Meta-analysis of longitudinal neurocognitive performance in people at clinical high-risk for psychosis

Identifying clinical and proteomic markers for early diagnosis and prognosis prediction of major psychiatric disorders

BACKGROUND

To clarify if blood proteins can predict disease progression among individuals at clinical high-risk of severe mental illness (CHR-SMI), we developed a statistical model incorporating clinical and blood protein markers to distinguish the transition group (who developed severe mental illness) (CHR-SMI-T) and from non-transition group (CHR-SMI-NT) at baseline.

METHODS

Ninety individuals (74 at CHR-SMI: 16 patients) were monitored for ≤4 years and were the focus of predictive models. Three predictive models (1 [100 clinical variables], 2 [158 peptides], and 3 [100 clinical variables +158 peptides]) were evaluated using area under the receiver operating characteristic (AUROC) values. Clinical and protein feature patterns were evaluated by linear mixed-effect analysis within the model at 12 and 24 months among patients who did (CHR-SMI-T) and did not transition (CHR-SMI-NT) and the entire group.

RESULT

Eighteen CHR-SMI individuals with major psychiatric disorders (first episode psychosis: 2; bipolar II disorder: 13; major depressive disorder; 3) developed disorders over an average of 17.7 months. The combined model showed the highest discriminatory performance (AUROC = 0.73). Cytosolic malate dehydrogenase and transgelin-2 levels were lower in the CHR-SMI-T than the CHR-SMI-NT group. Complement component C9, inter-alpha-trypsin inhibitor heavy chain H4, von Willebrand factor, and C-reactive protein were lower in the patient than the CHR-SMI-NT group. These differences were non-significant after FDR adjustment.

LIMITATIONS

Small sample, no control for medication use.

CONCLUSION

This exploratory study identified clinical and proteomic markers that might predict severe mental illness early onset, which could aid in early detection and intervention. Future studies with larger samples and controlled variables are needed to validate these findings.

Associations between white matter microstructure and cognitive decline in major depressive disorder versus controls in Germany: a prospective case-control cohort study

BACKGROUND

Cognitive deficits are a key source of disability in individuals with major depressive disorder (MDD) and worsen with disease progression. Despite their clinical relevance, the underlying mechanisms of cognitive deficits remain poorly elucidated, hampering effective treatment strategies. Emerging evidence suggests that alterations in white matter microstructure might contribute to cognitive dysfunction in MDD. We aimed to investigate the complex association between changes in white matter integrity, cognitive decline, and disease course in MDD in a comprehensive longitudinal dataset.

METHODS

In the naturalistic, observational, prospective, case-control Marburg-Münster Affective Disorders Cohort Study, individuals aged 18-65 years and of Caucasian ancestry were recruited from local psychiatric hospitals in Münster and Marburg, Germany, and newspaper advertisements. Individuals diagnosed with MDD and individuals without any history of psychiatric disorder (ie, healthy controls) were included in this subsample analysis. Participants had diffusion-weighted imaging, a battery of neuropsychological tests, and detailed clinical data collected at baseline and at 2 years of follow-up. We used linear mixed-effect models to compare changes in cognitive performance and white matter integrity between participants with MDD and healthy controls. Diffusion-weighted imaging analyses were conducted using tract-based spatial statistics. To correct for multiple comparisons, threshold free cluster enhancement (TFCE) was used to correct α-values at the family-wise error rate (FWE; ptfce-FWE). Effect sizes were estimated by conditional, partial R2 values (sr2) following the Nakagawa and Schielzeth method to quantify explained variance. The association between changes in cognitive performance and changes in white matter integrity was analysed. Finally, we examined whether the depressive disease course between assessments predicted cognitive performance at follow-up and whether white matter integrity mediated this association. People with lived experience were not involved in the research and writing process.

