Characterising the structure of cognitive heterogeneity in schizophrenia spectrum disorders. A systematic review and narrative synthesis

Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment Reduces Variability in Brain Function in Schizophrenia: Data From a Double-Blind, Randomized, Sham-Controlled Trial

BACKGROUND/HYPOTHESIS

There is increasing awareness of interindividual variability in brain function, with potentially major implications for repetitive transcranial magnetic stimulation (rTMS) efficacy. We perform a secondary analysis using data from a double-blind randomized controlled 4-week trial of 20 Hz active versus sham rTMS to dorsolateral prefrontal cortex (DLPFC) during a working memory task in participants with schizophrenia. We hypothesized that rTMS would change local functional activity and variability in the active group compared with sham.

STUDY DESIGN

83 participants were randomized in the original trial, and offered neuroimaging pre- and post-treatment. Of those who successfully completed both scans (n = 57), rigorous quality control left n = 42 (active/sham: n = 19/23), who were included in this analysis. Working memory-evoked activity during an N-Back (3-Back vs 1-Back) task was contrasted. Changes in local brain activity were examined from an 8 mm ROI around the rTMS coordinates. Individual variability was examined as the mean correlational distance (MCD) in brain activity pattern from each participant to others within the same group.

RESULTS

We observed an increase in task-evoked left DLPFC activity in the active group compared with sham (F1,36 = 5.83, False Discovery Rate (FDR))-corrected P = .04). Although whole-brain activation patterns were similar in both groups, active rTMS reduced the MCD in activation pattern compared with sham (F1,36 = 32.57, P < .0001). Reduction in MCD was associated with improvements in attention performance (F1,16 = 14.82, P = .0014, uncorrected).

CONCLUSIONS

Active rTMS to DLPFC reduces individual variability of brain function in people with schizophrenia. Given that individual variability is typically higher in schizophrenia patients compared with controls, such reduction may "normalize" brain function during higher-order cognitive processing.

Longitudinal clinical outcomes based on cognitive and hippocampal clusters of first episode psychosis

BACKGROUND

In first episode psychosis (FEP), cognitive impairments are core features contributing to clinical and functional heterogeneity. Significant impairment indicates greater clinical severity throughout the course of the illness, particularly for negative symptoms. Hippocampal volume is smaller in FEP than in healthy controls (notably subfields like Cornu Ammonis 1-3 and subiculum), and is related to cognitive impairments and negative symptoms. The aim of this study was to compare the clinical and functional trajectories of FEP subgroups as a function of cognitive performance and hippocampal volumes.

METHODS

One hundred FEP patients and sixty healthy controls initially assessed using the CogState research battery, underwent 3 T MRI to extract hippocampal subfields and adjacent structures using the MAGeT brain algorithm. Clinical assessments were carried out for negative (Motivational and Pleasure - MAP, and diminished expression - EXP) and depressive symptoms, and global functioning. Measurements were taken at 4 time points (3, 9, 15, 21 months following program entry). Based on available first timepoint standardized cognitive and hippocampal features, using healthy controls as reference, clusters were determined by a hierarchical ascending classification. Their clinical and functional longitudinal trajectories were analyzed using linear mixed-effects models.

RESULTS

Three baseline clusters were revealed: normal-range hippocampal volume with low attention, working and verbal memory (FEP 0), small hippocampus with low verbal memory and social cognition (FEP 1), and large hippocampus with low verbal memory (FEP 2). At baseline, the clusters did not differ on symptoms severity and global functioning. Longitudinally, MAP, EXP and depressive symptoms decreased over time in FEP 0. Global functioning improved in FEP 0 and FEP 1, while FEP 2 was clinically and functionally stable over time. Longitudinal inter-group comparisons did not yield any significant differences.

CONCLUSION

The clusters were dissociated between hippocampus and cognition, but their trajectories suggest the importance of hippocampal integrity in the clinical and/or functional outcome. Future studies are needed to understand intervention efficiency depending on hippocampal integrity.

Neuropsychological profiles in first-episodes psychosis and their relationship with clinical, metacognition and social cognition variables

An increasing interest in the assessment of neuropsychological performance variability in people with first-episode psychosis (FEP) has emerged. However, its association with clinical and functional outcomes requires further study. Furthermore, FEP neuropsychological subgroups have not been characterized by clinical insight or metacognition and social cognition domains. The aim of this exploratory study was to identify specific groups of patients with FEP based on neuropsychological variables and to compare their sociodemographic, clinical, metacognition and social cognition profiles. A sample of 149 FEP was recruited from adult mental health services. Neuropsychological performance was assessed by a neuropsychological battery (WAIS-III; TMT; WSCT; Stroop Test; TAVEC). The assessment also included sociodemographic characteristics, clinical, functional, metacognition and social cognition variables. Two distinct neuropsychological profiles emerged: one neuropsychological impaired cluster (N = 56) and one relatively intact cluster (N = 93). Significant differences were found between both profiles in terms of sociodemographic characteristics (age and level of education) (p = 0.001), clinical symptoms (negative, positive, disorganized, excitement and anxiety) (p = 0.041-0.001), clinical insight (p = 0.038-0.017), global functioning (p = 0.014), as well as in social cognition domains (emotional processing and theory of mind) (p = 0.001; p = 0.002). No significant differences were found in metacognitive variables (cognitive insight and 'jumping to conclusions' bias). Relationship between neurocognitive impairment, social cognition and metacognition deficits are discussed. Early identifying of neuropsychological profiles in FEP, characterized by significant differences in clinical and social cognition variables, could provide insight into the prognosis and guide the implementation of tailored early-intervention.

Exploring the latent cognitive structure in schizophrenia: implications for antipsychotic treatment responses

BACKGROUND

Individuals diagnosed with schizophrenia present diverse degrees and types of cognitive impairment, leading to variations in responses to antipsychotic treatments. Understanding the underlying cognitive structures is crucial for assessing this heterogeneity. Utilizing latent profile analysis (LPA) enables the delineation of latent categories of cognitive function. Integrating this approach with a dimensional perspective allows for the exploration of the relationship between cognitive function and treatment response.

METHODS

This study examined 647 patients from two distinct cohorts. Utilizing LPA within the discovery cohort (n = 333) and the replication cohort (n = 314), latent subtypes were identified categorically. The stability of cognitive structures was evaluated employing Latent Transition Analysis (LTA). The relationship between cognitive function and treatment response were investigated by comparing Positive and Negative Syndrome Scale (PANSS) reduction rates across diverse cognitive subtypes. Furthermore, dimensional insights were gained through correlation analyses between cognitive tests and PANSS reduction rates.

RESULTS

In terms of categorical, individuals diagnosed with schizophrenia can be categorized into three distinct subtypes: those 'without cognitive deficit', those 'with mild-moderate cognitive 'eficit', and those 'with moderate-severe cognitive deficit'. There are significant differences in PANSS reduction rates among patients belonging to these subtypes following antipsychotic treatment (p < 0.05). Furthermore, from a dimensional perspective, processing speed at baseline is positively correlated with PANSS score reduction rates at week 8/week 10 (p < 0.01).

CONCLUSIONS

Our findings have unveiled the latent subtypes of cognitive function in schizophrenia, illuminating the association between cognitive function and responses to antipsychotic treatment from both categorical and dimensional perspectives.

An experimental and computational investigation of executive functions and inner speech in schizophrenia spectrum disorders

Flexible goal-directed human cognition is supported by many forms of self-directed manipulation of representations. Among them, Inner-Speech (IS; covert self-directed speech) acts on second-order representations (e.g., goals/sub-goals), empowering attention and feedback processing. Interestingly, patients with Schizophrenia Spectrum Disorders (SSD) show impaired Executive Functions (EF; e.g., cognitive flexibility) and, probably, a related IS alteration. However, fragmentary evidence and no computational modeling prevent a clear assessment of these processes and focused therapeutic interventions. Here, we address these issues by exploiting a translational approach that integrates experimental clinical data, machine learning, and computational modeling. First, we administered the Wisconsin Cards Sorting Test (WCST; a neuropsychological test probing cognitive flexibility) to 162 SSD patients and 108 healthy control participants, and we computed the clinical behavioural data with a data-driven clustering algorithm. Second, we extracted the cluster neuropsychological profiles with our theory-based validated computational model of the WCST. Finally, we exploited our model to emulate an IS-based psychotherapeutic intervention for SSD subpopulations. We identified different SSD sub-populations and global trends (e.g., a descending feedback sensitivity); however, extremely different neuropsychological profiles emerged. In particular, 'Relatively Intact' patients showed an unexpected profile (distraction/reasoning failures), quite divergent from the perseverative/rigid profile of the others. Importantly, the former showed no impact of Interfering-IS, while the others showed increased Interfering-IS strongly affecting their cognition. These differences highlight that SSD populations require a cluster-dependent individualisation of the intervention to achieve adequate cognitive performance. Overall, these results support a clear definition of neuropsychological profiles and the related Interfering-IS impact in SSD subpopulations, thus showing important implications for basic research (e.g., cognitive neuroscience) and clinical fields (clinical psychology and psychiatry).

Cognitive presentation at psychosis onset through premorbid deterioration and exposure to environmental risk factors

BACKGROUND

Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.

METHODS

A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.

RESULTS

The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.

