The response to antipsychotic treatment in schizophrenia appears to vary, and as such it has been proposed that different subtypes of schizophrenia exist, defined by treatment-response. This has not ...been formally examined using meta-analysis. Randomised controlled trials comparing placebo and antipsychotics in acute treatment of schizophrenia listed in PubMed, EMBASE and PsycINFO from inception until 30 November 2018 were examined. Relative variability of symptomatic improvement in antipsychotic-treated individuals compared to placebo-treated individuals was quantified using coefficient of variation ratio (CVR). Mean difference in symptom change was quantified using Hedges' g. In addition, individual patient data from two clinical trials was examined in terms of both the distribution of total symptom change, and the variability of individual symptoms and symptom factors. In total, 11,006 articles were identified. Sixty six met inclusion criteria, reporting on 17,202 patients. Compared with placebo, antipsychotic-treated patients demonstrated greater total symptom improvement (g = 0.47, p < 0.001) and reduced variability in symptomatic improvement for total (CVR = 0.86, p < 0.001), positive (CVR = 0.89, p < 0.001), and negative symptoms (CVR = 0.86, p = 0.001). Lower variability in antipsychotic-response relative to placebo was associated with studies published earlier (z = 3.98, p < 0.001), younger patients (z = 3.07, p = 0.002), higher dose treatments (z = -2.62, p = 0.009), and greater mean-difference in symptom-change (z = -5.70, p < 0.001). In the individual patient dataset (N = 522 patients), antipsychotic treated patients did not show significantly increased variability for any individual symptom, and there was no evidence of a bimodal distribution of response. Compared to placebo, antipsychotic treatment shows greater improvement and lower variability of change in total, positive and negative symptoms. This is contrary to the hypothesis that there is a subtype of antipsychotic non-responsive schizophrenia. Instead our findings, provide evidence for a relatively homogeneous effect of antipsychotic treatment in improving symptoms of schizophrenia.
A wide range of neuropsychiatric disorders, from schizophrenia to drug addiction, involve abnormalities in both the mesolimbic dopamine system and the cortical salience network. Both systems play a ...key role in the detection of behaviorally relevant environmental stimuli. Although anatomical overlap exists, the functional relationship between these systems remains unknown. Preclinical research has suggested that the firing of mesolimbic dopamine neurons may activate nodes of the salience network, but in vivo human research is required given the species-specific nature of this network.
We employed positron emission tomography to measure both dopamine release capacity (using the D2/3 receptor ligand 11C-PHNO, n = 23) and dopamine synthesis capacity (using 18F-DOPA, n = 21) within the ventral striatum. Resting-state functional magnetic resonance imaging was also undertaken in the same individuals to investigate salience network functional connectivity. A graph theoretical approach was used to characterize the relationship between dopamine measures and network connectivity.
Dopamine synthesis capacity was associated with greater salience network connectivity, and this relationship was particularly apparent for brain regions that act as information-processing hubs. In contrast, dopamine release capacity was associated with weaker salience network connectivity. There was no relationship between dopamine measures and visual and sensorimotor networks, indicating specificity of the findings.
Our findings demonstrate a close relationship between the salience network and mesolimbic dopamine system, and they are relevant to neuropsychiatric illnesses in which aberrant functioning of both systems has been observed.
Two important clinical questions are whether there is a subtype of schizophrenia which responds differently to clozapine relative to other antipsychotics, and whether greater efficacy of clozapine is ...dependent on the degree of treatment-resistance. The authors address this by examining both variability and magnitude of response in patients treated with clozapine and other antipsychotics for both treatment-resistant schizophrenia (TRS) and non-resistant schizophrenia. Double-blind randomised controlled trials comparing clozapine with other antipsychotics in patients with schizophrenia were identified using five databases. Standard deviations and means of change in total, positive, and negative symptoms were extracted. Variability ratio (VR) and coefficient of variation ratio (CVR) were used to quantify relative variability in symptom change. Hedges' g was used to quantify mean differences. Ten TRS studies (n = 822) and 29 non-TRS studies (n = 2566) were meta-analysed. Relative variability in change of total symptoms did not differ significantly between clozapine and other antipsychotics in TRS studies (VR = 1.84; 95%CI, 0.85-4.02). These findings were similar with CVR, and for positive and negative symptoms. Clozapine was superior to other antipsychotics in improving total symptoms in both TRS (g = 0.34; 95%CI, 0.13-0.56) and non-TRS (g = 0.20; 95%CI, 0.08-0.32) studies. Furthermore, clozapine was superior in improving positive symptoms in both study groups, but not for negative symptoms. Pooled effect sizes showed no significant difference between TRS and non-TRS studies. These findings do not support a subtype of schizophrenia which responds specifically to clozapine. Clozapine is more effective than other antipsychotics irrespective of treatment-resistance, arguing for its use more generally in schizophrenia. PROSPERO CRD42018086507.
First-episode psychosis (FEP) is associated with metabolic alterations. However, it is not known if there is heterogeneity in these alterations beyond what might be expected due to normal individual ...differences, indicative of subgroups of patients at greater vulnerability to metabolic dysregulation.
