CAPR) battery, consisting of behavioral tasks that require minimal training to administer, can be administered online, and are tied to the neurobiological systems and computational mechanisms implicated in psychosis. The aims of our study are as follows: (1A) to develop a psychosis-risk calculator through the application of machine learning (ML) methods to the measures from the CAPR battery, (1B) evaluate group differences on the risk calculator score and test the hypothesis that the risk calculator score of the CHR group will differ from help-seeking and healthy controls, (1C) evaluate how baseline CAPR battery performance relates to symptomatic outcome two years later (i.e., conversion and symptomatic worsening). These aims will be explored in 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across the study sites. This project will provide a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods that can be used to facilitate the earliest possible detection of psychosis risk.

Imaging synaptic dopamine availability in individuals at clinical high-risk for psychosis: a [11C]-(+)-PHNO PET with methylphenidate challenge study

Patients at clinical high-risk (CHR) for psychosis show elevations in [¹⁸F]DOPA uptake, an estimate of dopamine (DA) synthesis capacity, in the striatum predictive of conversion to schizophrenia. Intrasynaptic DA levels can be inferred from imaging the change in radiotracer binding at D₂ receptors due to a pharmacological challenge. Here, we used methylphenidate, a DA reuptake inhibitor, and [¹¹C]-(+)-PHNO, to measure synaptic DA availability in CHR both in striatal and extra-striatal brain regions. Fourteen unmedicated, nonsubstance using CHR individuals and 14 matched control subjects participated in the study. Subjects underwent two [¹¹C]-(+)-PHNO scans, one at baseline and one following administration of a single oral dose (60 mg) of methylphenidate. [¹¹C]-(+)-PHNO BP_ND, the binding potential relative to the nondisplaceable compartment, was derived using the simplified reference tissue model with cerebellum as reference tissue. The percent change in BP_ND between scans, ΔBP_ND, was computed as an index of synaptic DA availability, and group comparisons were performed with a linear mixed model. An overall trend was found for greater synaptic DA availability (∆BP_ND) in CHR than controls (p = 0.06). This was driven entirely by ∆BP_ND in ventral striatum (-34 ± 14% in CHR, -20 ± 12% in HC; p = 0.023). There were no significant group differences in any other brain region. There were no significant differences in DA transmission in any striatal region between converters and nonconverters, although this finding is limited by the small sample size (N = 2). There was a strong and negative correlation between ΔBP_ND in VST and severity of negative symptoms at baseline in the CHR group (r = -0.66, p < 0.01). We show abnormally increased DA availability in the VST in CHR and an inverse relationship with negative symptoms. Our results suggest a potential early role for mesolimbic dopamine overactivity in CHR. Longitudinal studies are needed to ascertain the significance of the differential topography observed here with the [¹⁸F]DOPA literature.

The relationship between grey matter volume and striatal dopamine function in psychosis: a multimodal 18F-DOPA PET and voxel-based morphometry study

A leading hypothesis for schizophrenia and related psychotic disorders proposes that cortical brain disruption leads to subcortical dopaminergic dysfunction, which underlies psychosis in the majority of patients who respond to treatment. Although supported by preclinical findings that prefrontal cortical lesions lead to striatal dopamine dysregulation, the relationship between prefrontal structural volume and striatal dopamine function has not been tested in people with psychosis. We therefore investigated the in vivo relationship between striatal dopamine synthesis capacity and prefrontal grey matter volume in treatment-responsive patients with psychosis, and compared them to treatment non-responsive patients, where dopaminergic mechanisms are not thought to be central. Forty patients with psychosis across two independent cohorts underwent ¹⁸F-DOPA PET scans to measure dopamine synthesis capacity (indexed as the influx rate constant K_i^cer) and structural 3T MRI. The PET, but not MR, data have been reported previously. Structural images were processed using DARTEL-VBM. GLM analyses were performed in SPM12 to test the relationship between prefrontal grey matter volume and striatal K_i^cer. Treatment responders showed a negative correlation between prefrontal grey matter and striatal dopamine synthesis capacity, but this was not evident in treatment non-responders. Specifically, we found an interaction between treatment response, whole striatal dopamine synthesis capacity and grey matter volume in left (pFWE corr. = 0.017) and right (pFWE corr. = 0.042) prefrontal cortex. We replicated the finding in right prefrontal cortex in the independent sample (pFWE corr. = 0.031). The summary effect size was 0.82. Our findings are consistent with the long-standing hypothesis of dysregulation of the striatal dopaminergic system being related to prefrontal cortex pathology in schizophrenia, but critically also extend the hypothesis to indicate it can be applied to treatment-responsive schizophrenia only. This suggests that different mechanisms underlie the pathophysiology of treatment-responsive and treatment-resistant schizophrenia.

