Treatment Resistance In Schizophrenia Research Articles

Neuromelanin-Sensitive MRI as Candidate Marker for Treatment Resistance in First-Episode Schizophrenia.

Markers for treatment resistance in schizophrenia are needed to reduce delays in effective treatment. Nigrostriatal hyperdopaminergic function plays a critical role in the pathology of schizophrenia, yet antipsychotic nonresponders do not show increased dopamine function. Neuromelanin-sensitive MRI (NM-MRI), which indirectly measures dopamine function in the substantia nigra, has potential as a noninvasive marker for nonresponders. Increased NM-MRI signal has been shown in psychosis, but has not yet been assessed in nonresponders. In this study, the authors investigated whether nonresponders show lower NM-MRI signal than responders. NM-MRI scans were acquired in 79 patients with first-episode psychosis and 20 matched healthy control subjects. Treatment response was assessed at a 6-month follow-up. An a priori voxel-wise analysis within the substantia nigra tested the relation between NM-MRI signal and treatment response in patients. Fifteen patients were classified as nonresponders and 47 patients as responders. Seventeen patients were excluded, primarily because of medication nonadherence or change in diagnosis. Voxel-wise analysis revealed 297 significant voxels in the ventral tier of the substantia nigra that were negatively associated with treatment response. Nonresponders and healthy control subjects had significantly lower NM-MRI signal than responders. Receiver operating characteristic curve analysis showed that NM-MRI signal separated nonresponders with areas under the curve between 0.62 and 0.85. In addition, NM-MRI signal in patients did not change over 6 months. These findings provide further evidence for dopaminergic differences between medication responders and nonresponders and support the potential of NM-MRI as a clinically applicable marker for treatment resistance in schizophrenia.

Associations of the Gut Microbiome With Treatment Resistance in Schizophrenia

There is growing interest in the role of gut microbiome composition in schizophrenia. However, lifestyle factors are often neglected, and few studies have investigated microbiome composition in treatment-resistant schizophrenia. To explore associations between the gut microbiome and schizophrenia diagnosis, treatment resistance, clozapine response, and treatment-related adverse effects while adjusting for demographic and lifestyle factors. In this case-control study of adults aged 20 to 63 years, stool samples and data on demographic characteristics, lifestyle, and medication use were collected and gut microbiome measures obtained using shotgun metagenomics. Participants with a schizophrenia diagnosis were referred through psychiatric inpatient units and outpatient clinics. Data were collected for 4 distinct groups: control individuals without a psychiatric diagnosis (past or present), individuals with treatment-responsive schizophrenia taking nonclozapine antipsychotic medications, clozapine-responsive individuals with treatment-resistant schizophrenia, and clozapine-nonresponsive individuals with treatment-resistant schizophrenia. Participants were recruited between November 2020 and November 2021. Control individuals were recruited in parallel through posters and online advertisements and matched for age, sex, and body mass index (BMI) to the individuals with schizophrenia. Participants were excluded if taking antibiotics in the past 2 months, if unable to communicate in English or otherwise follow study instructions, were pregnant or planning to become pregnant, or had any concomitant disease or condition making them unsuited to the study per investigator assessment. Data were analyzed from January 2022 to March 2023. Omics relationship matrices, α and β diversity, and relative abundance of microbiome features. Data were collected for 97 individuals (71 [74%] male; mean [SD] age, 40.4 [10.3] years; mean [SD] BMI, 32.8 [7.4], calculated as weight in kilograms divided by height in meters squared). Significant microbiome associations with schizophrenia were observed at multiple taxonomic and functional levels (eg, common species: b2, 30%; SE, 13%; adjusted P = .002) and treatment resistance (eg, common species: b2, 27%; SE, 16%; adjusted P = .03). In contrast, limited evidence was found for microbiome associations with clozapine response, constipation, or metabolic syndrome. Significantly decreased microbial richness was found in individuals with schizophrenia compared to control individuals (t95 = 4.25; P < .001; mean [SD] for control individuals, 151.8 [32.31]; mean [SD] for individuals with schizophrenia, 117.00 [36.2]; 95% CI, 18.6-51.0), which remained significant after a covariate and multiple comparison correction. However, limited evidence was found for differences in β diversity (weighted UniFrac) for schizophrenia diagnosis (permutational multivariate analysis of variance [PERMANOVA]: R2, 0.03; P = .02), treatment resistance (R2, 0.02; P = .18), or clozapine response (R2, 0.04; P = .08). Multiple differentially abundant bacterial species (19) and metabolic pathways (162) were found in individuals with schizophrenia, which were primarily associated with treatment resistance and clozapine exposure. The findings in this study are consistent with the idea that clozapine induces alterations to gut microbiome composition, although the possibility that preexisting microbiome differences contribute to treatment resistance cannot be ruled out. These findings suggest that prior reports of microbiome alterations in individuals with chronic schizophrenia may be due to medication or lifestyle factors and that future studies should incorporate these variables in their design and interpretation.

