Identifying patients at high risk of relapse during antipsychotic tapering remains a significant clinical challenge. This study aims to investigate whether a higher metabolic baseline is associated with increased risk of relapse in a cohort of 83 patients with schizophrenia undergoing tapering of antipsychotic medication. We used data from a tapering program that tapered antipsychotics in patients with schizophrenia during a period of six months, and patients were invited for a re-examination 12 months after baseline. We only collected blood samples at baseline. Mean age was 38.6 (SD 11.63) years. Baseline Positive and Negative Syndrome Scale total score was 62 (SD 14.6) and baseline mean antipsychotic dose was 403 mg (SD 307.8 mg) chlorpromazine equivalent. After 12 months, 29 (35%) patients had experienced relapse which was associated with a higher LDL baseline (3.16 mmol/L ±0.94 [122 mg/dL]) than stable patients (2.56 mmol/L ±0.80 [99 mg/dL] P = 0.001). In a binary logistic regression, increased LDL was associated with an increased risk of developing relapse during tapering (adjusted odds ratio 2.09, [1.11, 3.93], p = 0.022). The underlying mechanism behind an association between plasma-lipids and clinical stability remains largely unknown, indicating that new hypotheses are called for.

PURPOSE:Negative symptoms remain a primary driver of functional disability in schizophrenia spectrum disorders. This article presents the official Danish Multidisciplinary Psychiatry Group's (DMPG) national clinical guideline for the assessment and treatment of negative symptoms in psychotic disorders across the lifespan. MATERIALS AND METHODS:A systematic literature search for systematic reviews and meta-analyses published between 2019 and 2024 was conducted in PubMed and PsycInfo. Studies were screened and extracted by independent reviewers using Covidence. To ensure clinical utility, recommendations were formulated by synthesizing the evidence base with expert consensus, which included extrapolating adult data to formulate guidance for children and adolescents where primary evidence is scarce. RESULTS:The consensus process yielded 21 specific clinical recommendations. The guideline mandates the assessment of five distinct domains (anhedonia, asociality, alogia, avolition, and blunted affect) using dedicated scales like the BNSS. It provides clear guidance on pharmacological strategies, including a conditional endorsement of modafinil augmentation and a recommendation against cannabinoids. Evidence-based psychosocial interventions, such as cognitive behavioral therapy and cognitive remediation, are also recommended. CONCLUSIONS:The guideline establishes a comprehensive, clinically actionable framework for managing negative symptoms in children, adolescents, and adults. Furthermore, it emphasizes that advancing the field requires future research to utilize domain-specific tools to accurately distinguish primary from secondary negative symptoms.

Background: Mental disorders have been associated with systemic chronic inflammation, and conditions such as depression and schizophrenia are increasingly linked to inflammatory processes. Soluble urokinase plasminogen activator receptor (suPAR) is a biomarker of chronic inflammation and has proven useful as a prognostic marker in various somatic diseases. This review examines the evidence for suPAR use in psychiatric populations and evaluates its potential role in clinical psychiatry. Method: A systematic search of Embase and PubMed was conducted using three concepts: biomarker, mental health–related terms, and psychotropics. Clinical and epidemiological studies investigating mental disorders with quantitatively measured suPAR were included. Screening was performed independently by two investigators. Results: Of 2781 identified studies, 32 met inclusion criteria. Elevated plasma suPAR levels were consistently observed in patients with psychosis and major depression, whereas findings for other psychiatric disorders were less conclusive. Evidence for predictive or prognostic applications remains sparse and inconclusive. Higher suPAR levels were associated with increased risk of subsequent antidepressant use and hospital admission for depression. Additionally, higher baseline suPAR levels were linked to a greater likelihood of antidepressant response and faster treatment effects. Discussion: It remains unclear whether elevated suPAR reflects immune activation intrinsic to psychiatric disorders or confounding factors such as lifestyle or psychotropic medication. Longitudinal data on suPAR and symptom development are lacking. Although suPAR is a potential biomarker within psychiatry, methodological inconsistencies persist, and its routine clinical use in psychiatry is premature.