FINDINGS

881 participants were selected for our study, of whom 418 (47%) had MDD (mean age 36·8 years [SD 13·4], 274 [66%] were female, and 144 [34%] were male) and 463 (53%) were healthy controls (mean age 35·6 years [13·5], 295 [64%] were female, and 168 [36%] were male). Baseline assessments were done between Sept 11, 2014, and June 3, 2019, and after a mean follow-up of 2·20 years (SD 0·19), follow-up assessments were done between Oct 6, 2016, and May 31, 2021. Participants with MDD had lower cognitive performance than did healthy controls (p<0·0001, sr2=0·056), regardless of timepoint. Analyses of diffusion-weighted imaging indicated a significant diagnosis × time interaction with a steeper decline in white matter integrity of the superior longitudinal fasciculus over time in participants with MDD than in healthy controls (ptfce-FWE=0·026, sr2=0·002). Furthermore, cognitive decline was robustly associated with the decline in white matter integrity over time across both groups (ptfce-FWE<0·0001, sr2=0·004). In participants with MDD, changes in white matter integrity (p=0·0040, β=0·071) and adverse depressive disease course (p=0·0022, β=-0·073) independently predicted lower cognitive performance at follow-up.

INTERPRETATION

Alterations of white matter integrity occurred over time to a greater extent in participants with MDD than in healthy controls, and decline in white matter integrity was associated with a decline in cognitive performance across groups. Our findings emphasise the crucial role of white matter microstructure and disease progression in depression-related cognitive dysfunction, making both priority targets for future treatment development.

FUNDING

German Research Foundation (DFG).

Neurocognition in adolescents and young adults at clinical high risk for psychosis: Predictive stability for social and role functioning

The prodromal phase of schizophrenia provides an optimal opportunity to mitigate the profound functional disability that is often associated with fully expressed psychosis. Considerable evidence supports the importance of neurocognition in the development of interpersonal (social) and academic (role) skills. Further findings from adolescents and young adults at clinical high risk for developing psychosis (CHRP) suggest that treatment for functioning might be most effective when targeting early and specific neurocognitive deficits. The current study addresses this critical intervention issue by examining the potential of neurocognitive deficits at intake for predicting social and role functioning over time in CHR-P youth. The study included 345 CHR-P participants from the second phase of the North American Prodrome Longitudinal Study (NAPLS2) with baseline neurocognition and 2-year follow-up data on social and role functioning. Slower baseline processing speed consistently predicted poor social functioning over time, while attention deficits predicted poor role functioning at baseline and follow-up. In addition, the impact of processing speed and attention impairments on social and role functioning, respectively, persisted even when adjusting the regression models for attenuated positive, negative, and disorganized symptoms, and transition status. The current study demonstrates for, arguably the first time, that processing speed and attention are strongly predictive of social and role functioning over time, respectively, above and beyond the impact of symptoms and those CHR-P individuals that develop psychosis over the course of the study. These findings imply that early neurocognition is a critical treatment target linked to the developmental trajectory of social and role functioning.

PsyCog: A computerised mini battery for assessing cognition in psychosis

Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) (N = 135), Clinical High Risk (CHR) (N = 233), and First Episode Psychosis (FEP) (N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design.

Do Cognitive Subtypes Exist in People at Clinical High Risk for Psychosis? Results From the EU-GEI Study

BACKGROUND AND HYPOTHESIS

Cognition has been associated with socio-occupational functioning in individuals at Clinical High Risk for Psychosis (CHR-P). The present study hypothesized that clustering CHR-P participants based on cognitive data could reveal clinically meaningful subtypes.

STUDY DESIGN

A cohort of 291 CHR-P subjects was recruited through the multicentre EU-GEI high-risk study. We explored whether an underlying cluster structure was present in the cognition data. Clustering of cognition data was performed using k-means clustering and density-based spatial clustering of applications with noise. Cognitive subtypes were validated by comparing differences in functioning, psychosis symptoms, transition outcome, and grey matter volume between clusters. Network analysis was used to further examine relationships between cognition scores and clinical symptoms.

STUDY RESULTS

No underlying cluster structure was found in the cognitive data. K-means clustering produced "spared" and "impaired" cognition clusters similar to those reported in previous studies. However, these clusters were not associated with differences in functioning, symptomatology, outcome, or grey matter volume. Network analysis identified cognition and symptoms/functioning measures that formed separate subnetworks of associations.

