Addressing the unmet needs of patients with persistent negative symptoms of schizophrenia: emerging pharmacological treatment options.
ABSTRACT: The negative symptoms of schizophrenia represent an impairment of normal emotional responses, thought processes and behaviors, and include blunting or flattening of affect, alogia/aprosody, avolition/apathy, anhedonia, and asociality. Negative symptoms contribute to a reduced quality of life, increased functional disability, increased burden of illness, and poorer long-term outcomes, to a greater degree than positive symptoms. Primary negative symptoms are prominent and persistent in up to 26% of patients with schizophrenia, and they are estimated to occur in up to 58% of outpatients at any given time. Negative symptoms respond less well to medications than positive symptoms, and to date treatment options for negative symptoms have been limited, with no accepted standard treatment. Modest benefits have been reported with a variety of different agents, including second-generation antipsychotics and add-on therapy with antidepressants and other pharmacological classes. Recent clinical research focusing on negative symptoms target novel biological systems, such as glutamatergic neurotransmission. Different approaches include: enhancing N-methyl-D-aspartate receptor function with agents that bind directly to the glycine ligand site or with glycine reuptake inhibitors; influencing the metabotropic glutamate receptor (mGluR2/3) with positive allosteric modulators; and stimulating nicotinic acetylcholine receptors. In conclusion, the lack of clearly efficacious pharmacological treatments for the management of negative symptoms represents a significant unmet need, especially considering the importance of these symptoms on patient outcomes. Hence, further research to identify and characterize novel pharmacological treatments for negative symptoms is greatly needed.
Project description:Prior studies using exploratory factor analysis provide evidence that negative symptoms are best conceptualized as 2 dimensions reflecting diminished motivation and expression. However, the 2-dimensional model has yet to be evaluated using more complex mathematical techniques capable of testing structure. In the current study, network analysis was applied to evaluate the latent structure of negative symptoms using a community-detection algorithm. Two studies were conducted that included outpatients with schizophrenia (SZ; Study 1: n = 201; Study 2: n = 912) who were rated on the Brief Negative Symptom Scale (BNSS). In both studies, network analysis indicated that the 13 BNSS items divided into 6 negative symptom domains consisting of anhedonia, avolition, asociality, blunted affect, alogia, and lack of normal distress. Separation of these domains was statistically significant with reference to a null model of randomized networks. There has been a recent trend toward conceptualizing the latent structure of negative symptoms in relation to 2 distinct dimensions reflecting diminished expression and motivation. However, the current results obtained using network analysis suggest that the 2-dimensional conceptualization is not complex enough to capture the nature of the negative symptom construct. Similar to recent confirmatory factor analysis studies, network analysis revealed that the latent structure of negative symptom is best conceptualized in relation to the 5 domains identified in the 2005 National Institute of Mental Health consensus development conference (anhedonia, avolition, asociality, blunted affect, and alogia) and potentially a sixth domain consisting of lack of normal distress. Findings have implications for identifying pathophysiological mechanisms and targeted treatments.
Project description:Network analysis was used to examine how densely interconnected individual negative symptom domains are, whether some domains are more central than others, and whether sex influenced network structure. Participants included outpatients with schizophrenia (SZ; n = 201), a bipolar disorder (BD; n = 46) clinical comparison group, and healthy controls (CN; n = 27) who were rated on the Brief Negative Symptom Scale. The mutual information measure was used to construct negative symptom networks. Groups were compared on macroscopic network properties to evaluate overall network connectedness, and microscopic properties to determine which domains were most central. Macroscopic analyses indicated that patients with SZ had a less densely connected negative symptom network than BD or CN groups, and that males with SZ had less densely connected networks than females. Microscopic analyses indicated that alogia and avolition were most central in the SZ group, whereas anhedonia was most central in BD and CN groups. In addition, blunted affect, alogia, and asociality were most central in females with SZ, and alogia and avolition were most central in males with SZ. These findings suggest that negative symptoms may be highly treatment resistant in SZ because they are not very densely connected. Less densely connected networks may make treatments less likely to achieve global reductions in negative symptoms because individual domains function in isolation with little interaction. Sex differences in centralities suggest that the search for pathophysiological mechanisms and targeted treatment development should be focused on different sets of symptoms in males and females.
Project description:The participants in the NIMH-MATRICS Consensus Development Conference on Negative Symptoms recommended that an instrument be developed that measured blunted affect, alogia, asociality, anhedonia, and avolition. The Brief Negative Symptom Scale (BNSS) is a 13-item instrument designed for clinical trials and other studies that measures these 5 domains. The interrater, test-retest, and internal consistency of the instrument were strong, with respective intraclass correlation coefficients of 0.93 for the BNSS total score and values of 0.89-0.95 for individual subscales. Comparisons with positive symptoms and other negative symptom instruments supported the discriminant and concurrent validity of the instrument.