Positive symptom phenotypes appear progressively in "EDiPS", a new animal model of the schizophrenia prodrome

An increase in dopamine (DA) synthesis capacity in the dorsal striatum (DS) during the prodromal stage of schizophrenia becomes more pronounced as patients progress to the full disorder. Understanding this progression is critical to intervening in disease course. We developed an animal model-Enhanced Dopamine in Prodromal Schizophrenia (EDiPS)-which uses a genetic construct to increase DA synthesis capacity in the DS of male rats. We assessed pre-pulse inhibition (PPI) and amphetamine (AMPH)-induced locomotion (0.6 mg/kg) in EDiPS animals longitudinally after post-natal day 35 (when the EDiPS construct is administered). We also assessed their response to repeated acute restraint stress. In adult EDiPS animals, we measured baseline and evoked extracellular DA levels, and their stereotyped responses to 5 mg/kg AMPH. AMPH-induced hyperlocomotion was apparent in EDiPS animals 6-weeks after construct administration. There was an overall PPI deficit in EDiPS animals across all timepoints, however the stress response of EDiPS animals was unaltered. Adult EDiPS animals show normal baseline and potassium-evoked DA release in the DS. These findings suggest that key behavioural phenotypes in EDiPS animals show a progressive onset, similar to that demonstrated by patients as they transition to schizophrenia. The EDiPS model could therefore be used to investigate the molecular mechanisms underlying the prodrome of schizophrenia.

Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review

Psychotic disorders are highly debilitating and constitute a major public health burden. Identifying markers of psychosis risk and resilience is a necessary step toward understanding etiology and informing prevention and treatment efforts in individuals at clinical high risk (CHR) for psychosis. In this context, it is important to consider that neural risk markers have been particularly useful in identifying mechanistic determinants along with predicting clinical outcomes. Notably, despite a growing body of supportive literature and the promise of recent findings identifying potential neural markers, the current work on CHR resilience markers has received little attention. The present review provides a brief overview of brain-based risk markers with a focus on predicting symptom course. Next, the review turns to protective markers, examining research from nonpsychiatric and schizophrenia fields to build an understanding of framing, priorities, and potential, applying these ideas to contextualizing a small but informative body of resiliency-relevant CHR research. Four domains (neurocognition, emotion regulation, allostatic load, and sensory and sensorimotor function) were identified and are discussed in terms of behavioral and neural markers. Taken together, the literature suggests significant predictive value for brain-based markers for individuals at CHR for psychosis, and the limited but compelling resiliency work highlights the critical importance of expanding this promising area of inquiry.

High schizotypy traits are associated with reduced hippocampal resting state functional connectivity

Altered hippocampal functioning is proposed to play a critical role in the development of schizophrenia-spectrum disorders. Previous resting state functional Magnetic Resonance Imaging (rs-fMRI) studies report disrupted hippocampal connectivity in patients with psychosis and in individuals with clinical high risk, yet hippocampal connectivity has not been investigated in people with high schizotypy traits. Here we used rs-fMRI to examine hippocampal connectivity in healthy people with low (LS, n = 23) and high levels (HS, n = 22) of schizotypal traits assessed using the Schizotypy Personality Questionnaire. Using a bilateral hippocampal seed region, we examined resting state functional connectivity (RSFC) between hippocampus and striatal, thalamic and prefrontal cortex regions of interest. Compared to LS, HS participants showed lower RSFC between hippocampus and striatum and between hippocampus and thalamus. Whilst the group effect of reduced hippocampal RSFC in striatal and thalamic regions was driven by total schizotypy scores, positive schizotypy subfactor scores were significantly positively correlated with hippocampus-caudate/thalamus RSFC. Group differences in RSFC were not observed between hippocampus and prefrontal cortex. These results demonstrate that subclinical schizotypal traits are associated with altered hippocampal connectivity in striatal and thalamic regions and provide further support that hippocampal dysconnectivity confers risk for schizophrenia spectrum disorders.

Predicting the individual risk of psychosis conversion in at-risk mental state (ARMS): a multivariate model reveals the influence of nonpsychotic prodromal symptoms

