Cognitive variability in psychotic disorders: a cross-diagnostic cluster analysis

Artificial intelligence in insanity evaluation. Potential opportunities and current challenges

The formulation of a scientific opinion on whether the individual who committed a crime should be held responsible for his/her actions or should be considered not responsible by reason of insanity is very difficult. Indeed, forensic psychopathological decision on insanity is highly prone to errors and is affected by human cognitive biases, resulting in low inter-rater reliability. In this context, artificial intelligence can be extremely useful to improve the inter-subjectivity of insanity evaluation. In this paper, we discuss the possible applications of artificial intelligence in this field as well as the challenges and pitfalls that hamper the effective implementation of AI in insanity evaluation. In particular, thus far, it is possible to apply only supervised algorithms without knowing which is the ground truth and which data should be used to train and test the algorithms. In addition, it is not known which percentage of accuracy of the algorithms is sufficient to support partial or total insanity, nor which are the boundaries between sanity and partial or total insanity. Finally, ethical aspects have not been sufficiently investigated. We conclude that these pitfalls should be resolved before AI can be safely and reliably applied in criminal trials.

Differences in EEG complexity of cognitive activities among subtypes of schizophrenia

Introduction

The neural mechanisms that underpin cognitive impairments in patients with schizophrenia remain unclear. Previous studies have typically treated patients as a homogeneous group, despite the existence of distinct symptom presentations between deficit and non-deficit subtypes. This approach has been found to be inadequate, necessitating separate investigation.

Methods

This study was conducted at Daizhuang Hospital in Jining City, China, from January 2022 to October 2023. The study sample comprised 30 healthy controls, 19 patients with deficit schizophrenia, and 19 patients with non-deficit schizophrenia, all aged between 18 and 45 years. Cognitive abilities were evaluated using a change detection task. The NeuroScan EEG/ERP System, comprising 64 channels and utilising standard 10-20 electrode placements, was employed to record EEG signals. The multiscale entropy and sample entropy of the EEG signals were calculated.

Results

The healthy controls demonstrated superior task performance compared to both the non-deficit (p < 0.001) and deficit groups(p < 0.001). Significant differences in multiscale entropy between the three groups were observed at multiple electrode sites. In the task state, there are significant differences in the sample entropy of the β frequency band among the three groups of subjects. Under simple conditions of difficulty, the performance of the healthy controls exhibited a positive correlation with alpha band sample entropy(r = 0.372) and a negative correlation with beta band sample entropy (r = -0.411). Deficit patients demonstrated positive correlations with alpha band sample entropy (r = 0.370), whereas non-deficit patients exhibited negative correlations with both alpha and beta band sample entropy (r = -0.451, r = -0.362). Under difficult conditions of difficulty, the performance of healthy controls demonstrated a positive correlation with beta band sample entropy (r = 0.486). Deficit patients exhibited a positive correlation with alpha band sample entropy (r = 0.351), while non-deficit patients demonstrated a negative correlation with beta band sample entropy (r = -0.331).

Conclusion

The results of this study indicate that cognitive impairment in specific subtypes of schizophrenia may have distinct physiological underpinnings, underscoring the need for further investigation.

Cognitive Impairment in Psychotic Disorders Is Associated with Brain Reductive Stress and Impaired Energy Metabolism as Measured by 31P Magnetic Resonance Spectroscopy

BACKGROUND AND HYPOTHESIS

Convergent evidence shows the presence of brain metabolic abnormalities in psychotic disorders. This study examined brain reductive stress and energy metabolism in people with psychotic disorders with impaired or average range cognition. We hypothesized that global cognitive impairment would be associated with greater brain metabolic dysregulation.

STUDY DESIGN

Participants with affective and non-affective psychosis (n = 62) were administered the MATRICS Consensus Cognitive Battery (MCCB) and underwent a 31P-magnetic resonance spectroscopy scan at 4T. We used a cluster-analysis approach to identify 2 clusters of participants with and without cognitive dysfunction. We compared clusters on brain redox balance or reductive stress, measured by the ratio of nicotinamide adenine dinucleotide (NAD+) and its reduced form NADH, in addition to creatine kinase (CK) enzymatic activity and pH.

STUDY RESULTS

The mean (SD) age of participants was 25.1 (6.3) years. The mean NAD+/NADH ratio differed between groups, with lower NAD+/NADH ratio, suggesting more reductive stress, in the impaired cognitive cluster (t = -2.60, P = .01). There was also a significant reduction in CK activity in the impaired cognitive cluster (t = -2.19, P = .03). Intracellular pH did not differ between the 2 cluster groups (t = 1.31, P = .19). The clusters did not significantly differ on severity of mood and psychotic symptomatology or other measures of illness severity.

CONCLUSIONS

Our results demonstrate that psychotic disorders with greater cognitive impairment have greater brain metabolic dysregulation, with more reductive stress and decrease in energy metabolic rate markers. This provides new evidence for the potential of emerging metabolic therapies to treat cognitive deficits in psychotic disorders.

Transdiagnostic modeling of clinician-rated symptoms in affective and nonaffective psychotic disorders

Prevailing factor models of psychosis are centered on schizophrenia-related disorders defined by the Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases, restricting generalizability to other clinical presentations featuring psychosis, even though affective psychoses are more common. This study aims to bridge this gap by conducting exploratory and confirmatory factor analyses, utilizing clinical ratings collected from patients with either affective or nonaffective psychoses (n = 1,042). Drawing from established clinical instruments, such as the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery-Åsberg Depression Rating Scale, a broad spectrum of core psychotic symptoms was considered for the model development. Among the candidate models considered, including correlated factors and multifactor models, a model with seven correlated factors encompassing positive symptoms, negative symptoms, depression, mania, disorganization, hostility, and anxiety was most interpretable with acceptable fit. The seven factors exhibited expected associations with external validators, were replicable through cross-validation, and were generalizable across affective and nonaffective psychoses. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Longitudinal inference of multiscale markers in psychosis: from hippocampal centrality to functional outcome