Patients with psychotic disorders exhibit a continuum of heterogenous symptoms with both differences and similarities across diagnostic categories and illness stages. Tools that capture this individualized variability are warranted for tailoring personalized treatment. To address this, we employed Affinity Scores as an individual-centric statistical approach that complements diagnostic information by modeling individualized patterns within multivariate data. We included 670 participants aged 18–60: 284 healthy controls [HC], 201 individuals at ultra-high risk [UHR], 128 patients with first-episode psychosis [FEP], and 57 patients with a history of schizophrenia [SCZ]. Clinical, cognitive, and demographic data were standardized, and dimensional Affinity Scores were computed using participant-specific neighborhood graphs, weighting proximal neighbors. Multivariate features were derived by integrating Affinity Scores across domains. We evaluated classification accuracy of diagnostic alignment, tested associations with regional brain volumes, and applied elastic net logistic regression to predict UHR-outcomes after one year (remission and transition to psychosis). Affinity Scores revealed diverse individual profiles across the psychosis continuum. Diagnostic classification accuracies ranged from 0.59–0.85, improving with contextual neighborhood information. Significant associations emerged between Affinity Scores and frontal, temporal, and parietal brain volumes, reflecting both shared and distinct neurobiological patterns. For UHR-individuals, two heterogeneity indices predicted transition (ROC AUC = 0.865, Brier = 0.027) and remission (ROC AUC = 0.813, Brier = 0.045) after one year, indicating increased diversity as prognostically relevant. This proof-of-concept study demonstrates how Affinity Scores capture individual-level heterogeneity, complement diagnostic information and predict clinical outcome, and holds promise as a novel and transparent tool for improved diagnostics and tailored treatment strategies informed by individualized profiles.

Abstract Background A subset of patients with schizophrenia do not respond sufficiently to conventional antipsychotic treatment and often have a more complex clinical course, including high rates of sleep disturbances, which can contribute to further worsening of symptoms. However, sleep disturbances are often overlooked in clinical psychiatric settings, and non-pharmacological treatment options are not initiated. Cognitive behavioral therapy for insomnia (CBT-I) has been shown to effectively ameliorate sleep disturbances in schizophrenia but is yet to be assessed in treatment-resistant schizophrenia. In the present study, we aim to investigate the efficacy of CBT-I versus standard cognitive behavioral therapy (CBT), an active control intervention. Methods Sixty patients diagnosed with treatment-resistant schizophrenia and comorbid sleep disturbance will be included in this randomized intervention study. Included patients will be randomized to 8–10 sessions of psychotherapy with either CBT-I (active intervention) or regular CBT (active control) following baseline. At baseline and 12-week follow-up, patients will be assessed with clinical interviews (Positive and Negative Syndrome Scale), self-reported measures (e.g., Insomnia Severity Index), and polysomnography. The 24-week follow-up will include the same assessments apart from polysomnography. The active intervention group will receive an individual course of treatment with CBT-I focused on the patients’ sleep patterns, while the active control group will receive an individual course of treatment with standard cognitive behavioral therapy (CBT) focused on patients’ psychopathology. It is hypothesized that while both groups will show improvements on central outcome measures, CBT-I will show greater improvements in sleep disturbances. Further, it is hypothesized that the improvement in sleep disturbances will correlate with an improvement in positive symptoms. Lastly, it is anticipated that the CBT-I group will show objective improvements in sleep architecture, such as sleep latency, wake after sleep onset, sleep efficiency, and total sleep time, compared to the CBT group. Discussion Should CBT-I prove efficacious in improving sleep disturbances in treatment-resistant schizophrenia, it would provide an avenue for a cost-beneficial, short-term, and implementable non-pharmacological treatment of a severe comorbidity in complex schizophrenia patients. Potential issues pertaining to the completion of the study are discussed. Trial registration ClinicalTrials.gov NCT06749444. Registered on December 27, 2024.