To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS' symptoms at first presentation and using a multivariate machine learning method known as logistic regression with Elastic-net shrinkage. 46 young individuals who sought help from the specialized outpatient unit at Sainte-Anne hospital and who met CAARMS criteria for UHR were assessed, among whom 27 were reassessed at follow-up (22.4 ± 6.54 months) and included in the analysis. Elastic net logistic regression was trained, using CAARMS items at baseline to predict individual evolution between converters (UHR-P) and non-converters (UHR-NP). Elastic-net was used to select the few CAARMS items that best predict the clinical evolution. All validations and significances of predictive models were computed with non-parametric re-sampling strategies that provide robust estimators even when the distributional assumption cannot be guaranteed. Among the 25 CAARMS items, the Elastic net selected 'obsessive-compulsive symptoms' and 'aggression/dangerous behavior' as risk factors for conversion while 'anhedonia' and 'mood swings/lability' were associated with non-conversion at follow-up. In the ten-fold stratified cross-validation, the classification achieved 81.8% of sensitivity (P = 0.035) and 93.7% of specificity (P = 0.0016). Non-psychotic prodromal symptoms bring valuable information to improve the prediction of conversion to psychosis. Elastic net logistic regression applied to clinical data is a promising way to switch from group prediction to an individualized prediction.

Structural and functional imaging markers for susceptibility to psychosis

The introduction of clinical criteria for the operationalization of psychosis high risk provided a basis for early detection and treatment of vulnerable individuals. However, about two-thirds of people meeting clinical high-risk (CHR) criteria will never develop a psychotic disorder. In the effort to increase prognostic precision, structural and functional neuroimaging have received growing attention as a potentially useful resource in the prediction of psychotic transition in CHR patients. The present review summarizes current research on neuroimaging biomarkers in the CHR state, with a particular focus on their prognostic utility and limitations. Large, multimodal/multicenter studies are warranted to address issues important for clinical applicability such as generalizability and replicability, standardization of clinical definitions and neuroimaging methods, and consideration of contextual factors (e.g., age, comorbidity).

Predicting psychosis risk using a specific measure of cognitive control: a 12-month longitudinal study

BACKGROUND

Identifying risk factors of individuals in a clinical-high-risk state for psychosis are vital to prevention and early intervention efforts. Among prodromal abnormalities, cognitive functioning has shown intermediate levels of impairment in CHR relative to first-episode psychosis and healthy controls, highlighting a potential role as a risk factor for transition to psychosis and other negative clinical outcomes. The current study used the AX-CPT, a brief 15-min computerized task, to determine whether cognitive control impairments in CHR at baseline could predict clinical status at 12-month follow-up.

METHODS

Baseline AX-CPT data were obtained from 117 CHR individuals participating in two studies, the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP) and the Understanding Early Psychosis Programs (EP) and used to predict clinical status at 12-month follow-up. At 12 months, 19 individuals converted to a first episode of psychosis (CHR-C), 52 remitted (CHR-R), and 46 had persistent sub-threshold symptoms (CHR-P). Binary logistic regression and multinomial logistic regression were used to test prediction models.

RESULTS

Baseline AX-CPT performance (d-prime context) was less impaired in CHR-R compared to CHR-P and CHR-C patient groups. AX-CPT predictive validity was robust (0.723) for discriminating converters v. non-converters, and even greater (0.771) when predicting CHR three subgroups.

CONCLUSIONS

These longitudinal outcome data indicate that cognitive control deficits as measured by AX-CPT d-prime context are a strong predictor of clinical outcome in CHR individuals. The AX-CPT is brief, easily implemented and cost-effective measure that may be valuable for large-scale prediction efforts.

Timing of menarche and abnormal hippocampal connectivity in youth at clinical-high risk for psychosis

The "estrogen hypothesis" suggests that estrogen is a protective factor against psychotic disorders such as schizophrenia. Although the precise protective mechanisms are still unclear, one potential explanation lies in the role that increased estrogens play in mediating hippocampal plasticity, as this may reduce hippocampal dysconnectivity that is characteristically observed in psychosis. In support of this view, later age at menarche- less available estrogen during critical early adolescent development- is related to earlier onset of psychosis and increased symptom severity. Furthermore, if estrogens have protective effects, then we should see this effect in the psychosis risk period in those at clinical high-risk (CHR) for psychosis - i.e., individuals showing attenuated symptoms at imminent risk for transitioning to a psychotic diagnosis. This study examined whether earlier age at menarche would result in more normative hippocampal connectivity in CHR youth; menarche is an easily assessed, developmental marker associated with the availability of estrogens. Resting-state connectivity was examined in sixty female participants (26 CHR and 34 healthy control; age 12-21) using a cross-sectional approach; hippocampal connectivity was found to relate to age at menarche. Later age at menarche in the CHR group related to increased hippocampal dysconnectivity to the occipital cortex (a region with a neurotrophic response to estrogen) compared to the controls. Results suggest that earlier availability of estrogens may have neuroprotective effects on hippocampal plasticity. Findings have relevance for understanding sex differences and etiology, as well as guiding novel treatments.

Adolescents at clinical high risk for psychosis show qualitatively altered patterns of activation during rule learning

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Novel investigation of novel rule learning in psychosis risk.