CONCLUSIONS

Stratifying patients according to cognitive performance has the potential to inform clinical care. However, we did not find evidence of cognitive clusters in this CHR-P sample. We suggest that care needs to be taken in inferring the existence of distinct cognitive subtypes from unsupervised learning studies. Future research in CHR-P samples could explore the existence of cognitive subtypes across a wider range of cognitive domains.

New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment

Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.

Cognitive functions following initiation of antipsychotic medication in adolescents and adults at clinical high risk for psychosis: a naturalistic sub group analysis using the MATRICS consensus cognitive battery

BACKGROUND

The effects of antipsychotic (AP) medications on cognitive functions in individuals at clinical high-risk (CHR) of psychosis are poorly understood. This study compared the effects of AP treatment on cognitive improvement in CHR adolescents and adults.

METHODS

A total of 327 CHR participants, with an age range of 13 to 45 years, who underwent baseline neuropsychological assessments and a 1-year clinical follow-up were included. Participants with CHR were categorized into four groups based on their age: adolescents (aged < 18) and adults (aged ≥ 18), as well as their antipsychotic medication status (AP+ or AP-). Therefore, the four groups were defined as Adolescent-AP-, Adolescent-AP+, Adult-AP-, and Adult-AP+.

RESULTS

During the follow-up, 231 CHR patients received AP treatment, 94 converted to psychosis, and 161 completed the 1-year follow-up. The Adolescent-AP+ group had more positive symptoms, lower general functions, and cognitive impairments than the Adolescent-AP- group at baseline, but no significant differences were observed among adults. The Adolescent-AP+ group showed a significant increase in the risk of conversion to psychosis (p < 0.001) compared to the Adolescent-AP- group. The Adult-AP+ group showed a decreasing trend in the risk of conversion (p = 0.088) compared to the Adult-AP- group. The Adolescent-AP- group had greater improvement in general functions (p < 0.001), neuropsychological assessment battery mazes (p = 0.025), and brief visuospatial memory test-revised (p = 0.020), as well as a greater decrease in positive symptoms (p < 0.001) at follow-up compared to the Adolescent-AP+ group. No significant differences were observed among adults.

CONCLUSIONS

Early use of AP was not associated with a positive effect on cognitive function in CHR adolescents. Instead, the absence of AP treatment was associated with better cognitive recovery, suggesting that AP exposure might not be the preferred choice for cognitive recovery in CHR adolescents, but may be more reasonable for use in adults.

The magnitude and variability of neurocognitive performance in first-episode psychosis: a systematic review and meta-analysis of longitudinal studies

Neurocognitive deficits are a core feature of psychotic disorders, but it is unclear whether they affect all individuals uniformly. The aim of this systematic review and meta-analysis was to synthesize the evidence on the magnitude, progression, and variability of neurocognitive functioning in individuals with first-episode psychosis (FEP). A multistep literature search was conducted in several databases up to November 1, 2022. Original studies reporting on neurocognitive functioning in FEP were included. The researchers extracted the data and clustered the neurocognitive tasks according to the seven Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) domains and six additional domains. Random-effect model meta-analyses, assessment of publication biases and study quality, and meta-regressions were conducted. The primary effect size reported was Hedges g of (1) neurocognitive functioning in individuals at FEP measuring differences with healthy control (HC) individuals or (2) evolution of neurocognitive impairment across study follow-up intervals. Of 30,384 studies screened, 54 were included, comprising 3,925 FEP individuals and 1,285 HC individuals. Variability analyses indicated greater variability in FEP compared to HC at baseline and follow-up. We found better neurocognitive performance in the HC group at baseline and follow-up but no differences in longitudinal neurocognitive changes between groups. Across the 13 domains, individuals with FEP showed improvement from baseline in all studied domains, except for visual memory. Metaregressions showed some differences in several of the studied domains. The findings suggest that individuals with FEP have marked cognitive impairment, but there is greater variability in cognitive functioning in patients than in HC. This suggests that subgroups of individuals suffer severe disease-related cognitive impairments, whereas others may be much less affected. While these impairments seem stable in the medium term, certain indicators may suggest potential further decline in the long term for a specific subgroup of individuals, although more research is needed to clarify this. Overall, this study highlights the need for tailored neurocognitive interventions for individuals with FEP based on their specific deficits and progression.