Introduction Childhood adversities are well-established risk factors for the later development of severe mental illness, and experiences of bullying are frequently reported among individuals with psychotic disorders. Bullying may influence symptom presentation, illness trajectory, and treatment responsiveness. It has been hypothesized that patients with psychosis and trauma could benefit from psychotherapeutic interventions. This scoping review aims to synthesize existing literature on the association between childhood bullying and psychotic disorders, including implications for treatment. Methods A systematic search was conducted in PubMed and Embase on June 24, 2025, using the terms “bullying” AND “schizophrenia” OR “psychoses.” After removing duplicates, 324 records were screened independently by two reviewers. A total of 42 full-text articles and 4 abstracts met the inclusion criteria and were included in the synthesis. Results Evidence consistently indicates that childhood bullying increases the risk of developing psychosis, particularly when combined with other adversities or genetic vulnerability. While biological and psychological pathways—such as HPA axis dysregulation and maladaptive cognitive schemas—have been proposed, empirical support remains limited. Bullying has been associated with more severe paranoid ideation, persistent delusions, more abnormal self-experiences and poorer social cognitive functioning. Patients with bullying histories may also exhibit reduced responsiveness to antipsychotic medication. No studies directly examined the efficacy of psychotherapy in this population, though its potential value is widely acknowledged. Conclusions Despite consistent evidence linking childhood bullying to psychotic disorders, optimal treatment strategies remain unclear. Future research should prioritize evaluating potential mechanisms and targeted interventions to inform more effective, individualized treatment approaches.

PURPOSE OF REVIEW:Negative symptoms in schizophrenia remain an unmet treatment need. Recent guidelines and meta-analyses suggest that some pharmacological and psychosocial interventions show modest efficacy. Adding to this evidence, this review summarizes randomized clinical trials (RCTs) published between January 2024 and October 2025 on pharmacological, psychosocial, physical, digital, and neuromodulatory interventions targeting negative symptoms. RECENT FINDINGS:Most recent RCTs were small and methodologically heterogeneous, and effects on negative symptoms were generally modest. Exercise-based and body-oriented interventions, CBT-based interventions, psychosocial programmes, and digital tools were feasible and often associated with within-group improvement, but rarely superior to active controls or treatment as usual; only a larger yoga trial showed clear added benefit. Cognitive remediation did not directly reduce negative symptoms, but recent work indicates that negative symptoms moderate the translation of cognitive gains into functional improvement. Pharmacological trials yielded mixed results, with signals for muscarinic agonist-antagonist treatment, selected repurposed agents, and sulforaphane. Neuromodulation studies, particularly intermittent theta burst stimulation and transcutaneous auricular vagus nerve stimulation, suggested small to moderate improvements that depended on stimulation parameters and treatment duration. SUMMARY:Current evidence confirms that negative symptoms are modifiable and underscores the need for adequately powered, mechanism-informed, multimodal trials with long-term follow-up.

