Changes in immunoglobulin levels during clozapine treatment in schizophrenia.

BACKGROUND AND HYPOTHESIS: Use of clozapine in treatment-resistant schizophrenia is often limited due to risk of adverse effects. Cross-sectional associations between clozapine treatment and low immunoglobulin levels have been reported, however prospective studies are required to establish temporal relationships. We tested the hypothesis that reductions in immunoglobulin levels would occur over the first 6 months following initiation of clozapine treatment. Relationships between immunoglobulin levels and symptom severity over the course of clozapine treatment were also explored. DESIGN: This prospective observational study measured immunoglobulin (Ig) levels (A, M and G) in 56 patients with treatment-resistant schizophrenia at 6-, 12- and 24-weeks following initiation with clozapine. Clinical symptoms were also measured at 12 weeks using the positive and negative syndrome scale (PANSS). RESULTS: IgA, IgG and IgM all decreased during clozapine treatment. For IgA and IgG the reduction was significant at 24 weeks (IgA: ß = -32.66, 95% CI = -62.38, -2.93, p = 0.03; IgG: ß = -63.96, 95% CI = -118.00, -9.31, p = 0.02). For IgM the reduction was significant at 12 and 24 weeks (12 weeks: ß = -23.48, 95% CI = -39.56, -7.42, p = 0.004; 24 weeks: ß = -33.12, 95 %CI = -50.30, -15.94, p = <0.001). Reductions in IgA and IgG during clozapine treatment were correlated with reductions in PANSS-total over 12 weeks (n = 32, IgA r = 0.59, p = 0.005; IgG r = 0.48, p = 0.03). CONCLUSIONS: The observed reductions in immunoglobulin levels over six months of clozapine treatment add further evidence linking clozapine to secondary antibody deficiency. Associations between Ig reduction and symptom improvement may however indicate that immune mechanisms contribute to both desirable and undesirable effects of clozapine.

Demographic and clinical variables associated with response to clozapine in schizophrenia: a systematic review and meta-analysis.

Clozapine is the only licensed pharmacotherapy for treatment-resistant schizophrenia. However, response to clozapine is variable. Understanding the demographic and clinical features associated with response to clozapine may be useful for patient stratification for clinical trials or for identifying patients for earlier initiation of clozapine. We systematically reviewed the literature to investigate clinical and demographic factors associated with variation in clozapine response in treatment-resistant patients with schizophrenia spectrum disorders. Subsequently, we performed a random-effects meta-analysis to evaluate differences in duration of illness, age at clozapine initiation, age of illness onset, body weight and years of education between clozapine responders and non-responders. Thirty-one articles were eligible for qualitative review and 17 of these were quantitatively reviewed. Shorter duration of illness, later illness onset, younger age at clozapine initiation, fewer hospitalisations and fewer antipsychotic trials prior to clozapine initiation showed a trend to be significantly associated with a better response to clozapine. Meta-analysis of seven studies, totalling 313 subjects, found that clozapine responders had a significantly shorter duration of illness compared to clozapine non-responders [g = 0.31; 95% confidence interval (CI) 0.06-0.56; p = 0.01]. The results imply that a delay in clozapine treatment may result in a poorer response and that a focus on prompt treatment with clozapine is warranted.

Clozapine Response in Schizophrenia and Hematological Changes.

BACKGROUND: Clozapine is the only effective medication for treatment-resistant schizophrenia; however, its mechanism of action remains unclear. The present study explored whether its effectiveness is related to changes in hematological measures after clozapine initiation. METHODS: Patients with treatment-resistant schizophrenia commenced on clozapine between January 2007 and December 2014 by the United Kingdom's largest mental health trust were identified from electronic patient records. Hematological data from these patients were obtained from a monitoring registry. White blood cell, neutrophil, and platelet count were assessed at baseline and during the early phase of clozapine treatment. Clozapine response at 3 months was defined as "much," or "very much" improved on the seven-point Clinical Global Impression-Improvement (CGI-I) subscale. RESULTS: In the total sample (n = 188), clozapine initiation was associated with a significant transient increase (peaking in weeks 3 to 4) in white blood cell, neutrophil, and platelet count (P < 0.001). There were 112 (59.6%) patients that responded to treatment; however, none of the hematological factors assessed at baseline, nor changes in these factors, were directly associated with treatment response. IMPLICATIONS: Clozapine treatment is associated with transient hematological changes during the first month of treatment; however, there was no evidence that these were related to the therapeutic response.

Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

BACKGROUND AND AIMS: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity and mortality, yet treatment retention, crucial for the effectiveness of medications like buprenorphine-naloxone, remains unpredictable. Our objective was to determine the predictability of 6-month retention in buprenorphine-naloxone treatment using electronic health record (EHR) data from diverse clinical settings and to identify key predictors. DESIGN: This retrospective observational study developed and validated machine learning-based clinical risk prediction models using EHR data. SETTING AND CASES: Data were sourced from Stanford University's healthcare system and Holmusk's NeuroBlu database, reflecting a wide range of healthcare settings. The study analyzed 1800 Stanford and 7957 NeuroBlu treatment encounters from 2008 to 2023 and from 2003 to 2023, respectively. MEASUREMENTS: Predict continuous prescription of buprenorphine-naloxone for at least 6 months, without a gap of more than 30 days. The performance of machine learning prediction models was assessed by area under receiver operating characteristic (ROC-AUC) analysis as well as precision, recall and calibration. To further validate our approach's clinical applicability, we conducted two secondary analyses: a time-to-event analysis on a single site to estimate the duration of buprenorphine-naloxone treatment continuity evaluated by the C-index and a comparative evaluation against predictions made by three human clinical experts. FINDINGS: Attrition rates at 6 months were 58% (NeuroBlu) and 61% (Stanford). Prediction models trained and internally validated on NeuroBlu data achieved ROC-AUCs up to 75.8 (95% confidence interval [CI] = 73.6-78.0). Addiction medicine specialists' predictions show a ROC-AUC of 67.8 (95% CI = 50.4-85.2). Time-to-event analysis on Stanford data indicated a median treatment retention time of 65 days, with random survival forest model achieving an average C-index of 65.9. The top predictor of treatment retention identified included the diagnosis of opioid dependence. CONCLUSIONS: US patients with opioid use disorder or opioid dependence treated with buprenorphine-naloxone prescriptions appear to have a high (∼60%) treatment attrition by 6 months. Machine learning models trained on diverse electronic health record datasets appear to be able to predict treatment continuity with accuracy comparable to that of clinical experts.

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Early trajectory of clinical global impression as a transdiagnostic predictor of psychiatric hospitalisation: a retrospective cohort study.

BACKGROUND: Identifying patients most at risk of psychiatric hospitalisation is crucial to improving service provision and patient outcomes. Existing predictors focus on specific clinical scenarios and are not validated with real-world data, limiting their translational potential. This study aimed to determine whether early trajectories of Clinical Global Impression Severity are predictors of 6 month risk of hospitalisation. METHODS: This retrospective cohort study used data from the NeuroBlu database, an electronic health records network from 25 US mental health-care providers. Patients with an ICD-9 or ICD-10 code of major depressive disorder, bipolar disorder, generalised anxiety disorder, post-traumatic stress disorder, schizophrenia or schizoaffective disorder, ADHD, or personality disorder were included. Using this cohort, we assessed whether clinical severity and instability (operationalised using Clinical Global Impression Severity measurements) during a 2-month period were predictors of psychiatric hospitalisation within the next 6 months. FINDINGS: 36 914 patients were included (mean age 29·7 years [SD 17·5]; 21 156 [57·3%] female, 15 748 [42·7%] male; 20 559 [55·7%] White, 4842 [13·1%] Black or African American, 286 [0·8%] Native Hawaiian or other Pacific Islander, 300 [0·8%] Asian, 139 [0·4%] American Indian or Alaska Native, 524 (1·4%) other or mixed race, and 10 264 [27·8%] of unknown race). Clinical severity and instability were independent predictors of risk of hospitalisation (adjusted hazard ratio [HR] 1·09, 95% CI 1·07-1·10 for every SD increase in instability; 1·11, 1·09-1·12 for every SD increase in severity; p<0·0001 for both). These associations were consistent across all diagnoses, age groups, and in both males and females, as well as in several robustness analyses, including when clinical severity and clinical instability were based on the Patient Health Questionnaire-9 rather than Clinical Global Impression Severity measurements. Patients in the top half of the cohort for both clinical severity and instability were at an increased risk of hospitalisation compared with those in the bottom half along both dimensions (HR 1·45, 95% CI 1·39-1·52; p<0·0001). INTERPRETATION: Clinical instability and severity are independent predictors of future risk of hospitalisation, across diagnoses, age groups, and in both males and females. These findings could help clinicians make prognoses and screen patients who are most likely to benefit from intensive interventions, as well as help health-care providers plan service provisions by adding additional detail to risk prediction tools that incorporate other risk factors. FUNDING: National Institute for Health and Care Research, National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Medical Research Council, Academy of Medical Sciences, and Holmusk.