Multiscale neuroscience conceptualizes mental illness as arising from aberrant interactions across and within multiple biopsychosocial scales. We leverage this framework to propose a multiscale disease progression model of psychosis, in which hippocampal-cortical dysconnectivity precedes impairments in episodic memory and social cognition, which lead to more severe negative symptoms and lower functional outcome. As psychosis represents a heterogeneous collection of biological and behavioral alterations that evolve over time, we further predict this disease progression for a subtype of the patient sample, with other patients showing normal-range performance on all variables. We sampled data from two cross-sectional datasets of first- and multi-episode psychosis, resulting in a sample of 163 patients and 119 non-clinical controls. To address our proposed disease progression model and evaluate potential heterogeneity, we applied a machine-learning algorithm, SuStaIn, to the patient data. SuStaIn uniquely integrates clustering and disease progression modeling and identified three patient subtypes. Subtype 0 showed normal-range performance on all variables. In comparison, Subtype 1 showed lower episodic memory, social cognition, functional outcome, and higher negative symptoms, while Subtype 2 showed lower hippocampal-cortical connectivity and episodic memory. Subtype 1 deteriorated from episodic memory to social cognition, negative symptoms, functional outcome to bilateral hippocampal-cortical dysconnectivity, while Subtype 2 deteriorated from bilateral hippocampal-cortical dysconnectivity to episodic memory and social cognition, functional outcome to negative symptoms. This first application of SuStaIn in a multiscale psychiatric model provides distinct disease trajectories of hippocampal-cortical connectivity, which might underlie the heterogeneous behavioral manifestations of psychosis.

Symptom Dimensions and Cognitive Impairments in Individuals at Clinical High Risk for Psychosis

BACKGROUND

Understanding the intricate relationships between symptom dimensions, clusters, and cognitive impairments is crucial for early detection and intervention in individuals at clinical high risk for psychosis. This study delves into this complex interplay in a clinical high risk sample with the aim of predicting the conversion to psychosis.

METHODS

A comprehensive cognitive assessment was performed in 744 clinical high risk individuals. The study included a 3-year follow-up period to allow assessment of conversion to psychosis. Symptom profiles were determined using the Structured Interview for Prodromal Syndromes. By applying factor analysis, symptom dimensions were categorized as dominant negative symptoms (NS), positive symptoms-stressful, and positive symptoms-odd. The factor scores were used to define 3 dominant symptom groups. Latent class analysis (LCA) and the factor mixture model (FMM) were employed to identify discrete clusters based on symptom patterns. The 3-class solution was chosen for the LCA and FMM analysis.

RESULTS

Individuals in the dominant NS group exhibited significantly higher conversion rates to psychosis than those in the other groups. Specific cognitive variables, including performance on the Brief Visuospatial Memory Test-Revised (odds ratio = 0.702, p = .001) and Neuropsychological Assessment Battery Mazes Test (odds ratio = 0.776, p = .024), significantly predicted conversion to psychosis. Notably, cognitive impairments associated with NS and positive symptoms-stressful groups affected different cognitive domains. LCA and FMM cluster 1, which was characterized by severe NS and positive symptoms-odd, exhibited more impairments in cognitive domains than other clusters. No significant difference in the conversion rate was observed among the LCA and FMM clusters.

CONCLUSIONS

These findings highlight the importance of NS in the development of psychosis and suggest specific cognitive domains that are affected by symptom dimensions.

Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks

Cognitive deficits are prevalent in individuals with psychosis and are associated with neurobiological changes, potentially serving as an endophenotype for psychosis. Using the HCP-Early-Psychosis-dataset (n = 226), we aimed to investigate cognitive subtypes (deficit/intermediate/spared) through data-driven clustering in affective (AP) and non-affective psychosis patients (NAP) and controls (HC). We explored differences between three clusters in symptoms, cognition, medication, and grey matter volume. Applying principal component analysis, we selected features for clustering. Features that explained most variance were scores for intelligence, verbal recognition and comprehension, auditory attention, working memory, reasoning and executive functioning. Fuzzy K-Means clustering on those features revealed that the subgroups significantly varied in cognitive impairment, clinical symptoms, and, importantly, also in medication and grey matter volume in fronto-parietal and subcortical networks. The spared cluster (86%HC, 37%AP, 17%NAP) exhibited unimpaired cognition, lowest symptoms/medication, and grey matter comparable to controls. The deficit cluster (4%HC, 10%AP, 47%NAP) had impairments across all domains, highest symptoms scores/medication dosage, and pronounced grey matter alterations. The intermediate deficit cluster (11%HC, 54%AP, 36%NAP) showed fewer deficits than the second cluster, but similar symptoms/medication/grey matter to the spared cluster. Controlling for medication, cognitive scores correlated with grey matter changes and negative symptoms across all patients. Our findings generally emphasize the interplay between cognition, brain structure, symptoms, and medication in AP and NAP, and specifically suggest a possible mediating role of cognition, highlighting the potential of screening cognitive changes to aid tailoring treatments and interventions.

Cognitive subtypes in youth at clinical high risk for psychosis

Introduction

Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories.

Methods

Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters.

Results

Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones.

Conclusion

Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.

Tablet-Based Cognitive and Eye Movement Measures as Accessible Tools for Schizophrenia Assessment: Multisite Usability Study

BACKGROUND

Schizophrenia is a complex mental disorder characterized by significant cognitive and neurobiological alterations. Impairments in cognitive function and eye movement have been known to be promising biomarkers for schizophrenia. However, cognitive assessment methods require specialized expertise. To date, data on simplified measurement tools for assessing both cognitive function and eye movement in patients with schizophrenia are lacking.

OBJECTIVE

This study aims to assess the efficacy of a novel tablet-based platform combining cognitive and eye movement measures for classifying schizophrenia.

METHODS

Forty-four patients with schizophrenia, 67 healthy controls, and 41 patients with other psychiatric diagnoses participated in this study from 10 sites across Japan. A free-viewing eye movement task and 2 cognitive assessment tools (Codebreaker task from the THINC-integrated tool and the CognitiveFunctionTest app) were used for conducting assessments in a 12.9-inch iPad Pro. We performed comparative group and logistic regression analyses for evaluating the diagnostic efficacy of the 3 measures of interest.

RESULTS

Cognitive and eye movement measures differed significantly between patients with schizophrenia and healthy controls (all 3 measures; P<.001). The Codebreaker task showed the highest classification effectiveness in distinguishing schizophrenia with an area under the receiver operating characteristic curve of 0.90. Combining cognitive and eye movement measures further improved accuracy with a maximum area under the receiver operating characteristic curve of 0.94. Cognitive measures were more effective in differentiating patients with schizophrenia from healthy controls, whereas eye movement measures better differentiated schizophrenia from other psychiatric conditions.