We employed meta-analysis of variance, indexed using the coefficient of variation ratio (CVR), to compare variability of the following metabolic parameters in antipsychotic naïve FEP and controls: fasting glucose, glucose post-oral glucose tolerance test (OGTT), fasting insulin, insulin resistance, haemoglobin A
(HbA
), total-cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol, and triglycerides. Standardised mean difference in metabolic parameters between groups was also calculated; meta-regression analyses examined physiological/demographic/psychopathological moderators of metabolic change.
Twenty-eight studies were analysed (1716 patients, 1893 controls). Variability of fasting glucose CVR = 1.32; 95% confidence interval (CI) 1.12-1.55;
= 0.001, glucose post-OGTT (CVR = 1.43; 95% CI 1.10-1.87;
= 0.008), fasting insulin (CVR = 1.31; 95% CI 1.09-1.58;
= 0.01), insulin resistance (CVR = 1.34; 95% CI 1.12-1.60;
= 0.001), HbA
(CVR = 1.18; 95% CI 1.06-1.27;
< 0.0001), total-cholesterol (CVR = 1.15; 95% CI 1.01-1.31;
= 0.03), LDL-cholesterol (CVR = 1.28; 95% CI 1.09-1.50;
= 0.002), and HDL-cholesterol (CVR = 1.15; 95% CI 1.00-1.31;
< 0.05), but not triglycerides, was greater in patients than controls. Mean glucose, glucose post-OGTT, fasting insulin, insulin resistance, and triglycerides were greater in patients; mean total-cholesterol and HDL-cholesterol were reduced in patients. Increased symptom severity and female sex were associated with worse metabolic outcomes.
Patients with FEP present with greater variability in metabolic parameters relative to controls, consistent with a subgroup of patients with more severe metabolic changes compared to others. Understanding determinants of metabolic variability could help identify patients at-risk of developing metabolic syndrome. Female sex and severe psychopathology are associated with poorer metabolic outcomes, with implications for metabolic monitoring in clinical practice.
Rationale
Anterior cingulate cortex (ACC) glutamatergic abnormalities are reported in treatment-resistant schizophrenia (TRS) and implicated in functional dysconnectivity and psychopathology. ...Preclinical evidence indicates riluzole reduces synaptic glutamate. However, it is unknown whether riluzole can modulate glutamate metabolite levels and associated functional connectivity in TRS.
Objectives
To examine the relationship between glutamatergic function and cortical connectivity and determine if riluzole can modulate glutamate metabolite levels and cortical functional connectivity in TRS.
Methods
Nineteen TRS patients and 18 healthy volunteers (HV) underwent magnetic resonance imaging consisting of MR spectroscopy measuring ACC glutamate plus glutamine (Glx), fMRI measuring resting ACC-functional connectivity, and arterial spin labelling measuring regional cerebral blood flow (rCBF), and clinical measures. They then received 50 mg riluzole twice daily for 2 days when imaging was repeated.
Results
Baseline (pre-riluzole) Glx levels were correlated directly with negative symptom severity (
r
= 0.49;
p
= 0.03) and inversely with verbal learning in TRS (
r
= − 0.63;
p
= 0.002), but not HV (
r
= − 0.24;
p
= 0.41). Connectivity between the ACC and anterior prefrontal cortex (aPFC) was correlated with verbal learning in TRS (
r
= 0.49;
p
= 0.04), but not HV (
r
= 0.28;
p
= 0.33). There was a significant group × time interaction effect on Glx levels (
p
< 0.05) and on ACC connectivity to the aPFC (
p
< 0.05, FWE-corrected). Riluzole decreased Glx and increased ACC-aPFC connectivity in TRS relative to HV. Change in Glx correlated inversely with change in ACC-aPFC connectivity in TRS (
r
= − 0.52;
p
= 0.02) but not HV (
r
= 0.01;
p
= 0.98). Riluzole did not alter rCBF (
p
> 0.05), indicating absence of a non-specific blood flow effect.
Conclusion
Results indicate glutamatergic function and cortical connectivity are linked to symptoms and cognitive measures and that it is possible to pharmacologically modulate them in TRS.
The dichotomies of ‘typical/atypical’ or ‘first/second generation’ have been employed for several decades to classify antipsychotics, but justification for their use is not clear. In the current ...analysis we argue that this classification is flawed from both clinical and pharmacological perspectives. We then consider what approach should ideally be employed in both clinical and research settings.
Vano et al discuss the study by van der Pluijm et al on the ability of neuromelanin-sensitive MRI (NM-MRI) to predict treatment response in schizophrenia. Neuromelanin is a product of dopamine ...metabolism that can be indexed in vivo using NM-MRI without the need for a radiotracer or contrast agent. The authors used NM-MRI of the SN-VTA in patients with first-episode psychosis and matched healthy control subjects. As per the naturalistic design, patients received antipsychotic treatment based on standard guidelines by their treating psychiatrist. At 6 months, patients were reassessed and classified as treatment nonresponders or responders, and a follow-up NM-MRI scan was performed. Patients also received clinical ratings on the Positive and Negative Syndrome Scale.
