Neuropsychological differences between treatment-resistant and treatment-responsive schizophrenia: a meta-analysis

Overcoming the barriers to identifying and managing treatment-resistant schizophrenia and to improving access to clozapine: A narrative review and recommendation for clinical practice

Clozapine is the only approved antipsychotic for treatment-resistant schizophrenia (TRS). Although a large body of evidence supports its efficacy and favorable risk-benefit ratio in individuals who have failed two or more antipsychotics, clozapine remains underused. However, variations in clozapine utilization across geographic and clinical settings suggest that it could be possible to improve its use. In this narrative review and expert opinion, we summarized information available in the literature on the mechanisms of action, effectiveness, and potential adverse events of clozapine. We identified barriers leading to discouragement in clozapine prescription internationally, and we proposed practical solutions to overcome each barrier. One of the main obstacles identified to the use of clozapine is the lack of appropriate training for physicians: we highlighted the need to develop specific professional programs to train clinicians, both practicing and in residency, on the relevance and efficacy of clozapine in TRS treatment, initiation, maintenance, and management of potential adverse events. This approach would facilitate physicians to identify eligible patients and offer clozapine as a treatment option in the early stage of the disease. We also noted that increasing awareness of the benefits of clozapine among healthcare professionals, people with TRS, and their caregivers can help promote the use of clozapine. Educational material, such as leaflets or videos, could be developed and distributed to achieve this goal. The information provided in this article may be useful to improve disease burden and support healthcare professionals, patients, and caregivers navigating the complex pathways to TRS management.

A systematic review and meta-analysis of the effect of clozapine on cognitive functions in patients with treatment-resistant schizophrenia

BACKGROUND

This study aimed to conduct a systematic review and meta-analysis on cognitive performances of patients with treatment-resistant schizophrenia (TRS) after clozapine treatment and to examine the potential effect of follow-up duration and clozapine dosage.

METHODS

Five electronic databases were searched and studies were included if treatment-resistant schizophrenia patients were treated with clozapine and with baseline and follow-up cognitive functions assessments. Cognitive measures were categorised into six domains based on DSM-5-TR. Random-effect model analysis was used to pool the effect estimates. Moderator effects of clozapine dosage, follow up duration, duration of illness, age, years of education and change in positive symptoms severity were examined with meta-regression.

FINDINGS

Nineteen articles were included with 50 cognitive measures reported. Systematic review found inconsistent results. Twelve cognitive measures were included for meta-analysis and found overall improvement of cognitive performances after clozapine treatment SMD = 0.11 [95 % CI 0.02, 0.20] (p = 0.021). Patients with younger age, more years of education and improvements in positive symptoms are more likely to improve in cognitive performances. Subgroup analysis found significant improvement in studies with follow-up periods of 6-months or longer but not for studies with shorter follow-up periods.

CONCLUSION

Clozapine may improve some domains of cognitive function, particularly over a longer period. However, the overall inconsistent results suggest that more studies with larger sample size and standard cognitive function assessments would be needed to enhance our understanding of the impact of clozapine on the cognitive functions in the TRS patients.

Modeling the effects of treatment resistance and anticholinergic burden on cognitive function domains in patients with schizophrenia

The contribution of anticholinergic burden to cognitive function in patients with treatment resistant schizophrenia (TRS) is uncertain. This case-control study aims to comprehensively examine the association between treatment resistance and cognitive functions and the contribution of anticholinergic burden in patients with schizophrenia. Anticholinergic burden of all patients was calculated using the Anticholinergic Cognitive Burden scale. Exploratory Factor Analysis of 11 cognitive assessments identified four cognitive domains: verbal memory, attention and general cognitive functions, visual memory and processing speed, and executive function. Two structural equation models (SEM) examined the relationship of TRS and these cognitive functions with, and without considering anticholinergic burden. A total of 288 participants were included (TRS N=111, non-TRS N=177). Patients with TRS performed poorer than the non-TRS group only in the executive function domain. Anticholinergic burden contributed significantly to the attention and general cognitive functions, visual memory and processing speed, and executive function. The impact of TRS on executive function was no longer significant after adding anticholinergic burden to the SEM. Results suggested that anticholinergic burden contributes to a wide range of cognitive function impairment in patients with schizophrenia and is likely to be part of the apparent differences of cognitive function between TRS and non-TRS.

