Cognitive Function In Schizophrenia Research Articles

Association between treatment resistance and cognitive function in schizophrenia.

Treatment-resistant schizophrenia (TRS) affects around 30% of individuals with schizophrenia. About half of the patients with TRS who are treated with clozapine do not show a meaningful clinical response, that is, clozapine resistance. To date, the relationship between cognitive function and treatment response categories is not entirely clear. This study evaluated the cognitive performance across subgroups stratified by treatment response, and we hypothesised that cognitive impairment increases with increased treatment resistance. This study was conducted at the Institute of Mental Health, Singapore, and included healthy controls and people with schizophrenia categorised into these groups: antipsychotic-responsive schizophrenia (ARS), clozapine-responsive TRS (TRS-CR) and clozapine-resistant TRS (ultra-treatment-resistant schizophrenia [UTRS]). Cognitive function was assessed using the Brief Assessment of Cognition-Short Form. Symptoms were measured with the Positive and Negative Syndrome Scale (PANSS). The planned statistical analyses included adjustments for covariates such as age, sex, PANSS scores and antipsychotic dose, which might affect cognitive function. There were significant differences in overall cognitive performance between the groups: ARS had the least impairment, followed by TRS-CR and UTRS. Antipsychotic dose, and PANSS negative and disorganisation/cognitive factors were significant predictors of overall cognitive function in all patient groups. Our study found differences in cognitive function that aligned with levels of treatment resistance: the greater the degree of treatment resistance, the poorer the cognitive function. Interventions to improve negative and disorganisation symptoms might be effective to enhance the cognitive function and treatment outcomes in schizophrenia.

NRN1 genetic variability and methylation changes as biomarkers for cognitive remediation therapy response in schizophrenia

Cognitive remediation therapy (CRT) demonstrates potential in enhancing cognitive function in schizophrenia (SZ), though the identification of molecular biomarkers remains challenging. The Neuritin-1 gene (NRN1) emerges as a promising candidate gene due to its association with SZ, cognitive performance and response to neurotherapeutic treatments. We aimed to investigate whether NRN1 genetic variability and methylation changes following CRT are related to cognitive improvements.Twenty-five SZ patients were randomly assigned to CRT or treatment-as-usual (TAU) groups, with cognitive function and NRN1 methylation assessed pre- and post-intervention using the MATRICS Consensus Cognitive Battery and EpiTYPER. Besides, eleven NRN1 polymorphisms were genotyped. Methylation changes (Δm = post - pre) were analyzed via sparse Partial Least Square Discriminant Analysis (sPLS-DA) to identify latent components (LCs) distinguishing CRT from TAU. To further explore methylation patterns of these LCs, CpG units were grouped into two subsets, yielding Δm means for those with increased and decreased methylation. Cognitive changes (Δcog = post - pre) were used to identify CRT improvers (CRTI, Δcog ≥1), and the association between methylation changes and cognitive improvements post-therapy was also tested.We identified two LCs that differentiated CRT from TAU with a classification error rate of 0.28. The main component, LC1, included 25 CpG units. The subsets of CpG units with increased and decreased post-therapy methylation differed significantly between the two treatment arms, suggesting that differences were not merely data-driven but reflected meaningful biological variation. Additionally, CpG units linked to therapy were also associated with cognitive improvement, with LC1 and the subset of CpG units showing increased methylation post-therapy distinguishing CRT-I from the rest of the patients across multiple cognitive domains. Furthermore, the effect of LC1 on speed processing improvement after CRT was enhanced by considering the NRN1-rs9405890 polymorphism. Notably, these CpG units, particularly those with increased methylation after CRT, overlapped with key gene regulatory elements.Our model, integrating genetics and epigenetics, boosts the understanding of CRT response variability and highlights this multi-level approach as a promising strategy for identifying potential NRN1-related biomarkers of CRT effects, though further studies with larger samples are needed.

Peak width of skeletonized mean diffusivity as a neuroimaging biomarker in first-episode schizophrenia.