Pharmacogenetic Factors of Clozapine-Induced Metabolic Syndrome

(1) Introduction: Despite modern therapies, approximately 20-30% of patients with schizophrenia remain resistant to psychopharmacotherapy. Clozapine is the only antipsychotic with proven efficacy for treatment resistance in schizophrenia (TRS). The most common adverse drug reaction (ADR) during clozapine administration are metabolic disturbances, particularly metabolic syndrome (MS). Because MS leads to a twofold increase in mortality from cardiovascular disease and a 1.5-fold increase in mortality from all causes, and clozapine is often the only treatment option for TRS, it is critical to monitor and management metabolic abnormalities. The high interindividual differences in the development of clozapine-induced MS suggest that genetic factors may play an important role. (2) Purpose: The aim of this study was to identify relevant single nucleotide polymorphisms (SNPs) of candidate genes for clozapine-induced MS, because based on these data, a genetic risk panel can be constructed to assess the likelihood of developing clozapine-induced MS in patients with schizophrenia. (3) Materials and Methods: We searched for full-text publications in PubMed, Web of Science, Springer, Google Scholar, and electronic libraries in English and Russian, available from inception to 30 October 2023. Keywords were the following: metabolic disturbances, clozapine, metabolic syndrome, schizophrenia, genes, adverse drug reactions, antipsychotics, pharmacogenetics, genetic biomarker, single nucleotide variant, polymorphism, association, variation, and metabolic syndrome genes. (4) Results: we included 6 naturalistic cross-sectional open-label trials, included patients with schizophrenia, schizoaffective, schizophreniform disorder or psychotic disorder, who were treated with first and second generations antipsychotics, among which there was also clozapine and 1 meta-analysis which reviewed association between HTR2C gene polymorphisms and anti-psychotic-induced MS in schizophrenia patients. According to the results of our scoping review the carriage of SNPs in the studied candidate genes associated with clozapine-induced MS are the following: 1) CYP1A2 gene: genotype AA of rs762551 (NG_008431.2:g.32035C&gt;A); 2) CYP2C19 gene: CYP2C19*2 polymorphism; 3) HTR2C gene: genotype CC of rs518147 (NM_000868.2:c.-697G&gt;C), minor allele C of rs1414334 (NG_012082.3:g.324497C&gt;G), genotype CC of rs518147 (NM_000868.2:c.-697G&gt;C), genotype GG of rs12836771 (NG_012082.3:g.71829A&gt;G); 4) LEP gene: genotypes AG and GG of rs7799039 (NG_044977.1:g.475G&gt;A); 5) LEPR gene: genotypes AG and GG of rs1137101 (NG_015831.2:g.177266A&gt;G). (4) Conclusions: Uncovering the genetic biomarkers of clozapine-induced MS may provide a key to developing a strategy for the personalized prevention and treatment of this ADRs of clozapine in patients with schizophrenia spectrum disorders in real clinical practice.