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Failed to replicate previous study comparing novel and practiced rule learning.

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No significant group differences, but effect size comparison revealed differences.

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Results suggest that psychosis risk group may rely on different rule retrieval strategies.

Background

The ability to flexibly apply rules to novel situations is a critical aspect of adaptive human behavior. While executive function deficits are known to appear early in the course of psychosis, it is unclear which specific facets are affected. Identifying whether rule learning is impacted at the early stages of psychosis is necessary for truly understanding the etiology of psychosis and may be critical for designing novel treatments. Therefore, we examined rule learning in healthy adolescents and those meeting criteria for clinical high risk (CHR) for psychosis.

Methods

24 control and 22 CHR adolescents underwent rapid, high-resolution fMRI while performing a paradigm which required them to apply novel or practiced task rules.

Results

Previous work has suggested that practiced rules rely on rostrolateral prefrontal cortex (RLPFC) during rule encoding and dorsolateral prefrontal cortex (DLPFC) during task performance, while novel rules show the opposite pattern. We failed to replicate this finding, with greater activity for novel rules during performance. Comparing the HC and CHR group, there were no statistically significant effects, but an effect size analysis found that the CHR group showed less activation during encoding and greater activation during performance. This suggests the CHR group may use less efficient reactive control to retrieve task rules at the time of task performance, rather than proactively during rule encoding.

Conclusions

These findings suggest that flexibility is qualitatively altered in the clinical high risk state, however, more data is needed to determine whether these deficits predict disease progression.

Atypical processing of uncertainty in individuals at risk for psychosis

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Humans at psychosis clinical high risk (CHR) over-estimate environmental volatility.

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Low-level prediction error (PE) signals evoke increased frontal activity in CHR.

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Volatility-related PEs are associated with reduced frontal activity in CHR.

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Frontal cortical activation to low-level PEs reflects impaired clinical functioning.

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Atypical PE learning signal representations may promote delusion formation in CHR.

Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals.

Non-medicated CHR individuals (n = 13) and control participants (n = 13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data.

Computational modelling of CHR individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning.

Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.

The benefit of foresight? An ethical evaluation of predictive testing for psychosis in clinical practice

Risk prediction for psychosis has advanced to the stage at which it could feasibly become a clinical reality. Neuroimaging biomarkers play a central role in many risk prediction models. Using such models to predict the likelihood of transition to psychosis in individuals known to be at high risk has the potential to meaningfully improve outcomes, principally through facilitating early intervention. However, this compelling benefit must be evaluated in light of the broader ethical ramifications of this prospective development in clinical practice. This paper advances ethical discussion in the field in two ways: firstly, through in-depth consideration of the distinctive implications of the clinical application of predictive tools; and, secondly, by evaluating the manner in which newer predictive models incorporating neuroimaging alter the ethical landscape. We outline the current state of the science of predictive testing for psychosis, with a particular focus on emerging neuroimaging biomarkers. We then proceed to ethical analysis employing the four principles of biomedical ethics as a conceptual framework. We conclude with a call for scientific advancement to proceed in tandem with ethical consideration, informed by empirical study of the views of high risk individuals and their families. This collaborative approach will help ensure that predictive testing progresses in an ethically acceptable manner that minimizes potential adverse effects and maximizes meaningful benefits for those at high risk of psychosis.

Selective Review of Neuroimaging Findings in Youth at Clinical High Risk for Psychosis: On the Path to Biomarkers for Conversion

First episode psychosis (FEP), and subsequent diagnosis of schizophrenia or schizoaffective disorder, predominantly occurs during late adolescence, is accompanied by a significant decline in function and represents a traumatic experience for patients and families alike. Prior to first episode psychosis, most patients experience a prodromal period of 1-2 years, during which symptoms first appear and then progress. During that time period, subjects are referred to as being at Clinical High Risk (CHR), as a prodromal period can only be designated in hindsight in those who convert. The clinical high-risk period represents a critical window during which interventions may be targeted to slow or prevent conversion to psychosis. However, only one third of subjects at clinical high risk will convert to psychosis and receive a formal diagnosis of a primary psychotic disorder. Therefore, in order for targeted interventions to be developed and applied, predicting who among this population will convert is of critical importance. To date, a variety of neuroimaging modalities have identified numerous differences between CHR subjects and healthy controls. However, complicating attempts at predicting conversion are increasingly recognized co-morbidities, such as major depressive disorder, in a significant number of CHR subjects. The result of this is that phenotypes discovered between CHR subjects and healthy controls are likely non-specific to psychosis and generalized for major mental illness. In this paper, we selectively review evidence for neuroimaging phenotypes in CHR subjects who later converted to psychosis. We then evaluate the recent landscape of machine learning as it relates to neuroimaging phenotypes in predicting conversion to psychosis.