Peak width of skeletonized mean diffusivity (PSMD), a fully automated diffusion tensor imaging (DTI) biomarker of white matter (WM) microstructure damage, has been shown to be associated with cognition in various WM pathologies. However, its application in schizophrenic disease remains unexplored. This study aims to investigate PSMD along with other DTI markers in first-episode schizophrenia patients compared to healthy controls (HCs), and explore the correlations between these metrics and clinical characteristics. A total of 56 first-episode drug-naive schizophrenia patients and 64 HCs were recruited for this study. Participants underwent structural imaging and DTI, followed by comprehensive clinical assessments, including the Positive and Negative Syndrome Scale (PANSS) for patients and cognitive function tests for all participants. We calculated PSMD, peak width of skeletonized fractional anisotropy (PSFA), axial diffusivity (PSAD), radial diffusivity (PSRD) values, skeletonized average mean diffusivity (MD), average fractional anisotropy (FA), average axial diffusivity (AD), and average radial diffusivity (RD) values as well as structural network global topological parameters, and examined between-group differences in these WM metrics. Furthermore, we investigated associations between abnormal metrics and clinical characteristics. Compared to HCs, patients exhibited significantly increased PSMD values (t = 2.467, p = 0.015), decreased global efficiency (Z = -2.188, p = 0.029), and increased normalized characteristic path length (lambda) (t = 2.270, p = 0.025). No significant differences were observed between the groups in the remaining metrics, including PSFA, PSAD, PSRD, average MD, FA, AD, RD, local efficiency, normalized cluster coefficient, small-worldness, assortativity, modularity, or hierarchy (p > 0.05). After adjusting for relevant variables, both PSMD and lambda values exhibited a significant negative correlation with reasoning and problem-solving scores (PSMD: r = -0.409, p = 0.038; lambda: r = -0.520, p = 0.006). No statistically significant correlations were observed between each PANSS score and the aforementioned metrics in the patient group (p > 0.05). Multivariate linear regression analysis revealed that increased PSMD (β = -0.426, t = -2.260, p = 0.034) and increased lambda (β = -0.490, t = -2.994, p = 0.007) were independently associated with decreased reasoning and problem-solving scores respectively ( = 0.295, F = 2.951, p = 0.029). But these significant correlations did not withstand FDR correction (p_FDR > 0.05). PSMD can be considered as a valuable neuroimaging biomarker that complements conventional diffusion measurements for investigating abnormalities in WM microstructural integrity and cognitive functions in schizophrenia.

Is game-based therapy effective for treating cognitive deficits in adults with schizophrenia? Evidence from a randomized controlled trial

Cognitive deficits in schizophrenia are a major contributor to poor functional outcomes and everyday functioning, making them a promising therapeutic target. Recent years have witnessed a dramatic increase in the use of digital interventions, such as game-based therapy, targeting various domains of cognition to treat mental disorders. Game-based digital interventions have been suggested to have therapeutic value in health care for people with schizophrenia. To support this idea, a novel, online training program (Komori Life) that targets cognitive deficits in schizophrenia was tested for feasibility of use and initial efficiency. Inpatients with schizophrenia were randomized to complete 20 sessions of either Komori Life (N = 40 completers) or treatment as usual (N = 40 completers). Cognitive and clinical assessments were performed at enrollment and after completion of the training intervention for all patients. In addition, 32 healthy volunteers were recruited as controls, and an eye-tracking paradigm was employed to assess attentional biases to emotional information before and after game intervention for all subjects. The results showed that there were no group differences in cognitive or clinical assessments at baseline between the two patient groups. After game training, there were still no group × time interactions on cognitive or clinical assessment scores. Regarding eye movement measurements, both patient groups showed increased attention to threatening stimuli compared to healthy controls in terms of attentional maintenance at baseline. After game training, the game training group revealed greater improvement in attentional bias towards threatening scenes (decreased percentage of total duration and percentage of total fixations towards threatening stimuli) relative to the treatment as usual group. Moreover, our results partially indicated that training effectiveness was associated with cognitive improvement and that heightened attentional maintenance to threats was associated with worse cognitive performance. This study provides initial evidence that a remote, online cognitive training program is feasible and effective in improving cognitive function in schizophrenia. This form of training may serve as a complementary therapy to existing psychiatric care. Clinical trial registration: the trial is registered at http://www.chictr.org.cn, identifier ChiCTR2100048403.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Aberrant brain functional connectivity mediates the effects of negative symptoms on cognitive function in schizophrenia: A structural equation model