CONCLUSIONS

High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients' trajectories involved risk factors that could be modified by tailored interventions.

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning

PURPOSE

The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magnetic resonance imaging (MRI) and machine learning (ML) algorithms to improve the classification of schizophrenia and its subtypes.

METHOD

We utilized a public dataset provided by the UCLA (University of California, Los Angeles) Consortium for Neuropsychiatric Research, containing structural MRI and resting-state fMRI (rsfMRI) data. We integrated all individuals within the dataset diagnosed with schizophrenia (N = 50), along with age- and gender-matched healthy individuals (N = 50). We extracted volumetrics of 66 subcortical and thickness of 72 cortical regions. Additionally, we obtained four graph-based measures for 116 intracranial regions from rsfMRI data, including degree, betweenness centrality, participation coefficient, and local efficiency. Employing conventional ML methods, we sought to distinguish the patients with schizophrenia from healthy individuals. Furthermore, we applied the methods for discriminating subtypes of schizophrenia. To streamline the feature set, various feature selection techniques were applied. Moreover, a validation phase involved employing the model on a dataset domestically acquired using the same imaging assessments (N = 13). Finally, we explored the correlation between neuroimaging features and behavioral assessments.

FINDING

The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. This result was achieved by the k-nearest neighbor algorithm, utilizing 12 brain neuroimaging features, selected by the feature selection method of minimum redundancy maximum relevance (MRMR). The model demonstrated effectiveness (72% accuracy) in estimating the patient's label for a new dataset acquired domestically. Using a linear support vector machine (SVM) on 62 features obtained from MRMR, patients with schizophrenic subtypes were classified with an accuracy of 64%. The highest Spearman correlation coefficient between the neuroimaging features and behavioral assessments was observed between the degree of the postcentral gyrus and mean reaction time in the verbal capacity task (r = 0.49, p = 0.001).

CONCLUSION

The findings of this study underscore the utility of MRI and ML algorithms in enhancing the diagnostic process for schizophrenia. Furthermore, these methods hold promise for detecting both brain-related abnormalities and cognitive impairments associated with this disorder.

Iowa Gambling Task performance in individuals with schizophrenia: the role of general versus specific cognitive abilities

Objective

We aimed to explore how specific cognitive processes, such as attention and executive functions, account for variance in decision-making measured by Iowa Gambling Task (IGT) performance among individuals with schizophrenia spectrum disorders.

Methods

Adults (N = 65, M age = 25.4) with schizophrenia spectrum disorders participating in a clinical trial (registered at clinicaltrials.gov NCT03048695) completed the IGT, neuropsychological tests of attention, response inhibition, mental flexibility, working memory, and planning, as well as subtests from the Wechsler tests of intelligence to estimate IQ. Associations between performance on specific tasks, a composite score of executive function and attention, and IGT performance measured in two ways, one using the total net score, decks (C+D) - (A+B) and the other as preference for decks with more frequent gains than losses, decks (B+D) - (A+C), were analyzed with correlational and hierarchical regression analysis controlling for estimated IQ and psychotic symptoms, measured by the Positive and Negative Syndrome Scale.

Results

In the regression analyses, the strongest predictor of IGT performance measured as the total net score was estimated IQ (b = 1.43, p <.001). Neither specific cognitive tasks nor the composite score of executive functioning significantly contributed to explaining variance in IGT total net score beyond IQ and symptoms of psychosis. However, IQ and symptoms of psychosis did not predict tendency towards selecting decks with different gain-to-loss frequency, whereas poorer composite executive functioning predicted a pattern of selecting decks A and C with more frequent losses, (b = 8.30, p <.05).

Discussion

The results suggest that both IQ and executive functions contribute to IGT performance, but in distinct ways. Whereas lower IQ may contribute to overall more disadvantageous decision-making, poorer executive functioning may contribute to a more risk-aversive decision-making style. A clinical implication may be that individuals with schizophrenia and lower IQ or poorer executive functioning will have a higher need for support and interventions targeting decision-making.

Leveraging Stacked Classifiers for Multi-task Executive Function in Schizophrenia Yields Diagnostic and Prognostic Insights

Cognitive impairment is a central characteristic of schizophrenia. Executive functioning (EF) impairments are often seen in mental disorders, particularly schizophrenia, where they relate to adverse outcomes. As a heterogeneous construct, how specifically each dimension of EF to characterize the diagnostic and prognostic aspects of schizophrenia remains opaque. We used classification models with a stacking approach on systematically measured EFs to discriminate 195 patients with schizophrenia from healthy individuals. Baseline EF measurements were moreover employed to predict symptomatically remitted or non-remitted prognostic subgroups. EF feature importance was determined at the group-level and the ensuing individual importance scores were associated with four symptom dimensions. EF assessments of inhibitory control (interference and response inhibitions), followed by working memory, evidently predicted schizophrenia diagnosis (area under the curve [AUC]=0.87) and remission status (AUC=0.81). The models highlighted the importance of interference inhibition or working memory updating in accurately identifying individuals with schizophrenia or those in remission. These identified patients had high-level negative symptoms at baseline and those who remitted showed milder cognitive symptoms at follow-up, without differences in baseline EF or symptom severity compared to non-remitted patients. Our work indicates that impairments in specific EF dimensions in schizophrenia are differentially linked to individual symptom-load and prognostic outcomes. Thus, assessments and models based on EF may be a promising tool that can aid in the clinical evaluation of this disorder.

What is schizophrenia - symptomatology

Schizophrenia is a highly heterogenous disorder with substantial interindividual variation in how the illness is experienced and how it presents clinically. The disorder is composed of primary symptom clusters-positive symptoms, negative symptoms, disorganization, neurocognitive deficits, and social cognitive impairments. These, along with duration, severity, and excluding other possible etiologies, comprise the diagnostic criteria for the disorder outlined in the two commonly used diagnostic classification systems-the Diagnostic Statistical Manual of Mental Disorders, Fifth Edition, Text Revision and the International Classification of Diseases, 11th Revision. These primary symptoms as well as accessory symptoms (mood disturbances, anxiety, violence) and comorbidities (substance use, suicidality) bear upon each other to varying degrees and impact functional outcomes. The following review presents two patient cases illustrating the clinical heterogeneity of schizophrenia, the natural history of the illness and diagnosis, followed by the current understanding of the primary symptom clusters, accessory symptoms, and comorbidities. In addition to noting symptom prevalence, onset, and change over time, attention is paid to the impact of symptoms on functional outcome.

Cognition in relation to non-auditory or multisensory hallucinations in schizophrenia-spectrum disorders: A scoping review

Multisensory hallucinations refer to unusual perceptual events in the absence of corresponding stimuli, experienced in two or more sensory modalities. Within the schizophrenia-spectrum disorder literature, the cognitive correlates of multisensory and non-auditory hallucinations remain largely unknown. This scoping review aimed to map and synthesise research that explored relationships between cognition and non-auditory and multisensory hallucinations in schizophrenia-spectrum disorders. Published, peer-reviewed, empirical research studies were sought through three databases: Web of Science, Scopus, and PubMed. Studies that had explored visual, olfactory, tactile, and gustatory hallucinations, or multisensory hallucinations, and their relationships to any basic cognitive mechanisms were included. Of 2218 records identified, a total of 17 studies met inclusion criteria. Visual hallucinations were the most frequently explored (13 studies); followed by olfactory hallucinations (five studies), tactile hallucinations (two studies) and multisensory hallucinations (two studies). Several cognitive mechanisms were studied, yet the majority were only explored in individual studies across the sensory modalities, limiting conclusions that could be drawn. Exploring the potential mechanistic drivers for hallucinations across multiple sensory modalities would advance the field significantly and allow for development of aetiological models that better capture the full gamut of hallucinatory experiences.

Global reward processing deficits predict negative symptoms transdiagnostically and transphasically in a severe mental illness-spectrum sample

Reward processing impairments are a key factor associated with negative symptoms in those with severe mental illnesses. However, past findings are inconsistent regarding which reward processing components are impaired and most strongly linked to negative symptoms. The current study examined the hypothesis that these mixed findings may be the result of multiple reward processing pathways (i.e., equifinality) to negative symptoms that cut across diagnostic boundaries and phases of illness. Participants included healthy controls (n = 100) who served as a reference sample and a severe mental illness-spectrum sample (n = 92) that included psychotic-like experiences, clinical high-risk for psychosis, bipolar disorder, and schizophrenia participants. All participants completed tasks measuring four RDoC Positive Valence System constructs: value representation, reinforcement learning, effort-cost computation, and hedonic reactivity. A k-means cluster analysis of the severe mental illness-spectrum samples identified three clusters with differential reward processing profiles that were characterized by: (1) global reward processing deficits (22.8%), (2) selective impairments in hedonic reactivity alone (40.2%), and (3) preserved reward processing (37%). Elevated negative symptoms were only observed in the global reward processing cluster. All clusters contained participants from each clinical group, and the distribution of these groups did not significantly differ among the clusters. Findings identified one pathway contributing to negative symptoms that was transdiagnostic and transphasic. Future work further characterizing divergent pathways to negative symptoms may help to improve symptom trajectories and personalized treatments.