Brain functional connectivity data enhance prediction of clinical outcome in youth at risk for psychosis

The first episode of psychosis is typically preceded by a prodromal phase with subthreshold symptoms and functional decline. Improved outcome prediction in this stage is needed to allow targeted early intervention. This study assesses a combined clinical and resting-state fMRI prediction model in 137 adolescents and young adults at Clinical High Risk (CHR) for psychosis from the Shanghai At Risk for Psychosis (SHARP) program. Based on outcome at one-year follow-up, participants were separated into three outcome categories including good outcome (symptom remission, N = 71), intermediate outcome (ongoing CHR symptoms, N = 30), and poor outcome (conversion to psychosis or treatment-refractory, N = 36). Validated clinical predictors from the psychosis-risk calculator were combined with measures of resting-state functional connectivity. Using multinomial logistic regression analysis and leave-one-out cross-validation, a clinical-only prediction model did not achieve a significant level of outcome prediction (F₁ = 0.32, p = .154). An imaging-only model yielded a significant prediction model (F₁ = 0.41, p = .016), but a combined model including both clinical and connectivity measures showed the best performance (F₁ = 0.46, p < .001). Influential predictors in this model included functional decline, verbal learning performance, a family history of psychosis, default-mode and frontoparietal within-network connectivity, and between-network connectivity among language, salience, dorsal attention, sensorimotor, and cerebellar networks. These findings suggest that brain changes reflected by alterations in functional connectivity may be useful for outcome prediction in the prodromal stage.

Discovery and Validation of Prediction Algorithms for Psychosis in Youths at Clinical High Risk

In the past 2 to 3 decades, clinicians have used the clinical high risk for psychosis (CHR-P) paradigm to better understand factors that contribute to the onset of psychotic disorders. While this paradigm is useful to identify individuals at risk, the CHR-P criteria are not sufficient to predict outcomes from the CHR-P population. Because approximately 25% of the CHR-P population will ultimately convert to psychosis, more precise methods of prediction are needed to account for heterogeneity in both risk factors and outcomes in the CHR-P population. To this end, several groups in recent years have used data-driven approaches to refine predictive algorithms to predict both conversion to psychosis and functional outcomes. These models have generally used either clinical and behavioral data, including demographics and measures of symptom severity, neurocognitive functioning, and social functioning, or neuroimaging data, including structural and functional measures, to predict conversion to psychosis in CHR-P samples. This review focuses on the empirical models that have been derived within each of these lines of research and evaluates the performance and methodology of these models. This review also serves to inform best practices for data-driven approaches and directions moving forward to improve our prediction of psychotic disorders and associated outcomes. Because sample size is still the most critical consideration in the current models, we urge that algorithms to predict conversion be conducted using multisite data in order to obtain the power necessary to conclusively determine predictive accuracy without overfitting.

Emerging Temporal Lobe Dysfunction in People at Clinical High Risk for Psychosis

Clinical high-risk (CHR) individuals have been increasingly utilized to investigate the prodromal phases of psychosis and progression to illness. Research has identified medial and lateral temporal lobe abnormalities in CHR individuals. Dysfunction in the medial temporal lobe, particularly the hippocampus, is linked to dysregulation of glutamate and dopamine via a hippocampal-striatal-midbrain network that may lead to aberrant signaling of salience underpinning the formation of delusions. Similarly, lateral temporal dysfunction may be linked to the disorganized speech and language impairments observed in the CHR stage. Here, we summarize the significance of these neurobiological findings in terms of emergent psychotic symptoms and conversion to psychosis in CHR populations. We propose key questions for future work with the aim to identify the neural mechanisms that underlie the development of psychosis.

Enhanced Dopamine in Prodromal Schizophrenia (EDiPS): a new animal model of relevance to schizophrenia

One of the most robust neurochemical abnormalities reported in patients living with schizophrenia is an increase in dopamine (DA) synthesis and release in the dorsal striatum (DS). Importantly, it appears that this increase progresses as a patient transitions from a prodromal stage to the clinical diagnosis of schizophrenia. Here we have recreated this pathophysiology in an animal model by increasing the capacity for DA synthesis preferentially within the DS. To achieve this we administer a genetic construct containing the rate-limiting enzymes in DA synthesis—tyrosine hydroxylase (TH), and GTP cyclohydrolase 1 (GCH1) (packaged within an adeno-associated virus)—into the substantia nigra pars compacta (SNpc) of adolescent animals. We refer to this model as “Enhanced Dopamine in Prodromal Schizophrenia” (EDiPS). We first confirmed that the TH enzyme is preferentially increased in the DS. As adults, EDiPS animals release significantly more DA in the DS following a low dose of amphetamine (AMPH), have increased AMPH-induced hyperlocomotion and show deficits in pre-pulse inhibition (PPI). The glutamatergic response to AMPH is also altered, again in the DS. EDiPS represents an ideal experimental platform to (a) understand how a preferential increase in DA synthesis capacity in the DS relates to “positive” symptoms in schizophrenia; (b) understand how manipulation of DS DA may influence other neurotransmitter systems shown to be altered in patients with schizophrenia; (c) allow researchers to follow an “at risk”-like disease course from adolescence to adulthood; and (d) ultimately allow trials of putative prophylactic agents to prevent disease onset in vulnerable populations.