BackgroundSchizophrenia is a severe psychiatric disorder, characterized by positive symptoms, negative symptoms, and cognitive deficits. Elucidating the mechanism of negative symptom and cognitive deficits could contribute to the treatment and prognosis of schizophrenia. We hypothesized that abnormal functional connectivity would be involved in the indirect effects of negative symptoms on cognitive function. MethodsA total of 150 schizophrenia male patients and 108 healthy controls matched for age, education and gender were enrolled in the study. The scores of Brief Negative Symptom Scale were divided into two factors: motivation and pleasure deficits (MAP) and diminished expression (EXP). Subsequently, a series of classic neurocognitive tests were used to evaluate cognitive functions. Resting-state fMRI data was collected from all participants. The Anatomical Automatic Labeling template was employed to establish regions of interest, thereby constructing the functional connectivity network across the entire brain. Eventually, scores of patients' negative symptoms scale, cognitive function, and strengths of abnormal functional connectivity were incorporated into a structural equation model to explore the interactions among variables. ResultsMAP exhibited a distinctly and significantly negative impact on cognitive function. The functional connectivity between the left insula and left precuneus, along with that between the left precuneus and right angular gyrus, collectively served as intermediaries, contributing to the indirect effects of MAP and EXP on cognitive function. ConclusionsOur findings demonstrated the moderating role of aberrant brain functional connectivity between negative symptoms and cognitive function, providing clues about the neural correlates of negative symptoms and cognitive deficits in schizophrenia.

Increased and sex-differentiated medial prefrontal cortex activation during the MATRICS Consensus Cognitive Battery in schizophrenia: A fNIRS study

Executive impairment in schizophrenia is common, but the mechanism remains unclear. This is the first study to use simultaneously functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in schizophrenia during the MATRICS Consensus Cognitive Battery (MCCB). Here, we monitored relative changes in oxyhemoglobin concentration in the medial prefrontal cortex (mPFC) during Trail Making Test, Symbol Coding Test and Mazes Test of the MCCB in 63 patients (29 females) with schizophrenia and 32 healthy controls (15 females). Results showed that patients with schizophrenia scored lower than healthy controls on all three tests (P < 0.001), but mPFC activation was significantly higher during the test (P < 0.03). Higher activation of the mPFC may reflect abnormal information processing in schizophrenia. In addition, the results also showed sex differences in hemodynamic activation during the task in patients with schizophrenia, and fNIRS has the potential to be a clinical adjunct to screening for cognitive function in schizophrenia.

Effect of Omega-3 Adjuvant Therapy on Cognitive Improvement and Levels of Glial Cell Line-Derived Neurotrophic Factor (GDNF) in Schizophrenia Patients Receiving Risperidone Therapy

Background: Schizophrenia is a disorder with severe and persistent psychotic manifestations accompanied by cognitive impairment. Treatment with atypical antipsychotic therapy (APG-2) provides only minimal benefit for the cognitive impairment of schizophrenia patients. Many efforts are currently being expanded to find new treatments that can serve as “co-treatments” to improve neurocognition from aspects of neurobiology and neuroplasticity. Several studies found that omega-3 fatty acids can improve cognitive function in schizophrenia patients.Objective: The objective is to assess the impact of omega-3 adjuvant therapy on improving cognitive function and elevating glial cell line-derived neurotrophic factor (GDNF) levels in individuals diagnosed with schizophrenia who are undergoing risperidone treatment.Method: A research study utilizing experimental analysis, including pre-tests and post-tests with non-random group selection, was conducted at Dadi Regional Special Hospital in South Sulawesi, Indonesia, between May and July 2023. Sample testing was carried out at the HUMRC Research Laboratory. The study involved 44 participants divided into two groups: a treatment group comprising 22 individuals who received 4 mg/day risperidone along with Omega-3 supplements for eight weeks and a control group of 22 individuals who received only 4 mg/day risperidone. Cognitive function was evaluated using the MoCA-Ina tool, while GDNF serum levels were determined through enzyme-linked immunosorbent assays (ELISA). Significance was assessed through the Chi-square, Wilcoxon, Mann-Whitney, Pearson and Spearman correlation tests.Results: There was an improvement in cognitive function and a significant increase of GDNF serum levels in schizophrenia patients who received omega-3 adjuvant therapy over 8 weeks compared to individuals with schizophrenia who solely received the antipsychotic risperidone. Conclusion: Supplementing standard risperidone therapy with omega-3 adjuvant can enhance cognitive function and elevate GDNF levels.