CONCLUSIONS

This multisite study demonstrates the feasibility and effectiveness of a tablet-based app for assessing cognitive functioning and eye movements in patients with schizophrenia. Our results suggest the potential of tablet-based assessments of cognitive function and eye movement as simple and accessible evaluation tools, which may be useful for future clinical implementation.

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.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.

Cognitive reserve, depressive symptoms, obesity, and change in employment status predict mental processing speed and executive function after COVID-19

The risk factors for post-COVID-19 cognitive impairment have been poorly described. This study aimed to identify the sociodemographic, clinical, and lifestyle characteristics that characterize a group of post-COVID-19 condition (PCC) participants with neuropsychological impairment. The study sample included 426 participants with PCC who underwent a neurobehavioral evaluation. We selected seven mental speed processing and executive function variables to obtain a data-driven partition. Clustering algorithms were applied, including K-means, bisecting K-means, and Gaussian mixture models. Different machine learning algorithms were then used to obtain a classifier able to separate the two clusters according to the demographic, clinical, emotional, and lifestyle variables, including logistic regression with least absolute shrinkage and selection operator (LASSO) (L1) and Ridge (L2) regularization, support vector machines (linear/quadratic/radial basis function kernels), and decision tree ensembles (random forest/gradient boosting trees). All clustering quality measures were in agreement in detecting only two clusters in the data based solely on cognitive performance. A model with four variables (cognitive reserve, depressive symptoms, obesity, and change in work situation) obtained with logistic regression with LASSO regularization was able to classify between good and poor cognitive performers with an accuracy and a weighted averaged precision of 72%, a recall of 73%, and an area under the curve of 0.72. PCC individuals with a lower cognitive reserve, more depressive symptoms, obesity, and a change in employment status were at greater risk for poor performance on tasks requiring mental processing speed and executive function. Study registration: www.ClinicalTrials.gov , identifier NCT05307575.

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.

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.

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.

Executive Functions and Psychopathology Dimensions in Deficit and Non-Deficit Schizophrenia

This study: (a) compared executive functions between deficit (DS) and non-deficit schizophrenia (NDS) patients and healthy controls (HC), controlling premorbid IQ and level of education; (b) compared executive functions in DS and NDS patients, controlling premorbid IQ and psychopathological symptoms; and (c) estimated relationships between clinical factors, psychopathological symptoms, and executive functions using structural equation modelling. Participants were 29 DS patients, 44 NDS patients, and 39 HC. Executive functions were measured with the Mazes Subtest, Spatial Span Subtest, Letter Number Span Test, Color Trail Test, and Berg Card Sorting Test. Psychopathological symptoms were evaluated with the Positive and Negative Syndrome Scale, Brief Negative Symptom Scale, and Self-evaluation of Negative Symptoms. Compared to HC, both clinical groups performed poorer on cognitive flexibility, DS patients on verbal working memory, and NDS patients on planning. DS and NDS patients did not differ in executive functions, except planning, after controlling premorbid IQ and negative psychopathological symptoms. In DS patients, exacerbation had an effect on verbal working memory and cognitive planning; in NDS patients, positive symptoms had an effect on cognitive flexibility. Both DS and NDS patients presented deficits, affecting the former to a greater extent. Nonetheless, clinical variables appeared to significantly affect these deficits.

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.

Clinical and developmental characteristics of cognitive subgroups in a transdiagnostic sample of schizophrenia spectrum disorders and bipolar disorder

Evidence suggests that neurocognitive dysfunction is a transdiagnostic feature of individuals across the continuum between schizophrenia and bipolar disorder. However, there is significant heterogeneity of neuropsychological and social-cognitive abilities in schizophrenia, schizoaffective disorder, and bipolar disorder. The current study aimed to investigate the clinical and developmental characteristics of cognitive subgroups within the schizo-bipolar spectrum. 147 clinically stable patients with schizophrenia, schizoaffective or bipolar disorder were assessed using clinical rating scales for current psychotic and affective symptoms, and a comprehensive neuropsychological battery including measures of social cognition (Hinting and Reading the mind from the Eyes (RMET) task)). Developmental history and premorbid academic functioning were also evaluated. The study also included 36 healthy controls. Neurocognitive subgroups were investigated using latent class analysis (LCA). The optimal number of clusters was determined based on the Bayesian information criterion. A logistic regression analysis was conducted to investigate the predictors of membership to the globally impaired subgroup. LCA revealed two neurocognitive clusters including globally impaired (n = 89, 60.5%) and near-normal cognitive functioning (n = 58, 39.5%) subgroups. The near-normal cognitive functioning subgroup was not significantly different from healthy controls. The globally impaired subgroup had a higher score of developmental abnormalities (p<0.001), poorer premorbid academic functioning, mothers who were less educated and more severe disorganized speech (p = 0.001) and negative symptoms (p = 0.004) compared to the near-normal cognitive functioning group. History of developmental abnormalities and persistent disorganization rather than diagnosis are significant predictors of the subgroup of individuals with global cognitive impairment in the schizophrenia-bipolar disorder continuum.

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.

Genetic and Structural Brain Correlates of Cognitive Subtypes Across Youth at Family Risk for Schizophrenia and Bipolar Disorder

OBJECTIVE

Cognitive impairment is an important feature of schizophrenia (SZ) and bipolar disorder (BP) with severity across the two disorders characterized by significant heterogeneity. Youth at family risk for SZ and BP were clustered based on cognitive function and examined in terms of the clinical, genetic, and brain imaging correlates of cluster membership.

METHOD

One hundred sixty participants, 32 offspring of patients with SZ, 59 offspring of patients with BP and 69 offspring of healthy control parents underwent clinical and cognitive assessments, genotyping and structural MRI. K-means clustering was used to group family risk participants based on cognitive measures. Clusters were compared in terms of cortical and subcortical brain measures as well as polygenic risk scores.

RESULTS

Participants were grouped in 3 clusters with intact, intermediate, and impaired cognitive performance. The intermediate and impaired clusters had lower total brain surface area compared with the intact cluster, with prominent localization in frontal and temporal cortices. No between-cluster differences were identified in cortical thickness and subcortical brain volumes. The impaired cluster also had poorer psychosocial functioning and worse PRS-COG compared with the other 2 clusters and with offspring of healthy control parents, while there was no significant between-cluster difference in terms of PRS-SZ and PRS-BP. PRS-COG predicted psychosocial functioning, yet this effect did not appear to be mediated by an effect of PRS-COG on brain area.