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

Neuroanatomical comparison of treatment-resistant and treatment-responsive schizophrenia patients using the cloud-based brain magnetic resonance image segmentation and parcellation system: An MRIcloud study

Recent developments in neuroimaging have improved our understanding of the biological mechanisms underlying schizophrenia. However, neuroimaging findings in treatment-resistant schizophrenia (TRS) remain unclear. In the present study, we aimed to explore potential neuroanatomical regions that may be associated with treatment resistance in schizophrenia patients by comparing neuroanatomical regions of TRS and non-TRS patients using the MRICloud method. A total of 33 schizophrenia patients (meeting DSM 5 diagnostic criteria for schizophrenia) were included in the study. Patients were dichotomized into TRS (n = 18) and non-TRS (n = 15) groups, and all patients underwent MRI. Neuroanatomical regions of TRS and non-TRS patients were compared using the MRICloud method. Disease severity was measured using the Positive and Negative Syndrome Scale (PANSS). Interestingly, a statistically significant greater left Corpus Collosum (CC) thickness was found in TRS patients compared to non-TRS patients. It is clear that further studies comparing TRS patients with non-TRS patients are needed, and these studies should focus on the circuits in the corpus callosum that are thought to play a role in treatment resistance. Further longitudinal studies are also needed to complement the cross-sectional studies, using a multimodal imaging approach in the patients with clearly defined TRS criteria.

Lateral hypothalamus orexinergic projection to the medial prefrontal cortex modulates chronic stress-induced anhedonia but not anxiety and despair

Chronic stress-induced anxiodepression is a common health problem, however its potential neurocircuitry mechanism remains unclear. We used behavioral, patch-clamp electrophysiology, chemogenetic, and optogenetic approaches to clarify the response of the lateral hypothalamus (LH) and the medial prefrontal cortex (mPFC) to stress, confirmed the structural connections between the LH and mPFC, and investigated the role of the LH-mPFC pathway in chronic stress-induced anxiodepression symptoms. Unpredictable chronic mild stress (UCMS) caused anxiodepression-like behaviors, including anxiety, anhedonia, and despair behaviors. We discovered that the activity of the LH and mPFC was both increased after restraint stress (RS), a stressor of UCMS. Then we found that the orexinergic neurons in the LH predominantly project to the glutamatergic neurons in the mPFC, and the excitability of these neurons were increased after UCMS. In addition, overactivated LH orexinergic terminals in the mPFC induced anhedonia but not anxiety and despair behaviors in naive mice. Moreover, chemogenetically inhibited LH-mPFC orexinergic projection neurons and blocked the orexin receptors in the mPFC alleviated anhedonia but not anxiety and despair behaviors in UCMS-treated mice. Our study identified a new neurocircuit from LH orexinergic neurons to mPFC and revealed its role in regulating anhedonia in response to stress. Overactivation of LHOrx-mPFC pathway selectively mediated chronic stress-induced anhedonia. In normal mice, the LHOrx-mPFC pathway exhibits relatively low activity. However, after chronic stress, the activity of orexinergic neuron in LH is overactivated, leading to an increased release of orexin into the mPFC. This heightened orexin concentration results in increased excitability of the mPFC through OX1R and OX2R, consequently triggering anhedonia.