Project description:Progress in the development of new pharmacological and psychosocial treatments for the negative symptoms of schizophrenia is impeded by limitations of available assessment instruments. The multi-site Collaboration to Advance Negative Symptom Assessment in Schizophrenia (CANSAS) was established to develop and validate a new clinical rating scale using a transparent, iterative, and data-driven process. The Clinical Assessment Interview for Negative Symptoms (CAINS) was designed to address limitations of existing measures and assess consensus-based sub-domains, including asociality, avolition, anhedonia, affective blunting, and alogia. The structure and psychometric properties of the CAINS were evaluated in a sample of 281 schizophrenia and schizoaffective outpatients at four sites. Converging structural analyses indicated that the scale was comprised of two moderately correlated factors - one reflecting experiential impairments (diminished motivation and enjoyment of social, vocational, and recreational activities) and one reflecting expressive impairments (diminished non-verbal and verbal communication). Item-level analyses revealed generally good distributional properties, inter-rater agreement, discriminating anchor points, and preliminary convergent and discriminant validity. Results indicate that the CAINS is a promising new measure for quantifying negative symptoms in clinical neuroscience and treatment studies. Results guided item modification or deletion, and the reliability and validity of the revised, shorter version of the CAINS is in the final phase of development within the CANSAS project.
Project description:BACKGROUND:The negative symptoms of schizophrenia include deficits in emotional expression and motivation. These deficits are stable over the course of illness and respond poorly to current medications. Previous studies have focused on negative symptoms as a single category; however, individual symptoms might be related to separate neurological disturbances. We analyzed data from the Functional Biomedical Informatics Research Network dataset to explore the relationship between individual negative symptoms and functional brain activity during an auditory oddball task. METHODS:Functional magnetic resonance imaging was conducted on 89 schizophrenia patients and 106 healthy controls during a two-tone auditory oddball task. Blood oxygenation level-dependent (BOLD) signal during the target tone was correlated with severity of five negative symptom domains from the Scale for the Assessment of Negative Symptoms. RESULTS:The severity of alogia, avolition/apathy and anhedonia/asociality was negatively correlated with BOLD activity in distinct sets of brain regions associated with processing of the target tone, including basal ganglia, thalamus, insular cortex, prefrontal cortex, posterior cingulate and parietal cortex. CONCLUSIONS:Individual symptoms were related to different patterns of functional activation during the oddball task, suggesting that individual symptoms might arise from distinct neural mechanisms. This work has potential to inform interventions that target these symptom-related neural disruptions.
Project description:<b>Background:</b> Negative symptoms are core features of schizophrenia and very challenging to be treated. Identification of their structure is crucial to provide a better treatment. Increasing evidence supports the superiority of a five-factor model (alogia, blunted affect, anhedonia, avolition, and asociality as defined by the NMIH-MATRICS Consensus); however, previous data primarily used the Brief Negative Symptoms Scale (BNSS). This study, including a calibration and a cross-validation sample (<i>n</i> = 268 and 257, respectively) of participants with schizophrenia, used the Clinical Assessment Interview for Negative Symptoms (CAINS) to explore the latent structure of negative symptoms and to test theoretical and data-driven (from this study) models of negative symptoms. <b>Methods:</b> Exploratory factor analysis (EFA) was carried out to investigate the structure of negative symptoms based on the CAINS. Confirmatory factor analysis (CFA) tested in a cross-validation sample four competing theoretical (one-factor, two-factor, five-factor, and hierarchical factor) models and two EFA-derived models. <b>Result:</b> None of the theoretical models was confirmed with the CFA. A CAINS-rated model from EFA consisting of five factors (expression, motivation for recreational activities, social activities, vocational, and close/intimate relationships) was an excellent fit to the data (comparative fix index = 0.97, Tucker-Lewis index = 0.96, and root mean square error of approximation = 0.07). <b>Conclusions:</b> This study cannot support recent data on the superiority of the five-factor model defined by the NMIH-MATRICS consensus and suggests that an alternative model might be a better fit. More research to confirm the structure of negative symptoms in schizophrenia, and careful methodological consideration, should be warranted before a definitive model can put forward and shape diagnosis and treatment of schizophrenia.
Project description:Negative symptoms are prevalent in the prodromal and first-episode phases of psychosis and highly predictive of poor clinical outcomes (eg, liability for conversion and functioning). However, the latent structure of negative symptoms is unclear in the early phases of illness. Determining the latent structure of negative symptoms in early psychosis (EP) is of critical importance for early identification, prevention, and treatment efforts. In the current study, confirmatory factor analysis was used to evaluate latent structure in relation to 4 theoretically derived models: 1. a 1-factor model, 2. a 2-factor model with expression (EXP) and motivation and pleasure (MAP) factors, 3. a 5-factor model with separate factors for the 5 National Institute of Mental Health (NIMH) consensus development conference domains (blunted affect, alogia, anhedonia, avolition, and asociality), and 4. a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 consensus domains. Participants included 164 individuals at clinical high risk (CHR) who met the criteria for a prodromal syndrome and 377 EP patients who were rated on the Brief Negative Symptom Scale. Results indicated that the 1- and 2-factor models provided poor fit for the data. The 5-factor and hierarchical models provided excellent fit, with the 5-factor model outperforming the hierarchical model. These findings suggest that similar to the chronic phase of schizophrenia, the latent structure of negative symptom is best conceptualized in relation to the 5 consensus domains in the CHR and EP populations. Implications for early identification, prevention, and treatment are discussed.