CONCLUSION

Stratification based on cognition may help to elucidate the biological underpinnings of cognitive heterogeneity across SZ and BP risk.

The role of glutamate and GABA in cognitive dysfunction in schizophrenia and mood disorders - A systematic review of magnetic resonance spectroscopy studies

Epidemiologic, genetic, and neurobiological studies suggest considerable overlap between schizophrenia and mood disorders. Importantly, both disorders are associated with a broad range of cognitive deficits as well as altered glutamatergic and GABAergic neurometabolism. We conducted a systematic review of magnetic resonance spectroscopy (MRS) studies investigating the relationship between glutamatergic and GABAergic neurometabolites and cognition in schizophrenia spectrum disorders and mood disorders. A literature search in Pubmed of studies published before April 15, 2019 was conducted and 37 studies were deemed eligible for systematic review. We found that alterations in glutamatergic and GABAergic neurotransmission have been identified relatively consistently in both schizophrenia and mood disorders. However, because of the vast heterogeneity of published studies in terms of illness stage, medication exposure, MRS acquisition parameters and data post-processing strategies, we still do not understand the relationship between those neurotransmitters and cognitive dysfunction in mental illness, which is a critical initial step for rational drug development. Our findings emphasize the need for coordinated multi-center studies that characterize cognitive function and its biological substrates in large and well-defined clinical populations, using harmonized imaging sequences and analytical methods with the goal to elucidate the underlying pathophysiological mechanisms and to inform future clinical trials.

Facial processing in bipolar disorder is mediated by clinical and biological aspects

OBJECTIVE

The process of detecting faces can be considered one of the initial steps in face recognition, which is essential for human interaction. We sought to investigate whether a face perception task reliably detects subtle perceptual disturbances between patients with bipolar disorder (BD) and healthy controls.

METHODS

In this multisite study, we examined differences between BD patients and matched healthy controls. Participants were instructed to detect the orientation (either left or right) of a face when it was presented as a face/non-face pair on a computer screen using Bayesian entropy estimation. Data analyses compared performance between the groups.

RESULTS

Overall, BD patients exhibited more perceptual disturbances compared with controls. BD patients who took olanzapine had better performance and faster reaction times (RTs) than patients who took lithium or were medication-naive. BD patients who took lithium had better performance and faster RTs than medication-naive patients. The medication-naive BD group exhibited greater disturbances than all other groups.

CONCLUSION

These findings highlight the reliability of the face perception task used herein and may be important for public health initiatives and follow-up studies that seek to understand the diverse effects of other variables that can affect sensory processing in this population.

Examining the association of life course neurocognitive ability with real-world functioning in schizophrenia-spectrum disorders

There is considerable variability in neurocognitive functioning within schizophrenia-spectrum disorders, and neurocognitive performance ranges from severe global impairment to normative performance. Few investigations of neurocognitive clusters have considered the degree to which deterioration relative to premorbid neurocognitive abilities is related to key illness characteristics. Moreover, while neurocognition and community functioning are strongly related, understanding of the sources of variability in the association between these two domains is also limited; it is unknown what proportion of participants would over-perform or under-perform the level of functioning expected based on current neurocognitive performance vs. lifelong attainment. This study examined data from 954 outpatients with schizophrenia-spectrum disorders across three previous studies. Neurocognition, community functioning, and symptoms were assessed. Neurocognitive subgroups were created based on current neurocognition, estimated premorbid IQ, and degree of deterioration from premorbid using z-score cut-offs; functional subgroups were created with cluster analysis based on the Specific Level of Functioning Scale and current neurocognition. The sample was neurocognitively heterogeneous; 65% displayed current neurocognitive impairment and 84% experienced some level of deterioration. Thirty percent of our sample was relatively higher functioning despite significant neurocognitive impairment. Individuals with better community functioning, regardless of neurocognitive performance, had lower symptom severity compared to those with worse functioning. These results highlight the variability in neurocognition and its role in functioning. Understanding individual differences in neurocognitive and functional profiles and the interaction between prior and current cognitive functioning can guide individualized treatment and selection of participants for clinical treatment studies.

Face specific inversion effects provide evidence for two subtypes of developmental prosopagnosia

Many studies have attempted to identify the perceptual underpinnings of developmental prosopagnosia (DP). The majority have focused on whether holistic and configural processing mechanisms are impaired in DP. However, previous work suggests that there is substantial heterogeneity in holistic and configural processing within the DP population; further, there is disagreement as to whether any deficits are face-specific or reflect a broader perceptual deficit. This study used a data-driven approach to examine whether there are systematic patterns of variability in DP that reflect different underpinning perceptual deficits. A group of individuals with DP (N = 37) completed a cognitive battery measuring holistic/configural and featural processing in faces and non-face objects. A two-stage cluster analysis on data from the Cambridge Face Perception Test identified two subgroups of DPs. Across several tasks, the first subgroup (N = 21) showed typical patterns of holistic/configural processing (measured via inversion effects); the second (N = 16) was characterised by reduced or abolished inversion effects compared to age-matched control participants (N = 91). The subgroups did not differ on tasks measuring upright face matching, object matching, non-face holistic processing, or composite effects. These findings indicate two separable pathways to face recognition impairment, one characterised by impaired configural processing and the other potentially by impaired featural processing. Comparisons to control participants provide some preliminary evidence that the deficit in featural processing may extend to some non-face stimuli. Our results demonstrate the utility of examining both the variability between and consistency across individuals with DP as a means of illuminating our understanding of face recognition in typical and atypical populations.

Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia

Background

Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms.

Methods

Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T1-weighted structural neuroimaging data from 84 patients (aged 16-35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16-37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters.

Results

HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE.

Discussion

Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted.

Transdiagnostic comparisons of intellectual abilities and work outcome in patients with mental disorders: multicentre study

BACKGROUND

Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes.

AIMS

The present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner.

METHOD

Seven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ.

RESULTS

Four clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters.

CONCLUSIONS

Intellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.