Role of the immune-kynurenine pathway in treatment-resistant schizophrenia

BACKGROUND

The immune-inflammatory response system (IRS) and kynurenine pathway (KP) have been implicated in the pathophysiology of schizophrenia. Studies have shown inflammation-related effects on KP metabolism in patients with schizophrenia. This study investigated the relationship between KP metabolites, IRS, and the compensatory immune-regulatory reflex system (CIRS) in patients with treatment-resistant schizophrenia (TRS).

METHODS

Patients with (n = 53) and without TRS (n = 47), and healthy controls (HCs, n = 49) were enrolled. We quantified plasma levels of pro-inflammatory cytokines (interleukin [IL]-1β, IL-2, IL-6, soluble(s)IL-6 receptor, IL-8, IL-12, IL-17, IL-18, interferon-γ, and tumor necrosis factor[TNF]-α) and anti-inflammatory cytokines (IL-1 receptor antagonist, IL-4, IL-10, tumor growth factor [TGF]-β1, TGF-β2, soluble (s) IL-2 receptor subunit α, sIL-2 receptor subunit β, and sTNF-α receptor 1) and calculated the IRS/CIRS ratio. We also tested serum metabolites of the KP, including kynurenine (KYN), kynurenic acid (KYNA), and quinolinic acid (QUIN), along with the QUIN/KYNA ratio.

RESULTS

Patients with TRS had significantly higher IRS/CIRS ratio than non-TRS patients (p = 0.002) and HCs (p = 0.007), and significantly lower KYN (p = 0.001) and KYNA (p = 0.01) levels than HCs. Binary logistic regression analysis revealed that a younger age at illness onset (odds ratio [OR] = 0.91, p = 0.02) and a higher IRS/CIRS ratio (OR = 1.22; p = 0.007) were risk factors for patients with TRS. After further adjusted for age of onset, the QUIN/KYNA ratio (β = 0.97; p = 0.02) significantly moderated the relationship between IRS/CIRS and TRS, showing that in the higher QUIN/KYNA condition, higher IRS/CIRS ratio were significantly and more likely to be associated with patients with TRS (β = 0.12, z = 3.19, p = 0.001), whereas in the low QUIN/KYNA condition, the association between IRS/CIRS ratio and TRS was weak and insignificant.

CONCLUSIONS

The peripheral immune response was imbalanced in TRS and was preferentially directed towards the IRS compared to patients without TRS and healthy controls, which is likely to play a role in neurotoxicity. Additionally, peripheral KP activation was also imbalanced, as evidenced by significantly reduced KYN and KYNA levels in patients with TRS compared to healthy controls, but none of KP metabolisms were significantly difference in non-TRS patients compared to healthy controls. QUIN/KYNA ratio involving to the degree of activation of NMDA receptors, indicated the neurotoxic level of the KP activation. The interaction between IRS/CIRS and QUIN/KYNA ratio was significant in predicting TRS, and our findings suggest a potential role for the immune-kynurenine pathway in TRS pathogenesis.

Gene expression imputation provides clinical and biological insights into treatment-resistant schizophrenia polygenic risk

Genome-wide association studies (GWAS) have revealed the polygenic nature of treatment-resistant schizophrenia TRS. Gene expression imputation allowed the translation of GWAS results into regulatory mechanisms and the construction of gene expression (GReX) risk scores (GReX-RS).  In the present study we computed GReX-RS from the largest GWAS of TRS to assess its association with clinical features. We perform transcriptome imputation in the largest GWAS of TRS to find GReX associated with TRS using brain tissues. Then, for each tissue, we constructed a GReX-RS of the identified genes in a sample of 254 genotyped first episode of psychosis (FEP) patients to test its association with clinical phenotypes, including clinical symptomatology, global functioning and cognitive performance. Our analysis provides evidence that the polygenic basis of TRS includes genetic variants that modulate the expression of certain genes in certain brain areas (substantia nigra, hippocampus, amygdala and frontal cortex), which at the same time are related to clinical features in FEP patients, mainly persistence of negative symptoms and cognitive alterations in sustained attention, which have also been suggested as clinical predictors of TRS. Our results provide a clinical explanation of the polygenic architecture of TRS and give more insight into the biological mechanisms underlying TRS.