Preclinical evidence points to disturbances in neural networks in psychosis involving interrelations between dopaminergic-, GABAergic- and glutamatergic neurotransmitter systems. In support, we have previously shown that aberrant interrelations between these neurotransmitters, in contrast to individual transmitter systems, can separate antipsychotic-naïve first-episode psychotic patients (AN-FEP) from healthy controls (HC). Here, we characterized neurotransmitter interrelations, examined their association with treatment response, and explored the effect of treatment on the interrelations. Sixty participants (29 AN-FEP and 31 HC) underwent dynamic [18F]-DOPA PET with arterial blood sampling to measure dopamine synthesis (DS) (k3) in nucleus accumbens (NAcc) and magnetic resonance spectroscopy (MRS) to estimate levels of glutamate (Glu) in anterior cingulate cortex (ACC) and thalamus, and gamma-aminobutyric-acid (GABA) in ACC. A subgroup of the patients was re-scanned after six weeks antipsychotic monotherapy with aripiprazole (PET: 10 AN-FEP; MRS: 27 AN-FEP; 30 HC). Psychopathology was assessed at both visits. Multiple linear regression models and linear mixed models were used to analyze data. We found a negative association between k3 (dependent variable) and GABA in HC (β = −0.15, p = 0.03) and a positive association in patients (β = 0.15, p = 0.04). The aberrant relationship between k3 and GABA was driven by the group-GABA interaction (p = 0.002) and related to treatment response (p = 0.02). No significant group interactions were found for the interrelations between k3 and Glu, but a positive association was found between k3 and Glu in thalamus (p = 0.04) in both groups and the association decreased after treatment in AN-FEP (p = 0.01). The data show that DS in NAcc and GABA levels in ACC are inversely interrelated in AN-FEP, and that the degree of abnormality predicts treatment effect. Moreover, antipsychotic treatment alters the relationship between dopaminergic activity in NAcc and Glu levels in thalamus. The findings suggest that combined instead of single neurotransmitter disturbances should be considered when novel therapeutics are developed for schizophrenia. Clinical trial registration: The Pan European Collaboration on Antipsychotic Naïve Schizophrenia II (PECANSII) study, ClinicalTrials.gov Identifier: NCT02339844. https://www.clinicaltrials.gov/study/NCT02339844 .

This case report stresses the importance of exercising caution when translating the names of prescribed drugs, especially when treating patients from abroad. We describe a young female migrant from Ukraine seeking help in the Danish mental healthcare system due to worsening psychotic symptoms. The misinterpretation of the sound-alike drugs Azapin (clozapine) and asenapine caused an acute dystonic reaction. This case illustrates various pitfalls regarding medication error. First, it uncovers a medication error due to a sound-alike drug and emphasises the importance of paying attention to national guidelines since first-line treatment can differ between countries. These factors combined increase the risk of medication error with potentially fatal consequences.

BACKGROUND:While antipsychotic medication reduces the risk of relapse for patients with schizophrenia, high prevalence of adverse effects results in low adherence. Lower doses of antipsychotics have been associated with increased level of function but also with increased risk of relapse. This study presents findings from a specialized deprescribing clinic. In addition, we aim to identify clinical predictors for relapse. METHODS:Patients diagnosed with schizophrenia were referred to the clinic, which offers a six-month guided tapering program. Antipsychotic dose was reduced by 10% every four weeks. Patients were monitored closely for symptom progression or decrease in level of function, with defined cut-offs prompting a pause in or cessation of dose reduction. RESULTS:After 12 months, the antipsychotic dose was reduced from 404 (±320 mg) to 255 (±236 mg) chlorpromazine equivalent. Of the 88 patients included, 22 (27%) experienced relapse during the six-month tapering period, while 29 (37%) experienced relapse at the 12-month follow-up visit and nine patients were antipsychotic free. Patients who remained stable experienced a slightly increased level of functioning and markedly fewer side effects (p < 0.001). Following relapse, patients were clinically stabilized and showed an improved attitude toward antipsychotic medication. The predictive models were weak. CONCLUSIONS:We show that most patients undergoing guided antipsychotic tapering remained stable after one year and improved in level of function, while most patients who relapsed were quickly stabilized. Our inability to create strong predictive models could be due to limitations in the study design, warranting future studies exploring tapering of antipsychotics in patients with schizophrenia.