Lifespan evolution of neurocognitive impairment in schizophrenia - A narrative review

Cognitive impairment is a well-recognized key feature of schizophrenia. Here we review the evidence on (1) the onset and sensitive periods of change in cognitive impairment before and after the first psychotic episode, and (2) heterogeneity in neurocognitive presentations across cognitive domains between and within individuals. Overall, studies suggest that mild cognitive impairment in individuals who develop schizophrenia or related disorders is already present during early childhood. Cross-sectional studies further suggest increasing cognitive impairments from pre- to post-psychosis onset, with the greatest declines between adolescence, the prodrome, and the first psychotic episode and with some variability between domains. Longitudinal studies with more than 10 years of observation time are scarce but support mild cognitive declines after psychosis onset until late adulthood. Whether and how much this cognitive decline exceeds normal aging, proceeds further in older patients, and is specific to certain cognitive domains and subpopulations of patients remains to be investigated. Finally, studies show substantial heterogeneity in cognitive performance in schizophrenia and suggest a variety of impairment profiles.

This review highlights a clear need for long-term studies that include a control group and individuals from adolescence to old age to better understand critical windows of cognitive change and their predictors. The available evidence stresses the importance of interventions that aim to counter cognitive decline during the prodromal years, as well as careful assessment of cognition in order to determine who will profit most from which cognitive training.

Clustering of cognitive subtypes in schizophrenia patients and their siblings: relationship with regional brain volumes

Schizophrenia patients (SZH) often show impaired cognition and reduced brain structural volumes; these deficits are also detectable in healthy relatives of SZH. However, there is considerable heterogeneity: a sizable percentage of SZH are relatively cognitively intact; clustering strategies have proved useful for categorising into cognitive subgroups. We used a clustering strategy to investigate relationships between subgroup assignment and brain volumes, in 102 SZH (N = 102) and 32 siblings of SZH (SZH-SIB), alongside 92 controls (CON) and 48 of their siblings. SZH had poorer performance in all cognitive domains, and smaller brain volumes within prefrontal and temporal regions compared to controls. We identified three distinct cognitive clusters (‘neuropsychologically normal’, ‘intermediate’, ‘cognitively impaired’) based on age- and gender-adjusted cognitive domain scores. The majority of SZH (60.8%) were assigned to the cognitively impaired cluster, while the majority of SZH-SIB (65.6%) were placed in the intermediate cluster. Greater right middle temporal volume distinguished the normal cluster from the more impaired clusters. Importantly, the observed brain volume differences between SZH and controls disappeared after adjustment for cluster assignment. This suggests an intimate link between cognitive performance levels and regional brain volume differences in SZH. This highlights the importance of accounting for heterogeneity in cognitive performance within SZH populations when attempting to characterise the brain structural abnormalities associated with the disease.

Serum levels of olanzapine are associated with acute cognitive effects in bipolar disorder

Bipolar (BPD) patients have deficits in cognition, but there are still controversies about the effects of some medications on their cognitive performance. Here, we investigated the relationship between cognition in terms of executive functions, memory, and attention in both first-episode medication-naive BPD patients and BPD patients taking olanzapine. Forty-one healthy controls, 40 unmedicated drug-naive BPD patients, and 34 BPD patients who took only olanzapine were recruited for the study. Cognitive performance was assessed using the Flanker test, Stroop test, and Corsi-block test. Bayesian multivariate regression analysis was run considering maximum robustness to avoid bias and to predict the outcomes. Our results revealed that unmedicated medication-naive BPD patients performed worse than healthy controls and the olanzapine group in some tasks. Additionally, BPD patients who took olanzapine had better cognitive performance than healthy controls and unmedicated BPD patients. The acute cognitive effects were predicted by olanzapine dosage and serum levels (i.e., large effects). The potential pro-cognitive effects of olanzapine in BPD patients should be carefully interpreted by considering various other clinical variables. We expect that our findings will contribute to further research in this area, with the goal of helping other researchers, patients, and the population.

Characterising cognitive heterogeneity in individuals at clinical high-risk for psychosis: a cluster analysis with clinical and functional outcome prediction

Schizophrenia is characterised by cognitive impairments that are already present during early stages, including in the clinical high-risk for psychosis (CHR-P) state and first-episode psychosis (FEP). Moreover, data suggest the presence of distinct cognitive subtypes during early-stage psychosis, with evidence for spared vs. impaired cognitive profiles that may be differentially associated with symptomatic and functional outcomes. Using cluster analysis, we sought to determine whether cognitive subgroups were associated with clinical and functional outcomes in CHR-P individuals. Data were available for 146 CHR-P participants of whom 122 completed a 6- and/or 12-month follow-up; 15 FEP participants; 47 participants not fulfilling CHR-P criteria (CHR-Ns); and 53 healthy controls (HCs). We performed hierarchical cluster analysis on principal components derived from neurocognitive and social cognitive measures. Within the CHR-P group, clusters were compared on clinical and functional variables and examined for associations with global functioning, persistent attenuated psychotic symptoms and transition to psychosis. Two discrete cognitive subgroups emerged across all participants: 45.9% of CHR-P individuals were cognitively impaired compared to 93.3% of FEP, 29.8% of CHR-N and 30.2% of HC participants. Cognitively impaired CHR-P participants also had significantly poorer functioning at baseline and follow-up than their cognitively spared counterparts. Specifically, cluster membership predicted functional but not clinical outcome. Our findings support the existence of distinct cognitive subgroups in CHR-P individuals that are associated with functional outcomes, with implications for early intervention and the understanding of underlying developmental processes.

Neurocognitive heterogeneity in 7-year-old children at familial high risk of schizophrenia or bipolar disorder: The Danish high risk and resilience study - VIA 7

BACKGROUND

Studies of neurocognitive heterogeneity in young children at familial high-risk of bipolar disorder (FHR-BP) or schizophrenia (FHR-SZ) are important to investigate inter-individual neurocognitive differences. We aimed to identify neurocognitive subgroups, describe prevalence of FHR-BP or FHR-SZ children herein, and examine risk ratios (RR) compared with controls.

METHODS

In a population-based cohort of 514 7-year-old children (197 FHR-SZ, 118 FHR-BP, and 199 matched controls) we used hierarchical cluster analyses to identify subgroups across 14 neurocognitive indices.