Definition, assessment and treatment of cognitive impairment associated with schizophrenia: expert opinion and practical recommendations

A considerable proportion of patients with schizophrenia perform below population norms on standardized neuropsychological tests, and the performance of those performing within normal range is lower than predicted based on parental education. Cognitive impairment predates the onset of psychosis, is observed during symptom remission and in non-affected first-degree relatives of patients. At the present time, cognitive deficits are regarded as key features of schizophrenia, important determinants of poor psychosocial outcome and targets for both pharmacological and non-pharmacological treatment strategies. A group of eight key opinion leaders reviewed and discussed latest advances in scientific research and current good clinical practices on assessment, management, and treatment of CIAS. In the present paper they summarize the current evidence, identify main gaps between current knowledge and mental health services clinical practice, and provide practical recommendations to reduce the gap.

Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis

BACKGROUND

Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD.

METHODS

Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability.

RESULTS

Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01).

CONCLUSIONS

Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Biomarkers of neurodegeneration in schizophrenia: systematic review and meta-analysis

QUESTION

Does neurodegenerative disease underlie the increased rate of dementia observed in older people with schizophrenia? Several studies have reported a higher prevalence of dementia in people with schizophrenia compared with the general population. This may reflect a higher risk of developing neurodegenerative diseases such as vascular dementia or Alzheimer's disease (AD). Alternatively, this may reflect non-pathological, age-related cognitive decline in a population with low cognitive reserve.

STUDY SELECTION AND ANALYSIS

We reviewed papers that compared postmortem findings, hippocampal MRI volume or cerebrospinal fluid (CSF) markers of AD, between patients with schizophrenia with evidence of cognitive impairment (age ≥45 years) with controls. We subsequently performed a meta-analysis of postmortem studies that compared amyloid-β plaques (APs) or neurofibrillary tangles (NFTs) in cognitively impaired patients with schizophrenia to normal controls or an AD group.

FINDINGS

No studies found a significant increase of APs or NFTs in cognitively impaired patients with schizophrenia compared with controls. All postmortem studies that compared APs or NFTs in patients with schizophrenia to an AD group found significantly more APs or NFTs in AD. No studies found a significant differences in CSF total tau or phosphorylated tau between patients with schizophrenia and controls. The two studies which compared CSF Aβ42 between patients with schizophrenia and controls found significantly decreased CSF Aβ42 in schizophrenia compared with controls. Hippocampal volume findings were mixed.

CONCLUSIONS

Studies have not found higher rates of AD-related pathology in cognitively impaired individuals with schizophrenia compared with controls. Higher rates of dementia identified in population studies may reflect a lack of specificity in clinical diagnostic tools used to diagnose dementia.

Characterizing cognitive subtypes in schizophrenia using cortical curvature

Cognitive deficits are a core symptom of schizophrenia, but research on their neural underpinnings has been challenged by the heterogeneity in deficits' severity among patients. Here, we address this issue by combining logistic regression and random forest to classify two neuropsychological profiles of patients with high (HighCog) and low (LowCog) cognitive performance in two independent samples. We based our analysis on the cortical features grey matter volume (VOL), cortical thickness (CT), and mean curvature (MC) of N = 57 patients (discovery sample) and validated the classification in an independent sample (N = 52). We investigated which cortical feature would yield the best classification results and expected that the 10 most important features would include frontal and temporal brain regions. The model based on MC had the best performance with area under the curve (AUC) values of 76% and 73%, and identified fronto-temporal and occipital brain regions as the most important features for the classification. Moreover, subsequent comparison analyses could reveal significant differences in MC of single brain regions between the two cognitive profiles. The present study suggests MC as a promising neuroanatomical parameter for characterizing schizophrenia cognitive subtypes.

Cognitive Function and Variability in Antipsychotic Drug-Naive Patients With First-Episode Psychosis: A Systematic Review and Meta-Analysis

Importance

Cognitive impairment contributes significantly to clinical outcome and level of function in individuals with psychotic disorders. These impairments are present already at psychosis onset at a group level; however, the question of heterogeneity in cognitive function among patients has not been systematically investigated.

Objective

To provide an updated quantification of cognitive impairment at psychosis onset before patients receive potentially confounding antipsychotic treatment, and to investigate variability in cognitive function compared with healthy controls.

Data Sources

In this systematic review and meta-analysis, PubMed articles were searched up to September 15, 2022.

Study Selection

Original studies reporting data on cognitive function in antipsychotic drug-naive patients with first-episode psychosis (FEP) were included.

Data Extraction and Synthesis

Data were independently extracted by 2 researchers. Cognitive tasks were clustered according to 6 domains of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery and the domain of executive function. Random-effects model meta-analyses of mean differences and coefficient of variation ratios (CVRs) were performed, as well as meta-regressions, assessment of study quality, and publication bias.

Main Outcomes and Measures

The main outcome measure was Hedges g for mean differences in cognition and CVR for within-group variability.

Results

Fifty studies were included in the analysis with a total of 2625 individuals with FEP (mean [SD] age, 25.2 [3.6] years, 60% male; 40% female) and 2917 healthy controls (mean [SD] age, 26.0 [4.6]; 55% male; 45% female). In all cognitive domains, the FEP group displayed significant impairment compared with controls (speed of processing: Hedges g = -1.16; 95% CI, -1.35 to -0.98; verbal learning: Hedges g = -1.08; 95% CI, -1.28 to -0.88; visual learning: Hedges g = -1.05; 95% CI, -1.27 to -0.82; working memory: Hedges g = -1.04; 95% CI, -1.35 to -0.73; attention: Hedges g = -1.03; 95% CI, -1.24 to -0.82; reasoning/problem solving: Hedges g = -0.90; 95% CI, -1.12 to -0.68; executive function: Hedges g = -0.88; 95% CI, -1.07 to -0.69). Individuals with FEP also exhibited a larger variability across all domains (CVR range, 1.34-1.92).

Conclusions and Relevance

Results of this systematic review and meta-analysis identified cognitive impairment in FEP before the initiation of antipsychotic treatment, with large effect sizes. The high variability within the FEP group suggests the need to identify those individuals with more severe cognitive problems who risk worse outcomes and could benefit the most from cognitive remediation.

Cognitive and inflammatory heterogeneity in severe mental illness: Translating findings from blood to brain

Recent findings link cognitive impairment and inflammatory-immune dysregulation in schizophrenia (SZ) and bipolar (BD) spectrum disorders. However, heterogeneity and translation between the periphery and central (blood-to-brain) mechanisms remains a challenge. Starting with a large SZ, BD and healthy control cohort (n = 1235), we aimed to i) identify candidate peripheral markers (n = 25) associated with cognitive domains (n = 9) and elucidate heterogenous immune-cognitive patterns, ii) evaluate the regulation of candidate markers using human induced pluripotent stem cell (iPSC)-derived astrocytes and neural progenitor cells (n = 10), and iii) evaluate candidate marker messenger RNA expression in leukocytes using microarray in available data from a subsample of the main cohort (n = 776), and in available RNA-sequencing deconvolution analysis of postmortem brain samples (n = 474) from the CommonMind Consortium (CMC). We identified transdiagnostic subgroups based on covariance between cognitive domains (measures of speed and verbal learning) and peripheral markers reflecting inflammatory response (CRP, sTNFR1, YKL-40), innate immune activation (MIF) and extracellular matrix remodelling (YKL-40, CatS). Of the candidate markers there was considerable variance in secretion of YKL-40 in iPSC-derived astrocytes and neural progenitor cells in SZ compared to HC. Further, we provide evidence of dysregulated RNA expression of genes encoding YKL-40 and related signalling pathways in a high neuroinflammatory subgroup in the postmortem brain samples. Our findings suggest a relationship between peripheral inflammatory-immune activity and cognitive impairment, and highlight YKL-40 as a potential marker of cognitive functioning in a subgroup of individuals with severe mental illness.

Relationship between social cognition and premorbid adjustment in psychosis: a systematic review

This systematic review provides a comprehensive overview of the association between premorbid adjustment and social cognition in people with psychotic spectrum disorder. Obtaining evidence of this association will facilitate early detection and intervention before the onset of psychosis. Literature searches were conducted in Scopus, PubMed and PsycINFO. Studies were eligible if they included patients with a psychotic disorder or at a high-risk state; social cognition and premorbid adjustment were measured; and the relationship between premorbid adjustment and social cognition was analysed. The authors independently extracted data from all included articles, and discrepancies were resolved through discussion. Literature searches were conducted in Scopus, PubMed and PsycINFO. Studies were eligible if they included patients with a psychotic disorder or at a high-risk state; social cognition and premorbid adjustment were measured; and the relationship between premorbid adjustment and social cognition was analysed. The authors independently extracted data from all included articles, and discrepancies were resolved through discussion. Of 229 studies identified, 23 met the inclusion criteria. Different methods of assessment were used to measure premorbid adjustment, such as the Premorbid Adjustment Scale or premorbid IQ, among others. Social cognition was assessed as a global measure or by domains using different instruments. A total of 16 articles found a relationship between social cognition (or its domains) and premorbid adjustment: general social cognition (n = 3); Theory of Mind (n  = 12); Emotional Recognition and Social Knowledge (n  = 1). This review shows evidence of a significant relationship between social cognition and premorbid adjustment, specifically between Theory of Mind and premorbid adjustment. Social cognition deficits may already appear in phases prior to the onset of psychosis, so an early individualized intervention with stimulating experiences in people with poor premorbid adjustment can be relevant for prevention. We recommend some future directions, such as carrying out longitudinal studies with people at high-risk of psychosis, a meta-analysis study, broadening the concept of premorbid adjustment, and a consensual assessment of social cognition and premorbid adjustment variables. PROSPERO registration number: CRD42022333886.

