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Social cognition has not previously been assessed in treatment-naive patients with chronic schizophrenia, in patients over 60 years of age, or in patients with less than 5 years of schooling.
We revised a commonly used measure of social cognition, the Reading the Mind in the Eyes Test (RMET), by expanding the instructions, using both self-completion and interviewer-completion versions (for illiterate respondents), and classifying each test administration as ‘successfully completed’ or ‘incomplete’. The revised instrument (RMET-CV-R) was administered to 233 treatment-naive patients with chronic schizophrenia (UT), 154 treated controls with chronic schizophrenia (TC), and 259 healthy controls (HC) from rural communities in China.
In bivariate and multivariate analyses, successful completion rates and RMET-CV-R scores (percent correct judgments about emotion exhibited in 70 presented slides) were highest in HC, intermediate in TC, and lowest in UT (adjusted completion rates, 97.0, 72.4, and 49.9%, respectively; adjusted RMET-CV-R scores, 45.4, 38.5, and 34.6%, respectively; all p < 0.02). Stratified analyses by the method of administration (self-completed v. interviewer-completed) and by education and age (‘educated-younger’ v. ‘undereducated-older’) show the same relationship between groups (i.e. NC>TC>UT), though not all differences remain statistically significant.
We find poorer social cognition in treatment-naive than in treated patients with chronic schizophrenia. The discriminant validity of RMET-CV-R in undereducated, older patients demonstrates the feasibility of administering revised versions of RMET to patients who may otherwise be considered ineligible due to education or age by changing the method of test administration and carefully assessing respondents' ability to complete the task successfully.
Antisaccade tasks can be used to index cognitive control processes, e.g. attention, behavioral inhibition, working memory, and goal maintenance in people with brain disorders. Though diagnoses of schizophrenia (SZ), schizoaffective (SAD), and bipolar I with psychosis (BDP) are typically considered to be distinct entities, previous work shows patterns of cognitive deficits differing in degree, rather than in kind, across these syndromes.
Large samples of individuals with psychotic disorders were recruited through the Bipolar-Schizophrenia Network on Intermediate Phenotypes 2 (B-SNIP2) study. Anti- and pro-saccade task performances were evaluated in 189 people with SZ, 185 people with SAD, 96 people with BDP, and 279 healthy comparison participants. Logistic functions were fitted to each group's antisaccade speed-performance tradeoff patterns.
Psychosis groups had higher antisaccade error rates than the healthy group, with SZ and SAD participants committing 2 times as many errors, and BDP participants committing 1.5 times as many errors. Latencies on correctly performed antisaccade trials in SZ and SAD were longer than in healthy participants, although error trial latencies were preserved. Parameters of speed-performance tradeoff functions indicated that compared to the healthy group, SZ and SAD groups had optimal performance characterized by more errors, as well as less benefit from prolonged response latencies. Prosaccade metrics did not differ between groups.
With basic prosaccade mechanisms intact, the higher speed-performance tradeoff cost for antisaccade performance in psychosis cases indicates a deficit that is specific to the higher-order cognitive aspects of saccade generation.
Antipsychotics are widely used for treating patients with psychosis, and target threshold psychotic symptoms. Individuals at clinical high risk (CHR) for psychosis are characterized by subthreshold psychotic symptoms. It is currently unclear who might benefit from antipsychotic treatment. Our objective was to apply a risk calculator (RC) to identify people that would benefit from antipsychotics.
Drawing on 400 CHR individuals recruited between 2011 and 2016, 208 individuals who received antipsychotic treatment were included. Clinical and cognitive variables were entered into an individualized RC for psychosis; personal risk was estimated and 4 risk components (negative symptoms-RC-NS, general function-RC-GF, cognitive performance-RC-CP, and positive symptoms-RC-PS) were constructed. The sample was further stratified according to the risk level. Higher risk was defined based on the estimated risk score (20% or higher).
In total, 208 CHR individuals received daily antipsychotic treatment of an olanzapine-equivalent dose of 8.7 mg with a mean administration duration of 58.4 weeks. Of these, 39 (18.8%) developed psychosis within 2 years. A new index of factors ratio (FR), which was derived from the ratio of RC-PS plus RC-GF to RC-NS plus RC-CP, was generated. In the higher-risk group, as FR increased, the conversion rate decreased. A small group (15%) of CHR individuals at higher-risk and an FR >1 benefitted from the antipsychotic treatment.