Brain regional homogeneity and function connectivity in attenuated psychosis syndrome -based on a resting state fMRI study

BACKGROUND

By combining regional homogeneity (ReHo) and functional connectivity (FC) analyses, this study aimed to explore brain functional alterations in Attenuated Psychosis Syndrome (APS), which could provide complementary information for the neurophysiological indicators for schizophrenia (SZ) associated brain dysfunction.

METHODS

Twenty-one APS subjects and twenty healthy controls were enrolled in the data acquisition of demographics and clinical characteristics as well as structural and resting-state functional magnetic resonance imaging (rs-fMRI). ReHo analysis was conducted to determine the peak coordinate of the abnormal regional brain activity. Then, identified brain regions were considered as seed regions and were used to calculate FC between reginal brain voxels and whole brain voxels. Finally, potential correlations between imaging indices and clinical data were also explored.

RESULTS

Four APS and two HC subjects were excluded because the largest dynamic translation or rotation had exceeded 2 mm / 2°. Compared with healthy controls (HCs), APS subjects exhibited higher ReHo values in the right middle temporal gyrus (MTG) and lower ReHo values in the left middle frontal gyrus (MFG), left superior frontal gyrus (SFG), left postcentral gyrus (PoCG), and left superior frontal gyrus, medial (SFGmed). Considered these areas as seed regions, the APS subjects showed abnormal enhancement in functional brain connections, predominantly in the frontal and temporal lobes.

CONCLUSIONS

We concluded that the APS subjects had spatially regional dysfunction and remoted synchronous dysfunction in the frontal and temporal lobes of the brain, and changes in ReHo and FC patterns may reveal the mechanism of brain dysfunctions and may serve as an imaging biomarker for the diagnosis and evaluation of SZ.

Brain volumetric alterations accompanied with loss of striatal medium-sized spiny neurons and cortical parvalbumin expressing interneurons in Brd1+/- mice

Schizophrenia is a common and severe mental disorder arising from complex gene-environment interactions affecting brain development and functioning. While a consensus on the neuroanatomical correlates of schizophrenia is emerging, much of its fundamental pathobiology remains unknown. In this study, we explore brain morphometry in mice with genetic susceptibility and phenotypic relevance to schizophrenia (Brd1^+/− mice) using postmortem 3D MR imaging coupled with histology, immunostaining and regional mRNA marker analysis. In agreement with recent large-scale schizophrenia neuroimaging studies, Brd1^+/− mice displayed subcortical abnormalities, including volumetric reductions of amygdala and striatum. Interestingly, we demonstrate that structural alteration in striatum correlates with a general loss of striatal neurons, differentially impacting subpopulations of medium-sized spiny neurons and thus potentially striatal output. Akin to parvalbumin interneuron dysfunction in patients, a decline in parvalbumin expression was noted in the developing cortex of Brd1^+/− mice, mainly driven by neuronal loss within or near cortical layer V, which is rich in corticostriatal projection neurons. Collectively, our study highlights the translational value of the Brd1^+/− mouse as a pre-clinical tool for schizophrenia research and provides novel insight into its developmental, structural, and cellular pathology.

Effect of Cannabidiol on Medial Temporal, Midbrain, and Striatal Dysfunction in People at Clinical High Risk of Psychosis: A Randomized Clinical Trial

Importance

Cannabidiol (CBD) has antipsychotic effects in humans, but how these are mediated in the brain remains unclear.

Objective

To investigate the neurocognitive mechanisms that underlie the therapeutic effects of CBD in psychosis.

Design, Setting, and Participants

In this parallel-group, double-blind, placebo-controlled randomized clinical trial conducted at the South London and Maudsley NHS Foundation Trust in London, United Kingdom, 33 antipsychotic medication-naive participants at clinical high risk (CHR) of psychosis and 19 healthy control participants were studied. Data were collected from July 2013 to October 2016 and analyzed from November 2016 to October 2017.

Interventions

A total of 16 participants at CHR of psychosis received a single oral dose of 600 mg of CBD, and 17 participants at CHR received a placebo. Control participants were not given any drug. All participants were then studied using functional magnetic resonance imaging (fMRI) while performing a verbal learning task.