Comparative analysis of anticholinergic burden scales to explain iatrogenic cognitive impairment in schizophrenia: results from the multicenter FACE-SZ cohort.

The anticholinergic properties of medications are associated with poorer cognitive performance in schizophrenia. Numerous scales have been developed to assess anticholinergic burden and yet, there is no consensus indicating which anticholinergic burden scale is more relevant for patients with schizophrenia. We aimed to identify valid scales for estimating the risk of iatrogenic cognitive impairment in schizophrenia. We identified 27 scales in a literature review. The responses to neuropsychological tests of 839 individuals with schizophrenia or schizoaffective disorder in the FACE-SZ database were collected between 2010 and 2021. We estimated the association between objective global cognitive performance and the 27 scales, the number of psychotropic drugs, and chlorpromazine and lorazepam equivalents in bivariable regressions in a cross-sectional design. We then adjusted the bivariable models with covariates: the predictors significantly associated with cognitive performance in multiple linear regressions were considered to have good concurrent validity to assess cognitive performance. Eight scales, the number of psychotropic drugs, and drug equivalents were significantly associated with cognitive impairment. The number of psychotropic drugs, the most convenient predictor to compute, was associated with worse executive function (Standardized β = -0.12, p = .004) and reasoning (Standardized β = -0.08, p = .037). Anticholinergic burden, the number of psychotropic drugs, and drug equivalents were weakly associated with cognition, thus suggesting that cognitive impairment in schizophrenia and schizoaffective disorder is explained by factors other than medication. The number of psychotropic drugs was the most parsimonious method to assess the risk of iatrogenic cognitive impairment.

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

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. 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. 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). 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.

Eosinophils and Cognitive Impairment in Schizophrenia: A New Perspective.

Schizophrenia is a complex psychiatric disorder characterized by a wide array of cognitive impairments. While research has predominantly focused on the neurological aspects of schizophrenia, emerging evidence suggests that the immune system, specifically eosinophils, may play a significant role in the cognitive deficits associated with the disorder. This review presents a novel perspective on the interplay between eosinophils and cognitive impairment in schizophrenia. Eosinophils, traditionally associated with allergic responses and inflammation, have garnered limited attention within the realm of neuropsychiatry. Recent studies have hinted at a potential link between eosinophil activation and the pathogenesis of schizophrenia. In this comprehensive review, we delve into the world of eosinophils, elucidating their nature, functions, and interactions with the immune system. We examine the cognitive deficits observed in individuals with schizophrenia and discuss existing theories on the etiology of these impairments, focusing on immune system involvement. The paper also highlights the evolving body of research that supports the idea of eosinophilic influence on schizophrenia-related cognitive deficits. Furthermore, we explore potential mechanisms through which eosinophils may exert their effects on cognitive function in schizophrenia, including interactions with other immune cells and inflammatory pathways. By discussing the clinical implications and potential therapeutic avenues stemming from this newfound perspective, we underscore the practical significance of this emerging field of research. While this paper acknowledges the limitations and challenges inherent in studying eosinophils within the context of schizophrenia, it serves as a posit for novel thought in this vexing disease space as well as a call to action for future research endeavors. By providing a comprehensive survey of the existing literature and posing unanswered questions, we aim to inspire a reimagining of the relationship between eosinophils and cognitive impairment in schizophrenia, ultimately advancing our understanding and treatment of this debilitating disorder.

Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients

BackgroundDistinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients.MethodsThe study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands.ResultsSignificant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups.ConclusionsAlterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

The relationship between the gut microbiota and oxidative stress in the cognitive function of schizophrenia: A pilot study in China

