Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants.

BACKGROUND: Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity. METHODS: 169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP. RESULTS: Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP. CONCLUSIONS: These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

Physical activity influences adherence to pharmacological treatments in patients with severe mental disorders: results from the multicentric, randomized controlled LIFESTYLE trial.

Introduction: Poor adherence to pharmacological treatment is frequent in people with severe mental disorders and it often causes lack of effectiveness of many psychotropic drugs. Thus, efforts should be made to improve adherence to pharmacological treatments in patients with these disorders. Methods: In this paper, based on the LIFESTYLE randomized, controlled multicentric trial, we aim to: 1) assess the level of adherence in a real-world sample of patients with severe mental disorders; 2) evaluate differences in treatment adherence according to patients' socio-demographic and clinical characteristics; 3) evaluate the impact of an innovative psychosocial intervention, on patients' adherence to treatments. The Lifestyle Psychosocial Group Intervention consists of group sessions, focused on different lifestyle behaviours, including healthy diet; physical activity; smoking habits; medication adherence; risky behaviours; and regular circadian rhythms. At end of each session a 20-min moderate physical activity is performed by the whole group. Results: The sample consists of 402 patients, mainly female (57.1%, N = 229), with a mean age of 45.6 years (±11.8). Less than 40% of patients reported a good adherence to pharmacological treatments. Adherence to treatments was not influenced by gender, age, diagnosis and duration of illness. At the end of the intervention, patients receiving the experimental intervention reported a significant improvement in the levels of adherence to treatments (T0: 35.8% vs. T3: 47.6%, p < 0.005). Patients practicing moderate physical activity reported a two-point improvement in the levels of adherence [odds ratio (OR): 1,542; 95% confidence intervals (CI): 1,157-2,055; p < 0.001], even after controlling for several confounding factors. Discussion: The experimental lifestyle intervention, which can be easily implemented in the routine clinical practice of mental health centres, was effective in improving adherence to pharmacological treatments.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

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.

Similarities and differences between multivariate patterns of cognitive and socio-cognitive deficits in schizophrenia, bipolar disorder and related risk.

Cognition and social cognition anomalies in patients with bipolar disorder (BD) and schizophrenia (SCZ) have been largely documented, but the degree of overlap between the two disorders remains unclear in this regard. We used machine learning to generate and combine two classifiers based on cognitive and socio-cognitive variables, thus delivering unimodal and multimodal signatures aimed at discriminating BD and SCZ from two independent groups of Healthy Controls (HC1 and HC2 respectively). Multimodal signatures discriminated well between patients and controls in both the HC1-BD and HC2-SCZ cohorts. Although specific disease-related deficits were characterized, the HC1 vs. BD signature successfully discriminated HC2 from SCZ, and vice-versa. Such combined signatures allowed to identify also individuals at First Episode of Psychosis (FEP), but not subjects at Clinical High Risk (CHR), which were classified neither as patients nor as HC. These findings suggest that both trans-diagnostic and disease-specific cognitive and socio-cognitive deficits characterize SCZ and BD. Anomalous patterns in these domains are also relevant to early stages of disease and offer novel insights for personalized rehabilitative programs.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study.

BACKGROUND: Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. METHODS: For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. FINDINGS: Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (ß=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (ß=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (ß=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (ß=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (ß=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-ß (TGF-ß)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077). INTERPRETATION: High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-ß and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions. FUNDING: National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

Reduced magnetic mismatch negativity: a shared deficit in psychosis and related risk.

BACKGROUND: Abnormal auditory processing of deviant stimuli, as reflected by mismatch negativity (MMN), is often reported in schizophrenia (SCZ). At present, it is still under debate whether this dysfunctional response is specific to the full-blown SCZ diagnosis or rather a marker of psychosis in general. The present study tested MMN in patients with SCZ, bipolar disorder (BD), first episode of psychosis (FEP), and in people at clinical high risk for psychosis (CHR). METHODS: Source-based MEG activity evoked during a passive auditory oddball task was recorded from 135 patients grouped according to diagnosis (SCZ, BD, FEP, and CHR) and 135 healthy controls also divided into four subgroups, age- and gender-matched with diagnostic subgroups. The magnetic MMN (mMMN) was analyzed as event-related field (ERF), Theta power, and Theta inter-trial phase coherence (ITPC). RESULTS: The clinical group as a whole showed reduced mMMN ERF amplitude, Theta power, and Theta ITPC, without any statistically significant interaction between diagnosis and mMMN reductions. The mMMN subgroup contrasts showed lower ERF amplitude in all the diagnostic subgroups. In the analysis of Theta frequency, SCZ showed significant power and ITPC reductions, while only indications of diminished ITPC were observed in CHR, but no significant decreases characterized BD and FEP. CONCLUSIONS: Significant mMMN alterations in people experiencing psychosis, also for diagnoses other than SCZ, suggest that this neurophysiological response may be a feature shared across psychotic disorders. Additionally, reduced Theta ITPC may be associated with risk for psychosis.