Treatment resistance NMDA receptor pathway polygenic score is associated with brain glutamate in schizophrenia.

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy (1H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (ß = -0.25, 95 % CI = -0.49, -0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (ß = 0.05, 95 % CI = -0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia.

Anterior cingulate glutamate metabolites as a predictor of antipsychotic response in first episode psychosis: data from the STRATA collaboration.

Elevated brain glutamate has been implicated in non-response to antipsychotic medication in schizophrenia. Biomarkers that can accurately predict antipsychotic non-response from the first episode of psychosis (FEP) could allow stratification of patients; for example, patients predicted not to respond to standard antipsychotics could be fast-tracked to clozapine. Using proton magnetic resonance spectroscopy (1H-MRS), we examined the ability of glutamate and Glx (glutamate plus glutamine) in the anterior cingulate cortex (ACC) and caudate to predict response to antipsychotic treatment. A total of 89 minimally medicated patients with FEP not meeting symptomatic criteria for remission were recruited across two study sites. 1H-MRS and clinical data were acquired at baseline, 2 and 6 weeks. Response was defined as >20% reduction in Positive and Negative Syndrome Scale (PANSS) Total score from baseline to 6 weeks. In the ACC, baseline glutamate and Glx were higher in Non-Responders and significantly predicted response (P < 0.02; n = 42). Overall accuracy was greatest for ACC Glx (69%) and increased to 75% when symptom severity at baseline was included in the model. Glutamate metabolites in the caudate were not associated with response, and there was no significant change in glutamate metabolites over time in either region. These results add to the evidence linking elevations in ACC glutamate metabolites to a poor antipsychotic response. They indicate that glutamate may have utility in predicting response during early treatment of first episode psychosis. Improvements in accuracy may be made by combining glutamate measures with other response biomarkers.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

A polygenic score indexing a DRD2-related co-expression network is associated with striatal dopamine function.

The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors. We aimed to investigate the relationship between the DRD2 gene network and in vivo striatal dopaminergic function, which is a phenotype robustly associated with psychosis and schizophrenia. To this aim, a sample of 92 healthy subjects underwent 18F-DOPA PET and was genotyped for genetic variations indexing the co-expression of the DRD2-related genetic network in order to calculate the PCI for each subject. The PCI was significantly associated with whole striatal dopamine synthesis capacity (p = 0.038). Exploratory analyses on the striatal subdivisions revealed a numerically larger effect size of the PCI on dopamine function for the associative striatum, although this was not significantly different than effects in other sub-divisions. These results are in line with a possible relationship between the DRD2-related co-expression network and schizophrenia and extend it by identifying a potential mechanism involving the regulation of dopamine synthesis. Future studies are needed to clarify the molecular mechanisms implicated in this relationship.