Through applying a personal risk assessment, the administration of antipsychotics should be limited to CHR individuals with predominantly positive symptoms and related function decline. A strict antipsychotic prescription strategy should be introduced to reduce inappropriate use.
Despite significant advancements in healthcare technology, digital health solutions – especially those for serious mental illnesses – continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India.
Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality.
Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement.
People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary – not substitutive – of therapeutic care from a clinician.
The ability to manage emotions is an important social-cognitive domain impaired in schizophrenia and linked to functional outcome. The goal of our study was to examine the impact of cognitive enhancement therapy (CET) on the ability to manage emotions and brain functional connectivity in early-course schizophrenia.
Participants were randomly assigned to CET (n = 55) or an enriched supportive therapy (EST) control group (n = 45). The resting-state functional magnetic resonance imaging scans and measures of emotion management performances were collected at baseline, 9, and 18 months follow-up. The final sample consisted of 37 CET and 25 EST participants, including 19 CET and 12 EST participants with imaging data. Linear mixed-effects models investigated the impact of treatment on emotion management and functional connectivity from the amygdala to ventrolateral and dorsolateral prefrontal cortex (dlPFC).
The CET group showed significant improvement over time in emotion management compared to EST. Neither functional connectivity changes nor main group differences were observed following treatment. However, a significant between-group interaction showed that improved emotion management ability was associated with increased functional connectivity between the left amygdala and the left dlPFC in the CET group exclusively.
Our results replicate the previous work demonstrating that CET is effective at improving some aspects of social cognition in schizophrenia. We found evidence that improvement in emotion management may be associated with a change in amygdala-dlPFC connectivity. This fronto-limbic circuit may provide a mechanistic link between the biology of emotion management processes that can be enhanced in individuals with schizophrenia.
Only 30% or fewer of individuals at clinical high risk (CHR) convert to full psychosis within 2 years. Efforts are thus underway to refine risk identification strategies to increase their predictive power. Our objective was to develop and validate the predictive accuracy and individualized risk components of a mobile app-based psychosis risk calculator (RC) in a CHR sample from the SHARP (ShangHai At Risk for Psychosis) program.
In total, 400 CHR individuals were identified by the Chinese version of the Structured Interview for Prodromal Syndromes. In the first phase of 300 CHR individuals, 196 subjects (65.3%) who completed neurocognitive assessments and had at least a 2-year follow-up assessment were included in the construction of an RC for psychosis. In the second phase of the SHARP sample of 100 subjects, 93 with data integrity were included to validate the performance of the SHARP-RC.
The SHARP-RC showed good discrimination of subsequent transition to psychosis with an AUC of 0.78 (p < 0.001). The individualized risk generated by the SHARP-RC provided a solid estimation of conversion in the independent validation sample, with an AUC of 0.80 (p = 0.003). A risk estimate of 20% or higher had excellent sensitivity (84%) and moderate specificity (63%) for the prediction of psychosis. The relative contribution of individual risk components can be simultaneously generated. The mobile app-based SHARP-RC was developed as a convenient tool for individualized psychosis risk appraisal.
The SHARP-RC provides a practical tool not only for assessing the probability that an individual at CHR will develop full psychosis, but also personal risk components that might be targeted in early intervention.
Autism Spectrum Disorder (ASD) and schizophrenia are neurodevelopmental disorders which share substantial overlap in cognitive deficits during adulthood. However, treatment evaluation in ASD and treatment comparisons across ASD and schizophrenia are limited by a dearth of empirical work establishing the validity of a standard cognitive battery across ASD and schizophrenia. Promisingly, the MATRICS Consensus Cognitive Battery (MCCB) has been validated in schizophrenia and encompasses cognitive domains that are impacted in ASD. Thus, this study aimed to establish MCCB's generalizability from schizophrenia to ASD.
Community-residing adults with schizophrenia (N = 100) and ASD (N = 113) underwent MCCB assessment. Using multigroup confirmatory factor analysis, MCCB's transdiagnostic validity was evaluated by examining whether schizophrenia and ASD demonstrate the same configuration, magnitude, and directionality of relationships within and among measures and their underlying cognitive domains.
