The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

INTRODUCTION: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention. METHODS: Self-report Likert-scale survey items were administered to individuals being screened with the Structured Interview for Psychosis-risk Syndromes (SIPS) and followed at eight early psychosis clinics. An a priori analytic plan included Spectral Clustering Analysis to reduce the item pool, followed by development of Support Vector Machine (SVM) classifiers. RESULTS: The cross-validated positive predictive value (PPV) of the EPSI at the default cut-off (76.5%) exceeded that of the clinician-administered SIPS (68.5%) at separating individuals who would not convert to psychosis within 12 months from those who either would convert within 12 months or who had already experienced a first episode psychosis (FEP). When used in tandem with the SIPS on clinical high risk participants, the EPSI increased the combined PPV to 86.6%. The SVM classified as FEP/converters only 1% of individuals in non-clinical and 4% of clinical low risk populations. Sensitivity of the EPSI, however, was 51% at the default cut-off. DISCUSSION: The EPSI identifies, comparably to the SIPS but in less time and with fewer resources, individuals who are either at very high risk to develop a psychotic disorder within 12 months or who are already psychotic. At its default cut-off, EPSI misses 49% of current or future psychotic cases. The cut-off can, however, be adjusted based on purpose. The EPSI is the first validated assessment to predict 12-month psychotic conversion. An online screening system, www.eps.telesage.org, is under development.

Hippocampal dysfunction in the pathophysiology of schizophrenia: a selective review and hypothesis for early detection and intervention.

Scientists have long sought to characterize the pathophysiologic basis of schizophrenia and develop biomarkers that could identify the illness. Extensive postmortem and in vivo neuroimaging research has described the early involvement of the hippocampus in the pathophysiology of schizophrenia. In this context, we have developed a hypothesis that describes the evolution of schizophrenia-from the premorbid through the prodromal stages to syndromal psychosis-and posits dysregulation of glutamate neurotransmission beginning in the CA1 region of the hippocampus as inducing attenuated psychotic symptoms and initiating the transition to syndromal psychosis. As the illness progresses, this pathological process expands to other regions of the hippocampal circuit and projection fields in other anatomic areas including the frontal cortex, and induces an atrophic process in which hippocampal neuropil is reduced and interneurons are lost. This paper will describe the studies of our group and other investigators supporting this pathophysiological hypothesis, as well as its implications for early detection and therapeutic intervention.

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire-Brief Version (PQ-B) and 148 additional items were administered to 229 individuals being screened with the SIPS at 7 North American Prodrome Longitudinal Study sites and at Columbia University. Fifty individuals were found to have SIPS scores of 0, 1, or 2, making them clinically low risk (CLR) controls; 144 were classified as clinically high risk (CHR) (SIPS 3-5) and 35 were found to have first episode psychosis (FEP) (SIPS 6). Spectral clustering analysis, performed on 124 of the items, yielded two cohesive item groups, the first mostly related to psychosis and mania, the second mostly related to depression, anxiety, and social and general work/school functioning. Items within each group were sorted according to their usefulness in distinguishing between CLR and CHR individuals using the Minimum Redundancy Maximum Relevance procedure. A receiver operating characteristic area under the curve (AUC) analysis indicated that maximal differentiation of CLR and CHR participants was achieved with a 26-item solution (AUC=0.899±0.001). The EPS-26 outperformed the PQ-B (AUC=0.834±0.001). For screening purposes, the self-report EPS-26 appeared to differentiate individuals who are either CLR or CHR approximately as well as the clinician-administered SIPS. The EPS-26 may prove useful as a self-report screener and may lead to a decrease in the duration of untreated psychosis. A validation of the EPS-26 against actual conversion is underway.

Baseline demographics, clinical features and predictors of conversion among 200 individuals in a longitudinal prospective psychosis-risk cohort.

BACKGROUND: DSM-5 proposes an Attenuated Psychosis Syndrome (APS) for further investigation, based upon the Attenuated Positive Symptom Syndrome (APSS) in the Structured Interview for Psychosis-Risk Syndromes (SIPS). SIPS Unusual Thought Content, Disorganized Communication and Total Disorganization scores predicted progression to psychosis in a 2015 NAPLS-2 Consortium report. We sought to independently replicate this in a large single-site high-risk cohort, and identify baseline demographic and clinical predictors beyond current APS/APSS criteria. METHOD: We prospectively studied 200 participants meeting criteria for both the SIPS APSS and DSM-5 APS. SIPS scores, demographics, family history of psychosis, DSM Axis-I diagnoses, schizotypy, and social and role functioning were assessed at baseline, with follow-up every 3 months for 2 years. RESULTS: The conversion rate was 30% (n = 60), or 37.7% excluding participants who were followed under 2 years. This rate was stable across time. Conversion time averaged 7.97 months for 60% who developed schizophrenia and 15.68 for other psychoses. Mean conversion age was 20.3 for males and 23.5 for females. Attenuated odd ideas and thought disorder appear to be the positive symptoms which best predict psychosis in a logistic regression. Total negative symptom score, Asian/Pacific Islander and Black/African-American race were also predictive. As no Axis-I diagnosis or schizotypy predicted conversion, the APS is supported as a distinct syndrome. In addition, cannabis use disorder did not increase risk of conversion to psychosis. CONCLUSIONS: NAPLS SIPS findings were replicated while controlling for clinical and demographic factors, strongly supporting the validity of the SIPS APSS and DSM-5 APS diagnosis.

The impact of emotion awareness and regulation on social functioning in individuals at clinical high risk for psychosis.