Cognitive impairment is a core symptom of schizophrenia. The gut microbiota (GM) and oxidative stress may play important roles in the pathophysiological mechanisms of cognitive impairment. This study aimed to explore the relationship between GM and oxidative stress in the cognitive function of schizophrenia. GM obtained by 16S RNA sequencing and serum superoxide dismutase (SOD) levels from schizophrenia patients (N = 68) and healthy controls (HCs, N = 72) were analyzed. All psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). Correlation analysis was used to explore the relationship between GM, SOD, and cognitive function. Machine learning models were used to identify potential biomarkers. Compared to HCs, the relative abundances of Collinsella, undefined Ruminococcus, Lactobacillus, Eubacterium, Mogibacterium, Desulfovibrio, Bulleidia, Succinivibrio, Corynebacterium, and Atopobium were higher in patients with schizophrenia, but Faecalibacterium, Anaerostipes, Turicibacter, and Ruminococcus were lower. In patients with schizophrenia, the positive factor, general factor, and total score of MCCB positively correlated with Lactobacillus, Collinsella, and Lactobacillus, respectively; SOD negatively correlated with Eubacterium, Collinsella, Lactobacillus, Corynebacterium, Bulleidia, Mogibacterium, and Succinivibrio, but positively correlated with Faecalibacterium, Ruminococcus, and MCCB verbal learning index scores; Faecalibacterium and Turicibacter were positively correlated with MCCB visual learning index scores and speed of processing index scores, respectively. Our findings revealed a correlation between SOD and GM and confirmed that cognitive dysfunction in patients with schizophrenia involves abnormal SOD levels and GM changes.

Sex dimorphism controls dysbindin-related cognitive dysfunctions in mice and humans with the contribution of COMT.

Cognitive dysfunctions are core-enduring symptoms of schizophrenia, with important sex-related differences. Genetic variants of the DTBPN1 gene associated with reduced dysbindin-1 protein (Dys) expression negatively impact cognitive functions in schizophrenia through a functional epistatic interaction with Catechol-O-methyltransferase (COMT). Dys is involved in the trafficking of dopaminergic receptors, crucial for prefrontal cortex (PFC) signaling regulation. Moreover, dopamine signaling is modulated by estrogens via inhibition of COMT expression. We hypothesized a sex dimorphism in Dys-related cognitive functions dependent on COMT and estrogen levels. Our multidisciplinary approach combined behavioral-molecular findings on genetically modified mice, human postmortem Dys expression data, and in vivo fMRI during a working memory task performance. We found cognitive impairments in male mice related to genetic variants characterized by reduced Dys protein expression (pBonferroni = 0.0001), as well as in male humans through a COMT/Dys functional epistatic interaction involving PFC brain activity during working memory (t(23) = -3.21; pFDR = 0.004). Dorsolateral PFC activity was associated with lower working memory performance in males only (p = 0.04). Also, male humans showed decreased Dys expression in dorsolateral PFC during adulthood (pFDR = 0.05). Female Dys mice showed preserved cognitive performances with deficits only with a lack of estrogen tested in an ovariectomy model (pBonferroni = 0.0001), suggesting that genetic variants reducing Dys protein expression could probably become functional in females when the protective effect of estrogens is attenuated, i.e., during menopause. Overall, our results show the differential impact of functional variants of the DTBPN1 gene interacting with COMT on cognitive functions across sexes in mice and humans, underlying the importance of considering sex as a target for patient stratification and precision medicine in schizophrenia.

Association between increased BMI and cognitive function in first-episode drug-naïve male schizophrenia.

Although the adverse effects of obesity in schizophrenia are documented, there is limited research exists on the implications for untreated initial schizophrenia. Our investigation aimed to explore the connections between BMI and cognitive function in first-episode drug-naïve (FEDN)schizophrenia. We enrolled 143 FEDN schizophrenia patients, and collected data on their body mass index, fasting blood glucose and lipid levels. Cognitive function was measured with the MATRICS Consensus Cognitive Battery (MCCB). Using correlation and regression analysis to assess the relationship between BMI and cognitive performance. The prevalence rate of overweight plus obesity in FEDN schizophrenia patients was 33.57%. Patients with FEDN schizophrenia exhibited extensive cognitive impairment, and those who were overweight/obesity demonstrated more severe impairments in working memory and visual learning when compared to normal/under weight counterparts. Correlation analysis indicated a negative association between working memory and BMI and TG, as well as a link between visual learning and BMI and LDL-C. Multiple linear regression analysis revealed that a higher BMI predicted a decrease in working memory in FEDN schizophrenia patients. Our results indicate that the rate of overweight plus obesity is high in FEDN schizophrenia patients, and there is an association between BMI and cognitive function in schizophrenia, particularly in relation to working memory.