Unsupervised Machine Learning Driven Analysis of Verbatims of Treatment-Resistant Schizophrenia Patients Having Followed Avatar Therapy

(1) Background: The therapeutic mechanisms underlying psychotherapeutic interventions for individuals with treatment-resistant schizophrenia are mostly unknown. One of these treatment techniques is avatar therapy (AT), in which the patient engages in immersive sessions while interacting with an avatar representing their primary persistent auditory verbal hallucination. The aim of this study was to conduct an unsupervised machine-learning analysis of verbatims of treatment-resistant schizophrenia patients that have followed AT. The second aim of the study was to compare the data clusters obtained from the unsupervised machine-learning analysis with previously conducted qualitative analysis. (2) Methods: A k-means algorithm was performed over the immersive-session verbatims of 18 patients suffering from treatment-resistant schizophrenia who followed AT to cluster interactions of the avatar and the patient. Data were pre-processed using vectorization and data reduction. (3): Results: Three clusters of interactions were identified for the avatar's interactions whereas four clusters were identified for the patient's interactions. (4) Conclusion: This study was the first attempt to conduct unsupervised machine learning on AT and provided a quantitative insight into the inner interactions that take place during immersive sessions. The use of unsupervised machine learning could yield a better understanding of the type of interactions that take place in AT and their clinical implications.

Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study

BACKGROUND

Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases.

METHODS

Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up.

RESULTS

On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049).

CONCLUSIONS

Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions.

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.

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.

Treatment-resistant schizophrenia: How far have we traveled?

Treatment-resistant schizophrenia is a lack of adequate response to antipsychotic medications resulting in incomplete functional and social recovery from the illness. Different definitions have been proposed for clinical practice and research work. Antipsychotics that are used in the management of schizophrenia mainly act on multiple dopaminergic pathways which are implicated in the development of symptoms of schizophrenia. Newer antipsychotics also are implicated to affect the serotonergic pathways. Clozapine is the only evidence-based treatment available for the management of treatment-resistant cases. Neurobiologically, there is a considerable overlap between treatment-resistant and treatment-responsive cases. The factors that are implicated in the evolution of treatment resistance are still not conclusive. These make the management of such patients a challenge. However, certain peculiarities of treatment-resistant schizophrenia have been identified which can guide us in the early identification and precise treatment of the treatment-resistant cases.

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, β = 3.73, 95% CI = 1.26-6.20, P = 0.004; Glx, β = 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 (β = 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.

Schizophrenia: A developmental disorder with a risk of non-specific but avoidable decline

The onset of schizophrenia is determined by biological and social risk factors operating predominantly during development. These result in subtle deviations in brain structure and cognitive function. Striatal dopamine dysregulation follows, causing abnormal salience and resultant psychotic symptoms. Most people diagnosed as having schizophrenia do not progressively deteriorate; many improve or recover. However, poor care can allow a cycle of deterioration to be established, stress increasing dopamine dysregulation, leading to more stress consequent on continuing psychotic experiences, and so further dopamine release. Additionally, long-term antipsychotics can induce dopamine supersensitivity with resultant relapse and eventually treatment resistance. Some patients suffer loss of social and cognitive function, but this is a consequence of the hazards that afflict the person with schizophrenia, not a direct consequence of genetic predisposition. Thus, brain health and cognition can be further impaired by chronic medication effects, cardiovascular and cerebrovascular events, obesity, poor diet, and lack of exercise; drug use, especially of tobacco and cannabis, are likely to contribute. Poverty, homelessness and poor nutrition which become the lot of some people with schizophrenia, can also affect cognition. Regrettably, the model of progressive deterioration provides psychiatry and its funders with an alibi for the effects of poor care.