Chronic psychosocial adversity induces vulnerability to mental illnesses. Animal studies demonstrate that this may be mediated by dopaminergic dysfunction. We therefore investigated whether long-term ...exposure to psychosocial adversity was associated with dopamine dysfunction and its relationship to psychological and physiological responses to acute stress. Using 3,4-dihydroxy-6-
F-fluoro-
-phenylalanine (
F-DOPA) positron emission tomography (PET), we compared dopamine synthesis capacity in
= 17 human participants with high cumulative exposure to psychosocial adversity with
= 17 age- and sex-matched participants with low cumulative exposure. The PET scan took place 2 hr after the induction of acute psychosocial stress using the Montréal Imaging Stress Task to induce acute psychosocial stress. We found that dopamine synthesis correlated with subjective threat and physiological response to acute psychosocial stress in the low exposure group. Long-term exposure to psychosocial adversity was associated with dampened striatal dopaminergic function (p=0.03,
= 0.80) and that psychosocial adversity blunted physiological yet potentiated subjective responses to acute psychosocial stress. Future studies should investigate the roles of these changes in vulnerability to mental illnesses.
Dopaminergic and glutamatergic dysfunction is believed to play a central role in the pathophysiology of schizophrenia. However, it is unclear if abnormalities predate the onset of schizophrenia in ...individuals at high clinical or genetic risk for the disorder. We systematically reviewed and meta‐analyzed studies that have used neuroimaging to investigate dopamine and glutamate function in individuals at increased clinical or genetic risk for psychosis. EMBASE, PsycINFO and Medline were searched form January 1, 1960 to November 26, 2020. Inclusion criteria were molecular imaging measures of striatal presynaptic dopaminergic function, striatal dopamine receptor availability, or glutamate function. Separate meta‐analyses were conducted for genetic high‐risk and clinical high‐risk individuals. We calculated standardized mean differences between high‐risk individuals and controls, and investigated whether the variability of these measures differed between the two groups. Forty‐eight eligible studies were identified, including 1,288 high‐risk individuals and 1,187 controls. Genetic high‐risk individuals showed evidence of increased thalamic glutamate + glutamine (Glx) concentrations (Hedges’ g=0.36, 95% CI: 0.12‐0.61, p=0.003). There were no significant differences between high‐risk individuals and controls in striatal presynaptic dopaminergic function, striatal D2/D3 receptor availability, prefrontal cortex glutamate or Glx, hippocampal glutamate or Glx, or basal ganglia Glx. In the meta‐analysis of variability, genetic high‐risk individuals showed reduced variability of striatal D2/D3 receptor availability compared to controls (log coefficient of variation ratio, CVR=–0.24, 95% CI: –0.46 to –0.02, p=0.03). Meta‐regressions of publication year against effect size demonstrated that the magnitude of differences between clinical high‐risk individuals and controls in presynaptic dopaminergic function has decreased over time (estimate=–0.06, 95% CI: –0.11 to –0.007, p=0.025). Thus, other than thalamic glutamate concentrations, no neurochemical measures were significantly different between individuals at risk for psychosis and controls. There was also no evidence of increased variability of dopamine or glutamate measures in high‐risk individuals compared to controls. Significant heterogeneity, however, exists between studies, which does not allow to rule out the existence of clinically meaningful differences.
Globally, there are more than 25 licensed antipsychotic medications. Antipsychotics are commonly described as either typical or atypical, but this dichotomous classification does not reflect the ...diversity of their pharmacological and clinical profiles. There is a need for a data-driven antipsychotic classification scheme suitable for clinicians and researchers that maps onto both pharmacological and clinical effects. Receptor affinity provides one starting point for such a scheme.
We analyzed affinities of 27 antipsychotics for 42 receptors from 3325 in vitro receptor binding studies. We used a clustering algorithm to group antipsychotics based on receptor affinity. Using a machine learning model, we examined the ability of this grouping to predict antipsychotic-induced clinical effects quantified according to an umbrella review of clinical trial and treatment guideline data.
Clustering resulted in 4 groups of antipsychotics. The predominant receptor affinity and clinical effect “fingerprints” of these 4 groups were defined as follows: group 1, muscarinic (M2–M5) receptor antagonism (cholinergic and metabolic side effects); group 2, dopamine (D2) partial agonism and adrenergic antagonism (overall low side-effect burden); group 3, serotonergic and dopaminergic antagonism (overall moderate side-effect burden); and group 4, dopaminergic antagonism (extrapyramidal side effects and hyperprolactinemia). Groups 1 and 4 were more efficacious than groups 2 and 3. The classification was shown to predict out-of-sample clinical effects of individual drugs.
A receptor affinity–based grouping not only reflects compound pharmacology but also detects meaningful clinical differences. This approach has the potential to benefit both patients and researchers by guiding treatment and informing drug development.
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