Association of antidepressant and benzodiazepine use, and anticholinergic burden with cognitive performance in schizophrenia

Schizophrenia is characterized by cognitive impairment affecting everyday functioning. Earlier research has hypothesized that antidepressants may associate with better cognitive functioning, but results are mixed. This study explored the association between antidepressant use and cognitive performance in terms of reaction time and visual learning in a clinical sample. In addition, we examined benzodiazepine use and anticholinergic burden. Study participants were drawn from the SUPER-Finland cohort, collected among patients with psychotic illnesses in 2016–2018 throughout Finland (n = 10,410). The analysis included adults with a schizophrenia diagnosis (F20) and results from a cognitive assessment (n = 3365). Information about medications and psychosocial factors were gathered through questionnaire and interview. Cognitive performance was assessed with the Cambridge Neuropsychological Test Automated Battery (CANTAB) with two subtests measuring reaction time and visual learning. Almost 36 % of participants used at least one antidepressant. The use of antidepressants in general was not associated with performance in the reaction time and visual learning tasks. However, the use of SNRI antidepressants was associated with a faster reaction time. Benzodiazepine use and a higher anticholinergic burden were associated with poorer performance in both tests. The results strengthen earlier findings that there is no association between antidepressant use in general and cognitive performance in schizophrenia. However, the association of SNRI medications with a faster reaction time warrants further research. Moreover, the results suggest that more attention should be paid to the anticholinergic burden of the medications used by patients with schizophrenia, as well as avoiding continuous benzodiazepine use.

Associations between Verbal Fluency and Asymmetry of White Matter Integrity in the Superior Longitudinal Fasciculus in At-Risk Mental States for Psychosis.

Verbal fluency is one of the most severely impaired components of cognitive function in schizophrenia and is also impaired in at-risk mental states (ARMSs) for psychosis. The aim of this study was to explore the markers of disease progression in subjects with ARMSs by comparing the association between the white matter integrity of the superior longitudinal fasciculus (SLF) and verbal fluency in subjects with ARMSs and healthy control (HC) subjects. The correlations of the fractional anisotropy (FA) values on diffusion tensor imaging (DTI) and the laterality index (LI) values of SLF branches I, II, and III with the verbal fluency performance were analyzed in right-handed subjects with ARMSs (ARMS group; n = 18) and HC subjects (HC group; n = 34) aged 18 to 40 years old. In the HC group compared with the ARMS group, the LI values suggested right lateralization of the SLF II and III. Letter fluency was significantly correlated with the LI of the SLF III in both the ARMS and HC groups. The regression coefficient (β) of this correlation was calculated using the least squares method and yielded a positive number (73.857) in the ARMS group and a negative number (-125.304) in the HC group. The association of the rightward asymmetry of the SLF III with the verbal fluency performance observed in the HC group appeared to be lost in the ARMS group, and this could serve as one of the markers of the pathological progression to psychosis in patients with schizophrenia.

Reward Learning as a Potential Mechanism for Improvement in Schizophrenia Spectrum Disorders Following Cognitive Remediation: Protocol for a Clinical, Nonrandomized, Pre-Post Pilot Study.