IntroductionIn this study we assessed the contribution of psychopathology, including the two domains of negative symptoms (motivational deficit and expressive deficit), processing speed as an index of neurocognition, and emotion recognition, as an index of social cognition, to poor functional outcomes in people with schizophrenia.MethodsThe Positive and Negative Syndrome Scale was used to evaluate positive symptoms and disorganization and the Brief Negative Symptom Scale to assess negative symptoms. The Symbol Coding and the Trail Making Test A and B were used to rate processing speed and the Facial Emotion Identification Test to assess emotion recognition. Functional outcome was assessed with the Personal and Social Performance Scale (PSP). Regression analyses were performed to identify predictors of functional outcome. Mediation analyses was used to investigate whether social cognition and negative symptom domains fully or partially mediated the impact of processing speed on functional outcome.ResultsOne hundred and fifty subjects from 8 different European centers were recruited. Our data showed that the expressive deficit predicted global functioning and together with motivational deficit fully mediated the effects of neurocognition on it. Motivational deficit was a predictor of personal and social functioning and fully mediated neurocognitive impairment effects on the same outcome. Both motivational deficit and neurocognitive impairment predicted socially useful activities, and the emotion recognition domain of social cognition partially mediated the impact of neurocognitive deficits on this outcome.ConclusionsOur results indicate that pathways to functional outcomes are specific for different domains of real-life functioning and that negative symptoms and social cognition mediate the impact of neurocognitive deficits on different domains of functioning. Our results suggest that both negative symptoms and social cognition should be targeted by psychosocial interventions to enhance the functional impact of neurocognitive remediation.

Objective: Over time, most patients with schizophrenia wish to reduce or discontinue their antipsychotic medication treatment. In Denmark, a specialized government-funded outpatient clinic was established to offer guided antipsychotic dose reduction. This study aimed to provide data on motivations for and previous experiences with antipsychotic tapering among patients attending the clinic. Methods: Patients completed an open-ended survey on their motivations for discontinuing or tapering antipsychotic medication and recorded their expectations about these outcomes. They also provided information on previous experiences with discontinuing medication and their level of symptoms, functioning, and side effects. Results: The survey was completed by 76 (86%) of 88 patients. The main motivations for discontinuing antipsychotics were adverse effects (71%) and uncertainty about the necessity of taking antipsychotics (29%). Other factors included concerns about long-term effects, disagreeing with the diagnosis, experiencing an insufficient effect, and feeling stigmatized by taking medication. Previous experience with discontinuation of antipsychotics was reported by 42 patients, of whom 23 reported relapse as the outcome. Most patients believed they could succeed in dose reduction (N=73 of 75, 97%) or discontinuation (N=62 of 75, 83%). Conclusions: Motivational factors reported for professionally guided antipsychotic dose reduction align with previous studies examining patients choosing to discontinue these medications. Despite reports of relapse during prior discontinuation attempts, most patients still reported motivation for and belief in successful dose reduction or discontinuation. An understanding of patients' motivations and beliefs is paramount to an optimal treatment alliance. Offering guided dose reduction may reduce sudden and unsupported discontinuation of antipsychotics.

Abstract Background 80% of patients value information on treatment options as an important part of recovery, further patients with a history of psychotic episodes feel excluded from decision making about their antipsychotic treatment, and on top of that, mental health staff is prone to be reluctant to support shared decision making and medication tapering for patients with schizophrenia. This case series aims to demonstrate the tapering of antipsychotic medication and how guided tapering affects the patient’s feeling of autonomy and psychiatric rehabilitation. Case presentation We present six patients diagnosed with schizophrenia (International Classification of Mental and Behavioral Disorders– 10th Edition codes F20.0–5, F20.7–9) who underwent professionally guided tapering in our clinic. The clinic aims to guide the patients to identify the lowest possible dose of antipsychotic medication in a safe setting to minimise the risk of severe relapse. Two patients completely discontinued their antipsychotic medication, two suffered a relapse during tapering, one chose to stop the tapering at a low dose, and one patient with treatment resistant schizophrenia, which is still tapering down. Conclusions Reducing the antipsychotic dose increased emotional awareness in some patients (n = 4) helping them to develop better strategies to handle stress and increased feelings of recovery. Patients felt a greater sense of autonomy and empowerment during the tapering process, even when discontinuation was not possible. Increased awareness in patients and early intervention during relapse may prevent severe relapse. Impact and implications Some patients with schizophrenia might be over medicated, leading to unwanted side effects and the wish to reduce their medication. The patients in our study illustrate how guided tapering of antipsychotic medication done jointly with the patient can lead to improved emotional awareness and the development of effective symptom management strategies. This may in turn lead to a greater sense of empowerment and identity and give life more meaning, supporting the experience of personal recovery.

