Mesostriatal Dopaminergic Circuit Dysfunction in Schizophrenia: A Multimodal Neuromelanin-sensitive MRI and [18F]-DOPA PET Study.

BACKGROUND: Striatal hyperdopaminergia is implicated in the pathoetiology of schizophrenia, but how this relates to dopaminergic midbrain activity is unclear. Neuromelanin-sensitive MRI (NM-MRI) provides a marker of long-term dopamine function. We examined if midbrain NM-MRI contrast-to-noise ratio (NM-CNR) was higher in people with schizophrenia relative to controls and if this correlated with dopamine synthesis capacity. METHODS: N=154 participants (n=74 individuals with schizophrenia and n=80 healthy controls) underwent NM-MRI of the substantia nigra and ventral tegmental area (SN-VTA). A subset of the schizophrenia group (n=38) also received [18F]-DOPA PET to measure dopamine synthesis capacity (Kicer) in the SN-VTA and striatum. RESULTS: SN-VTA NM-CNR was significantly higher in patients with schizophrenia relative to controls (effect size=0.38, p=0.019). This effect was greatest for voxels in the medial and ventral SN-VTA. In patients, SN-VTA Kicer positively correlated with SN-VTA NM-CNR (r=0.44, p=0.005) and striatal Kicer (r=0.71, p<0.001). Voxelwise analysis demonstrated that SN-VTA NM-CNR was positively associated with striatal Kicer (r=0.53, p=0.005) and that this relationship appeared strongest between the ventral SN-VTA and associative striatum in schizophrenia. CONCLUSIONS: Our results suggest that neuromelanin levels are higher in patients with schizophrenia relative to controls, particularly in midbrain regions that project to parts of the striatum which receive innervation from the limbic and association cortices. The direct relationship between measures of neuromelanin and dopamine synthesis suggests that these aspects of schizophrenia pathophysiology are linked. Our findings highlight specific mesostriatal circuits as the loci of dopamine dysfunction in schizophrenia and, thus, potential therapeutic targets.

An automatic analysis framework for FDOPA PET neuroimaging.

In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Kicer: for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.

Magnitude and variability of structural brain abnormalities in neuropsychiatric disease: protocol for a network meta-analysis of MRI studies.

INTRODUCTION: Structural MRI is the most frequently used method to investigate brain volume alterations in neuropsychiatric disease. Previous meta-analyses have typically focused on a single diagnosis, thereby precluding transdiagnostic comparisons. METHODS AND ANALYSIS: We will include all structural MRI studies of adults that report brain volumes for participants from at least two of the following diagnostic groups: healthy controls, schizophrenia, schizoaffective disorder, delusional disorder, psychotic depression, clinical high risk for psychosis, schizotypal personality disorder, psychosis unspecified, bipolar disorder, autism spectrum disorder, major depressive disorder, attention deficit hyperactivity disorder, obsessive compulsive disorder, post-traumatic stress disorder, emotionally unstable personality disorder, 22q11 deletion syndrome, generalised anxiety disorder, social anxiety disorder, panic disorder, mixed anxiety and depression. Network meta-analysis will be used to synthesise eligible studies. The primary analysis will examine standardised mean difference in average volume, a secondary analysis will examine differences in variability of volumes. DISCUSSION: This network meta-analysis will provide a transdiagnostic integration of structural neuroimaging studies, providing researchers with a valuable summary of a large literature. PROSPERO REGISTRATION NUMBER: CRD42020221143.

The clinical significance of duration of untreated psychosis: an umbrella review and random-effects meta-analysis.

The idea that a longer duration of untreated psychosis (DUP) leads to poorer outcomes has contributed to extensive changes in mental health ser-vices worldwide and has attracted considerable research interest over the past 30 years. However, the strength of the evidence underlying this notion is unclear. To address this issue, we conducted an umbrella review of available meta-analyses and performed a random-effects meta-analysis of primary studies. MEDLINE, Web of Science, PsycINFO and EMBASE were searched from inception to September 3, 2020 to identify relevant meta-analyses of studies including patients with schizophrenia spectrum disorders, first-episode psychosis, or affective and non-affective psychosis. Thirteen meta-analyses were included, corresponding to 129 individual studies with a total sample size of 25,657 patients. We detected potential violations of statistical assumptions in some of these meta-analyses. We therefore conducted a new random-effects meta-analysis of primary studies. The association between DUP and each outcome was graded according to a standardized classification into convincing, highly suggestive, suggestive, weak, or non-significant. At first presentation, there was suggestive evidence for a relationship between longer DUP and more severe negative symptoms (beta=-0.07, p=3.6×10-5 ) and higher chance of previous self-harm (odds ratio, OR=1.89, p=1.1×10-5 ). At follow-up, there was highly suggestive evidence for a relationship between longer DUP and more severe positive symptoms (beta=-0.16, p=4.5×10-8 ), more severe negative symptoms (beta=-0.11, p=3.5×10-10 ) and lower chance of remission (OR=2.16, p=3.0×10-10 ), and suggestive evidence for a relationship between longer DUP and poorer overall functioning (beta=-0.11, p=2.2×10-6 ) and more severe global psychopathology (beta=-0.16, p=4.7×10-6 ). Results were unchanged when analysis was restricted to prospective studies. These effect sizes are clinically meaningful, with a DUP of four weeks predicting >20% more severe symptoms at follow-up relative to a DUP of one week. We conclude that DUP is an important prognostic factor at first presentation and predicts clinically relevant outcomes over the course of illness. We discuss conceptual issues in DUP research and methodological limitations of current evidence, and provide recommendations for future research.