Effects of Goal Management Training on self-efficacy, self-esteem, and quality of life for persons with schizophrenia spectrum disorders

Persons with schizophrenia often show executive dysfunction assessed with both subjective (self-report) and objective (neuropsychological tests) measures. In a recent randomized controlled trial (RCT), subjective executive functioning in everyday life was improved following Goal Management Training (GMT). The aim of the current study is to investigate the potential of GMT to improve secondary well-being outcomes from that RCT, including self-esteem, self-efficacy, and quality of life in persons with schizophrenia spectrum disorders. Since well-being is frequently lower in persons with schizophrenia compared to healthy individuals, further knowledge about well-being as an outcome after cognitive remediation may have implications for clinical treatment. Sixty-five participants were randomly assigned to GMT (n = 31) or a waiting list control condition (n = 34). Assessments were conducted at baseline (T1), immediately after the intervention (T2-5 weeks), and at six-month follow-up (T3). Measures included the Rosenberg Self-Esteem Scale, the Perceived Quality of Life Scale, and the General Self-Efficacy Scale. Results were analyzed using a linear mixed model analysis for repeated measures. There were no significant effects of GMT on self-esteem or quality of life. Only the GMT group showed a significant increase in self-efficacy that was most evident at six months follow-up, F(1, 34) = 10.71, p = 0.002, d = 0.71. Improved self-efficacy was found to correlate significantly with a reduction in perceived executive dysfunction in an exploratory post hoc analysis. Our findings demonstrate the potential of GMT in improving self-efficacy in schizophrenia Clinical trial registration:https://clinicaltrials.gov, NCT03048695.

Cortical impoverishment in a stable subgroup of schizophrenia: Validation across various stages of psychosis

BACKGROUND

Cortical thinning is a well-known feature in schizophrenia. The considerable variation in the spatial distribution of thickness changes has been used to parse heterogeneity. A 'cortical impoverishment' subgroup with a generalized reduction in thickness has been reported. However, it is unclear if this subgroup is recoverable irrespective of illness stage, and if it relates to the glutamate hypothesis of schizophrenia.

METHODS

We applied hierarchical cluster analysis to cortical thickness data from magnetic resonance imaging scans of three datasets in different stages of psychosis (n = 288; 160 patients; 128 healthy controls) and studied the cognitive and symptom profiles of the observed subgroups. In one of the samples, we also studied the subgroup differences in 7-Tesla magnetic resonance spectroscopy glutamate concentration in the dorsal anterior cingulate cortex.

RESULTS

Our consensus-based clustering procedure consistently produced 2 subgroups of participants. Patients accounted for 75%-100% of participants in one subgroup that was characterized by significantly lower cortical thickness. Both subgroups were equally symptomatic in clinically unstable stages, but cortical impoverishment indicated a higher symptom burden in a clinically stable sample and higher glutamate levels in the first-episode sample. There were no subgroup differences in cognitive and functional outcome profiles or antipsychotic exposure across all stages.

CONCLUSIONS

Cortical thinning does not vary with functioning or cognitive impairment, but it is more prevalent among patients, especially those with glutamate excess in early stages and higher residual symptom burden at later stages, providing an important mechanistic clue to one of the several possible pathways to the illness.

Effect of immersive virtual reality-based cognitive remediation in patients with mood or psychosis spectrum disorders: study protocol for a randomized, controlled, double-blinded trial

BACKGROUND

Cognitive impairments are prevalent across mood disorders and psychosis spectrum disorders, but there is a lack of real-life-like cognitive training programmes. Fully immersive virtual reality has the potential to ensure motivating and engaging cognitive training directly relevant to patients' daily lives. We will examine the effect of a 4-week, intensive virtual reality-based cognitive remediation programme involving daily life challenges on cognition and daily life functioning in patients with mood disorders or psychosis spectrum disorders and explore the neuronal underpinnings of potential treatment efficacy.

METHODS

The trial has a randomized, controlled, double-blinded, parallel-group design. We will include 66 symptomatically stable outpatients with mood disorders or psychosis spectrum disorders aged 18-55 years with objective and subjective cognitive impairment. Assessments encompassing a virtual reality test of daily life cognitive skills, neuropsychological testing, measures of daily life functioning, symptom ratings, questionnaires on subjective cognitive complaints, and quality of life are carried out at baseline, after the end of 4 weeks of treatment and at a 3-month follow-up after treatment completion. Functional magnetic resonance imaging scans are performed at baseline and at the end of treatment. The primary outcome is a broad cognitive composite score comprising five subtasks on a novel ecologically valid virtual reality test of daily life cognitive functions. Two complete data sets for 54 patients will provide a power of 80% to detect a clinically relevant between-group difference in the primary outcome. Behavioural data will be analysed using linear mixed models in SPSS, while MRI data will be analysed with the FMRIB Expert Analysis Tool (FEAT). Treatment-related changes in neural activity from baseline to end of treatment will be investigated for the dorsal prefrontal cortex and hippocampus as the regions of interest.

DISCUSSION

The results will provide insight into whether virtual reality-based cognitive remediation has beneficial effects on cognition and functioning in symptomatically stable patients with mood disorders or psychosis spectrum disorders, which can aid future treatment development.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06038955. Registered on September 15, 2023.

To what extent does white matter map to cognition in bipolar disorder? A systematic review of the evidence

Cognitive impairment is a prominent feature of bipolar disorder (BD), however the neural substrates underpinning it remain unclear. Several studies have explored white matter as a correlate of cognitive functioning in BD cohorts, but mixed results and varied methodologies from one to another make inferences about this relationship difficult to draw. Here we sought to systematically synthesise the findings of these studies to more clearly explicate the nature and extent of relationships between white matter and cognition in BD and determine best practice methodologies and areas for future research in this area. Using PRISMA guidelines, we identified and systematically reviewed 37 relevant studies, all of which were cross-sectional by design. There was substantial methodological heterogeneity and variability in the clinical presentations of BD cohorts encapsulated within the studies we reviewed, which complicated our synthesis of the findings. Nonetheless, there was some evidence that cognition is related to both white matter macrostructure and microstructure in people with BD. In particular, multiple microstructural studies consistently reported that higher fractional anisotropy, both globally and in the corpus callosum, associated with better complex attention skills and executive functioning. However, several reports did not identify any associations at all, and in general, associations between WM and cognition tended to only be evident in studies utilising larger samples and post-hoc selection of WM regions of interest. Further research with increased statistical power and standardised methods are required moving forward.

Exploring the cognitive profiles related to unimodal auditory versus multisensory hallucinations in schizophrenia-spectrum disorders

INTRODUCTION

Hallucinations can be experienced across multiple sensory modalities, but psychiatric studies investigating the cognitive mechanisms of hallucinations have been somewhat restricted to the auditory domain. This study explored the cognitive profiles of individuals experiencing multisensory hallucinations (MH) in schizophrenia-spectrum disorders (SSD) and compared these to those experiencing unimodal auditory hallucinations (AH) or no hallucinations (NH).

METHODS

Participants included SSD patients (n = 119) stratified by current hallucination status (NH, AH, MH) and nonclinical controls (NCs; n = 113). Group performance was compared across several cognitive domains: speed of processing, attention, working memory, verbal learning, visual learning, reasoning and problem-solving, social cognition, and inhibition.

RESULTS

The clinical groups performed worse than NCs but differences between the clinical groups were not evident across most cognitive domains. Exploratory analyses revealed that the MH group was more impaired on the visual learning task compared to the NH (but not AH) group.

CONCLUSIONS

Preliminary results suggest that impaired visual learning may be related to MH. This could be attributed to the presence of visual hallucinations (VH), or greater psychopathology, in this group. However, replication is needed, as well as the investigation of other potential cognitive mechanisms of MH.

Intra- and inter-individual cognitive variability in schizophrenia and bipolar spectrum disorder: an investigation across multiple cognitive domains

There is substantial cognitive heterogeneity among patients with schizophrenia (SZ) and bipolar disorders (BD). More knowledge about the magnitude and clinical correlates of performance variability could improve our understanding of cognitive impairments. Using double generalized linear models (DGLMs) we investigated cognitive mean and variability differences between patients with SZ (n = 905) and BD spectrum disorders (n = 522), and healthy controls (HC, n = 1170) on twenty-two variables. The analysis revealed significant case-control differences on 90% of the variables. Compared to HC, patients showed larger intra-individual (within subject) variability across tests and larger inter-individual (between subject) variability in measures of fine-motor speed, mental processing speed, and inhibitory control (SZ and BD), and in verbal learning and memory and intellectual functioning (SZ). In SZ, we found that lager intra -and inter (on inhibitory control and speed functions) individual variability, was associated with lower functioning and more negative symptoms. Inter-individual variability on single measures of memory and intellectual function was additionally associated with disorganized and positive symptoms, and use of antidepressants. In BD, there were no within-subject associations with symptom severity. However, greater inter-individual variability (primarily on inhibitory control and speeded functions) was associated with lower functioning, more negative -and disorganized symptoms, earlier age at onset, longer duration of illness, and increased medication use. These results highlight larger individual differences in patients compared to controls on various cognitive domains. Further investigations of the causes and correlates of individual differences in cognitive function are warranted.