The association between clinical, sociodemographic, familial, and environmental factors and treatment resistance in schizophrenia: A machine-learning-based approach

BackgroundPrediction of treatment resistance in schizophrenia (TRS) would be helpful to reduce the duration of ineffective treatment and avoid delays in clozapine initiation. We applied machine learning to identify clinical, sociodemographic, familial, and environmental variables that are associated with TRS and could potentially predict TRS in the future. Study designBaseline and follow-up data on trait(-like) variables from the Genetic Risk and Outcome of Psychosis (GROUP) study were used. For the main analysis, we selected patients with non-affective psychotic disorders who met TRS (n = 200) or antipsychotic-responsive criteria (n = 423) throughout the study. For a sensitivity analysis, we only selected patients who met TRS (n = 76) or antipsychotic-responsive criteria (n = 123) at follow-up but not at baseline. Random forest models were trained to predict TRS in both datasets. SHapley Additive exPlanation values were used to examine the variables' contributions to the prediction. Study resultsPremorbid functioning, age at onset, and educational degree were most consistently associated with TRS across both analyses. Marital status, current household, intelligence quotient, number of moves, and family loading score for substance abuse also consistently contributed to the prediction of TRS in the main or sensitivity analysis. The diagnostic performance of our models was modest (area under the curve: 0.66–0.69). ConclusionsWe demonstrate that various clinical, sociodemographic, familial, and environmental variables are associated with TRS. Our models only showed modest performance in predicting TRS. Prospective large multi-centre studies are needed to validate our findings and investigate whether the model's performance can be improved by adding data from different modalities.

Minor physical anomalies may be related to treatment resistance in patients with schizophrenia

This study investigates the relationship between minor physical anomalies (MPA) and treatment resistance in schizophrenia (TRS). We evaluated 137 patients and 100 healthy controls by using a modified Waldrup MPA scale. Thirteen MPA items were found more frequently in the schizophrenia group than in the controls. The total MPA score was higher in TRS, and MPAs in the eye and mouth regions were more frequent in TRS (n = 57) than in non-TRS. Total MPA score was correlated to Brief Psychiatric Rating Scale-Expanded (BPRS-E) total and BPRS-positive scores in TRS. Our findings suggest that MPA might contribute to treatment resistance in schizophrenia.

Treatment Resistance in Schizophrenia Is Associated with Attention Deficit/Hyperactivity Disorder and Gut Microbiota: A Genetic Correlation and Mendelian Randomization Study

Introduction: Observational studies highlight associations of common diseases with individual schizophrenia symptoms. However, it is unclear whether these diseases are associated with individual treatment-resistant schizophrenia (TRS). We aimed to explore the genetic associations between common immune diseases, metabolic diseases, psychiatric disorders, gut microbiota and TRS. Methods: Genome-wide association study (GWAS) summary data of European participants (n = ∼456,327) included TRS, 11 psychiatric disorders, 23 immune and metabolic diseases, body mass index, height, and 211 gut microbiota. In this genetic correlation and two-sample Mendelian randomization (MR) study, linkage disequilibrium score (LDSC) regression was applied to infer genetic correlation estimates. Two-sample MR tested potential causal associations of genetic variants associated with common immune diseases, metabolic diseases, psychiatric disorders, and gut microbiota with TRS. Results: LDSC revealed candidate associations between attention deficit/hyperactivity disorder (ADHD), schizophrenia, intestinal infectious diseases, obesity and TRS (genetic correlation range, 0.230–0.702; p < 0.05). Two-sample MR analyses suggested that ADHD was positively associated with TRS (estimate [SE] = 0.204 [0.073], p = 0.005), a finding that remained stable across statistical models. Besides, schizophrenia and genus Barnesiella levels were causally associated with TRS but not consistent across MR approaches. Conclusion: This study reports genetic correlations between ADHD, schizophrenia, intestinal infectious diseases, obesity and TRS. The study also found that genus Barnesiella was associated with TRS. These findings may have clinical implications, highlighting the possible strategy for TRS prevention.