RESULTS

Three neurocognitive subgroups were derived: A Mildly Impaired (30%), Typical (51%), and Above Average subgroup (19%). The Mildly Impaired subgroup significantly underperformed controls (Cohen d = 0.11-1.45; Ps < 0.001) except in set-shifting (P = .84). FHR-SZ children were significantly more prevalent in the Mildly Impaired subgroup; FHR-BP children were more so in the Above Average subgroup (X² (2, N = 315) = 9.64, P < .01). 79.7% FHR-BP and 64.6% FHR-SZ children demonstrated typical or above average neurocognitive functions. Neurocognitive heterogeneity related significantly to concurrent functioning, psychopathology severity, home environment adequacy, and polygenic scores for schizophrenia (Ps <. 01). Compared with controls, FHR-SZ and FHR-BP children had a 93% (RR, 1.93; 95% CI, 1.40-2.64) and 8% (RR, 1.08; 95% CI, 0.71-1.66) increased risk of Mildly Impaired subgroup membership.

LIMITATIONS

Limitations include the cross-sectional design and smaller FHR-BP sample size.

CONCLUSIONS

Identification of neurocognitive heterogeneity in preadolescent children at FHR-BP or FHR-SZ may ease stigma and enable pre-emptive interventions to enhance neurocognitive functioning and resilience to mental illness in the impaired sub-population.

The neurobiological characterization of distinct cognitive subtypes in early-phase schizophrenia-spectrum disorders

INTRODUCTION

Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures.

METHODS

Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA.

RESULTS

Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume.

DISCUSSION

Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.

Identifying social cognition subgroups in euthymic patients with bipolar disorder: a cluster analytical approach

BACKGROUND

Bipolar disorder (BD) is associated with social cognition (SC) impairments even during remission periods although a large heterogeneity has been described. Our aim was to explore the existence of different profiles on SC in euthymic patients with BD, and further explore the potential impact of distinct variables on SC.

METHODS

Hierarchical cluster analysis was conducted using three SC domains [Theory of Mind (ToM), Emotional Intelligence (EI) and Attributional Bias (AB)]. The sample comprised of 131 individuals, 71 patients with BD and 60 healthy control subjects who were compared in terms of SC performance, demographic, clinical, and neurocognitive variables. A logistic regression model was used to estimate the effect of SC-associated risk factors.

RESULTS

A two-cluster solution was identified with an adjusted-performance group (N = 48, 67.6%) and a low-performance group (N = 23, 32.4%) with mild deficits in ToM and AB domains and with moderate difficulties in EI. Patients with low SC performance were mostly males, showed lower estimated IQ, higher subthreshold depressive symptoms, longer illness duration, and poorer visual memory and attention. Low estimated IQ (OR 0.920, 95% CI 0.863-0.981), male gender (OR 5.661, 95% CI 1.473-21.762), and longer illness duration (OR 1.085, 95% CI 1.006-1.171) contributed the most to the patients clustering. The model explained up to 35% of the variance in SC performance.

CONCLUSIONS

Our results confirmed the existence of two discrete profiles of SC among BD. Nearly two-thirds of patients exhibited adjusted social cognitive abilities. Longer illness duration, male gender, and lower estimated IQ were associated with low SC performance.

Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders

Grey matter volume (GMV) may be associated with polygenic risk for schizophrenia (PRS-SZ) and severe cognitive deficits in people with schizophrenia, schizoaffective disorder (collectively SSD), and bipolar disorder (BD). This study examined the interactive effects of PRS-SZ and cognitive subtypes of SSD and BD in relation to GMV. Two-step cluster analysis was performed on 146 clinical cases (69 SSD and 77 BD) assessed on eight cognitive domains (verbal and visual memory, executive function, processing speed, visual processing, language ability, working memory, and planning). Among them, 55 BD, 51 SSD, and 58 healthy controls (HC), contributed to focal analyses of the relationships between cognitive subtypes, PRS-SZ and their interaction on GMV. Two distinct cognitive subtypes were evident among the combined sample of cases: a 'cognitive deficit' group (CD; N = 31, 20SSD/11BD) showed severe impairment across all cognitive indices, and a 'cognitively spared' (CS; N = 75; 31SSD/44BD) group showed intermediate cognitive performance that was significantly worse than the HC group but better than the CD subgroup. A cognitive subgroup-by-PRS-SZ interaction was significantly associated with GMV in the left precentral gyrus. Moderation analyses revealed a significant negative relationship between PRS-SZ and GMV in the CD group only. At low and average (but not high) PRS-SZ, larger precentral GMV was evident in the CD group compared to both CS and HC groups, and in the CS group compared to HCs. This study provides evidence for a relationship between regional GMV changes and PRS-SZ in psychosis spectrum cases with cognitive deficits, but not in cases cognitively spared.

Profiling the Interrogee: Applying the Person-Centered Approach in Investigative Interviewing Research

In the past, deception detection research has explored whether there were specific personal characteristics that were related to lying and found that factors such as personality and morality are indeed related to lying. However, past research has usually focused on a variable-centered approach. Yet, a person-centered might be more suitable here as it allows for the study of people in an integrative manner. In this experiment, 673 students completed a questionnaire which included measures of the five factors of personality, the level of moral disengagement, the perceived cognitive load when lying, lying strategies, frequency of lying and the LiES scale, a tool measuring the tendency to tell self-serving, altruistic and vindicative lies. We performed a Latent Profile Analysis to integrate personality, moral disengagement, and perceived cognitive load scores into specific profiles. Then, we related profile membership to lying behavior. We obtained four profiles, and found that extraversion, moral disengagement, and the perceived cognitive load contributed most to profile differences. We also found that lying frequency did not differ across profiles, whereas lying tendency did. In conclusion, our results suggest that several facets of the individual play a joint role in lying behavior, and that adopting a person-centered approach might be a good strategy to explore the role of interpersonal differences in lie detection research.

Cognitive clusters in first-episode psychosis

Impairments in a broad range of cognitive domains have been consistently reported in some individuals with first-episode psychosis (FEP). Cognitive deficits can be observed during the prodromal stage. However, the course of cognitive deficits is still unclear. The aim of this study was to identify cognitive subgroups over time and to compare their sociodemographic, clinical and functional profiles. A total of 114 patients with Schizophrenia Spectrum Disorders were included in the present study. We assessed subjects through psychiatric scales and eight neuropsychological tests at baseline and at two-year follow-up visit. We performed the Partition Around Medoids algorithm with all cognitive variables. Furthermore, we performed a logistic regression to identify the predictors related to the different cognitive clusters at follow-up. Two distinct subgroups were found: the first cluster characterized by cognitive impairment and a second cluster had relatively intact cognition in comparison with norms. Up to 54.7% of patients with cognitive deficits at baseline tended to improve during the first two years of treatment. Patients with intact cognition at follow-up had a higher socioeconomic status, later age of onset, lower negative symptoms and a higher cognitive reserve (CR) at baseline. CR and age of onset were the baseline variables that predicted cognitive impairment. This research allows us to obtain a better understanding of the heterogeneous profile of psychotic disorders. Identifying the characteristics of patients who will present a cognitive impairment could improve early detection and intervention. These results suggest that enhancing CR could contribute to improving the course of the illness.