Project description:<h4>Objective</h4>Negative symptoms are currently viewed as having a 2-dimensional structure, with factors reflecting diminished expression (EXP) and motivation and pleasure (MAP). However, several factor-analytic studies suggest that the consensus around a 2-dimensional model is premature. The current study investigated and cross-culturally validated the factorial structure of BNSS-rated negative symptoms across a range of cultures and languages.<h4>Method</h4>Participants included individuals diagnosed with a psychotic disorder who had been rated on the Brief Negative Symptom Scale (BNSS) from 5 cross-cultural samples, with a total N = 1691. First, exploratory factor analysis was used to extract up to 6 factors from the data. Next, confirmatory factor analysis evaluated the fit of 5 models: (1) a 1-factor model, 2) a 2-factor model with factors of MAP and EXP, 3) a 3-factor model with inner world, external, and alogia factors; 4) a 5-factor model with separate factors for blunted affect, alogia, anhedonia, avolition, and asociality, and 5) a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 aforementioned domains.<h4>Results</h4>Models with 4 factors or less were mediocre fits to the data. The 5-factor, 6-factor, and the hierarchical second-order 5-factor models provided excellent fit with an edge to the 5-factor model. The 5-factor structure demonstrated invariance across study samples.<h4>Conclusions</h4>Findings support the validity of the 5-factor structure of BNSS-rated negative symptoms across diverse cultures and languages. These findings have important implications for the diagnosis, assessment, and treatment of negative symptoms.
Project description:Background:The "Avolition-apathy" domain of the negative symptoms was found to include different symptoms by factor analytic studies on ratings derived by different scales. In particular, the relationship of anhedonia with this domain is controversial. Recently introduced negative symptom rating scales provide a better assessment of anhedonia, allowing the distinction of anticipatory and consummatory aspects, which might be related to different psychopathological dimensions. The study of associations with external validators, such as electrophysiological, brain imaging or cognitive indices, might shed further light on the status of anhedonia within the Avolition-apathy domain. Objectives:We used brain electrical microstates (MSs), which represent subsecond periods of quasi-stable scalp electrical field, associated with resting-state neural networks (and thus with global patterns of functional connectivity), to test whether the component symptoms of Avolition-apathy share the same correlates. Method:We analyzed multichannel resting EEGs in 142 individuals with schizophrenia (SCZ) and in 64 healthy controls (HC), recruited within the add-on EEG study of the Italian Network for Research on Psychoses. Relative time contribution, duration and occurrence of four MS classes (MS-A/-B/-C/-D) were calculated. Group differences on MS parameters (contribution and duration) and their associations with negative symptom domains (assessed using the Brief Negative Symptoms Scale) were investigated. Results:SCZ, in comparison to HC, showed increased contribution and duration of MS-C. The contribution of MS-A positively correlated with Avolition-apathy, but not with Expressive deficit. Within the Avolition-apathy domain, anticipatory anhedonia, avolition and asociality, but not consummatory anhedonia, showed the same correlations with MS-A contribution. Conclusion:Our findings support the existence of distinct electrophysiological correlates of Avolition-apathy with respect to Expressive deficit, and lend support to the hypothesis that only the anticipatory component of anhedonia shares the same pathophysiological underpinnings of the Avolition-apathy domain.
Project description:Negative symptoms occur in several major mental health disorders with undetermined mechanisms and unsatisfactory treatments; identification of their neural correlates might unveil the underlying pathophysiological basis and pinpoint the therapeutic targets. In this study, participants with major depressive disorder (n?=?24), schizophrenia (n?=?22), and healthy controls (n?=?20) were assessed with 10 frequently used negative symptom scales followed by principal component analysis (PCA) of the scores. A linear model with the prominent components identified by PCA was then regressed on gray and white-matter volumes estimated from T1-weighted magnetic resonance imaging. In depressed patients, negative symptoms such as blunted affect, alogia, withdrawal, and cognitive impairment, assessed mostly via clinician-rated scales were inversely associated with gray matter volume in the bilateral cerebellum. In patients with schizophrenia, anhedonia, and avolition evaluated via self-rated scales inversely related to white-matter volume in the left anterior limb of internal capsule/anterior thalamic radiation and positively in the left superior longitudinal fasiculus. The pathophysiological mechanisms underlying negative symptoms might differ between depression and schizophrenia. These results also point to future negative symptom scale development primarily focused on detecting and monitoring the corresponding changes to brain structure or function.