Treatment resistance in schizophrenia: a meta-analysis of prevalence and correlates.

To determine the prevalence and correlates of treatment-resistant schizophrenia (TRS) through a systematic review and meta-analysis. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, an electronic search was performed in PubMed and Embase through May 17, 2022. All study designs that assessed a minimum of 20 schizophrenia-spectrum patients and provided data on TRS prevalence or allowed its calculation were included. Estimates were produced using a random-effects model meta-analysis. The TRS prevalence across 50 studies (n = 29,390) was 36.7% (95%CI 33.1-40.5, p < 0.0001). The prevalence ranged from 22% (95%CI 18.4-25.8) in first-episode to 39.5% (95%CI 32.2-47.0) in multiple-episode samples (Q = 18.27, p < 0.0001). Primary treatment resistance, defined as no response from the first episode, was 23.6% (95%CI 20.5-26.8) vs. 9.3% (95%CI 6.8-12.2) for later-onset/secondary (≥ 6 months after initial treatment response). Longer illness duration and recruitment from long-term hospitals or clozapine clinics were associated with higher prevalence estimates. In meta-regression analyses, older age and poor functioning predicted greater TRS. When including only studies with lower bias risk, the TRS prevalence was 28.4%. Different study designs and recruitment strategies accounted for most of the observed heterogeneity in TRS prevalence rates. The results point to early-onset and later-onset TRS as two separate disease pathways requiring clinical attention.

Investigating the relationship between the kynurenine pathway and treatment resistance in schizophrenia

Investigating the relationship between the kynurenine pathway and treatment resistance in schizophrenia

Association of cortical thickness and cognition with schizophrenia treatment resistance.

Approximately a third of patients with schizophrenia fail to adequately respond to antipsychotic medications, a condition known as treatment resistance (TR). We aimed to assess cognitive and cortical thickness deficits and their relationship to TR in schizophrenia. We recruited patients with schizophrenia (n = 127), including patients at treatment initiation (n = 45), treatment-responsive patients (n = 40) and TR patients (n = 42), and healthy controls (n = 83). Clinical symptoms, neurocognitive function, and structural images were assessed. We performed group comparisons, and explored association of cortical thickness and cognition with TR. The TR patients showed significantly more severe clinical symptoms and cognitive impairment relative to the treatment-responsive group. Compared to healthy controls, 56 of 68 brain regions showed significantly reduced cortical thickness in patients with schizophrenia. Reductions in five regions were significantly associated with TR (reduction in TR relative to treatment-responsive patients), i.e. in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cognition deficits were also significantly correlated with cortical thickness in these five regions in patients with schizophrenia. Cortical thickness of the right caudal middle frontal gyrus, superior frontal cortex and pars opercularis of the inferior frontal cortex also significantly mediated effects of cognitive deficits on TR. Treatment resistance in schizophrenia was associated with reduced thickness in the right caudal middle frontal gyrus, superior frontal cortex, fusiform gyrus, pars opercularis of the inferior frontal cortex, and supramarginal cortex. Cortical abnormalities further mediate cognitive deficits known to be associated with TR.