Cognitive impairment is common with schizophrenia spectrum disorders. Cognitive remediation (CR) is effective in improving global cognition, but not all individuals benefit from this type of intervention. A better understanding of the potential mechanism of action of CR is needed. One proposed mechanism is reward learning (RL), the cognitive processes responsible for adapting behavior following positive or negative feedback. It is proposed that the structure of CR enhances RL and motivation to engage in increasingly challenging tasks, and this is a potential mechanism by which CR improves cognitive functioning in schizophrenia. Our primary objective is to examine reward processing in individuals with schizophrenia before and after completing CR and to compare this with a group of matched clinical controls. We will assess whether RL mediates the relationship between CR and improved cognitive function and reduced negative symptoms. Potential differences in social RL and nonsocial RL in individuals with schizophrenia will also be investigated and compared with a healthy matched control group. We propose a clinical, nonrandomized, pre-post pilot study comparing the impact of CR on RL and neurocognitive outcomes. The study will use a combination of objective and subjective measures to assess neurocognitive, psychiatric symptoms, and neurophysiological domains. A total of 40 individuals with schizophrenia spectrum disorders (aged 18-35 years) will receive 12 weeks of CR therapy (n=20) or treatment as usual (n=20). Reward processing will be evaluated using a reinforcement learning task with 2 conditions (social reward vs nonsocial reward) at baseline and the 12-week follow-up. Functional magnetic resonance imaging responses will be measured during this task. To validate the reinforcement learning task, RL will also be assessed in 20 healthy controls, matched for age, sex, and premorbid functioning. Mixed-factorial ANOVAs will be conducted to evaluate treatment group differences. For the functional magnetic resonance imaging analysis, computational modeling will allow the estimation of learning parameters at each point in time, during each task condition, for each participant. We will use a variational Bayesian framework to measure how learning occurred during the experimental task and the subprocesses that underlie this learning. Second-level group analyses will examine how learning in patients differs from that observed in control participants and how CR alters learning efficiency and the underlying neural activity. As of September 2023, this study has enrolled 15 participants in the CR group, 1 participant in the treatment-as-usual group, and 11 participants in the healthy control group. Recruitment is expected to be completed by September 2024. Data analysis is expected to be completed and published in early 2025. The results of this study will contribute to the knowledge of CR and RL processes in severe mental illness and the understanding of the systems that impact negative symptoms and cognitive impairments within this population. DERR1-10.2196/52505.

Inference of social cognition in schizophrenia patients with neurocognitive domains and neurocognitive tests using automated machine learning

AimIt has been suggested that single neurocognitive domain or neurocognitive test can be used to determine the overall cognitive function in schizophrenia using machine learning algorithms. It is unknown whether social cognition in schizophrenia patients can be estimated with machine learning based on neurocognitive domains or neurocognitive tests. MethodsTo predict social cognition in schizophrenia, we applied an automated machine learning (AutoML) framework resulting from the analysis of predictive factors such as six neurocognitive domain scores and nine neurocognitive test scores of 380 schizophrenia patients in the Taiwanese population. Four clinical parameters (i.e., age, gender, subgroup, and education) were also used as predictive factors. We utilized an AutoML framework called Tree-based Pipeline Optimization Tool (TPOT) to generate predictive pipelines automatically. ResultsThe analysis revealed that all neurocognitive domains and tests except the reasoning and problem solving domain/test showed significant associations with social cognition. In addition, a TPOT-generated pipeline can best predict social cognition in schizophrenia using seven predictive factors, including five neurocognitive domains (i.e., speed of processing, sustained attention, working memory, verbal learning and memory, and visual learning and memory) and two clinical parameters (i.e., age and gender). This predictive pipeline consists of machine learning algorithms such as function transformers, an approximate feature map, independent component analysis, and linear regression. ConclusionThe study indicates that an AutoML framework such as TPOT may provide a promising way to produce truly effective machine learning pipelines for predicting social cognition in schizophrenia using neurocognitive domains and/or neurocognitive tests.

Immediate post performance judgements about cognitive performance in schizophrenia and bipolar disorder: associations with test performance and subjective overall judgments regarding abilities

ABSTRACT Introduction: The study explored associations between the accuracy of post assessment judgements of cognitive performance with global self-assessments of psychosocial functioning compared to evaluations generated by observers in schizophrenia and bipolar disorder. Methods: An abbreviated cognitive assessment based on the MATRICS Consensus Cognitive Battery was administered to 122 individuals with schizophrenia and 113 with bipolar disorder. They provided self-estimates of their performance after each subtest. In addition, self-reports on cognition, social cognition, and everyday functioning were collected and compared to observer ratings. Results: Both groups overestimated their cognitive function, but in bipolar disorder, there was 30% shared variance between task performance and self-rated task performance (vs. 5% in schizophrenia). Significant correlations were found between self-reported everyday outcomes and both actual and self-assessed performance. In schizophrenia, immediate judgements were only related to self-rated functioning, not to observer rated functioning. In bipolar disorder, impairments in self-assessment of performance correlated with observer ratings of cognitive ability, which was not observed in schizophrenia. Conclusions: While both groups showed correlations between cognitive performance and introspective accuracy, individuals with bipolar disorder showed higher accuracy in assessing their cognitive performance and other outcomes. Notably, impairments in introspective accuracy were associated with observer-rated functioning exclusively in bipolar disorder.