BACKGROUND: Social functioning (SF) difficulties are ubiquitous among individuals at clinical high risk for psychosis (CHR), but it is not yet clear why. One possibility is suggested by the observation that effective SF requires adaptive emotion awareness and regulation. Previous reports have documented deficits in emotion awareness and regulation in individuals with schizophrenia, and have shown that such deficits predicted SF. However, it is unknown whether these deficits are present prior to the onset of psychosis or whether they are linked to SF in CHR individuals. METHOD: We conducted a cross-sectional comparison of emotion awareness and regulation in 54 individuals at CHR, 87 with schizophrenia and 50 healthy controls (HC). Then, within the CHR group, we examined links between emotion awareness, emotion regulation and SF as indexed by the Global Functioning Scale: Social (Cornblatt et al. 2007). RESULTS: Group comparisons indicated significant differences between HC and the two clinical groups in their ability to identify and describe feelings, as well as the use of suppression and reappraisal emotion-regulation strategies. Specifically, the CHR and schizophrenia groups displayed comparable deficits in all domains of emotion awareness and emotion regulation. A hierarchical multiple regression analysis indicated that difficulties describing feelings accounted for 23.2% of the SF variance. CONCLUSIONS: The results indicate that CHR individuals display substantial emotion awareness and emotion-regulation deficits, at severity comparable with those observed in individuals with schizophrenia. Such deficits, in particular difficulties describing feelings, predate the onset of psychosis and contribute significantly to poor SF in this population.

Imaging glutamate in schizophrenia: review of findings and implications for drug discovery.

Currently, all treatments for schizophrenia (SCZ) function primarily by blocking D(2)-type dopamine receptors. Given the limitations of these medications, substantial efforts have been made to identify alternative neurochemical targets for treatment development in SCZ. One such target is brain glutamate. The objective of this article is to review and synthesize the proton magnetic resonance spectroscopy ((1)H MRS) and positron emission tomography (PET)/single-photon emission computed tomography (SPECT) investigations that have examined glutamatergic indices in SCZ, including those of modulatory compounds such as glutathione (GSH) and glycine, as well as data from ketamine challenge studies. The reviewed (1)H MRS and PET/SPECT studies support the theory of hypofunction of the N-methyl-D-aspartate receptor (NMDAR) in SCZ, as well as the convergence between the dopamine and glutamate models of SCZ. We also review several advances in MRS and PET technologies that have opened the door for new opportunities to investigate the glutamate system in SCZ and discuss some ways in which these imaging tools can be used to facilitate a greater understanding of the glutamate system in SCZ and the successful and efficient development of new glutamate-based treatments for SCZ.

Striatal dopamine release in schizophrenia comorbid with substance dependence.

Dopamine (DA) has a role in the pathophysiology of schizophrenia and addiction. Imaging studies have indicated that striatal DA release is increased in schizophrenia, predominantly in the precommissural caudate (preDCA), and blunted in addiction, mostly in the ventral striatum (VST). Therefore, we aimed to measure striatal DA release in patients with comorbid schizophrenia and substance dependence. We used [(11)C]raclopride positron emission tomography and an amphetamine challenge to measure baseline DA D2-receptor availability (BPND) and its percent change post-amphetamine (ΔBPND, to index amphetamine-induced DA release) in striatal subregions in 11 unmedicated, drug-free patients with both schizophrenia and substance dependence, and 15 healthy controls. There were no significant group differences in baseline BPND. Linear mixed modeling using ΔBPND as the dependent variable and striatal region of interest as a repeated measure indicated a significant main effect of diagnosis, F(1,24)=8.38, P=0.008, with significantly smaller ΔBPND in patients in all striatal subregions (all P ≤ 0.04) except VST. Among patients, change in positive symptoms after amphetamine was significantly associated with ΔBPND in the preDCA (rs=0.69, P=0.03) and VST (rs=0.64, P=0.05). In conclusion, patients with comorbid schizophrenia and substance dependence showed significant blunting of striatal DA release, in contrast to what has been found in schizophrenia without substance dependence. Despite this blunting, DA release was associated with the transient amphetamine-induced positive-symptom change, as observed in schizophrenia. This is the first description of a group of patients with schizophrenia who display low presynaptic DA release, yet show a psychotic reaction to increases in D2 stimulation, suggesting abnormal postsynaptic D2 function.

Antipsychotic drug mechanisms: links between therapeutic effects, metabolic side effects and the insulin signaling pathway.

The exact therapeutic mechanism of action of antipsychotic drugs remains unclear. Recent evidence has shown that second-generation antipsychotic drugs (SGAs) are differentially associated with metabolic side effects compared to first-generation antipsychotic drugs (FGAs). Their proclivity to cause metabolic disturbances correlates, to some degree, with their comparative efficacy. This is particularly the case for clozapine and olanzapine. In addition, the insulin signaling pathway is vital for normal brain development and function. Abnormalities of this pathway have been found in persons with schizophrenia and antipsychotic drugs may ameliorate some of these alterations. This prompted us to hypothesize that the therapeutic antipsychotic and adverse metabolic effects of antipsychotic drugs might be related to a common pharmacologic mechanism. This article reviews insulin metabolism in the brain and related abnormalities associated with schizophrenia with the goals of gaining insight into antipsychotic drug effects and possibly also into the pathophysiology of schizophrenia. Finally, we speculate about one potential mechanism of action (that is, functional selectivity) that would be consistent with the data reviewed herein and make suggestions for the future investigation that is required before a therapeutic agent based on these data can be realized.