Managing treatment resistance in schizophrenia: A joint study in Hong Kong and Singapore

This study surveyed clinicians in psychiatry in Hong Kong and Singapore to understand their familiarity and prescribing practices in treatment-resistant schizophrenia (TRS) and clozapine-resistant schizophrenia (CRS). All clinicians in psychiatry in both regions were invited through email to participate in an anonymous online survey. The survey collected information on the participants' characteristics, their familiarity and experience with clozapine use, and their treatment practices in TRS and CRS. Data collection took place between September 2019 and February 2020 in Hong Kong and December 2018 and March 2019 in Singapore. 261 clinicians responded to the survey, with response rates of 19% (105 out of 556 participants) in Hong Kong and 50% (156 out of 309 participants) in Singapore. The majority of respondents (99.0% in Hong Kong; 87.9% in Singapore) were familiar with treatment guidelines for TRS. However, approximately half (54.2% in Hong Kong; 41.7% in Singapore) delayed the prescription of clozapine when indicated. In terms of alternatives to clozapine, approximately half or more of the clinicians in both regions would use high dose antipsychotics, long-acting injectable antipsychotics, antipsychotic polypharmacy, while the adjuvant use of mood stabilizers and electroconvulsive therapy differed between the two regions. In those with CRS, between 10 and 20% of the respondents added adjuvant mood stabilizers or antipsychotics, and 3-10% would use an antidepressant. Clozapine delays occur in spite of clinicians' familiarity with treatment guidelines. More research is needed to guide the use of augmentation strategies and the search for effective treatments beyond clozapine.

A predictor model of treatment resistance in schizophrenia using data from electronic health records.

ObjectivesTo develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs.MethodsWe used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records.ResultsWe reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel’s C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic.ConclusionsRoutinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS.

Neuromelanin MRI as Biomarker for Treatment Resistance in First Episode Schizophrenia

Treatment resistance in schizophrenia (TRS) is a major clinical problem with 20-35% of psychotic patients showing non-response to standard antipsychotic treatment. Neuromelanin-sensitive MRI sequence (NM-MR), which indirectly measures dopamine synthesis in the substantia nigra (SN), has potential as biomarker for TRS, since TRS patients have lower dopamine synthesis than treatment responders with positron emission tomography imaging. NM-MRI indeed shows increased signal in schizophrenia patients, but has not yet been tested in TRS.

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.

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia

About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

Exploring the interplay between kynurenine pathway, cognition, metabolic syndrome and treatment resistance in schizophrenia

Exploring the interplay between kynurenine pathway, cognition, metabolic syndrome and treatment resistance in schizophrenia

Complete blood count inflammatory markers in treatment-resistant schizophrenia: Evidence of association between treatment responsiveness and levels of inflammation

Accumulating evidence suggests that the variable response to antipsychotic treatment in schizophrenia reflects distinct biological subtypes. The pathophysiology of schizophrenia is associated with alteration in the immune system which can be measured with complete blood count (CBC) markers of systemic inflammation, including the neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR). While previous research suggested a decrease in CBC inflammatory markers following treatment, it is unknown if treatment or response to treatment is associated with CBC markers in treatment-resistant schizophrenia. Here, we retrospectively analyzed the CBC at admission and discharge in schizophrenia inpatients classified as treatment-responsive, treatment-resistant, and ultra-treatment-resistant. Despite similar NLR at admission, the subtypes manifested different changes in NLR during treatment resulting in significant differences at discharge. Only the treatment-responsive group presented a significant decrease in inflammatory markers after treatment. Additionally, we found that the responsive group had a higher PLR at admission and was the only subgroup to demonstrate a significant reduction following treatment. In sum, our results support the idea that persistent inflammation is a biological trait marker of treatment resistance in schizophrenia.

Antipsychotic treatment strategies for acute phase and treatment resistance in schizophrenia: A systematic review of the guidelines and algorithms