Patients with schizophrenia exhibit structural and functional dysconnectivity but the relationship to the well-documented cognitive impairments is less clear. This study investigates associations between structural and functional connectivity and executive functions in antipsychotic-naïve patients experiencing schizophrenia. Sixty-four patients with schizophrenia and 95 matched controls underwent cognitive testing, diffusion weighted imaging and resting state functional magnetic resonance imaging. In the primary analyses, groupwise interactions between structural connectivity as measured by fixel-based analyses and executive functions were investigated using multivariate linear regression analyses. For significant structural connections, secondary analyses examined whether functional connectivity and associations with executive functions also differed for the two groups. In group comparisons, patients exhibited cognitive impairments across all executive functions compared to controls (p < 0.001), but no group difference were observed in the fixel-based measures. Primary analyses revealed a groupwise interaction between planning abilities and fixel-based measures in the left anterior thalamic radiation (p = 0.004), as well as interactions between cognitive flexibility and fixel-based measures in the isthmus of corpus callosum and cingulum (p = 0.049). Secondary analyses revealed increased functional connectivity between grey matter regions connected by the left anterior thalamic radiation (left thalamus with pars opercularis p = 0.018, and pars orbitalis p = 0.003) in patients compared to controls. Moreover, a groupwise interaction was observed between cognitive flexibility and functional connectivity between contralateral regions connected by the isthmus (precuneus p = 0.028, postcentral p = 0.012), all p-values corrected for multiple comparisons. We conclude that structural and functional connectivity appear to associate with executive functions differently in antipsychotic-naïve patients with schizophrenia compared to controls.

Long-acting injectable antipsychotics (LAI) is a frequently used treatment modality which has advantages over oral antipsychotics regarding hospitalization or relapse prevention. However, the pharmacokinetic properties of LAI greatly differ from oral antipsychotics. This necessitates an increased knowledge about LAI among clinicians, especially when commencing treatment, changing doses and discontinuing treatment. In this review, we summarize an array of clinically important characteristics of LAI and give a conceptual framework for understanding the pharmacokinetics of LAI.

Treatment-resistance in patients with schizophrenia is a major obstacle for improving outcome in patients, especially in those not gaining from clozapine. Novel research implies that glutamatergic and GABAergic abnormalities may be present in treatment-resistant patients, and preclinical research suggests that clozapine affects the GABAergic system. Moreover, clozapine may have a neuroprotective role.To investigate these issues, we conducted a systematic review to evaluate the relationship between clozapine and in vivo measures of gamma-aminobutyric acid (GABA), glutamate (glu), and N-acetylaspartate (NAA) brain levels in treatment- and ultra-treatment-resistant schizophrenia patients (TRS and UTRS).Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we included three longitudinal and six cross sectional studies utilizing proton magnetic resonance spectroscopy (H-MRS) that explored brain metabolite levels in clozapine-treated patients.Findings were limited by a small number of studies and definite conclusions cannot be drawn, but the present studies may imply that clozapine reduces glutamate levels in striatal but not cortical areas, whereas glutamatergic metabolites and GABA levels may be increased in ACC in the combined group of TRS and UTRS. Clozapine may also increase NAA in cortical areas. Importantly, this review highlights the need for further clinical studies investigating the effect of clozapine on brain levels of glutamate, GABA, and NAA as well as metabolite group differences in patients with UTRS compared with TRS.