Main Outcomes and Measures

Brain activation during verbal encoding and recall, indexed using the blood oxygen level-dependent hemodynamic response fMRI signal.

Results

Of the 16 participants in the CBD group, 6 (38%) were female, and the mean (SD) age was 22.43 (4.95) years; of 17 in the placebo group, 10 (59%) were female, and the mean (SD) age was 25.35 (5.24) years; and of 19 in the control group, 8 (42%) were female, and the mean (SD) age was 23.89 (4.14) years. Brain activation (indexed using the median sum of squares ratio of the blood oxygen level-dependent hemodynamic response effects model component to the residual sum of squares) was analyzed in 15 participants in the CBD group, 16 in the placebo group, and 19 in the control group. Participants receiving placebo had reduced activation relative to controls in the right caudate during encoding (placebo: median, -0.027; interquartile range [IQR], -0.041 to -0.016; control: median, 0.020; IQR, -0.022 to 0.056; P < .001) and in the parahippocampal gyrus and midbrain during recall (placebo: median, 0.002; IQR, -0.016 to 0.010; control: median, 0.035; IQR, 0.015 to 0.039; P < .001). Within these 3 regions, activation in the CBD group was greater than in the placebo group but lower than in the control group (parahippocampal gyrus/midbrain: CBD: median, -0.013; IQR, -0.027 to 0.002; placebo: median, -0.007; IQR, -0.019 to 0.008; control: median, 0.034; IQR, 0.005 to 0.059); the level of activation in the CBD group was thus intermediate to that in the other 2 groups. There were no significant group differences in task performance.

Conclusions and Relevance

Cannabidiol may partially normalize alterations in parahippocampal, striatal, and midbrain function associated with the CHR state. As these regions are critical to the pathophysiology of psychosis, the influence of CBD at these sites could underlie its therapeutic effects on psychotic symptoms.

Trial Registration

isrctn.org Identifier: ISRCTN46322781.

Increased Resting Hippocampal and Basal Ganglia Perfusion in People at Ultra High Risk for Psychosis: Replication in a Second Cohort

We recently reported that resting hippocampal, basal ganglia and midbrain perfusion is elevated in people at ultra high risk (UHR) for psychosis. The present study sought to replicate our previous finding in an independent UHR cohort, and examined the relationship between resting perfusion in these regions, psychosis and depression symptoms, and traumatic experiences in childhood. Pseudo-Continuous Arterial Spin Labelling (p-CASL) imaging was used to measure resting cerebral blood flow (rCBF) in 77 UHR for psychosis individuals and 25 healthy volunteers in a case-control design. UHR participants were recruited from clinical early detection services at 3 sites in the South of England. Symptoms levels were assessed using the Comprehensive Assessment of At Risk Mental States (CAARMS), the Hamilton Depression Scale (HAM-D), and childhood trauma was assessed retrospectively using the Childhood Trauma Questionnaire (CTQ). Right hippocampal and basal ganglia rCBF were significantly increased in UHR subjects compared to controls, partially replicating our previous finding in an independent cohort. In UHR participants, positive symptoms were positively correlated with rCBF in the right pallidum. CTQ scores were positively correlated with rCBF values in the bilateral hippocampus and negatively associated with rCBF in the left prefrontal cortex. Elevated resting hippocampal and basal ganglia activity appears to be a consistent finding in individuals at high risk for psychosis, consistent with data from preclinical models of the disorder. The association with childhood trauma suggests that its influence on the risk of psychosis may be mediated through an effect on hippocampal function.

Early intervention for everyone? A review of cross-cultural issues and their treatment in ultra-high-risk (UHR) cohorts

AIM

Over the past 20 years, early management of psychosis has become both a research and policy priority. In Western countries, psychotic disorders appear more prevalent in migrant and minority ethnic groups than in native or dominant groups. Moreover, disparities exist in health conditions and access to care among immigrants and minority ethnic groups, compared with native-born and majority groups. Appropriate early detection tools are necessary for the different groups.

METHODS

This systematic review provides a synthesis of the assessment and discussion of transcultural issues in ultra-high-risk (UHR) cohorts. The Medline database was searched via PubMed for peer-reviewed articles published in English from 1995 to 2017. All 79 studies included are prospective UHR cohort studies that used the Comprehensive Assessment of At-Risk Mental States (CAARMS).

RESULTS

In UHR cohort studies that used the CAARMS, transcultural data (native language, ethnicity, place of birth, migration) are rarely collected, and inadequate ability to speak the dominant language is a common exclusion criterion. When they are included, the CAARMS scores differ between some minorities and the native-born majority group.