BackgroundTo summarize the current state of knowledge on antipsychotic treatment strategies for the acute phase and treatment resistance in schizophrenia, we conducted a systematic review of guidelines and algorithms. MethodsWe conducted a systematic literature search to identify clinical guidelines and algorithms on this topic using MEDLINE and Embase. We extracted information on recommendations for antipsychotic treatment strategies, including those for non-response (i.e., increasing antipsychotic dose and switching to another antipsychotic) and treatment resistance. ResultsWe identified a total of 17 guidelines/algorithms in various countries that were published after 2011. With respect to antipsychotic dose, most of the guidelines (N = 10/11) agreed starting with a low dose or the lowest licensed/effective dose and then titrating the dose upwards. Regarding antipsychotic treatment strategies for non-response, all of the guidelines (N = 9/9) recommended increasing antipsychotic dose towards the upper end of its approved dose range. Five guidelines suggested for increasing beyond the therapeutic dose range in exceptional cases, while overall 10 guidelines including them were negative about such strategy. The vast majority of guidelines (N = 16/17) recommended switching to another antipsychotic for non-response; however, some guidelines mentioned the lack of evidence for these strategies other than the use of clozapine. All the guidelines (N = 17/17) endorsed initiating clozapine after failure to respond to 2 different antipsychotics. Four guidelines endorsed an early use of clozapine, yet as the third antipsychotic. ConclusionThe currently available guidelines and algorithms recommended increasing antipsychotic dose and switching to another antipsychotic, particularly clozapine for treatment-resistant schizophrenia, during the acute phase of schizophrenia for non-response.

N-methyl-D-aspartate Receptor Antibody and White Matter Deficits in Schizophrenia Treatment-Resistance.

Insufficient or lack of response to antipsychotic medications in some patients with schizophrenia is a major challenge in psychiatry, but the underlying mechanisms remain unclear. Two seemingly unrelated observations, cerebral white matter and N-methyl-D-aspartate receptor (NMDAR) hypofunction, have been linked to treatment-resistant schizophrenia (TRS). As NMDARs are critical to axonal myelination and signal transduction, we hypothesized that NMDAR antibody (Ab), when present in schizophrenia, may impair NMDAR functions and white matter microstructures, contributing to TRS. In this study, 50 patients with TRS, 45 patients with nontreatment-resistant schizophrenia (NTRS), 53 patients with schizophrenia at treatment initiation schizophrenia (TIS), and 90 healthy controls were enrolled. Serum NMDAR Ab levels and white matter diffusion tensor imaging fractional anisotropy (FA) were assessed. The white matter specificity effects by NMDAR Ab were assessed by comparing with effects on cortical and subcortical gray matter. Serum NMDAR Ab levels of the TRS were significantly higher than those of the NTRS (P = .035). In patients with TRS, higher NMDAR Ab levels were significantly associated with reduced whole-brain average FA (r = -.37; P = .026), with the strongest effect at the genu of corpus callosum (r = -.50; P = .0021, significant after correction for multiple comparisons). Conversely, there was no significant correlation between whole-brain or regional cortical thickness or any subcortical gray matter structural volume and NMDAR Ab levels in TRS. Our finding highlights a potential NMDAR mechanism on white matter microstructure impairment in schizophrenia that may contribute to their treatment resistance to antipsychotic medications.

Using data from schizophrenia outcome study to estimate the time to treatment outcome and the early-response cut-off score that predicts outcome at week 16

Background Being able to make an estimation of the time to clinical outcome, and making predictions early during treatment about the possibility of later response/non-response to treatment, is an important asset that can help to guide treatment strategies and counsel patients and caregivers about treatment expectations. Objectives The study aimed to determine the time course to treatment outcome and the psychopathological cut-off score at week 4 that predicts outcome at week 16. Methods This was a naturalistic follow-up study of 160 incident cases of schizophrenia over 16 weeks. Four intervals of follow-up clinical assessments were done. Standard criteria for response and remission were applied. Results The mean (median) times, in weeks, to response and remission using Brief Psychiatric Rating Scale (BPRS) data were 8.1(8.0); 8.4(8.0); and 10.9 (12.0), respectively. The Areas Under the Curves were high, for response (0.909; 95% C.I., 0.85-0.97) and remission (0.86; 95% C.I., 0.81 -0.94) at week 16. A cut-off score of 20.7% reduction in the total BPRS score at week 4, predicted response status (79.5% sensitivity, 84.2% specificity) and remission status (77.6% sensitivity, 73.3% specificity) at week 16. In addition, a cut-off of 10.21% reduction in the total Scale for Assessment of Negative Symptoms (SANS) score at week 4, predicted response (70.8% sensitivity, 95.5% specificity) at week 16. Discussion The results are in line with the general clinical impression that, by 2 months, most acutely ill inpatients are fit for discharge; and introduced for further investigation 10.21% reduction in SANS Score as a marker of treatment resistance in schizophrenia.