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.

Heterogeneity and Factorial Structure in Alzheimer's Disease: A Cognitive Perspective

BACKGROUND

Alzheimer's disease (AD) patients show heterogeneous cognitive profiles which suggest the existence of cognitive subgroups. A deeper comprehension of this heterogeneity could contribute to move toward a precision medicine perspective.

OBJECTIVE

In this study, we aimed 1) to investigate AD cognitive heterogeneity as a product of the combination of within- (factors) and between-patients (sub-phenotypes) components, and 2) to promote its assessment in clinical practice by defining a small set of critical tests for this purpose.

METHODS

We performed factor mixture analysis (FMA) on neurocognitive assessment results of N = 230 patients with a clinical diagnosis of AD. This technique allowed to investigate the structure of cognitive heterogeneity in this sample and to characterize the core features of cognitive sub-phenotypes. Subsequently, we performed a tests selection based on logistic regression to highlight the best tests to detect AD patients in our sample. Finally, the accuracy of the same tests in the discrimination of sub-phenotypes was evaluated.

RESULTS

FMA revealed a structure characterized by five latent factors and four groups, which were identifiable by means of a few cognitive tests and were mainly characterized by memory deficits with visuospatial difficulties ("Visuospatial AD"), typical AD cognitive pattern ("Typical AD"), less impaired memory ("Mild AD"), and language/praxis deficits with relatively spared memory ("Nonamnestic AD").

CONCLUSION

The structure of cognitive heterogeneity in our sample of AD patients, as studied by FMA, could be summarized by four sub-phenotypes with distinct cognitive characteristics easily identifiable in clinical practice. Clinical implications under the precision medicine framework are discussed.

Cognitive subtypes in recent onset psychosis: distinct neurobiological fingerprints?

In schizophrenia, neurocognitive subtypes can be distinguished based on cognitive performance and they are associated with neuroanatomical alterations. We investigated the existence of cognitive subtypes in shortly medicated recent onset psychosis patients, their underlying gray matter volume patterns and clinical characteristics. We used a K-means algorithm to cluster 108 psychosis patients from the multi-site EU PRONIA (Prognostic tools for early psychosis management) study based on cognitive performance and validated the solution independently (N = 53). Cognitive subgroups and healthy controls (HC; n = 195) were classified based on gray matter volume (GMV) using Support Vector Machine classification. A cognitively spared (N = 67) and impaired (N = 41) subgroup were revealed and partially independently validated (N_spared = 40, N_impaired = 13). Impaired patients showed significantly increased negative symptomatology (p_fdr = 0.003), reduced cognitive performance (p_fdr < 0.001) and general functioning (p_fdr < 0.035) in comparison to spared patients. Neurocognitive deficits of the impaired subgroup persist in both discovery and validation sample across several domains, including verbal memory and processing speed. A GMV pattern (balanced accuracy = 60.1%, p = 0.01) separating impaired patients from HC revealed increases and decreases across several fronto-temporal-parietal brain areas, including basal ganglia and cerebellum. Cognitive and functional disturbances alongside brain morphological changes in the impaired subgroup are consistent with a neurodevelopmental origin of psychosis. Our findings emphasize the relevance of tailored intervention early in the course of psychosis for patients suffering from the likely stronger neurodevelopmental character of the disease.

Altered Parvalbumin Basket Cell Terminals in the Cortical Visuospatial Working Memory Network in Schizophrenia

BACKGROUND

Visuospatial working memory (vsWM), which is commonly impaired in schizophrenia, involves information processing across the primary visual cortex, association visual cortex, posterior parietal cortex, and dorsolateral prefrontal cortex (DLPFC). Within these regions, vsWM requires inhibition from parvalbumin-expressing basket cells (PVBCs). Here, we analyzed indices of PVBC axon terminals across regions of the vsWM network in schizophrenia.

METHODS

For 20 matched pairs of subjects with schizophrenia and unaffected comparison subjects, tissue sections from the primary visual cortex, association visual cortex, posterior parietal cortex, and DLPFC were immunolabeled for PV, the 65- and 67-kDa isoforms of glutamic acid decarboxylase (GAD65 and GAD67) that synthesize GABA (gamma-aminobutyric acid), and the vesicular GABA transporter. The density of PVBC terminals and of protein levels per terminal was quantified in layer 3 of each cortical region using fluorescence confocal microscopy.

RESULTS

In comparison subjects, all measures, except for GAD65 levels, exhibited a caudal-to-rostral decline across the vsWM network. In subjects with schizophrenia, the density of detectable PVBC terminals was significantly lower in all regions except the DLPFC, whereas PVBC terminal levels of PV, GAD67, and GAD65 proteins were lower in all regions. A composite measure of inhibitory strength was lower in subjects with schizophrenia, although the magnitude of the diagnosis effect was greater in the primary visual, association visual, and posterior parietal cortices than in the DLPFC.

CONCLUSIONS

In schizophrenia, alterations in PVBC terminals across the vsWM network suggest the presence of a shared substrate for cortical dysfunction during vsWM tasks. However, regional differences in the magnitude of the disease effect on an index of PVBC inhibitory strength suggest region-specific alterations in information processing during vsWM tasks.

Long-term trajectory of cognitive performance in people with bipolar disorder and controls: 6-year longitudinal study

BACKGROUND

Cross-sectional studies have found impaired cognitive functioning in patients with bipolar disorder, but long-term longitudinal studies are scarce.

AIMS

The aims of this study were to examine the 6-year longitudinal course of cognitive functioning in patients with bipolar disorder and healthy controls. Subsets of patients were examined to investigate possible differences in cognitive trajectories.

METHOD

Patients with bipolar I disorder (n = 44) or bipolar II disorder (n = 28) and healthy controls (n = 59) were tested with a comprehensive cognitive test battery at baseline and retested after 6 years. We conducted repeated measures ANCOVAs with group as a between-subject factor and tested the significance of group and time interaction.