Across schizophrenia and ASD, the same subsets of MCCB measures inform three cognitive domains: processing speed, attention/working memory, and learning. Except for group means in category fluency, continuous performance, and spatial span, both groups show vastly comparable factor structures and characteristics.
To our knowledge, this study is the first to establish the validity of a standard cognitive battery in adults with ASD and furthermore the first to establish a cognitive battery's comparability across ASD and schizophrenia. Cognitive domain scores can be compared across new samples using weighted sums of MCCB scores resulting from this study. These findings highlight MCCB's applicability to ASD and support its utility for standardizing treatment evaluation of cognitive outcomes across the autism-schizophrenia spectrum.
Given the substantial overlap in cognitive dysfunction between bipolar disorder (BD) and schizophrenia (SZ), we examined the utility of the MATRICS Consensus Cognitive Battery (MCCB)—developed for use in SZ—for the measurement of cognition in patients with BD with psychosis (BDP) and its association with community functioning. The MCCB, Multnomah Community Ability Scale, and measures of clinical symptoms were administered to participants with BDP (n=56), SZ (n=37), and healthy controls (HC) (n=57). Groups were compared on clinical and cognitive measures; linear regressions examined associations between MCCB and community functioning. BDP and SZ groups performed significantly worse than HC on most neurocognitive domains; BDP and HC did not differ on Social Cognition. Patients with BDP performed better than patients with SZ on most cognitive measures, although groups only differed on social cognition, working memory, verbal memory, and the composite after controlling for clinical variables. MCCB was not associated with community functioning. The MCCB is an appropriate measure of neurocognition in BDP but does not appear to capture social cognitive deficits in this population. The addition of appropriate social cognitive measures is recommended. (JINS, 2015, 21, 468–472)
In this paper, we review the history of the concept of neuroplasticity as it relates to the understanding of neuropsychiatric disorders, using schizophrenia as a case in point. We briefly review the myriad meanings of the term neuroplasticity, and its neuroscientific basis. We then review the evidence for aberrant neuroplasticity and metaplasticity associated with schizophrenia as well as the risk for developing this illness, and discuss the implications of such understanding for prevention and therapeutic interventions. We argue that the failure and/or altered timing of plasticity of critical brain circuits might underlie cognitive and deficit symptoms, and may also lead to aberrant plastic reorganization in other circuits, leading to affective dysregulation and eventually psychosis. This “dysplastic” model of schizophrenia can suggest testable etiology and treatment-relevant questions for the future.
One branch of the tryptophan catabolic cascade is the kynurenine pathway, which produces neurotoxic [3-hydroxykynurenine (3-OHKY), quinolinic acid] and neuroinhibitory (kynurenic acid) compounds. Kynurenic acid acts as a competitive antagonist at the glycine site of N-methyl-d-asparate receptors at high concentrations and as a non-competitive antagonist on the α7-nicotinic acetylcholine receptor at low concentrations. Kynurenine compounds also influence cognitive functions known to be disrupted in schizophrenia. Alterations in tryptophan metabolism are therefore of potential significance for the pathophysiology of this disorder. In this paper, tryptophan metabolites were measured from plasma using high-pressure liquid chromatography coupled with electrochemical coulometric array detection, and relationships were tested between these metabolic signatures and clinical symptoms for 25 first-episode neuroleptic-naive schizophrenia patients. Blood samples were collected and clinical and neurological symptoms were rated at baseline and again at 4 wk following initiation of treatment. Level of 3-OHKY and total clinical symptom scores were correlated when patients were unmedicated and neuroleptic-naive, and this relationship differed significantly from the correlation observed for patients 4 wk after beginning treatment. Baseline psychosis symptoms were predicted only by neurological symptoms. Moreover, baseline 3-OHKY predicted clinical change at 4 wk, with the lowest concentrations of 3-OHKY being associated with the greatest improvement in symptoms. Taken together, our findings suggest a neurotoxic product of tryptophan metabolism, 3-OHKY, predicts severity of clinical symptoms during the early phase of illness and before exposure to antipsychotic drugs. Baseline level of 3-OHKY may also predict the degree of clinical improvement following brief treatment with antipsychotics.