S67. TREATMENT-RESISTANCE AFFECTS LONG-TERM COGNITIVE TRAJECTORIES IN SCHIZOPHRENIA: A LONGITUDINAL STUDY

BackgroundSchizophrenia is a highly heterogeneous disorder, and despite extensive research progress approximately 30% of patients with schizophrenia show poor response to first-line antipsychotics, denoted as treatment-resistant schizophrenia (TRS). Meta-analytic evidence showed that clozapine is the most effective antipsychotic for TRS, although 40% of TRS patients do not respond even to clozapine (ultra-treatment-resistant schizophrenia -UTR). Recent studies indicated that TRS is neurobiologically and categorically distinct from treatment-responsive schizophrenia, being associated with elevated glutamate levels in the anterior cingulate cortex and unaltered striatal dopamine synthesis. Moreover, the striking majority of TRS patients do not respond to first-line antipsychotic therapy since disease onset and present more severe cognitive deficits since first episode of psychosis, further suggesting the presence of a distinct and more disrupted neurobiological substrate. It is widely known that cognitive impairment is a core feature of schizophrenia and determines a significant detrimental impact on long-term functional outcome, which represents the ultimate treatment goal. However, despite the central role of cognition in schizophrenia, to date no study has investigated longitudinal cognitive outcome among TRS patients.Based on these evidences, the aim of this study is to evaluate longitudinal cognitive trajectories in a sample of clinically stabilized patients with schizophrenia, stratified according to antipsychotic response. We hypothesized that treatment-resistance is associated with a more severe long-term cognitive decline.MethodsWe enrolled 93 patients with schizophrenia (DSM-V), stratified as follows: 32 first-line responders (FLR), 42 TRS and 19 UTR. Cognition was longitudinally assessed at baseline and at least after 6 years of follow-up (mean: 9.3±2.8 years) using the Brief Assessment of Cognition in Schizophrenia (BACS). From BACS subscores we calculated for each patient a Cognitive Index, as a measure of overall cognitive functioning. In order to quantify global cognitive functioning changes during the course of illness, we estimated effect size score for Cognitive Index using Cohen’s d. Finally, General linear Models (GLM) were performed with overall cognitive index effect size as dependent variable, treatment (FLR/TRS/UTR) as categorical variable and age, duration of illness and education as covariates.ResultsThe first GLM (FLR vs TRS+UTR) showed a significant main effect of treatment (F=7.34, p=0.01), with worse cognitive outcome between resistant patients. Consistently, the second GLM (FLR/TRS/UTR) resulted significant as well (F=17.90, p<0.001), with UTR group showing worse cognitive trajectory (Fisher’s post-hoc: p<0.001, UTR Cognitive Index effect size = -0.7).DiscussionThis is the first study to longitudinally evaluate cognitive trajectories of patients with schizophrenia according to their antipsychotic response. We showed that treatment resistance is associated with a more severe cognitive decline, with worse outcome among UTR patients. These data suggest that greater severity of treatment resistance in schizophrenia is associated with greater cognitive impairment, possibly due to the presence of a distinct and more disrupted neurobiological substrate that affects both cognition and antipsychotic response. These findings further highlight the necessity of early individuation and tailored pharmacological treatment for TRS patients, in order to improve long-term clinical, cognitive and functional outcome.