The Complex Interplay Between Physical Activity and Recovery Styles in Patients With Severe Mental Disorders in a Real-World Multicentric Study.

Compared with the general population, people with severe mental disorders have significantly worse physical health and a higher mortality rate, which is partially due to the adoption of unhealthy lifestyle behaviors, such as heavy smoking, use of alcohol or illicit drugs, unbalanced diet, and physical inactivity. These unhealthy behaviors may also play a significant role in the personal and functional recovery of patients with severe mental disorders, although this relationship has been rarely investigated in methodologically robust studies. In this paper, we aim to: a) describe the levels of physical activity and recovery style in a sample of patients with severe mental disorders; b) identify the clinical, social, and illness-related factors that predict the likelihood of patients performing physical activity. The global sample consists of 401 patients, with a main psychiatric diagnosis of bipolar disorder (43.4%, N = 174), psychosis spectrum disorder (29.7%; N = 119), or major depression (26.9%; N = 118). 29.4% (N = 119) of patients reported performing physical activity regularly, most frequently walking (52.1%, N = 62), going to the gym (21.8%, N = 26), and running (10.9%, N = 13). Only 15 patients (3.7%) performed at least 75 min of vigorous physical activity per week. 46.8% of patients adopted sealing over as a recovery style and 37.9% used a mixed style toward integration. Recovery style is influenced by gender (p < 0.05) and age (p < 0.05). The probability to practice regular physical activity is higher in patients with metabolic syndrome (Odds Ratio - OR: 2.1; Confidence Interval - CI 95%: 1.2-3.5; p < 0.050), and significantly lower in those with higher levels of anxiety/depressive symptoms (OR: 0.877; CI 95%: 0.771-0.998; p < 0.01). Globally, patients with severe mental disorders report low levels of physical activities, which are associated with poor recovery styles. Psychoeducational interventions aimed at increasing patients' motivation to adopt healthy lifestyle behaviors and modifying recovery styles may improve the physical health of people with severe mental disorders thus reducing the mortality rates.

A polygenic score indexing a DRD2-related co-expression network is associated with striatal dopamine function.

The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors. We aimed to investigate the relationship between the DRD2 gene network and in vivo striatal dopaminergic function, which is a phenotype robustly associated with psychosis and schizophrenia. To this aim, a sample of 92 healthy subjects underwent 18F-DOPA PET and was genotyped for genetic variations indexing the co-expression of the DRD2-related genetic network in order to calculate the PCI for each subject. The PCI was significantly associated with whole striatal dopamine synthesis capacity (p = 0.038). Exploratory analyses on the striatal subdivisions revealed a numerically larger effect size of the PCI on dopamine function for the associative striatum, although this was not significantly different than effects in other sub-divisions. These results are in line with a possible relationship between the DRD2-related co-expression network and schizophrenia and extend it by identifying a potential mechanism involving the regulation of dopamine synthesis. Future studies are needed to clarify the molecular mechanisms implicated in this relationship.

Real-world clinical and cost-effectiveness of community clozapine initiation: mirror cohort study.