Real-life outcomes in biotypes of psychotic disorders based on neurocognitive performance

Aiming at discerning potential biotypes within the psychotic syndrome, we have recently reported the possible existence of two clusters or biotypes across schizophrenia and bipolar disorder characterized by their cognitive performance using the Brief Assessment of Cognition in Schizophrenia (BACS) instrument and validated with independent biological and clinical indexes (Fernández-Linsenbarth et al. in Schizophr Res 229:102-111, 2021). In this previous work, the group with larger cognitive deficits (N = 93, including 69 chronic schizophrenia, 17 first episodes (FE) of schizophrenia and 7 bipolar disorder patients) showed smaller thalamus and hippocampus volume and hyper-synchronic electroencephalogram than the group with milder deficits (N = 105, including 58 chronic schizophrenia, 25 FE and 22 bipolar disorder patients). We predicted that if these biotypes indeed corresponded to different cognitive and biological substrates, their adaptation to real life would be different. To this end, in the present work we have followed up the patients' population included in that work at 1st and 3rd years after the date of inclusion in the 2021 study and we report on the statistical comparisons of each clinical and real-life outcomes between them. The first cluster, with larger cognitive deficits and more severe biological alterations, showed during that period a decreased capacity for job tenure (1st and 3rd years), more admissions to a psychiatric ward (1st year) and a higher likelihood for quitting psychiatric follow-up (3rd year). Patients in the second cluster, with moderate cognitive deficits, were less compliant with prescribed treatment at the 3rd year. The differences in real-life outcomes may give additional external validity to that yielded by biological measurements to the described biotypes based on neurocognition.

The relationship between cognitive clusters and telomere length in bipolar-schizophrenia spectrum disorders

BACKGROUND

Schizophrenia and bipolar disorder are complex mental illnesses that are associated with cognitive deficits. There is considerable cognitive heterogeneity that exists within both disorders. Studies that cluster schizophrenia and bipolar patients into subgroups based on their cognitive profile increasingly demonstrate that, relative to healthy controls, there is a severely compromised subgroup and a relatively intact subgroup. There is emerging evidence that telomere shortening, a marker of cellular senescence, may be associated with cognitive impairments. The aim of this study was to explore the relationship between cognitive subgroups in bipolar-schizophrenia spectrum disorders and telomere length against a healthy control sample.

METHODS

Participants included a transdiagnostic group diagnosed with bipolar, schizophrenia or schizoaffective disorder (n = 73) and healthy controls (n = 113). Cognitive clusters within the transdiagnostic patient group, were determined using K-means cluster analysis based on current cognitive functioning (MATRICS Consensus Cognitive Battery scores). Telomere length was determined using quantitative PCRs genomic DNA extracted from whole blood. Emergent clusters were then compared to the healthy control group on telomere length.

RESULTS

Two clusters emerged within the patient group that were deemed to reflect a relatively intact cognitive group and a cognitively impaired subgroup. Telomere length was significantly shorter in the severely impaired cognitive subgroup compared to the healthy control group.

CONCLUSIONS

This study replicates previous findings of transdiagnostic cognitive subgroups and associates shorter telomere length with the severely impaired cognitive subgroup. These findings support emerging literature associating cognitive impairments in psychiatric disorders to accelerated cellular aging as indexed by telomere length.

Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach

Introduction

Prior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and examine relationships between cognitive subgroups and a comprehensive array of illness-related variables.

Methods

Two-hundred-eighty-nine Chinese patients aged 26-55 years presenting with FEP to an early intervention program in Hong Kong were recruited. Assessments encompassing premorbid adjustment, illness-onset profile, symptom severity, psychosocial functioning, subjective quality-of-life, and a battery of cognitive tests were conducted. Hierarchical cluster-analysis was employed, optimized with k-means clustering and internally-validated by discriminant-functional analysis. Cognitive subgroup comparisons in illness-related variables, followed by multivariable multinominal-regression analyzes were performed to identify factors independently predictive of cluster membership.

Results

Three clusters were identified including patients with globally-impaired (n = 101, 34.9%), intermediately-impaired (n = 112, 38.8%) and relatively-intact (n = 76, 26.3%) cognition (GIC, IIC and RIC subgroups) compared to demographically-matched healthy-controls' performance (n = 50). GIC-subgroup was older, had lower educational attainment, greater positive, negative and disorganization symptom severity, poorer insight and quality-of-life than IIC- and RIC-subgroups, and higher antipsychotic-dose than RIC-subgroup. IIC-subgroup had lower education levels and more severe negative symptoms than RIC-subgroup, which had better psychosocial functioning than two cognitively-impaired subgroups. Educational attainment and disorganization symptoms were found to independently predict cluster membership.

Discussion

Our results affirmed cognitive heterogeneity in FEP and identified three subgroups, which were differentially associated with demographic and illness-related variables. Further research should clarify longitudinal relationships of cognitive subgroups with clinical and functional outcomes in FEP.

The "zipper model of empathy" applied to violence in schizophrenia: A search for social cognitive underpinnings of lack of empathic behavior

BACKGROUND

The "zipper model of empathy" has been proposed for psychopathy. It postulates that empathic behavior may fail to arise due to impaired facial emotion recognition. In this study, we examined if the model may be of relevance for schizophrenia.

METHODS

In a sample of participants with schizophrenia and a history of severe interpersonal violence, associations between measures of social cognition (emotion recognition, theory of mind) and aspects of psychopathy (lack of empathy, lack of remorse) were investigated. A non-violent sample experiencing schizophrenia served as a control group.

RESULTS

Correlation analyses revealed a specific and statistically significant association between facial emotion recognition and lack of empathy in the violent sample. Follow-up analyses identified that neutral emotions were of particular importance. Logistic regression analyses confirmed that impairments in facial emotion recognition predicted levels of empathy in the violent sample experiencing schizophrenia.

CONCLUSIONS

Our results suggest that the "zipper model of empathy" may be relevant for schizophrenia. The findings further point to the potential benefit of including social cognitive training in the treatment of persons with schizophrenia and a history of interpersonal aggression.

Neurocognitive subgroups among newly diagnosed patients with schizophrenia spectrum or bipolar disorders: A hierarchical cluster analysis

Studies across schizophrenia (SZ) and bipolar disorder (BD) indicate common transdiagnostic neurocognitive subgroups. However, existing studies of patients with long-term illness precludes insight into whether impairments result from effects of chronic illness, medication or other factors. This study aimed to investigate whether neurocognitive subgroups across SZ and BD can be demonstrated during early illness stages. Data from overlapping neuropsychological tests were pooled from cohort studies of antipsychotic-naïve patients with first-episode SZ spectrum disorders (n = 150), recently diagnosed BD (n = 189) or healthy controls (HC) (n = 280). Hierarchical cluster analysis was conducted to examine if transdiagnostic subgroups could be identified based on the neurocognitive profile. Patterns of cognitive impairments and patient characteristics across subgroups were examined. Patients could be clustered into two, three and four subgroups, of which the three-cluster solution (with 83% accuracy) was selected for posthoc analyses. This solution revealed a subgroup covering 39% of patients (predominantly BD) who were cognitively relatively intact, a subgroup of 33% of patients (more equal distributions of SZ and BD) displaying selective deficits, particularly in working memory and processing speed, and a subgroup of 28% (mainly SZ) with global impairments. The globally impaired group exhibited lower estimated premorbid intelligence than the other subgroups. Globally impaired BD patients also showed more functional disability than cognitively relatively intact patients. No differences were observed across subgroups in symptoms or medications. Neurocognitive results can be understood by clustering analysis with similar clustering solutions occurring across diagnoses. The subgroups were not explained by clinical symptoms or medication, suggesting neurodevelopmental origins.

The multimodal Munich Clinical Deep Phenotyping study to bridge the translational gap in severe mental illness treatment research

Introduction

Treatment of severe mental illness (SMI) symptoms, especially negative symptoms and cognitive dysfunction in schizophrenia, remains a major unmet need. There is good evidence that SMIs have a strong genetic background and are characterized by multiple biological alterations, including disturbed brain circuits and connectivity, dysregulated neuronal excitation-inhibition, disturbed dopaminergic and glutamatergic pathways, and partially dysregulated inflammatory processes. The ways in which the dysregulated signaling pathways are interconnected remains largely unknown, in part because well-characterized clinical studies on comprehensive biomaterial are lacking. Furthermore, the development of drugs to treat SMIs such as schizophrenia is limited by the use of operationalized symptom-based clusters for diagnosis.

Methods

In line with the Research Domain Criteria initiative, the Clinical Deep Phenotyping (CDP) study is using a multimodal approach to reveal the neurobiological underpinnings of clinically relevant schizophrenia subgroups by performing broad transdiagnostic clinical characterization with standardized neurocognitive assessments, multimodal neuroimaging, electrophysiological assessments, retinal investigations, and omics-based analyzes of blood and cerebrospinal fluid. Moreover, to bridge the translational gap in biological psychiatry the study includes in vitro investigations on human-induced pluripotent stem cells, which are available from a subset of participants.