RESULTS

By and large, the change in cognitive functioning between baseline and follow-up did not differ significantly between participants with bipolar disorder and healthy controls. Comparing subsets of patients, for example those with bipolar I and II disorder and those with and without manic episodes during follow-up, did not reveal subgroups more vulnerable to cognitive decline.

CONCLUSIONS

Cognitive performance remained stable in patients with bipolar disorder over a 6-year period and evolved similarly to healthy controls. These findings argue against the notion of a general progressive decline in cognitive functioning in bipolar disorder.

Disentangling Cognitive Heterogeneity in Psychotic Spectrum Disorders

Neuropsychological impairments represent a central feature of psychosis-spectrum disorders. It is characterized by a great both within- and between-subjects variability (i.e. cognitive heterogeneity), which needs to be better disentangled. The present study aimed to describe the distribution of performance on the Brief Assessment of Cognition in Schizophrenia (BACS) by using the Equivalent Scores, in order to balance statistical methodological problems. To do so, cognitive performance groups were branded, identifying the main factors contributing to cognitive heterogeneity. A sample of 583 patients with a diagnosis of Schizophrenia or Psychotic Disorder Not Otherwise Specified was enrolled and assessed for neurocognition and intellectual level. K-means cluster analysis was performed based on BACS Equivalent Scores. Differences among clusters were analyzed throughout Analysis of Variance and Discriminant Function Analysis in order to identify the most significant predictors of cluster membership. For each cognitive task, roughly 40% of patients displayed poor performance, while up to 63% displayed a symbol-coding deficit. K-means cluster analysis depicted three profiles characterized by "near-normal" cognition, widespread impairment, and "borderline" profile. Discriminant analysis selected Verbal IQ and diagnosis as predictors of cluster membership. Our findings support the usefulness of Equivalent Scores and cluster analysis to explain cognitive heterogeneity, and tailor better interventions.

Cognitive profiles of healthy siblings of first-episode schizophrenia patients

AIM

Cognitive deficit in psychotic illness is intensively studied, different cognitive subtypes have been suggested. In recent years, there has been an increase in the number of studies in patients with schizophrenia and their relatives searching for endophenotypes of the disease. The aim of our study was to investigate cognitive performance and cognitive subtypes in the siblings of the patients.

METHODS

Four groups of subjects were included: patients with a first episode of psychotic illness, the siblings of these patients, and two control groups. All the study subjects (N = 84) had a battery of neuropsychological tests that measured basic cognitive domains - memory, executive functions, attention, visual-spatial skills, language skills and psychomotor speed - administered to them. The data were assessed with pairwise t-tests for group comparisons. The siblings were distributed into three groups according to their cognitive performance: non-deficit, partial deficit, and global deficit. Subsequently, the patients were assigned into three groups corresponding to their siblings' performance.

RESULTS

Our results revealed attenuation of abstract thinking in the siblings compared to the controls. As expected, the patients showed impairment across all cognitive domains. The patients and siblings demonstrated similar profiles in each subtype, in the severity of their impairment, and in their patterns of cognitive performance.

CONCLUSIONS

Our results suggest that the cognitive profile can be considered as an endophenotype of psychotic disorders.

Decreased integration of the frontoparietal network during a working memory task in major depressive disorder

BACKGROUND

Working memory deficits are a common feature in major depressive disorder and are associated with poor functional outcomes. Intact working memory performance requires the recruitment of large-scale brain networks. However, it is unknown how the disrupted recruitment of distributed regions belonging to these large-scale networks at the whole-brain level brings about working memory impairment seen in major depressive disorder.

METHODS

We used graph theory to examine the functional connectomic metrics (local and global efficiency) at the whole-brain and large-scale network levels in 38 patients with major depressive disorder and 41 healthy controls during a working memory task. Altered connectomic metrics were studied in a moderation model relating to clinical symptoms and working memory accuracy in patients, and a machine learning method was employed to assess whether these metrics carry enough illness-specific information to discriminate patients from controls.

RESULTS

Global efficiency of the frontoparietal network was reduced in major depressive disorder (false discovery rate corrected, p = 0.014); this reduction predicted worse working memory performance in patients with less severe illness burden indexed by Brief Psychiatric Rating Scale (β =-0.43, p = 0.035, t =-2.2, 95% confidence interval = [-0.043,-0.002]). We achieved a classification accuracy and area under the curve of 73.42% and 0.734, respectively, to discriminate patients from controls based on connectomic metrics, and the global efficiency of the frontoparietal network contributed most to the diagnostic classification.

CONCLUSIONS

We report a putative mechanistic link between the global efficiency of the frontoparietal network and impaired n-back performance in major depressive disorder. This relationship is more pronounced at lower levels of symptom burden, indicating the possibility of multiple pathways to cognitive deficits in severe major depressive disorder.

Cognitive Subtyping in Schizophrenia: A Latent Profile Analysis

Cognitive dysfunction is a core feature of schizophrenia. The subtyping of cognitive performance in schizophrenia may aid the refinement of disease heterogeneity. The literature on cognitive subtyping in schizophrenia, however, is limited by variable methodologies and neuropsychological tasks, lack of validation, and paucity of studies examining longitudinal stability of profiles. It is also unclear if cognitive profiles represent a single linear severity continuum or unique cognitive subtypes. Cognitive performance measured with the Brief Assessment of Cognition in Schizophrenia was analyzed in schizophrenia patients (n = 767). Healthy controls (n = 1012) were included as reference group. Latent profile analysis was performed in a schizophrenia discovery cohort (n = 659) and replicated in an independent cohort (n = 108). Longitudinal stability of cognitive profiles was evaluated with latent transition analysis in a 10-week follow-up cohort. Confirmatory factor analysis (CFA) was carried out to investigate if cognitive profiles represent a unidimensional structure. A 4-profile solution was obtained from the discovery cohort and replicated in an independent cohort. It comprised of a "less-impaired" cognitive subtype, 2 subtypes with "intermediate cognitive impairment" differentiated by executive function performance, and a "globally impaired" cognitive subtype. This solution showed relative stability across time. CFA revealed that cognitive profiles are better explained by distinct meaningful profiles than a severity linear continuum. Associations between profiles and negative symptoms were observed. The subtyping of schizophrenia patients based on cognitive performance and its associations with symptomatology may aid phenotype refinement, mapping of specific biological mechanisms, and tailored clinical treatments.