The efficacy and heterogeneity of antipsychotic response in schizophrenia: A meta-analysis.

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.

Comparative effects of 18 antipsychotics on metabolic function in patients with schizophrenia, predictors of metabolic dysregulation, and association with psychopathology: a systematic review and network meta-analysis.

BACKGROUND: Antipsychotic treatment is associated with metabolic disturbance. However, the degree to which metabolic alterations occur in treatment with different antipsychotics is unclear. Predictors of metabolic dysregulation are poorly understood and the association between metabolic change and change in psychopathology is uncertain. We aimed to compare and rank antipsychotics on the basis of their metabolic side-effects, identify physiological and demographic predictors of antipsychotic-induced metabolic dysregulation, and investigate the relationship between change in psychotic symptoms and change in metabolic parameters with antipsychotic treatment. METHODS: We searched MEDLINE, EMBASE, and PsycINFO from inception until June 30, 2019. We included blinded, randomised controlled trials comparing 18 antipsychotics and placebo in acute treatment of schizophrenia. We did frequentist random-effects network meta-analyses to investigate treatment-induced changes in body weight, BMI, total cholesterol, LDL cholesterol, HDL cholesterol, triglyceride, and glucose concentrations. We did meta-regressions to examine relationships between metabolic change and age, sex, ethnicity, baseline weight, and baseline metabolic parameter level. We examined the association between metabolic change and psychopathology change by estimating the correlation between symptom severity change and metabolic parameter change. FINDINGS: Of 6532 citations, we included 100 randomised controlled trials, including 25 952 patients. Median treatment duration was 6 weeks (IQR 6-8). Mean differences for weight gain compared with placebo ranged from -0·23 kg (95% CI -0·83 to 0·36) for haloperidol to 3·01 kg (1·78 to 4·24) for clozapine; for BMI from -0·25 kg/m2 (-0·68 to 0·17) for haloperidol to 1·07 kg/m2 (0·90 to 1·25) for olanzapine; for total-cholesterol from -0·09 mmol/L (-0·24 to 0·07) for cariprazine to 0·56 mmol/L (0·26-0·86) for clozapine; for LDL cholesterol from -0·13 mmol/L (-0.21 to -0·05) for cariprazine to 0·20 mmol/L (0·14 to 0·26) for olanzapine; for HDL cholesterol from 0·05 mmol/L (0·00 to 0·10) for brexpiprazole to -0·10 mmol/L (-0·33 to 0·14) for amisulpride; for triglycerides from -0·01 mmol/L (-0·10 to 0·08) for brexpiprazole to 0·98 mmol/L (0·48 to 1·49) for clozapine; for glucose from -0·29 mmol/L (-0·55 to -0·03) for lurasidone to 1·05 mmol/L (0·41 to 1·70) for clozapine. Greater increases in glucose were predicted by higher baseline weight (p=0·0015) and male sex (p=0·0082). Non-white ethnicity was associated with greater increases in total cholesterol (p=0·040) compared with white ethnicity. Improvements in symptom severity were associated with increases in weight (r=0·36, p=0·0021), BMI (r=0·84, p<0·0001), total-cholesterol (r=0·31, p=0·047), and LDL cholesterol (r=0·42, p=0·013), and decreases in HDL cholesterol (r=-0·35, p=0·035). INTERPRETATION: Marked differences exist between antipsychotics in terms of metabolic side-effects, with olanzapine and clozapine exhibiting the worst profiles and aripiprazole, brexpiprazole, cariprazine, lurasidone, and ziprasidone the most benign profiles. Increased baseline weight, male sex, and non-white ethnicity are predictors of susceptibility to antipsychotic-induced metabolic change, and improvements in psychopathology are associated with metabolic disturbance. Treatment guidelines should be updated to reflect our findings. However, the choice of antipsychotic should be made on an individual basis, considering the clinical circumstances and preferences of patients, carers, and clinicians. FUNDING: UK Medical Research Council, Wellcome Trust, National Institute for Health Research Oxford Health Biomedical Research Centre.