Results

Here, we report on the feasibility of this multimodal approach, which has been successfully initiated in the first participants in the CDP cohort; to date, the cohort comprises over 194 individuals with SMI and 187 age and gender matched healthy controls. In addition, we describe the applied research modalities and study objectives.

Discussion

The identification of cross-diagnostic and diagnosis-specific biotype-informed subgroups of patients and the translational dissection of those subgroups may help to pave the way toward precision medicine with artificial intelligence-supported tailored interventions and treatment. This aim is particularly important in psychiatry, a field where innovation is urgently needed because specific symptom domains, such as negative symptoms and cognitive dysfunction, and treatment-resistant symptoms in general are still difficult to treat.

A new era for schizophrenia drug development - Lessons for the future

For many patients and their treating clinicians, the pharmacological management of psychotic symptoms centres on trying to find a regime that balances efficacy and quality of life, impairing side effects associated with dopamine antagonism. Recent reports of a positive Phase III study from Karuna Therapeutics indicate that the first primarily non-dopamine-based treatment for schizophrenia may come to market soon with the potential for substantially reduced or differentiated side effects. Against a background of repeated failures, Karuna's success promises a desperately needed new treatment option for patients. It also reflects some hard-won lessons about the methodology for schizophrenia drug development. Teaser A positive Phase II study and positive media report from a Phase III study with xanomeline/trospium may herald the first truly new treatment option for schizophrenia patients in decades. This drug's journey to this point reflects some hard-won lessons about the methodology for schizophrenia drug development.

Cognitive function in early-phase schizophrenia-spectrum disorder: IQ subtypes, brain volume and immune markers

BACKGROUND

Evidence suggests that cognitive subtypes exist in schizophrenia that may reflect different neurobiological trajectories. We aimed to identify whether IQ-derived cognitive subtypes are present in early-phase schizophrenia-spectrum disorder and examine their relationship with brain structure and markers of neuroinflammation.

METHOD

161 patients with recent-onset schizophrenia spectrum disorder (<5 years) were recruited. Estimated premorbid and current IQ were calculated using the Wechsler Test of Adult Reading and a 4-subtest WAIS-III. Cognitive subtypes were identified with k-means clustering. Freesurfer was used to analyse 3.0 T MRI. Blood samples were analysed for hs-CRP, IL-1RA, IL-6 and TNF-α.

RESULTS

Three subtypes were identified indicating preserved (PIQ), deteriorated (DIQ) and compromised (CIQ) IQ. Absolute total brain volume was significantly smaller in CIQ compared to PIQ and DIQ, and intracranial volume was smaller in CIQ than PIQ (F(2, 124) = 6.407, p = 0.002) indicative of premorbid smaller brain size in the CIQ group. CIQ had higher levels of hs-CRP than PIQ (F(2, 131) = 5.01, p = 0.008). PIQ showed differentially impaired processing speed and verbal learning compared to IQ-matched healthy controls.

CONCLUSIONS

The findings add validity of a neurodevelopmental subtype of schizophrenia identified by comparing estimated premorbid and current IQ and characterised by smaller premorbid brain volume and higher measures of low-grade inflammation (CRP).

Working memory heterogeneity from age 7 to 11 in children at familial high risk of schizophrenia or bipolar disorder- The Danish High Risk and Resilience Study

BACKGROUND

Despite the genetic overlap between bipolar disorder and schizophrenia, working memory impairments are mainly found in children of parents with schizophrenia. However, working memory impairments are characterized by substantial heterogeneity, and it is unknown how this heterogeneity develops over time. We used a data-driven approach to assess working memory heterogeneity and longitudinal stability in children at familial high risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP).

METHODS

Based on the performances on four working memory tasks by 319 children (FHR-SZ, N = 202, FHR-BP, N = 118) measured at age 7 and 11, latent profile transition analysis was used to test for the presence of subgroups, and the stability of subgroup membership over time. Population-based controls (VIA 7, N = 200, VIA 11, N = 173) were included as a reference group. The working memory subgroups were compared based on caregiver- and teacher ratings of everyday working memory function, and dimensional psychopathology.

RESULTS

A model with three subgroups characterized by different levels of working memory function (an impaired subgroup, a mixed subgroup, and an above average subgroup) best fitted the data. The impaired subgroup had the highest ratings of everyday working memory impairments and psychopathology. Overall, 98 % (N = 314) stayed in the same subgroup from age 7 to 11.

CONCLUSION

Persistent working memory impairments are present in a subset of children at FHR-SZ and FHR-BP throughout middle childhood. Attention should be given to these children, as working memory impairments influence daily life, and may serve as a vulnerability marker of transition to severe mental illness.

Longitudinal clinical and functional outcome in distinct cognitive subgroups of first-episode psychosis: a cluster analysis

BACKGROUND

Cognitive deficits may be characteristic for only a subgroup of first-episode psychosis (FEP) and the link with clinical and functional outcomes is less profound than previously thought. This study aimed to identify cognitive subgroups in a large sample of FEP using a clustering approach with healthy controls as a reference group, subsequently linking cognitive subgroups to clinical and functional outcomes.

METHODS

204 FEP patients were included. Hierarchical cluster analysis was performed using baseline brief assessment of cognition in schizophrenia (BACS). Cognitive subgroups were compared to 40 controls and linked to longitudinal clinical and functional outcomes (PANSS, GAF, self-reported WHODAS 2.0) up to 12-month follow-up.

RESULTS

Three distinct cognitive clusters emerged: relative to controls, we found one cluster with preserved cognition (n = 76), one moderately impaired cluster (n = 74) and one severely impaired cluster (n = 54). Patients with severely impaired cognition had more severe clinical symptoms at baseline, 6- and 12-month follow-up as compared to patients with preserved cognition. General functioning (GAF) in the severely impaired cluster was significantly lower than in those with preserved cognition at baseline and showed trend-level effects at 6- and 12-month follow-up. No significant differences in self-reported functional outcome (WHODAS 2.0) were present.

CONCLUSIONS

Current results demonstrate the existence of three distinct cognitive subgroups, corresponding with clinical outcome at baseline, 6- and 12-month follow-up. Importantly, the cognitively preserved subgroup was larger than the severely impaired group. Early identification of discrete cognitive profiles can offer valuable information about the clinical outcome but may not be relevant in predicting self-reported functional outcomes.

Impact of early negative symptom patterns on the long-term outcomes of patients with first-episode schizophrenia-spectrum disorders: A 12-year follow up study

Given the strong prognostic value of early negative symptoms (NS), understanding their associations with long-term outcomes of schizophrenia is essential. The study examined early NS patterns in trajectory, severity and variability and their association with 12-year outcomes. NS in the first 36 months after onset and the symptomatology, cognitive function, and functioning at 12 years were examined in 330 patients with first-episode schizophrenia spectrum disorders. The relationships and pathways between the outcomes at 12 years and the trajectory, severity, and variability of early NS were examined. We found that the prediction of trajectory of early NS to long-term outcomes was limited, whereas variability was negatively associated with the patient's long-term executive function, and severity was positively associated with long-term symptomatology and negatively associated with long-term functioning. Path modelling revealed that the severity and variability of early NS influenced patients' long-term functioning via cognitive function and/or clinical symptom pathways. Our findings support the notion that severity of early NS influences the prognosis of schizophrenia and the closer examination revealed that the severity and variability of early NS are differentially associated with long-term clinical symptoms, executive function, and functional outcomes via distinct pathways.

Brain Morphological Characteristics of Cognitive Subgroups of Schizophrenia-Spectrum Disorders and Bipolar Disorder: A Systematic Review with Narrative Synthesis

Despite a growing body of research, there is yet to be a cohesive synthesis of studies examining differences in brain morphology according to patterns of cognitive function among both schizophrenia-spectrum disorder (SSD) and bipolar disorder (BD) individuals. We aimed to provide a systematic overview of the morphological differences-inclusive of grey and white matter volume, cortical thickness, and cortical surface area-between cognitive subgroups of these disorders and healthy controls, and between cognitive subgroups themselves. An initial search of PubMed and Scopus databases resulted in 1486 articles of which 20 met inclusion criteria and were reviewed in detail. The findings of this review do not provide strong evidence that cognitive subgroups of SSD or BD map to unique patterns of brain morphology. There is preliminary evidence to suggest that reductions in cortical thickness may be more strongly associated with cognitive impairment, whilst volumetric deficits may be largely tied to the presence of disease.

Factors Impacting Access and Engagement of Cognitive Remediation Therapy for People with Schizophrenia: A Systematic Review

OBJECTIVES

Neurocognitive deficits are central in schizophrenia. Cognitive remediation has proven effective in alleviating these deficits, with medium effect sizes. However, sizeable attrition rates are reported, with the reasons still uncertain. Furthermore, cognitive remediation is not part of routine mental health care. We conducted a systematic review to investigate factors that influence access and engagement of cognitive remediation in schizophrenia.

METHODS

We systematically searched the PubMed, Web of Science, and PsycINFO databases for peer-reviewed articles including a cognitive remediation arm, access, and engagement data, and participants with schizophrenia spectrum disorders aged 17-65 years old. Duplicates and studies without a distinct cognitive remediation component, protocol papers, single case studies, case series, and reviews/meta-analyses were excluded.

