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

Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia. Of those affected, 70–84% are reported to be treatment resistant from the outset. This raises the possibility that the neurobiological mechanisms of treatment resistance emerge before the onset of psychosis and have a neurodevelopmental origin. Neuropsychological investigations can offer important insights into the nature, origin and pathophysiology of treatment-resistant schizophrenia (TRS), but methodological limitations in a still emergent field of research have obscured the neuropsychological discriminability of TRS. We report on the first systematic review and meta-analysis to investigate neuropsychological differences between TRS patients and treatment-responsive controls across 17 published studies (1864 participants). Five meta-analyses were performed in relation to (1) executive function, (2) general cognitive function, (3) attention, working memory and processing speed, (4) verbal memory and learning, and (5) visual−spatial memory and learning. Small-to-moderate effect sizes emerged for all domains. Similarly to previous comparisons between unselected, drug-naïve and first-episode schizophrenia samples v. healthy controls in the literature, the largest effect size was observed in verbal memory and learning [dl = −0.53; 95% confidence interval (CI) −0.29 to −0.76; z = 4.42; p < 0.001]. A sub-analysis of language-related functions, extracted from across the primary domains, yielded a comparable effect size (dl = −0.53, 95% CI −0.82 to −0.23; z = 3.45; p < 0.001). Manipulating our sampling strategy to include or exclude samples selected for clozapine response did not affect the pattern of findings. Our findings are discussed in relation to possible aetiological contributions to TRS

A taxonomy of theory of mind measures and their relationship with alexithymia

Theory of Mind (ToM), the ability to represent the mental states of oneself and others, is an essential social skill disrupted across many psychiatric conditions. The transdiagnostic nature of ToM impairment means it is plausible that ToM impairment is related to alexithymia (difficulties identifying and describing one’s own emotions), as alexithymia is seen across psychiatric conditions. Whilst many studies have examined links between alexithymia and ToM, results are mixed. Therefore, the purpose of this systematic review is to provide a taxonomy of ToM tests and assess their relationship with alexithymia. Tests are grouped according to whether they assess propensity to engage spontaneously in ToM or accuracy of ToM inferences, with tests further subdivided into those that do, and do not, require emotion recognition. A review of 63 suitable studies suggests that alexithymia is often associated with reduced ToM, and inaccurate ToM when tasks require emotion recognition. This latter finding appears due to impaired emotion recognition, rather than ToM impairment per se. Further directions and considerations for future research are discussed

Cross-sectional study comparing cognitive function in treatment responsive versus treatment non-responsive schizophrenia: evidence from the STRATA study

Background 70%–84% of individuals with antipsychotic treatment resistance show non-response from the first episode. Emerging cross-sectional evidence comparing cognitive profiles in treatment resistant schizophrenia to treatment-responsive schizophrenia has indicated that verbal memory and language functions may be more impaired in treatment resistance. We sought to confirm this finding by comparing cognitive performance between antipsychotic non-responders (NR) and responders (R) using a brief cognitive battery for schizophrenia, with a primary focus on verbal tasks compared against other measures of cognition. Design Cross-sectional. Setting This cross-sectional study recruited antipsychotic treatment R and antipsychotic NR across four UK sites. Cognitive performance was assessed using the Brief Assessment of Cognition in Schizophrenia (BACS). Participants One hundred and six participants aged 18–65 years with a diagnosis of schizophrenia or schizophreniform disorder were recruited according to their treatment response, with 52 NR and 54 R cases. Outcomes Composite and subscale scores of cognitive performance on the BACS. Group (R vs NR) differences in cognitive scores were investigated using univariable and multivariable linear regressions adjusted for age, gender and illness duration. Results Univariable regression models observed no significant differences between R and NR groups on any measure of the BACS, including verbal memory (ß=−1.99, 95% CI −6.63 to 2.66, p=0.398) and verbal fluency (ß=1.23, 95% CI −2.46 to 4.91, p=0.510). This pattern of findings was consistent in multivariable models. Conclusions The lack of group difference in cognition in our sample is likely due to a lack of clinical distinction between our groups. Future investigations should aim to use machine learning methods using longitudinal first episode samples to identify responder subtypes within schizophrenia, and how cognitive factors may interact within this