CONCLUSIONS

This systematic review demonstrates barriers to the access to participation in early intervention research for migrants and ethnic minorities. This selection bias may result in lower validity for the CAARMS among these populations and thus in inadequate intervention programmes. Along with targeted studies, minorities' access to participation in UHR cohorts should be improved through 3 tools: interpreters at recruitment and for administration of CAARMS, a guide to cultural formulation and transcultural data collection.

Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization

Understanding the fundamental alterations in brain functioning that lead to psychotic disorders remains a major challenge in clinical neuroscience. In particular, it is unknown whether any state-independent biomarkers can potentially predict the onset of psychosis and distinguish patients from healthy controls, regardless of paradigm. Here, using multi-paradigm fMRI data from the North American Prodrome Longitudinal Study consortium, we show that individuals at clinical high risk for psychosis display an intrinsic “trait-like” abnormality in brain architecture characterized as increased connectivity in the cerebello–thalamo–cortical circuitry, a pattern that is significantly more pronounced among converters compared with non-converters. This alteration is significantly correlated with disorganization symptoms and predictive of time to conversion to psychosis. Moreover, using an independent clinical sample, we demonstrate that this hyperconnectivity pattern is reliably detected and specifically present in patients with schizophrenia. These findings implicate cerebello–thalamo–cortical hyperconnectivity as a robust state-independent neural signature for psychosis prediction and characterization.

Brain function alterations in schizophrenia and other psychotic disorders remain poorly understood. Here, the authors discover that increased neural connectivity in the cerebello-thalamo-cortical circuitry predicts psychosis in those at high risk, and is present in people with schizophrenia.

Verbal learning and hippocampal dysfunction in schizophrenia: A meta-analysis

This meta-analysis summarizes research examining whether deficits in verbal learning are related to bilateral hippocampal volume reductions in patients with or at risk for schizophrenia and in healthy controls. 17 studies with 755 patients with schizophrenia (SCZ), 232 Genetic High Risk (GHR) subjects and 914 healthy controls (HC) were included. Pooled correlation coefficients were calculated between hemisphere (left, right or total) and type of recall (immediate or delayed) for each diagnostic group individually (SCZ, GHR and HC). In SCZ, left and right hippocampal volume positively correlated with immediate (r=0.256, 0.230) and delayed (r=0.132, 0.231) verbal recall. There was also a correlation between total hippocampal volume and delayed recall (r=0.233). None of these correlations were significant in healthy controls. There was however, a positive correlation between left hippocampal volume and immediate recall in the GHR group (r=0.356). The results suggest that hippocampal volume affects immediate and delayed verbal learning capacity in schizophrenia and provides further evidence of hippocampal dysfunction in the pathophysiology of schizophrenia.

At-risk mental state for psychosis: identification and current treatment approaches

The concept of an ‘at-risk mental state’ for psychosis arose from previous work attempting to identify a putative psychosis prodrome. In this article we summarise the current criteria used to identify ‘at-risk’ individuals, such as the ultra-high-risk (UHR) criteria, and the further identification of important clinical risk factors or biomarkers to improve prediction of who might develop a psychotic disorder. We also discuss important ethical issues in classifying and treating at-risk individuals, current treatment trials in this area and what treatment current services can offer.

A Neurophysiological Perspective on a Preventive Treatment against Schizophrenia Using Transcranial Electric Stimulation of the Corticothalamic Pathway

Schizophrenia patients are waiting for a treatment free of detrimental effects. Psychotic disorders are devastating mental illnesses associated with dysfunctional brain networks. Ongoing brain network gamma frequency (30–80 Hz) oscillations, naturally implicated in integrative function, are excessively amplified during hallucinations, in at-risk mental states for psychosis and first-episode psychosis. So, gamma oscillations represent a bioelectrical marker for cerebral network disorders with prognostic and therapeutic potential. They accompany sensorimotor and cognitive deficits already present in prodromal schizophrenia. Abnormally amplified gamma oscillations are reproduced in the corticothalamic systems of healthy humans and rodents after a single systemic administration, at a psychotomimetic dose, of the glutamate N-methyl-d-aspartate receptor antagonist ketamine. These translational ketamine models of prodromal schizophrenia are thus promising to work out a preventive noninvasive treatment against first-episode psychosis and chronic schizophrenia. In the present essay, transcranial electric stimulation (TES) is considered an appropriate preventive therapeutic modality because it can influence cognitive performance and neural oscillations. Here, I highlight clinical and experimental findings showing that, together, the corticothalamic pathway, the thalamus, and the glutamatergic synaptic transmission form an etiopathophysiological backbone for schizophrenia and represent a potential therapeutic target for preventive TES of dysfunctional brain networks in at-risk mental state patients against psychotic disorders.