RESULTS

We included 67 studies that reported data on access and engagement, and extracted quantitative and qualitative data. Access data were limited, with most interventions delivered on-site, to outpatients, and in middle- to high-income countries. We found a median dropout rate of 14.29%. Only a small number of studies explored differences between dropouts and completers (n = 5), and engagement factors (n = 13). Dropouts had higher negative symptomatology and baseline self-efficacy, and lower baseline neurocognitive functioning and intrinsic motivation compared to completers. The engagement was positively associated with intrinsic motivation, self-efficacy, perceived usefulness, educational level, premorbid intelligence quotient, baseline neurocognitive functioning, some neurocognitive outcomes, and therapeutic alliance; and negatively associated with subjective cognitive complaints. Qualitative results showed good acceptability of cognitive remediation, with some areas for improvement.

CONCLUSIONS

Overall, access and engagement results are scarce and heterogeneous. Further investigations of cognitive remediation for inpatients, as well as remote delivery, are needed. Future clinical trials should systematically explore attrition and related factors. Determining influential factors of access and engagement will help improve the implementation and efficacy of cognitive remediation, and thus the recovery of people with schizophrenia.

Neurocognitive Subgroups in Children at Familial High-risk of Schizophrenia or Bipolar disorder: Subgroup Membership Stability or Change From Age 7 to 11-The Danish High Risk and Resilience Study

BACKGROUND AND HYPOTHESIS

Subgroups with distinct levels of neurocognitive functioning exist in children of parents with schizophrenia or bipolar disorder. However, studies investigating the temporal stability of subgroup membership are currently lacking. We hypothesized that a minority of children at familial high-risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) would transition to a different neurocognitive subgroup from age 7 to 11 and that most transitions would be to a more impaired subgroup.

STUDY DESIGN

Latent profile analysis was used to identify subgroups at two assessments (age 7 and 11) based on the performance of 320 children at FHR-SZ or FHR-BP across eight neurocognitive functions. Temporal stability in subgroup membership was evaluated with latent profile transition analysis. Population-based controls (age 7, n = 199; age 11, n = 178) were included as a reference group. Children transitioning to a more impaired subgroup were compared with nontransitioning children on sex, FHR-status, global functioning, and psychopathology.

STUDY RESULTS

At both assessment points, we identified three subgroups based on neurocognitive performance: a moderately-severely impaired, a mildly impaired, and an above-average subgroup. A total of 12.8% of children transitioned to a different subgroup, of which the majority (85.2%) moved to a more impaired subgroup. Parental diagnosis of schizophrenia, but neither parental diagnosis of bipolar disorder, global functioning at age 7, psychopathology, nor sex significantly differentiated children transitioning to a more impaired subgroup from nontransitioning children.

CONCLUSIONS

During pre-adolescence, neurocognitive developmental lag is associated with being at FHR-SZ. Close attention to these children's neurocognitive development is indicated.

Social cognitive heterogeneity in schizophrenia: A cluster analysis

This study examined social cognitive heterogeneity in Norwegian sample of individuals with schizophrenia (n = 82). They were assessed with three social cognitive tests: Emotion in Biological Motion (emotion processing), Relationships Across Domains (social perception), and Movie for the Assessment of Social Cognition (theory of mind). Hierarchical and k-means cluster analyses using standardized scores on these three tests provided two clusters. The first cluster (68 %) had mild social cognitive impairments (<0.5 standard deviations below healthy comparison participants). The second cluster (32 %) had severe social cognitive impairments (>2 standard deviations below healthy comparison participants). Validity of the two social cognitive subgroups was indicated by significant differences in functioning, symptom load and nonsocial cognition. Our study shows that social cognitive tests can be used for clinical and cognitive subtyping. This is of potential relevance for treatment.

Longer illness duration is associated with greater individual variability in functional brain activity in Schizophrenia, but not bipolar disorder

BACKGROUND

Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity.

METHODS

Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a 'variability score'.

RESULTS

Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e-09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027).

CONCLUSION

An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.

Evidence that a working memory cognitive phenotype within schizophrenia has a unique underlying biology

It is suggested studying phenotypes within the syndrome of schizophrenia will accelerate understanding the complex molecular pathology of the disorder. Supporting this hypothesis, we have identified a sub-group within schizophrenia with impaired working memory (WM) and have used Affymetrix™ Human Exon 1.0 ST Arrays to compare their blood RNA levels (n=16) to a group of with intact WM (n=18). Levels of 72 RNAs were higher in blood from patients with impaired WM, 11 of which have proven links to the maintenance of different aspects of working memory (cognition). Overall, changed gene expression in those with impaired WM could be linked to cognition through glutamatergic activity, olfaction, immunity, inflammation as well as energy and metabolism. Our data gives preliminary support to the hypotheses that there is a working memory deficit phenotype within the syndrome of schizophrenia with has a biological underpinning. In addition, our data raises the possibility that a larger study could show that the specific changes in gene expression we have identified could prove to be the biomarkers needed to develop a blood test to identify those with impaired WM; a significant step toward allowing the use of personalised medicine directed toward improving their impaired working memory.

Identifying and revealing different brain neural activities of cognitive subtypes in early course schizophrenia

Background

Cognitive subtypes of schizophrenia may exhibit different neurobiological characteristics. This study aimed to reveal the underlying neurobiological features between cognitive subtypes in the early course of schizophrenia (ECS). According to prior studies, we hypothesized to identify 2–4 distinct cognitive subtypes. We further hypothesized that the subtype with relatively poorer cognitive function might have lower brain spontaneous neural activity than the subtype with relatively better cognitive function.

Method

Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Resting-state functional magnetic resonance imaging scanning was conducted for each individual. There were 155 ECS individuals and 97 healthy controls (HCs) included in the subsequent analysis. Latent profile analysis (LPA) was used to identify the cognitive subtypes in ECS individuals, and amplitude of low-frequency fluctuations (ALFFs) was used to measure brain spontaneous neural activity in ECS individuals and HCs.

Results

LPA identified two cognitive subtypes in ECS individuals, containing a severely impaired subtype (SI, n = 63) and a moderately impaired subtype (MI, n = 92). Compared to HCs, ECS individuals exhibited significantly increased ALFF in the left caudate and bilateral thalamus and decreased ALFF in the bilateral medial prefrontal cortex and bilateral posterior cingulate cortex/precuneus (PCC/PCu). In ECS cognitive subtypes, SI showed significantly higher ALFF in the left precentral gyrus (PreCG) and lower ALFF in the left PCC/PCu than MI. Furthermore, ALFFs of left PreCG were negatively correlated with several MCCB cognitive domains in ECS individuals, while ALFF of left PCC/PCu presented opposite correlations.

Conclusion

Our findings suggest that differences in the brain spontaneous neural activity of PreCG and PCC/PCu might be the potential neurobiological features of the cognitive subtypes in ECS, which may deepen our understanding of the role of PreCG and PCC/PCu in the pathogenesis of cognitive impairment in schizophrenia.

The impact of smoking status on cognition and brain morphology in schizophrenia spectrum disorders

BACKGROUND

Cigarette smoking is associated with worse cognition and decreased cortical volume and thickness in healthy cohorts. Chronic cigarette smoking is prevalent in schizophrenia spectrum disorders (SSD), but the effects of smoking status on the brain and cognition in SSD are not clear. This study aimed to understand whether cognitive performance and brain morphology differed between smoking and non-smoking individuals with SSD compared to healthy controls.

METHODS

Data were obtained from the Australian Schizophrenia Research Bank. Cognitive functioning was measured in 299 controls and 455 SSD patients. Cortical volume, thickness and surface area data were analysed from T1-weighted structural scans obtained in a subset of the sample (n = 82 controls, n = 201 SSD). Associations between smoking status (cigarette smoker/non-smoker), cognition and brain morphology were tested using analyses of covariance, including diagnosis as a moderator.

RESULTS

No smoking by diagnosis interactions were evident, and no significant differences were revealed between smokers and non-smokers across any of the variables measured, with the exception of a significantly thinner left posterior cingulate in smokers compared to non-smokers. Several main effects of smoking in the cognitive, volume and thickness analyses were initially significant but did not survive false discovery rate (FDR) correction.

CONCLUSIONS

Despite the general absence of significant FDR-corrected findings, trend-level effects suggest the possibility that subtle smoking-related effects exist but were not uncovered due to low statistical power. An investigation of this topic is encouraged to confirm and expand on our findings.

Psychosis and Hopelessness Mediate the Relationship Between Reduced Sleep and Suicidal Ideation in Schizophrenia Spectrum Disorders

OBJECTIVE

Suicide is a major cause of death amongst individuals with schizophrenia spectrum disorders (SSD). Despite numerous risk factors being identified, accurate prediction of suicidality and provision of tailored and effective treatment is difficult. One factor that may warrant particular attention as a contributor to increased psychopathology and suicidality in SSD is disturbed sleep. Sleep disturbances have been reliably linked to greater levels of suicidal ideation and are highly prevalent amongst individuals with SSD. This study aimed to examine if reduced sleep duration and psychopathology are associated with increased suicidal ideation.