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 preexisting 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.Funding: This work was supported by a Stratified Medicine Programme grant to J.H.M from the Medical Research Council (grant number MR/L011794/1 which funded the research and supported S.E.S., A.F.P., R.M.M., J.T.R.W. & J.H.M.) E.M’s PhD is funded by the MRC-doctoral training partnership studentship in Biomedical Sciences at King’s College London. J.H.M, E.K, R.M.M are part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. A.P.K. is funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. O.A. is further funded by an NIHR Post-Doctoral Fellowship (PDF2018-11-ST2-020). The views expressed are those of the authors and not necessarily those of the NHS, the MRC, the NIHR or the Department of Health. E.M.J. is supported by the UCL/UCLH Biomedical Research Centre. The AESOP (London, UK) cohort was funded by the UK Medical Research Council (Ref: G0500817). The Bologna (Italy) cohort was funded by the European Community’s Seventh Framework Program under grant agreement (agreement No. HEALTH-F2-2010–241909, Project EU-GEI). The GAP (London, UK) cohort was funded by the UK National Institute of Health Research (NIHR) Specialist Biomedical Research Centre for Mental Health, South London and Maudsley NHS Mental Health Foundation Trust (SLaM) and the Institute of Psychiatry, Psychology, and Neuroscience at King’s College London; Psychiatry Research Trust; Maudsley Charity Research Fund; and the European Community’s Seventh Framework Program grant (agreement No. HEALTH-F2-2009-241909, Project EU-GEI). The Oslo (Norway) cohort was funded by the Stiftelsen KG Jebsen, Research Council of Norway (#223273, under the Centers of Excellence funding scheme, and #300309, #283798) and the South-Eastern Norway Regional Health Authority (#2006233, #2006258, #2011085, #2014102, #2015088, #2017-112). The Paris (France) cohort was funded by European Community’s Seventh Framework Program grant (agreement No. HEALTHF2-2010–241909, Project EU-GEI). The Santander (Spain) cohort was funded by the following grants (to B.C.F): Instituto de Salud Carlos III, FIS 00/3095, PI020499, PI050427, PI060507, Plan Nacional de Drogas Research Grant 2005-Orden sco/3246/2004, and SENY Fundatio Research Grant CI 2005-0308007, Fundacion Marques de Valdecilla A/02/07 and API07/011. SAF2016-76046-R and SAF2013-46292-R (MINECO and FEDER). The West London (UK) cohort was funded The Wellcome Trust (Grant Numbers: 042025; 052247; 064607)

PsyCog:A computerised mini battery for assessing cognition in psychosis

Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) ( N = 135), Clinical High Risk (CHR) ( N = 233), and First Episode Psychosis (FEP) ( N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design. </p

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

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

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

Importance: 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. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). 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]). Main Outcomes and Measures: 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. Results: The study included a total of 85490 participants (48635 [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). Conclusions and Relevance: 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

No effect of age on emotion recognition after accounting for cognitive factors and depression

A decline in emotion recognition ability across the lifespan has been well documented. However, whether age predicts emotion recognition difficulties after accounting for potentially confounding factors which covary with age remains unclear. Although previous research suggested that age-related decline in emotion recognition ability may be partly a consequence of cognitive (fluid intelligence, processing speed) and affective (e.g., depression) factors, recent theories highlight a potential role for alexithymia (difficulty identifying and describing one’s emotions) and interoception (perception of the body’s internal state). This study therefore aimed to examine the recognition of anger and disgust across the adult lifespan in a group of 140 20–90-year-olds to see whether an effect of age would remain after controlling for a number of cognitive and affective factors potentially impacted by age. In addition, using an identity recognition control task, the study aimed to determine whether the factors accounting for the effects of age on emotion discrimination also contribute towards generalised face processing difficulties. Results revealed that discrimination of disgust and anger across the lifespan was predicted by processing speed and fluid intelligence, and negatively by depression. No effect of age was found after these factors were accounted for. Importantly, these effects were specific to emotion discrimination; only crystallised intelligence accounted for unique variance in identity discrimination. Contrary to expectations, although interoception and alexithymia were correlated with emotion discrimination abilities, these factors did not explain unique variance after accounting for other variables