BACKGROUND:Facial expressions are a core aspect of non-verbal communication. Reduced emotional expressiveness of the face is a common negative symptom of schizophrenia, however, quantifying negative symptoms can be clinically challenging and involves a considerable element of rater subjectivity. We used computer vision to investigate if (i) automated assessment of facial expressions captures negative as well as positive and general symptom domains, and (ii) if automated assessments are associated with treatment response in initially antipsychotic-naïve patients with first-episode psychosis. METHOD:We included 46 patients (mean age 25.4 (6.1); 65.2% males). Psychopathology was assessed at baseline and after 6 weeks of monotherapy with amisulpride using the Positive and Negative Syndrome Scale (PANSS). Baseline interview videos were recorded. Seventeen facial action units (AUs), that is, activation of muscles, from the Facial Action Coding System were extracted using OpenFace 2.0. A correlation matrix was calculated for each patient. Facial expressions were identified using spectral clustering at group-level. Associations between facial expressions and psychopathology were investigated using multiple linear regression. RESULTS:Three clusters of facial expressions were identified related to different locations of the face. Cluster 1 was associated with positive and general symptoms at baseline, Cluster 2 was associated with all symptom domains, showing the strongest association with the negative domain, and Cluster 3 was only associated with general symptoms. Cluster 1 was significantly associated with the clinically rated improvement in positive and general symptoms after treatment, and Cluster 2 was significantly associated with clinical improvement in all domains. CONCLUSION:Using automated computer vision of facial expressions during PANSS interviews did not only capture negative symptoms but also combinations of the three overall domains of psychopathology. Moreover, automated assessments of facial expressions at baseline were associated with initial antipsychotic treatment response. The findings underscore the clinical relevance of facial expressions and motivate further investigations of computer vision in clinical psychiatry.

Cognitive impairments are core features in individuals across the psychosis continuum and predict functional outcomes. Nevertheless, substantial variability in cognitive functioning within diagnostic groups, along with considerable overlap with healthy controls, hampers the translation of research findings into personalized treatment planning.Aligned with precision medicine, we employed a data driven machine learning method, self-organizing maps, to conduct transdiagnostic clustering based on cognitive functions in a sample comprising 228 healthy controls, 200 individuals at ultra-high risk for psychosis, and 98 antipsychotic-naïve patients with first-episode psychosis.The self-organizing maps revealed six clinically distinct cognitive profiles that significantly predicted baseline functional level and changes in functional level after one year. Cognitive flexibility in particular, as well as specific executive functions emerged as cardinal in differentiating the profiles. The application of self-organizing maps appears to be a promising approach to inform clinical decision-making based on individualized cognitive profiles, including patient allocation to different interventions. Moreover, this method has the potential to enable cross-diagnostic stratification in research trials, utilizing data-driven subgrouping informed by categories from underlying dimensions of cognition rather than from clinical diagnoses. Finally, the method enables cross-diagnostic profiling across other data modalities, such as brain networks or metabolic subtypes.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a protective layer in the BBB, and GLX shedding leads to BBB dysfunction. This study aimed to investigate whether a panel of 11 GLX molecules derived from peripheral blood could differentiate antipsychotic-naïve first-episode psychosis patients (n47) from healthy controls (HC, n49) and whether GLX shedding correlated with symptom severity. Blood samples were collected at baseline and serum was isolated for GLX marker detection. Machine learning models were applied to test whether patterns in GLX markers could classify patient groups. Associations between GLX markers and symptom severity were explored. Patients showed significantly increased levels of three GLX markers compared to HC. Based on the panel of 11 GLX markers, machine learning models achieved a significant mean classification accuracy of 81%. Post hoc analysis revealed associations between increased GLX markers and symptom severity. This study demonstrates the potential of GLX molecules as immuno-neuropsychiatric biomarkers for early diagnosis of psychosis, as well as indicate a compromised BBB. Further research is warranted to explore the role of GLX in the early detection of psychotic disorders.