METHOD

One-hundred and eighteen adults with chronic SSD living within the community participated in this cross-sectional study. Psychosis symptoms were assessed using the Positive and Negative Syndrome Scale. Items 4 and 10 from the Montgomery-Asperg Depression Rating Scale and Item 2 from the Calgary Depression Scale for Schizophrenia were used to assess reduced sleep duration, current suicidal ideation, and hopelessness, respectively. All measures were rated concurrently.

RESULTS

A hierarchical logistic regression revealed that greater acute sleep disturbances were associated with increased suicidal ideation and this relationship was found to be uniquely mediated by both positive symptom severity and hopelessness.

CONCLUSION

These results suggest that individuals with SSD who exhibited disrupted or disordered sleep, positive symptoms and/or hopelessness should be routinely screened for suicidal thinking. Furthermore, interventions that effectively target sleep disruptions may provide much-needed action against suicidal ideation.HIGHLIGHTSReduced sleep found to be associated with increased suicidal ideationThis was uniquely mediated by both hopelessness and positive symptomsMore regular screening of sleep problems in schizophrenia is needed.

A New Treatment Paradigm: Targeting Trace Amine-Associated Receptor 1 (TAAR1) in Schizophrenia

This continuing education supplement is jointly provided by Medical Education Resources and CMEology. The supplement is supported by an independent educational grant from Sunovion Pharmaceuticals Inc. It was edited and peer reviewed by the Journal of Clinical Psychopharmacology.After reviewing the learning objectives and reading the supplement, please complete the Activity Evaluation/Credit Request form online at https://www.cmesurvey.site/TAAR1.

ABSTRACT

All currently available antipsychotics work via essentially the same mechanism: by antagonizing the dopamine D2 receptor. However, schizophrenia is an extremely heterogeneous condition, and antipsychotics do not adequately control symptoms for all patients. Negative and cognitive symptoms are especially difficult to manage with existing medications. Therefore, antipsychotic agents with novel mechanisms of action are urgently needed. Recently, a phase 2 clinical trial and extension study demonstrated that, relative to placebo, the trace amine-associated receptor 1 (TAAR1) agonist ulotaront was effective at controlling the positive, negative, and cognitive symptoms of schizophrenia. In addition, ulotaront seems to lack the weight gain, metabolic issues, and extrapyramidal symptoms associated with traditional antipsychotics. This agent is currently undergoing multiple phase 3 trials for the treatment of schizophrenia. Another TAAR1 agonist, ralmitaront, is being investigated for the treatment of schizophrenia and schizoaffective disorders. Two phase 2 clinical trials are underway, evaluating ralmitaront both as a monotherapy and an add-on therapy to traditional antipsychotics. In this supplement, we review the biologic, preclinical, and clinical data available for TAAR1 agonists, so that if and when they are approved for the treatment of schizophrenia, psychiatry specialists will be ready to use them to optimize patient outcomes. We also briefly review other emerging therapies in late-stage development for the treatment of schizophrenia.

Neurocognitive Artificial Neural Network Models Are Superior to Linear Models at Accounting for Dimensional Psychopathology

In recent years, there has been debate about the optimal conceptualisation of psychopathology. Structural models of psychopathology have been developed to counter issues, including comorbidity and poor diagnostic stability prevalent within the traditional nosological approach. Regardless of the conceptualisation of psychological dysfunction, deficits in neurocognitive abilities have been claimed to be an aetiological feature of psychopathology. Explorations of the association between neurocognition and psychopathology have typically taken a linear approach, overlooking the potential interactive dynamics of neurocognitive abilities. Previously, we proposed a multidimensional hypothesis, where within-person interactions between neurocognitive domains are fundamental to understanding the role of neurocognition within psychopathology. In this study, we used previously collected psychopathology data for 400 participants on psychopathological symptoms, substance use, and performance on eight neurocognitive tasks and compared the predictive accuracy of linear models to artificial neural network models. The artificial neural network models were significantly more accurate than the traditional linear models at predicting actual (a) lower-level and (b) high-level dimensional psychopathology. These results provide support for the multidimensional hypothesis: that the study of non-linear interactions and compensatory neurocognitive profiles are integral to understanding the functional associations between neurocognition and of psychopathology.

First-Episode Psychosis Patients Who Deteriorated in the Premorbid Period Do Not Have Higher Polygenic Risk Scores Than Others: A Cluster Analysis of EU-GEI Data

Cluster studies identified a subgroup of patients with psychosis whose premorbid adjustment deteriorates before the onset, which may reflect variation in genetic influence. However, other studies reported a complex relationship between distinctive patterns of cannabis use and cognitive and premorbid impairment that is worthy of consideration. We examined whether: (1) premorbid social functioning (PSF) and premorbid academic functioning (PAF) in childhood and adolescence and current intellectual quotient (IQ) define different clusters in 802 first-episode of psychosis (FEP) patients; resulting clusters vary in (2) polygenic risk scores (PRSs) for schizophrenia (SCZ_PRS), bipolar disorder (BD_PRS), major depression (MD_PRS), and IQ (IQ_PRS), and (3) patterns of cannabis use, compared to 1,263 population-based controls. Four transdiagnostic clusters emerged (BIC = 2268.5): (1) high-cognitive-functioning (n = 205), with the highest IQ (Mean = 106.1, 95% CI: 104.3, 107.9) and PAF, but low PSF. (2) Low-cognitive-functioning (n = 223), with the lowest IQ (Mean = 73.9, 95% CI: 72.2, 75.7) and PAF, but normal PSF. (3) Intermediate (n = 224) (Mean_IQ = 80.8, 95% CI: 79.1, 82.5) with low-improving PAF and PSF. 4) Deteriorating (n = 150) (Mean_IQ = 80.6, 95% CI: 78.5, 82.7), with normal-deteriorating PAF and PSF. The PRSs explained 7.9% of between-group membership. FEP had higher SCZ_PRS than controls [F(4,1319) = 20.4, P < .001]. Among the clusters, the deteriorating group had lower SCZ_PRS and was likelier to have used high-potency cannabis daily. Patients with FEP clustered according to their premorbid and cognitive abilities. Pronounced premorbid deterioration was not typical of most FEP, including those more strongly predisposed to schizophrenia, but appeared in a cluster with a history of high-potency cannabis use.

Theory of mind in schizophrenia: a comparison of subgroups with low and high IQ

BACKGROUND

Social cognitive impairment is common in schizophrenia, but it is unclear if it is present in individuals with high IQ. This study compared theory of mind (ToM) in schizophrenia participants with low or high IQ to healthy controls.

METHODS

One hundred and nineteen participants (71 healthy controls, 17 high IQ (IQ ≥115), and 31 low IQ (IQ ≤95) schizophrenia participants) were assessed with the Movie for the Assessment of Social Cognition, providing scores for total, cognitive, and affective ToM, along with overmentalizing, undermentalizing, and no-mentalizing errors. IQ was measured with Wechsler Abbreviated Scale of Intelligence; clinical symptoms with the Positive and Negative Syndrome Scale.

RESULTS

Healthy controls performed better than the low IQ schizophrenia group for all ToM scores, and better than the high IQ schizophrenia group for the total score and under- and no-mentalizing errors. The high IQ group made fewer overmentalizing errors and had better total and cognitive ToM than the low IQ group. Their number of overmentalizing errors was indistinguishable from healthy controls.

CONCLUSION

Global ToM impairment was present in the low IQ schizophrenia group. Overmentalizing was not present in the high IQ group and appears related to lower IQ. Intact higher-level reasoning may prevent the high IQ group from making overmentalizing errors, through self-monitoring or inhibition. We propose that high IQ patients are chiefly impaired in lower-level ToM, whereas low IQ patients also have impaired higher-level ToM. Conceivably, this specific impairment could help explain the lower functioning reported in persons with intact IQ.

Effects of socioeconomic status in cognition of people with schizophrenia: results from a Latin American collaboration network with 1175 subjects

BACKGROUND

Cognition heavily relies on social determinants and genetic background. Latin America comprises approximately 8% of the global population and faces unique challenges, many derived from specific demographic and socioeconomic variables, such as violence and inequality. While such factors have been described to influence mental health outcomes, no large-scale studies with Latin American population have been carried out. Therefore, we aim to describe the cognitive performance of a representative sample of Latin American individuals with schizophrenia and its relationship to clinical factors. Additionally, we aim to investigate how socioeconomic status (SES) relates to cognitive performance in patients and controls.

METHODS

We included 1175 participants from five Latin American countries (Argentina, Brazil, Chile, Colombia, and Mexico): 864 individuals with schizophrenia and 311 unaffected subjects. All participants were part of projects that included cognitive evaluation with MATRICS Consensus Cognitive Battery and clinical assessments.

RESULTS

Patients showed worse cognitive performance than controls across all domains. Age and diagnosis were independent predictors, indicating similar trajectories of cognitive aging for both patients and controls. The SES factors of education, parental education, and income were more related to cognition in patients than in controls. Cognition was also influenced by symptomatology.

CONCLUSIONS

Patients did not show evidence of accelerated cognitive aging; however, they were most impacted by a lower SES suggestive of deprived environment than controls. These findings highlight the vulnerability of cognitive capacity in individuals with psychosis in face of demographic and socioeconomic factors in low- and middle-income countries.