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

PURPOSE OF REVIEW

This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis.

RECENT FINDINGS

Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.

The potential of digital behavioural tests as a diagnostic aid for psychosis

Timely interventions have a proven benefit for people experiencing psychotic illness. One bottleneck to accessing timely interventions is the referral process to the specialist team for early psychosis (STEP). Many general practitioners lack awareness or confidence in recognising psychotic symptoms or state. Additionally, referrals for people without apparent psychotic symptoms, although beneficial at a population level, lead to excessive workload for STEPs. There is a clear unmet need for accurate stratification of STEPs users and healthy cohorts. Here we propose a new approach to addressing this need via the application of digital behavioural tests. To demonstrate that digital behavioural tests can be used to discriminate between the STEPs users (SU; n = 32) and controls (n = 32, age and sex matched), we compared performance of five different classifiers applied to objective, quantitative and interpretable features derived from the 'mirror game' (MG) and trail making task (TMT). The MG is a movement coordination task shown to be a potential socio-motor biomarker of schizophrenia, while TMT is a neuropsychiatric test of cognitive function. All classifiers had AUC in the range of 0.84-0.92. The best of the five classifiers (linear discriminant classifier) achieved an outstanding performance, AUC = 0.92 (95%CI 0.75-1), Sensitivity = 0.75 (95%CI 0.5-1), Specificity = 1 (95%CI 0.75-1), evaluated on 25% hold-out and 1000 folds. Performance of all analysed classifiers is underpinned by the large effect sizes of the differences between the cohorts in terms of the features used for classification what ensures generalisability of the results. We also found that MG and TMT are unsuitable in isolation to successfully differentiate between SU with and without at-risk-mental-state or first episode psychosis with sufficient level of performance. Our findings show that standardised batteries of digital behavioural tests could benefit both clinical and research practice. Including digital behavioural tests into healthcare practice could allow precise phenotyping and stratification of the highly heterogenous population of people referred to STEPs resulting in quicker and more personalised diagnosis. Moreover, the high specificity of digital behavioural tests could facilitate the identification of more homogeneous clinical high-risk populations, benefiting research on prognostic instruments for psychosis. In summary, our study demonstrates that cheap off-the-shelf equipment (laptop computer and a leap motion sensor) can be used to record clinically relevant behavioural data that could be utilised in digital mental health applications.

Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment

Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.

Comparing a Computerized Digit Symbol Test to a Pen-and-Paper Classic

Background and Hypothesis

Processing speed dysfunction is a core feature of psychosis and predictive of conversion in individuals at clinical high risk (CHR) for psychosis. Although traditionally measured with pen-and-paper tasks, computerized digit symbol tasks are needed to meet the increasing demand for remote assessments. Therefore we: (1) assessed the relationship between traditional and computerized processing speed measurements; (2) compared effect sizes of impairment for progressive and persistent subgroups of CHR individuals on these tasks; and (3) explored causes contributing to task performance differences.

Study Design

Participants included 92 CHR individuals and 60 healthy controls who completed clinical interviews, the Brief Assessment of Cognition in Schizophrenia Symbol Coding test, the computerized TestMyBrain Digit Symbol Matching Test, a finger-tapping task, and a self-reported motor abilities measure. Correlations, Hedges' g, and linear models were utilized, respectively, to achieve the above aims.

Study Results

Task performance was strongly correlated (r = 0.505). A similar degree of impairment was seen between progressive (g = -0.541) and persistent (g = -0.417) groups on the paper version. The computerized task uniquely identified impairment for progressive individuals (g = -477), as the persistent group performed similarly to controls (g = -0.184). Motor abilities were related to the computerized version, but the paper version was more related to symptoms and psychosis risk level.

Conclusions

The paper symbol coding task measures impairment throughout the CHR state, while the computerized version only identifies impairment in those with worsening symptomatology. These results may be reflective of sensitivity differences, an artifact of existing subgroups, or evidence of mechanistic differences.