Cognitive function and treatment response trajectories in first-episode schizophrenia: evidence from a prospective cohort study.

OBJECTIVES: This prospective cohort study tested for associations between baseline cognitive performance in individuals early within their first episode and antipsychotic treatment of psychosis. We hypothesised that poorer cognitive functioning at the initial assessment would be associated with poorer antipsychotic response following the subsequent 6 weeks. DESIGN: Prospective cohort . SETTING: National Health Service users with a first-episode schizophrenia diagnosis, recently starting antipsychotic medication, recruited from two UK sites (King's College London, UK and University of Manchester, UK). Participants attended three study visits following screening. PARTICIPANTS: Eighty-nine participants were recruited, with 46 included in the main analysis. Participants required to be within the first 2 years of illness onset, had received minimal antipsychotic treatment, have the capacity to provide consent, and be able to read and write in English. Participants were excluded if they met remission criteria or showed mild to no symptoms. PRIMARY AND SECONDARY OUTCOME MEASURES: Antipsychotic response was determined at 6 weeks using the Positive and Negative Syndrome Scale (PANSS), with cognitive performance assessed at each visit using the Brief Assessment of Cognition in Schizophrenia (BACS). The groups identified (responders and non-responders) from trajectory analyses, as well as from >20% PANSS criteria, were compared on baseline BACS performance. RESULTS: Trajectory analyses identified 84.78% of the sample as treatment responsive, and the remaining 15.22% as treatment non-responsive. Unadjusted and adjusted logistic regressions observed no significant relationship between baseline BACS on subscale and total performance (BACS t-score: OR=0.98, p=0.620, Cohen's d=0.218) and antipsychotic response at 6 weeks. CONCLUSIONS: This investigation identified two clear trajectories of treatment response in the first 6 weeks of antipsychotic treatment. Responder and non-responder groups did not significantly differ on performance on the BACS, suggesting that larger samples may be required or that an association between cognitive performance and antipsychotic response is not observable in the first 2 years of illness onset. TRIAL REGISTRATION NUMBER: REC: 17/NI/0209.

Impaired verbal memory function is related to anterior cingulate glutamate levels in schizophrenia: findings from the STRATA study.

Impaired cognition is associated with lower quality of life and poor outcomes in schizophrenia. Brain glutamate may contribute to both clinical outcomes and cognition, but these relationships are not well-understood. We studied a multicentre cohort of 85 participants with non-affective psychosis using proton magnetic resonance spectroscopy. Glutamate neurometabolites were measured in the anterior cingulate cortex (ACC). Cognition was assessed using the Brief Assessment for Cognition in Schizophrenia (BACS). Patients were categorised as antipsychotic responders or non-responders based on treatment history and current symptom severity. Inverted U-shaped associations between glutamate or Glx (glutamate + glutamine) with BACS subscale and total scores were examined with regression analyses. We then tested for an interaction effect of the antipsychotic response group on the relationship between glutamate and cognition. ACC glutamate and Glx had a positive linear association with verbal memory after adjusting for age, sex and chlorpromazine equivalent dose (glutamate, ß = 3.73, 95% CI = 1.26-6.20, P = 0.004; Glx, ß = 3.38, 95% CI = 0.84-5.91, P = 0.01). This association did not differ between good and poor antipsychotic response groups. ACC glutamate was also positively associated with total BACS score (ß = 3.12, 95% CI = 0.01-6.23, P = 0.046), but this was not significant after controlling for antipsychotic dose. Lower glutamatergic metabolites in the ACC were associated with worse verbal memory, and this relationship was independent of antipsychotic response. Further research on relationships between glutamate and cognition in antipsychotic responsive and non-responsive illness could aid the stratification of patient groups for targeted treatment interventions.

Dopamine and Glutamate in Antipsychotic-Responsive Compared With Antipsychotic-Nonresponsive Psychosis: A Multicenter Positron Emission Tomography and Magnetic Resonance Spectroscopy Study (STRATA).

The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min-1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity.