Biological Predictors of Clozapine Response: A Systematic Review

Blood Cell Count Ratios at Baseline are Associated with Initial Clinical Response to Clozapine in Treatment-Resistant, Clozapine-Naïve, Schizophrenia-Spectrum Disorder

BACKGROUND

Clozapine is the recommended treatment for managing treatment-resistant schizophrenia (TRS), and immunological mechanisms may be involved in its unique antipsychotic efficacy. This study investigated whether baseline immune abnormalities measured with blood cell count ratios can predict the clinical response after initiating treatment with clozapine in patients with clozapine naïve TRS.

METHODS

A longitudinal design was developed, involving 32 patients diagnosed with treatment-resistant, clozapine-naïve schizophrenia-spectrum disorder. Patients were evaluated at baseline before clozapine starting and 8 weeks of follow-up. Psychopathological status and immune abnormalities (blood cell count ratios: neutrophil-lymphocyte ratio [NLR], monocyte-lymphocyte ratio [MLR], platelet-lymphocyte ratio [PLR] and basophil-lymphocyte ratio [BLR]) were evaluated in each visit.

RESULTS

Baseline NLR (b=- 0.364; p=0.041) and MLR (b =- 0.400; p=0.023) predicted the change in positive symptoms over the 8-week period. Patients who exhibited a clinical response showed higher baseline NLR (2.38±0.96 vs. 1.75±0.83; p=0.040) and MLR (0.21±0.06 vs. 0.17±0.02; p=0.044) compared to non-responders. In the ROC analysis, the threshold points to distinguish between responders and non-responders were approximately 1.62 for NLR and 0.144 for MLR, yielding AUC values of 0.714 and 0.712, respectively. No statistically significant differences were observed in the blood cell count ratios from baseline to the 8-week follow-up.

CONCLUSION

Our study emphasizes the potential clinical significance of baseline NLR and MLR levels as predictors of initial clozapine treatment response in patients with TRS. Future studies with larger sample sizes and longer follow-up periods should replicate our findings.

Higher orexin-A levels are associated with treatment response to clozapine in patients with schizophrenia: A cross-sectional study

BACKGROUND

Clozapine is the primary antipsychotic (APD) for treatment-resistant schizophrenia (TRS). However, only 40% of patients with TRS respond to clozapine, constituting a subgroup of clozapine-resistant patients. Recently, the neuropeptide orexin-A was shown to be involved in the pathophysiology of schizophrenia. This study evaluated the association of orexin-A levels with the clozapine response in patients with TRS.

METHODS

We recruited 199 patients with schizophrenia, including 37 APD-free and 162 clozapine-treated patients. Clozapine-treated patients were divided into clozapine-responsive (n = 100) and clozapine-resistant (n = 62) groups based on whether they had achieved psychotic remission defined by the 18-item Brief Psychiatric Rating Scale (BPRS-18). We compared blood orexin-A levels among the three groups and performed regression analysis to determine the association of orexin-A level with treatment response in clozapine-treated patients. We also explored the correlation between orexin-A levels and cognitive function, assessed using the CogState Schizophrenia Battery.

RESULTS

Clozapine-responsive patients had higher orexin-A levels than clozapine-resistant and APD-free patients. Orexin-A level was the only factor significantly associated with treatment response after adjustment. Orexin-A levels were negatively correlated with BPRS-18 full scale and positive, negative, and general symptoms subscale scores. We also observed a positive correlation between orexin-A levels and verbal memory, visual learning and memory, and working memory function.

CONCLUSIONS

This cross-sectional study showed that higher levels of orexin-A are associated with treatment response to clozapine in patients with TRS. Future prospective studies examining changes in orexin-A level following clozapine treatment and the potential benefit of augmenting orexin-A signaling are warranted.

Evidence for Therapeutic Drug Monitoring of Atypical Antipsychotics

Second-generation antipsychotics (SGAs), also known as atypical antipsychotics, are a newer class of antipsychotic drugs used to treat schizophrenia, bipolar disorder, and related psychiatric conditions. The plasma concentration of antipsychotic drugs is a valid measure of the drug at its primary target structure in the brain, and therefore determines the efficacy and safety of these drugs. However, despite the well-known high variability in pharmacokinetics of these substances, psychiatric medication is usually administered in uniform dosage schedules. Therapeutic drug monitoring (TDM), as the specific method that can help personalised medicine in dose adjustment according to the characteristics of the individual patient, minimizing the risk of toxicity, monitoring adherence, and increasing cost-effectiveness in the treatment, thus seems to be an elegant tool to solve this problem. Non-response to therapeutic doses, uncertain adherence to medication, suboptimal tolerability, or pharmacokinetic drug-drug interactions are typical indications for TDM of SGAs. This review aims to summarize an overview of the current knowledge and evidence of the possibilities to tailor the dosage of selected SGAs using TDM, including the necessary pharmacokinetic parameters for personalised pharmacotherapy.

A systematic review of neuroimaging studies of clozapine-resistant schizophrenia

This systematic review aimed to review neuroimaging studies comparing clozapine-resistant schizophrenia patients with clozapine-responding patients, and with first-line antipsychotic responding (FLR) patients. A total of 19 studies including 6 longitudinal studies were identified. Imaging techniques comprised computerized tomography (CT, n = 3), structural magnetic resonance imaging (MRI, n = 7), magnetic resonance spectroscopy (MRS, n = 5), functional MRI (n = 1), single-photon emission computerized tomography (SPECT, n = 3) and diffusion tensor imaging (DTI, n = 1). The most consistent finding was hypo-frontality in the clozapine-resistant group compared with the clozapine-responding group with possible differences in frontal-striatal-basal ganglia circuitry as well as the GABA level between the two treatment-resistant groups. Additional statistically significant findings were reported when comparing clozapine-resistant patients with the FLR group, including lower cortical thickness and brain volume of multiple brain regions as well as lower Glx/Cr level in the dorsolateral prefrontal cortex. Both treatment-resistant groups were found to have extensive differences in neurobiological features in comparison with the FLR group. Overall results suggested treatment-resistant schizophrenia is likely to be a neurobiological distinct type of the illness. Clozapine-resistant and clozapine-responding schizophrenia are likely to have both shared and distinct neurobiological features. However, conclusions from existing studies are limited, and future multi-center collaborative studies are required with a consensus clinical definition of patient samples, multimodal imaging tools, and longitudinal study designs.

Developing prediction models for symptom severity around the time of discharge from a tertiary-care program for treatment-resistant psychosis

Antipsychotics are the only therapeutic class indicated in the symptomatic management of psychotic disorders. However, individuals diagnosed with schizophrenia or schizoaffective disorder may not always benefit from these first-line agents. This refractoriness to conventional treatment can be difficult to address in most clinical settings. Therefore, a referral to a tertiary-care program that is better able to deliver specialized care in excess of the needs of most individuals may be necessary. The average outcome following a period of treatment at these programs tends to be one of improvement. Nonetheless, accurate prognostication of individual-level responses may be useful in identifying those who are unlikely to improve despite receiving specialized care. Thus, the main objective of this study was to predict symptom severity around the time of discharge from the Refractory Psychosis Program in British Columbia, Canada using only clinicodemographic information and prescription drug data available at the time of admission. To this end, a different boosted beta regression model was trained to predict the total score on each of the five factors of the Positive and Negative Syndrome Scale (PANSS) using a data set composed of 320 hospital admissions. Internal validation of these prediction models was then accomplished by nested cross-validation. Insofar as it is possible to make comparisons of model performance across different outcomes, the correlation between predictions and observations tended to be higher for the negative and disorganized factors than the positive, excited, and depressed factors on internal validation. Past scores had the greatest effect on the prediction of future scores across all 5 factors. The results of this study serve as a proof of concept for the prediction of symptom severity using this specific approach.

Clozapine research from India: A systematic review

BACKGROUND

Although clozapine is much researched in western literature, a review on Indian research on clozapine published in 2010 reported limited data and need for further research in this area.

AIM

We aimed to conduct a systematic review of research on clozapine from India from 2010 to mid-2022 and also compare the same with research output before 2010.

METHODOLOGY

A systematic various search engines, i.e., PUBMED, Medknow, Hinari and Google Scholar was done using the key words clozapine and India. Published articles with clozapine in the title and having an author from India, published during 2010 to July 2022 were included.

RESULTS

Initial Internet and hand searches yielded 280 articles, out of which 126 articles were excluded due to various reasons and 154 articles, were included for the review. This included 84 case reports, 49 original articles, 11 review articles and 10 letters to the editor as comments. We found an increase in the number of publications during the period of 2010-2022 compared to 1997-2009 in all types of publications. Over the years a significant proportion of the articles focused on various side effects of clozapine, factors associated with response and non-response to clozapine and evaluation of outcomes other than efficacy/effectiveness. However, all the studies were limited to a single centre with no multicentric studies on clozapine.

CONCLUSION

Over the last 12 years or so, there is increase in the number of publications on clozapine. However, there is lack of multicentric studies.

Peripheral biomarkers of treatment-resistant schizophrenia: Genetic, inflammation and stress perspectives

Treatment-resistant schizophrenia (TRS) often results in severe disability and functional impairment. Currently, the diagnosis of TRS is largely exclusionary and emphasizes the improvement of symptoms that may not be detected early and treated according to TRS guideline. As the gold standard, clozapine is the most prescribed selection for TRS. Therefore, how to predict TRS in advance is critical for forming subsequent treatment strategy especially clozapine is used during the early stage of TRS. Although mounting studies have identified certain clinical factors and neuroimaging characteristics associated with treatment response in schizophrenia, the predictors for TRS remain to be explored. Biomarkers, particularly for peripheral biomarkers, show great potential in predicting TRS in view of their predictive validity, noninvasiveness, ease of testing and low cost that would enable their widespread use. Recent evidence supports that the pathogenesis of TRS may be involved in abnormal neurotransmitter systems, inflammation and stress. Due to the heterogeneity of TRS and the lack of consensus in diagnostic criteria, it is difficult to compare extensive results among different studies. Based on the reported neurobiological mechanisms that may be associated with TRS, this paper narratively reviews the updates of peripheral biomarkers of TRS, from genetic and other related perspectives. Although current evidence regarding biomarkers in TRS remains fragmentary, when taken together, it can help to better understand the neurobiological interface of clinical phenotypes and psychiatric symptoms, which will enable individualized prediction and therapy for TRS in the long run.

Genetic determinants associated with response to clozapine in schizophrenia: an umbrella review

OBJECTIVE

Clozapine response varies widely from person to person, which may be due to inter-individual genetic variability. This umbrella review aims to summarize the current evidence on associations between pharmacodynamic genes and response to clozapine treatment.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology, a systematic literature search was conducted in the PubMed and EMBASE databases from inception to November 2021 to identify systematic reviews and meta-analyses of studies that examined genetic determinants of clozapine response. The quality of the reviews was assessed with the AMSTAR-2 tool.

RESULTS

From a total of 128 records, 10 studies representing nine systematic reviews and one meta-analysis met our inclusion criteria. The overall quality of the included studies was poor. All systematic reviews concluded that the results of primary studies were largely negative or conflicting. Most evidence was found for an association with clozapine response and rs6313 and rs6314 within HTR2A and rs1062613 within HTR3A in the serotonergic system.

CONCLUSIONS

Conclusive evidence for associations between genetic variants and clozapine response is still lacking. Hypothesis-generating genetic studies in large, well-characterized study populations are urgently needed to obtain more consistent and clinically informative results. Future studies may also include multi-omics approaches to identify novel genetic determinants associated with clozapine response.

Naturalistic study on the use of clozapine in the early phases of non-affective psychosis: A 10-year follow-up study in the PAFIP-10 cohort

Clozapine is seldom prescribed in treatment-resistant schizophrenia (TRS) patients during early phases of the illness. We aimed to examine the pathway and patterns and the impact of clozapine use in patients with TRS who were followed up for 10 years after the first outbreak of the illness. Data were obtained retrospectively from an epidemiological cohort of first episode schizophrenia patients (n = 218) who had been treated in a specialized intervention program (PAFIP). Out of 218, 35 (16%) individuals were on clozapine at 10-year assessment, while 183 (84%) were taking other antipsychotics. Among those 183 psychosis subjects who were not on clozapine, 13 (7.1%) met criteria for TRS. In the clozapine group, ten (28.6%) met criteria for early-TR and twenty-five (71.4%) met criteria for late-TR. Before clozapine treatment was initiated, the median number of days under other antipsychotic treatment was 1551 days (IQR = 1715) and the median time that subjects remained on clozapine was 6.3 years (IC95%: 5.49-7.20). At 10 years, we found that those individuals taking clozapine had higher CGI total scores (F = 12.0, p = 0.001) and SANS total scores (F = 9.27, p = 0.003) than subjects taking other antipsychotics after correcting for baseline values. Interestingly, when performing these analyses at 10 years between subjects taking clozapine (n = 35) and subjects who despite meeting TRS criteria were not taking clozapine (n = 13), we found that subjects taking clozapine had significantly lower total scores on all clinical scales compared with subjects who met TRS criteria and were not taking clozapine (p values < 0.05). TRS patients who took the longest time to start clozapine (third tertile) showed significantly higher CGI scores at 10-year follow-up compared to those who initiated clozapine earlier (first tertile) (t = 2.60; p = 0.043). Our findings reinforce the need of a timely assessment of treatment-resistant criteria in early schizophrenia patients and highlight the long-term benefits of an early introduction of clozapine on those patients meeting treatment-resistant criteria.

Factors Associated With Poor Response to Clozapine in Schizophrenia: A Study From Northern India

PURPOSE/BACKGROUND

Limited numbers of studies have assessed the predictors of clozapine nonresponse. This study aimed to assess the demographic and clinical factors associated with an inadequate response to clozapine in patients with treatment-resistant schizophrenia (TRS).

METHODS/PROCEDURES

Two hundred eighty-seven outpatients with TRS receiving clozapine for more than 1 year were divided into 2 groups based on the need for a second antipsychotic medication and/or electroconvulsive therapy after receiving clozapine in the maximum tolerable dose for at least 3 months.

RESULTS/FINDINGS

One hundred two patients (35.4%) were considered to be clozapine nonresponders. Compared with responders, clozapine nonresponders were more often unemployed at the time of starting clozapine (P = 0.04), had a longer duration of untreated psychosis (P = 0.007), had received significantly higher number of adequate antipsychotic trials in the past (P = 0.02), had received antipsychotic polypharmacy in the past (P = 0.01), had experienced adverse effects with first- (P < 0.001) and second-generation antipsychotics (P = 0.01), and had more medical comorbidities (P = 0.03). The nonresponders more frequently had visual hallucinations (P = 0.001), and feelings/acts or impulses attributed to some external source (P = 0.03) in the lifetime, and had a significantly higher Clinical Global Impression severity score at the time of starting of clozapine (P < 0.001). While on clozapine, nonresponders received significantly higher dose of clozapine (P = 0.001) and higher proportion of them experienced constipation (P = 0.04), hypersalivation (P = 0.002), and obsessive-compulsive symptoms (P = 0.05) as adverse effects of clozapine.

CONCLUSIONS/IMPLICATIONS

The present study shows that approximately one-third of patients with TRS do not respond to clozapine. However, clozapine nonresponders, although broadly similar in sociodemographic profile to clozapine responders, differ from clozapine responders on past treatment profile.

Time-Dissociated Pharmacokinetic Pharmacodynamic Model of Cyclosporine Among Malaysian Renal Transplant Recipients

BACKGROUND

Cyclosporine is an essential component of many immunosuppressive regimens. However, its pharmacokinetic and pharmacodynamic (PKPD) modeling has not been widely investigated. This study aims to develop a time-dissociated PKPD model of cyclosporine in renal transplant patients.

METHODS

Medical records of renal transplant patients at Penang General Hospital were retrospectively analyzed. A time-dissociated PKPD model with covariate effects was developed using NONMEM to evaluate renal graft function response, quantified as estimated glomerular filtration rate (eGFR), toward the cyclosporine cumulative exposure (area under the concentration-time curve). The final model was integrated into a tool to predict the potential outcome. Individual eGFR predictions were evaluated based on the clinical response recorded as acute rejection/nephrotoxicity events.

RESULTS

A total of 1256 eGFR readings with 2473 drug concentrations were obtained from 107 renal transplant patients receiving cyclosporine. An Emax drug effect with a linear drug toxicity model best described the data. The baseline renal graft level (E0), maximum effect (Emax), area under the concentration-time curve achieving 50% of the maximum effect, and nephrotoxicity slope were estimated as 12.9 mL·min-1·1.73 m-2, 50.7 mL·min-1·1.73 m-2, 1740 ng·h·mL-1, and 0.00033, respectively. The hemoglobin level was identified as a significant covariate affecting the E0. The model discerned acute rejection from nephrotoxicity in 19/24 cases.

CONCLUSIONS

A time-dissociated PKPD model successfully described a large number of observations and was used to develop an online tool to predict renal graft response. This may help discern early rejection from nephrotoxicity, especially for patients unwilling to undergo a biopsy or those waiting for biopsy results.

Investigating structural subdivisions of the anterior cingulate cortex in schizophrenia, with implications for treatment resistance and glutamatergic levels

BACKGROUND

Abnormalities in the anterior cingulate cortex (ACC) are thought to play an important role in the pathophysiology of schizophrenia. Given regional variations in ACC structure, the present study aimed to examine ACC structural subdivisions and their relationships to treatment resistance and glutamatergic levels in schizophrenia.

METHODS

This study included 100 patients with schizophrenia and 52 healthy controls from 2 cohorts. We applied non-negative matrix factorization to identify accurate and stable spatial components of ACC structure. Between groups, we compared ACC structural indices in each spatial component based on treatment resistance or response and tested relationships with ACC glutamate + glutamine levels.

RESULTS

We detected reductions in cortical thickness and increases in mean diffusivity in the spatial components on the surface of the cingulate sulcus, especially in patients with treatment-resistant and clozapine-resistant schizophrenia. Notably, mean diffusivity in these components was higher in patients who did not respond to clozapine compared to those who did. Furthermore, these ACC structural alterations were related to elevated ACC glutamate + glutamine levels but not related to symptomatology or antipsychotic dose.

LIMITATIONS

Sample sizes, cross-sectional findings and mixed antipsychotic status were limitations of this study.

CONCLUSION

This study identified reproducible abnormalities in ACC structures in patients with treatment-resistant and clozapine-resistant schizophrenia. Given that these spatial components play a role in inhibitory control, the present study strengthens the notion that glutamate-related disinhibition is a common biological feature of treatment resistance in schizophrenia.

Clozapine augmentation with cariprazine for negative symptoms: a case series and literature review

Only about 50% of patients with treatment-resistant schizophrenia respond to clozapine, and many more patients continue to experience ongoing and prominent negative symptoms. These negative symptoms, for which there are limited pharmacological options, may represent the greatest barrier to functional recovery. Cariprazine is a novel antipsychotic drug that is a partial agonist at dopamine D₂ and D₃ receptors with preferential binding to the D₃ receptor, antagonism of 5HT_2B receptors, and partial agonism at 5HT_1A receptors. Cariprazine is currently licenced for the treatment of schizophrenia in Europe and the United States and has also been approved for bipolar disorder in the United States. There is a limited body of evidence to suggest clinical effectiveness as an augmentation strategy for negative symptoms in those treated with clozapine. In this case series, we present five cases of successful treatment of negative symptoms by clozapine combined with cariprazine in treatment-resistant psychosis.

Predictors of clozapine discontinuation at 2 years in treatment-resistant schizophrenia

INTRODUCTION

Little is known about predictors of clinical response to clozapine treatment in treatment-resistant psychosis. Most published cohorts are small, providing inconsistent results. We aimed to identify baseline clinical predictors of future clinical response in patients who initiate clozapine treatment, mainly focusing on the effect of age, duration of illness, baseline clinical symptoms and homelessness.

METHODOLOGY

Retrospective cohort of patients with treatment-resistant schizophrenia, aged between 15 and 60 years, that initiated clozapine between 2014 and 2017. Sociodemographic characteristics, years from illness diagnosis, and clinical presentation before the initiation of clozapine were collected and analyzed. All-cause discontinuation at two years follow-up was used as the primary measure of clozapine response.

RESULTS

261 patients were included with a median age at illness diagnosis of 23 years old (IQR 19-29) and a median age at clozapine initiation of 25 (IQR: 21-33). 72.33% (183/253) continued clozapine after two years follow-up. Being homeless was associated to higher clozapine non-adherence, with an OR of 2.78 (95%CI 1.051-7.38) (p = 0.039, controlled by gender). Older age at clozapine initiation and longer delay from first schizophrenia diagnosis to clozapine initiation were also associated with higher clozapine non-adherence, with each year increasing the odds of discontinuation by 1.043 (95%CI 1.02-1.07; p = 0.001) and OR 1.092 (95%CI 1.01-1.18;p = 0.032) respectively.

CONCLUSION

Starting clozapine in younger patients or shortly after schizophrenia diagnosis were associated with better adherence.

A New Look on an Old Issue: Comprehensive Review of Neurotransmitter Studies in Cerebrospinal Fluid of Patients with Schizophrenia and Antipsychotic Effect on Monoamine's Metabolism

Neurotransmitters metabolism has a key role in the physiopathology of schizophrenia as demonstrated by studies measuring monoamine metabolites in patient’s cerebrospinal fluid (CSF) since the beginning of the antipsychotic use. This comprehensive review aims to understand the anomalies of CSF monoamines in schizophrenia and their correlation with clinical and paraclinical features. We also review the influence of antipsychotic treatment on CSF monoamines and discuss the connection with metabolic and inflammatory processes. Studies comparing CSF homovanillic acid (HVA) levels between patients and controls are miscellaneous, due to the heterogeneity of samples studies. However, low HVA is associated with more positive symptoms and a poorer outcome and negatively correlated with brain ventricle size. Based on humans and animals’ studies, antipsychotic treatments increase HVA during the first week of administration and decrease progressively over the time with a fall-off after withdrawal. 5‐hydroxyindolacetic acetic acid levels do not seem to be different in the patient’s CSF compared to controls. Considering metabolic co-factors of neurotrans-mitters synthesis, there is evidence supporting an increase of kynurenic acid in the CSF of patients with schizophrenia. Few studies explore folate metabolism in CSF. Literature also emphasizes the relationship between folate metabolism, inflammation and monoamine’s metabolism. Those results suggest that the CSF monoamines could be correlated with schizophrenia symptoms and treatment outcome. However, further studies, exploring the role of CSF monoamines as biomarkers of disease severity and response to treatment are needed. They should assess the antipsychotic prescription, inflammatory markers and folate metabolism as potential confounding factors.

Clozapine resistant schizophrenia: Newer avenues of management

About 40%-70% of the patients with treatment-resistant schizophrenia have a poor response to adequate treatment with clozapine. The impact of clozapine-resistant schizophrenia (CRS) is even greater than that of treatment resistance in terms of severe and persistent symptoms, relapses and hospitalizations, poorer quality of life, and healthcare costs. Such serious consequences often compel clinicians to try different augmentation strategies to enhance the inadequate clozapine response in CRS. Unfortunately, a large body of evidence has shown that antipsychotics, antidepressants, mood stabilizers, electroconvulsive therapy, and cognitive-behavioural therapy are mostly ineffective in augmenting clozapine response. When beneficial effects of augmentation have been found, they are usually small and of doubtful clinical significance or based on low-quality evidence. Therefore, newer treatment approaches that go beyond the evidence are needed. The options proposed include developing a clinical consensus about the augmentation strategies that are most likely to be effective and using them sequentially in patients with CRS. Secondly, newer approaches such as augmentation with long-acting antipsychotic injections or multi-component psychosocial interventions could be considered. Lastly, perhaps the most effective way to deal with CRS would be to optimize clozapine treatment, which might prevent clozapine resistance from developing. Personalized dosing, adequate treatment durations, management of side effects and non-adherence, collaboration with patients and caregivers, and addressing clinician barriers to clozapine use are the principal ways of ensuring optimal clozapine treatment. At present, these three options could the best way to manage CRS until research provides more firm directions about the effective options for augmenting clozapine response.

Derivation and Molecular Characterization of a Morphological Subpopulation of Human iPSC Astrocytes Reveal a Potential Role in Schizophrenia and Clozapine Response

Astrocytes are the most abundant cell type in the human brain and are important regulators of several critical cellular functions, including synaptic transmission. Although astrocytes are known to play a central role in the etiology and pathophysiology of schizophrenia, little is known about their potential involvement in clinical response to the antipsychotic clozapine. Moreover, astrocytes display a remarkable degree of morphological diversity, but the potential contribution of astrocytic subtypes to disease biology and drug response has received little attention. Here, we used state-of-the-art human induced pluripotent stem cell (hiPSC) technology to derive a morphological subtype of astrocytes from healthy individuals and individuals with schizophrenia, including responders and nonresponders to clozapine. Using functional assays and transcriptional profiling, we identified a distinct gene expression signature highly specific to schizophrenia as shown by disease association analysis of more than 10 000 diseases. We further found reduced levels of both glutamate and the NMDA receptor coagonist d-serine in subtype astrocytes derived from schizophrenia patients, and that exposure to clozapine only rescued this deficiency in cells from clozapine responders, providing further evidence that d-serine in particular, and NMDA receptor-mediated glutamatergic neurotransmission in general, could play an important role in disease pathophysiology and clozapine action. Our study represents a first attempt to explore the potential contribution of astrocyte diversity to schizophrenia pathophysiology using a human cellular model. Our findings suggest that specialized subtypes of astrocytes could be important modulators of disease pathophysiology and clinical drug response, and warrant further investigations.

Impact cérébral structurel et fonctionnel de la Clozapine chez les patients souffrant de schizophrénie : revue systématique des études longitudinales en neuroimagerie

OBJECTIF

L'objectif de cette revue est d'identifier les corrélats anatomo-fonctionnels cérébraux lors d'un traitement par clozapine (CLZ) ainsi que les marqueurs anatomo-fonctionnels prédictifs de la réponse à la CLZ.

MÉTHODES

Nous avons réalisé une revue systématique de la littérature avec les bases de données MEDLINE et Web of Science afin d'identifier et d'examiner toutes les études longitudinales en neuroimagerie investiguant l'impact cérébral de la CLZ.

RÉSULTATS

30 études ont été incluses et analysées. La CLZ induit une diminution du volume et de la perfusion dans les noyaux gris centraux chez les patients répondeurs. Un plus grand volume de substance grise et perfusion dans ces structures avant l'instauration de la CLZ étaient associés à une meilleure réponse au traitement. La diminution de volume et de perfusion au niveau du cortex préfrontal (CPF) est observée malgré l'instauration de CLZ mais de façon moins importante chez les patients sous CLZ que chez les patients sous antipsychotiques typiques. Un plus grand volume au niveau du CPF avant l'instauration de la CLZ est associé à une meilleure réponse clinique dans la majorité des études. Enfin, la CLZ semble induire une réduction des altérations au niveau de la substance blanche.

CONCLUSION

Les corrélats anatomo-fonctionnels de la CLZ différent de ceux des autres antipsychotiques avec une action spécifique de la CLZ au niveau des ganglions de la base et du CPF pouvant participer à sa supériorité en termes de réponse clinique. Plusieurs données cliniques et d'imagerie conduisent à l'hypothèse d'un meilleur pronostic associé à une instauration plus rapide de la CLZ.

A Repeated Time-to-Positive Symptoms Improvement among Malaysian Patients with Schizophrenia Spectrum Disorders Treated with Clozapine

Clozapine remains the drug of choice for resistant schizophrenia. However, its dose-response relationship is still controversial. The current investigation aimed to develop a repeated time-to-positive symptoms improvement following the onset of clozapine treatment in Malaysian schizophrenia spectrum disorder patients. Data from patients’ medical records in the Psychiatric Clinic, Penang General Hospital, were retrospectively analyzed. Several parametric survival models were evaluated using nonlinear mixed-effect modeling software (NONMEM 7.3.0). Kaplan–Meier-visual predictive check (KM-VPC) and sampling-importance resampling (SIR) methods were used to validate the final model. A total of 116 patients were included in the study, with a mean follow-up of 306 weeks. Weibull hazard function best fitted the data. The hazard of positive symptoms improvement decreased 4% for every one-year increase in age over the median of 41 years (adjusted hazard ratio (aHR), 0.96; 95% confidence intervals (95% CI), (0.93–0.98)). However, patients receiving a second atypical antipsychotic agent had four-folds higher hazard (aHR, 4.01; 95% CI, (1.97–7.17)). The hazard increased 2% (aHR, 1.02; 95% CI, (1.01–1.03)) for every 1 g increase in the clozapine six months cumulative dose over the median of 34 g. The developed model provides essential information on the hazard of positive symptoms improvement after the first clozapine dose administration, including modifiable predictors of high clinical importance.

Clozapine Worsens Glucose Intolerance, Nonalcoholic Fatty Liver Disease, Kidney Damage, and Retinal Injury and Increases Renal Reactive Oxygen Species Production and Chromium Loss in Obese Mice

Clozapine is widely employed in the treatment of schizophrenia. Compared with that of atypical first-generation antipsychotics, atypical second-generation antipsychotics such as clozapine have less severe side effects and may positively affect obesity and blood glucose level. However, no systematic study of clozapine’s adverse metabolic effects—such as changes in kidney and liver function, body weight, glucose and triglyceride levels, and retinopathy—was conducted. This research investigated how clozapine affects weight, the bodily distribution of chromium, liver damage, fatty liver scores, glucose homeostasis, renal impairment, and retinopathy in mice fed a high fat diet (HFD). We discovered that obese mice treated with clozapine gained more weight and had greater kidney, liver, and retroperitoneal and epididymal fat pad masses; higher daily food efficiency; higher serum or hepatic triglyceride, aspartate aminotransferase, alanine aminotransferase, blood urea nitrogen, and creatinine levels; and higher hepatic lipid regulation marker expression than did the HFD-fed control mice. Furthermore, the clozapine group mice exhibited insulin resistance, poorer insulin sensitivity, greater glucose intolerance, and less Akt phosphorylation; their GLUT4 expression was lower, they had renal damage, more reactive oxygen species, and IL-1 expression, and, finally, their levels of antioxidative enzymes (superoxide dismutase, glutathione peroxidase, and catalase) were lower. Moreover, clozapine reduced the thickness of retinal cell layers and increased iNOS and NF-κB expression; a net negative chromium balance occurred because more chromium was excreted through urine, and this influenced chromium mobilization, which did not help overcome the hyperglycemia. Our clozapine group had considerably higher fatty liver scores, which was supported by the findings of lowered adiponectin protein levels and increased FASN protein, PNPLA3 protein, FABP4 mRNA, and SREBP1 mRNA levels. We conclude that clozapine can worsen nonalcoholic fatty liver disease, diabetes, and kidney and retinal injury. Therefore, long-term administration of clozapine warrants higher attention.

Integrative Genomic-Epigenomic Analysis of Clozapine-Treated Patients with Refractory Psychosis

Clozapine (CLZ) is the only antipsychotic drug that has been proven to be effective in patients with refractory psychosis, but it has also been proposed as an effective mood stabilizer; however, the complex mechanisms of action of CLZ are not yet fully known. To find predictors of CLZ-associated phenotypes (i.e., the metabolic ratio, dosage, and response), we explore the genomic and epigenomic characteristics of 44 patients with refractory psychosis who receive CLZ treatment based on the integration of polygenic risk score (PRS) analyses in simultaneous methylome profiles. Surprisingly, the PRS for bipolar disorder (BD-PRS) was associated with the CLZ metabolic ratio (pseudo-R2 = 0.2080, adjusted p-value = 0.0189). To better explain our findings in a biological context, we assess the protein-protein interactions between gene products with high impact variants in the top enriched pathways and those exhibiting differentially methylated sites. The GABAergic synapse pathway was found to be enriched in BD-PRS and was associated with the CLZ metabolic ratio. Such interplay supports the use of CLZ as a mood stabilizer and not just as an antipsychotic. Future studies with larger sample sizes should be pursued to confirm the findings of this study.

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.

A Machine Learning Approach Using Effective Connectivity to Predict Response to Clozapine Treatment

Clozapine is an anti-psychotic drug that is known to be effective in the treatment of patients with chronic treatment-resistant schizophrenia (TRS-SCZ), commonly estimated to be around one third of all cases. However, clinicians sometimes delay the initiation of this drug because of its adverse side-effects. Therefore, identification of predictive biological markers of clozapine response are extremely valuable to aid on-time initiation of treatment. In this study, we develop a machine learning (ML) algorithm based on pre-treatment electroencephalogram (EEG) data sets to predict response to clozapine treatment in 57 TRS-SCZs, where the treatment outcome, after at least one-year follow-up is determined using the positive and negative syndrome scale (PANSS). The ML algorithm has three steps: 1) a brain source localization (BSL) procedure using the linearly constrained minimum variance (LCMV) beamforming approach is employed on the EEG signals to extract source waveforms from 30 specified brain regions. 2) An effective connectivity measure named symbolic transfer entropy (STE) is applied to the source waveforms. 3) A ML algorithm is applied to the STE matrix to determine whether a set of features can be found to discriminate most-responder (MR) SCZ patients from least-responder (LR) ones. The findings of this study reveal that STE features can achieve an accuracy of 95.83%. This finding implies that analysis of pre-treatment EEG could contribute to our ability to distinguish MR from LR SCZs, and that the source STE matrix may prove to be a promising tool for the prediction of the clinical response to clozapine.

Possible pharmacogenetic factors in clozapine treatment failure: a case report

There is still much to learn about the predictors of therapeutic response in psychiatry, but progress is gradually being made and precision psychiatry is an exciting and emerging subspeciality in this field. This is critically important in the treatment of refractory psychotic disorders, where clozapine is the only evidence-based treatment but only about half the patients experience an adequate response. In this case report, we explore the possible biological mechanisms underlying treatment failure and discuss possible ways of improving clinical outcomes. Further work is required to fully understand why some patients fail to respond to the most effective treatment in refractory schizophrenia. Therapeutic drug monitoring together with early pharmacogenetic testing may offer a path for some patients with refractory psychotic symptoms unresponsive to clozapine treatment.

The Neurobiology of Treatment-Resistant Schizophrenia: Paths to Antipsychotic Resistance and A Roadmap for Future Research

(Reprinted with permission from NPJ Schizophrenia (2020) 6:1).

Predictors of Treatment-Resistant and Clozapine-Resistant Schizophrenia: A 12-Year Follow-up Study of First-Episode Schizophrenia-Spectrum Disorders

Studies on the long-term development and early predictors of treatment-resistant schizophrenia (TRS) and clozapine-resistant TRS (CR-TRS) in patients with first-episode schizophrenia-spectrum disorders (FES) are limited and have not considered the impact of early intervention services (EIS). This study aimed to explore the development of TRS and CR-TRS among patients with FES over 12 years of follow-up. Of the 1234 patients with FES, 15% developed TRS. A total of 450 patients with schizophrenia or schizoaffective disorder were included in a nested case-control study (157 TRS and 293 non-TRS). Younger age of onset, poorer premorbid social adjustment during adulthood, longer duration of first episode, a greater number of relapses, and a higher antipsychotic dose in the first 24 months were associated with earlier TRS. CR-TRS patients, constituting 25% of TRS patients, had a poorer premorbid social adjustment in late adolescence and longer delay before clozapine initiation compared with non-CR-TRS. CR-TRS had poorer clinical and functional outcomes at 12-year follow-up. However, TRS patients on clozapine had a lower mortality rate compared with non-TRS patients. EIS did not have a significant impact on the development of TRS, but patients in the EIS group had a shorter delay of clozapine initiation. Results suggested that neurodevelopmental factors, early clinical characteristics, and requirement for higher antipsychotic dose may be associated with TRS development, highlighting multiple pathways leading to this form of illness. Specific interventions including relapse prevention and early initiation of clozapine during the early course of illness may reduce the rate of TRS and improve patient outcomes.

Quantitative biomarkers to predict response to clozapine treatment using resting EEG data

Clozapine is an anti-psychotic drug that is known to be effective in the treatment of patients with chronic treatment-resistant schizophrenia (TRS-SCZ), commonly estimated to be around one third of all cases. However, clinicians sometimes delay the initiation of this drug because of its adverse side-effects. Therefore, identification of predictive biomarkers of clozapine response is extremely valuable to aid on-time initiation of clozapine treatment. In this study, we develop a machine learning (ML) algorithm based on the pre-treatment electroencephalogram (EEG) data sets to predict response to clozapine treatment in TRS-SCZs, where the treatment outcome, after at least one-year follow-up is determined using the Positive and Negative Syndrome Scale (PANSS). The ML algorithm has two steps: 1) an effective connectivity named symbolic transfer entropy (STE) is applied to resting state EEG waveforms, 2) the ML algorithm is applied to STE matrix to determine whether a set of features can be found to discriminate most responder (MR) SCZ patients from least responder (LR) ones. The findings of this study revealed that the STE features could achieve an accuracy of 89.90%. This finding implies that analysis of pre-treatment EEG could contribute to our ability to distinguish MR from LR SCZs, and that the STE matrix may prove to be a promising tool for the prediction of the clinical response to clozapine.

Progressive subcortical volume loss in treatment-resistant schizophrenia patients after commencing clozapine treatment

The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p < 0.001). Corrected post-hoc analyses demonstrated that patients had significant enlargement of lateral ventricles (F(1,59) = 48.89; p < 0.001) and reduction of thalamus (F(1,59) = 34.85; p < 0.001), caudate (F(1,59) = 59.35; p < 0.001), putamen (F(1,59) = 87.20; p < 0.001) and hippocampus (F(1,59) = 14.49; p < 0.001) volumes. Thalamus and putamen volume reduction was associated with improvement in PANSS (r = 0.42; p = 0.021, r = 0.39; p = 0.033), SANS (r = 0.36; p = 0.049, r = 0.40; p = 0.027) and GAF (r = -0.39; p = 0.038, r = -0.42; p = 0.024) scores. Reduced thalamic volume over time was associated with increased serum clozapine level at follow-up (r = -0.44; p = 0.010). Patients with treatment-resistant schizophrenia display progressive subcortical volume deficits after switching to clozapine despite experiencing symptomatic improvement. Thalamo-striatal progressive volumetric deficit associated with symptomatic improvement after clozapine exposure may reflect an adaptive response related to improved outcome rather than a harmful process.

Demographic and clinical features as predictors of clozapine response in patients with schizophrenia spectrum disorders: A systematic review and meta-analysis

OBJECTIVES

Clozapine (CLZ) is prescribed to (relatively) treatment-resistant patients with schizophrenia spectrum disorders. Currently, it is unknown what factors predict response to CLZ. Therefore, we performed meta-analyses to identify predictors of CLZ response, hence aiming to facilitate timely and efficient prescribing of CLZ.

METHODS

A systematic search was performed in 'Pubmed' and 'Embase' until 1 January 2019. Articles were eligible if they provided data on predictors of CLZ response measured demographic and clinical factors at baseline or biochemical factors at follow-up in schizophrenia spectrum disorder patients.

RESULTS

A total of 34 articles, total number of participants = 9386; N unique = 2094, were eligible. Factors significantly associated with better CLZ response were: lower age, lower PANSS negative score and paranoid schizophrenia subtype.

CONCLUSION

The results of our meta-analyses suggest that three baseline demographic and clinical features are associated with better clozapine response, i.e. relatively young age, few negative symptoms and paranoid schizophrenia subtype. These variables may be taken into account by clinicians who consider treating a specific patient with CLZ.

The neurobiology of treatment-resistant schizophrenia: paths to antipsychotic resistance and a roadmap for future research

Treatment-resistant schizophrenia (TRS), the persistence of positive symptoms despite ≥2 trials of adequate dose and duration of antipsychotic medication with documented adherence, is a serious clinical problem with heterogeneous presentations. TRS can vary in its onset (at the first episode of psychosis or upon relapse), in its severity, and in the response to subsequent therapeutic interventions (i.e., clozapine, electroconvulsive therapy). The heterogeneity of TRS indicates that the underlying neurobiology of TRS may differ not only from treatment-responsive schizophrenia but also among patients with TRS. Several hypotheses have been proposed for the neurobiological mechanisms underlying TRS, including dopamine supersensitivity, hyperdopaminergic and normodopaminergic subtypes, glutamate dysregulation, inflammation and oxidative stress, and serotonin dysregulation. Research supporting these hypotheses is limited in part by variations in the criteria used to define TRS, as well as by the biological and clinical heterogeneity of TRS. Clinical trial designs for new treatments should be informed by this heterogeneity, and further clinical research is needed to more clearly understand the underlying neurobiology of TRS and to optimize treatment for patients with TRS.

Imaging-Based Subtyping for Psychiatric Syndromes

Despite considerable research evidence demonstrating significant neurobiological alterations in psychiatric disorders, incorporating neuroimaging approaches into clinical practice remains challenging. There is an urgent need for biologically validated psychiatric disease constructs that can inform diagnostic algorithms and targeted treatment development. In this article, we present a conceptual review of the most robust and impactful findings from studies that use neuroimaging methods in efforts to define distinct disease subtypes, while emphasizing cross-diagnostic and dimensional approaches. In addition, we discuss current challenges in psychoradiology and outline potential future strategies for clinically applicable translation.

Treatment-Resistant Schizophrenia: Genetic and Neuroimaging Correlates

Schizophrenia is a severe neuropsychiatric disorder that affects approximately 0.5–1% of the population. Response to antipsychotic therapy is highly variable, and it is not currently possible to predict those patients who will or will not respond to antipsychotic medication. Furthermore, a high percentage of patients, approximately 30%, are classified as treatment-resistant (treatment-resistant schizophrenia; TRS). TRS is defined as a non-response to at least two trials of antipsychotic medication of adequate dose and duration. These patients are usually treated with clozapine, the only evidence-based pharmacotherapy for TRS. However, clozapine is associated with severe adverse events. For these reasons, there is an increasing interest to identify better targets for drug development of new compounds and to establish better biomarkers for existing medications. The ability of antipsychotics to improve psychotic symptoms is dependent on their antagonist and reverse agonist activities at different neuroreceptors, and some genetic association studies of TRS have focused on different pharmacodynamic factors. Some genetic studies have shown an association between antipsychotic response or TRS and neurodevelopment candidate genes, antipsychotic mechanisms of action (such as dopaminergic, serotonergic, GABAergic, and glutamatergic) or pharmacokinetic factors (i.e., differences in the cytochrome families). Moreover, there is a growing body of literature on the structural and functional neuroimaging research into TRS. Neuroimaging studies can help to uncover the underlying neurobiological reasons for such resistance and identify resistant patients earlier. Studies examining the neuropharmacological mechanisms of antipsychotics, including clozapine, can help to improve our knowledge of their action on the central nervous system, with further implications for the discovery of biomarkers and the development of new treatments. The identification of the underlying mechanisms of TRS is a major challenge for developing personalized medicine in the psychiatric field for schizophrenia treatment. The main goal of precision medicine is to use genetic and brain-imaging information to improve the safety, effectiveness, and health outcomes of patients via more efficiently targeted risk stratification, prevention, and tailored medication and treatment management approaches. The aim of this review is to summarize the state of art of pharmacogenetic, pharmacogenomic and neuroimaging studies in TRS.

Development of Neuroimaging-Based Biomarkers in Psychiatry

This chapter presents an overview of accumulating neuroimaging data with emphasis on translational potential. The subject will be described in the context of three disease states, i.e., schizophrenia, bipolar disorder, and major depressive disorder, and for three clinical goals, i.e., disease risk assessment, subtyping, and treatment decision.

Treatment resistant schizophrenia - review and a call to action

Recovery rates in schizophrenia remain suboptimal with up to one-third resistant to standard treatments, a population prevalence of 0.2%. Clozapine is the only evidenced-based treatment for treatment resistant schizophrenia (TRS), yet there are significant delays in its use or it may not be trialled, potentially impacting the chance of recovery. Better outcomes with earlier use of clozapine may be possible. There is emerging evidence that early treatment resistance is not uncommon from the earliest stages of psychosis. In this review, we provide an update on TRS, its epidemiology and its management, with a specific focus on the optimal use and timing of clozapine and augmentation strategies for the one-third of patients who do not respond to clozapine.