BACKGROUND: Clozapine is the only drug licensed for treatment-resistant schizophrenia (TRS) but the real-world clinical and cost-effectiveness of community initiation of clozapine is unclear. AIMS: The aim was to assess the feasibility and cost-effectiveness of community initiation of clozapine. METHOD: This was a naturalistic study of community patients recommended for clozapine treatment. RESULTS: Of 158 patients recommended for clozapine treatment, 88 (56%) patients agreed to clozapine initiation and, of these, 58 (66%) were successfully established on clozapine. The success rate for community initiation was 65.4%; which was not significantly different from that for in-patient initiation (58.82%, χ2(1,88) = 0.47, P = 0.49). Following clozapine initiation, there was a significant reduction in median out-patient visits over 1 year (from 24.00 (interquartile range (IQR) = 14.00-41.00) to 13.00 visits (IQR = 5.00-24.00), P < 0.001), and 2 years (from 47.50 visits (IQR = 24.75-71.00) to 22.00 (IQR = 11.00-42.00), P < 0.001), and a 74.71% decrease in psychiatric hospital bed days (z = -2.50, P = 0.01). Service-use costs decreased (1 year: -£963/patient (P < 0.001); 2 years: -£1598.10/patient (P < 0.001). Subanalyses for community-only initiation also showed significant cost reductions (1 year: -£827.40/patient (P < 0.001); 2 year: -£1668.50/patient (P < 0.001) relative to costs prior to starting clozapine. Relative to before initiation, symptom severity was improved in patients taking clozapine at discharge (median Positive and Negative Syndrome Scale total score: initial visit: 80 (IQR = 71.00-104.00); discharge visit 50.5 (IQR = 44.75-75.00), P < 0.001) and at 2 year follow-up (Health of Nation Outcome Scales total score median initial visit: 13.00 (IQR = 9.00-15.00); 2 year follow-up: 8.00 (IQR = 3.00-13.00), P = 0.023). CONCLUSIONS: These findings indicate that community initiation of clozapine is feasible and is associated with significant reductions in costs, service use and symptom severity.

Prevalence of antipsychotic-induced extrapyramidal symptoms and their association with neurocognition and social cognition in outpatients with schizophrenia in the "real-life".

First generation antipsychotics (FGAs) are more likely to induce extrapyramidal side-effects (EPS) than second generation antipsychotics (SGAs), and EPS have been shown associated to cognitive deficits in schizophrenia. So far, no study has explored the relationships between EPS and social cognition (SC) in people with schizophrenia. Therefore, we assessed the prevalence of EPS in a large sample of drug-treated community-dwelling persons with schizophrenia and explored their relationships with patients' neurocognitive and SC abilities. 875 patients underwent EPS, psychopathological, neurocognitive and SC assessments by means of standardized measures. Relationships between EPS, psychopathology and neurocognitive and SC measures were investigated by correlation tests. Moreover, a partial correlation network was computed by means of a network analysis. 256 patients were treated with FGAs alone or in combination with SGA and 619 with SGAs. EPS were significantly more frequent in FGA-treated group than in the SGA-treated one. Patients with EPS disclosed a more severe psychopathology and were more impaired in neurocognitive and SC measures compared to those without EPS. Disorganization, expressive deficit, and duration of illness were significantly associated to both neurocognitive and SC measures while EPS were associated to neurocognitive measures only. The network analysis showed that parkinsonism was the sole EPS directly connected to both psychopathological and neurocognitive indices whereas no direct connection emerged between EPS and SC measures. Present findings confirm that EPS are still present in the era of SGAs and contribute, together with other clinical variables, to the neurocognitive but not to the SC impairment of patients with schizophrenia.

The relationship between grey matter volume and striatal dopamine function in psychosis: a multimodal 18F-DOPA PET and voxel-based morphometry study.

A leading hypothesis for schizophrenia and related psychotic disorders proposes that cortical brain disruption leads to subcortical dopaminergic dysfunction, which underlies psychosis in the majority of patients who respond to treatment. Although supported by preclinical findings that prefrontal cortical lesions lead to striatal dopamine dysregulation, the relationship between prefrontal structural volume and striatal dopamine function has not been tested in people with psychosis. We therefore investigated the in vivo relationship between striatal dopamine synthesis capacity and prefrontal grey matter volume in treatment-responsive patients with psychosis, and compared them to treatment non-responsive patients, where dopaminergic mechanisms are not thought to be central. Forty patients with psychosis across two independent cohorts underwent 18F-DOPA PET scans to measure dopamine synthesis capacity (indexed as the influx rate constant Kicer) and structural 3T MRI. The PET, but not MR, data have been reported previously. Structural images were processed using DARTEL-VBM. GLM analyses were performed in SPM12 to test the relationship between prefrontal grey matter volume and striatal Kicer. Treatment responders showed a negative correlation between prefrontal grey matter and striatal dopamine synthesis capacity, but this was not evident in treatment non-responders. Specifically, we found an interaction between treatment response, whole striatal dopamine synthesis capacity and grey matter volume in left (pFWE corr. = 0.017) and right (pFWE corr. = 0.042) prefrontal cortex. We replicated the finding in right prefrontal cortex in the independent sample (pFWE corr. = 0.031). The summary effect size was 0.82. Our findings are consistent with the long-standing hypothesis of dysregulation of the striatal dopaminergic system being related to prefrontal cortex pathology in schizophrenia, but critically also extend the hypothesis to indicate it can be applied to treatment-responsive schizophrenia only. This suggests that different mechanisms underlie the pathophysiology of treatment-responsive and treatment-resistant schizophrenia.

A potential biomarker for treatment stratification in psychosis: evaluation of an [18F] FDOPA PET imaging approach.

[18F]FDOPA PET imaging has shown dopaminergic function indexed as Kicer differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [18F]FDOPA PET approaches had good test-rest reproducibility across striatal regions (Kicer ICC: 0.68-0.94, SUVRc ICC: 0.76-0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach: Kicer = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (Kicer: ~50%, SUVRc: 40-60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [18F]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of ~£3400 (equivalent to $4232 USD) per patient. These findings indicate [18F]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.

The influence of autistic symptoms on social and non-social cognition and on real-life functioning in people with schizophrenia: Evidence from the Italian Network for Research on Psychoses multicenter study.

BACKGROUND: Autism spectrum disorders (ASDs) and schizophrenia spectrum disorders (SSDs), although conceptualized as separate entities, may share some clinical and neurobiological features. ASD symptoms may have a relevant role in determining a more severe clinical presentation of schizophrenic disorder but their relationships with cognitive aspects and functional outcomes of the disease remain to be addressed in large samples of individuals. AIMS: To investigate the clinical, cognitive, and functional correlates of ASD symptoms in a large sample of people diagnosed with schizophrenia. METHODS: The severity of ASD symptoms was measured with the PANSS Autism Severity Scale (PAUSS) in 921 individuals recruited for the Italian Network for Research on Psychoses multicenter study. Based on the PAUSS scores, three groups of subjects were compared on a wide array of cognitive and functional measures. RESULTS: Subjects with more severe ASD symptoms showed a poorer performance in the processing speed (p = 0.010), attention (p = 0.011), verbal memory (p = 0.035), and social cognition (p = 0.001) domains, and an overall lower global cognitive composite score (p = 0.010). Subjects with more severe ASD symptoms also showed poorer functional capacity (p = 0.004), real-world interpersonal relationships (p < 0.001), and participation in community-living activities (p < 0.001). CONCLUSIONS: These findings strengthen the notion that ASD symptoms may have a relevant impact on different aspects of the disease, crucial to the life of people with schizophrenia. Prominent ASD symptoms may characterize a specific subpopulation of individuals with SSD.

Improving the "real life" management of schizophrenia spectrum disorders by LAI antipsychotics: A one-year mirror-image retrospective study in community mental health services.

Schizophrenia poses a significant economic burden on the healthcare system as well as it has a significant impact on society at large. Reasons for such a high economic burden of schizophrenia include the frequent relapses and hospitalizations occurring in this disorder. We analyze the effectiveness of long-acting injectable antipsychotics (LAIs) compared to oral medications, in terms of "clinical process management" in a sample of patients with a diagnosis of schizophrenia spectrum disorder treated in community mental health centers. An observational, retrospective, mirror-image study was carried out to evaluate the effectiveness of LAIs compared to oral medications in terms of number of hospitalizations, emergency visits and planned visits on a 10-year period (from July 2007 to June 2017). Differences between first and second generation LAIs were also explored. Our findings show that hospitalization and emergency visits are significantly decreased with the use of LAIs, while planned visits are increased in patients treated with LAIs. Our results suggest that LAIs, in particular, second generation ones, reduce hospitalization rates and emergency visits, improving the economic burden of schizophrenia. Therefore, LAIs should be considered a cost-effective treatment in the management of schizophrenia under routine conditions.

The effect of a genetic variant at the schizophrenia associated AS3MT/BORCS7 locus on striatal dopamine function: A PET imaging study.

One of the most statistically significant loci to result from large-scale GWAS of schizophrenia is 10q24.32. However, it is still unclear how this locus is involved in the pathoaetiology of schizophrenia. The hypothesis that presynaptic dopamine dysfunction underlies schizophrenia is one of the leading theories of the pathophysiology of the disorder. Supporting this, molecular imaging studies show evidence for elevated dopamine synthesis and release capacity. Thus, altered dopamine function could be a potential mechanism by which this genetic variant acts to increase the risk of schizophrenia. We therefore tested the hypothesis that the 10q24.32 region confers genetic risk for schizophrenia through an effect on striatal dopamine function. To this aim we investigated the in vivo relationship between a GWAS schizophrenia-associated SNP within this locus and dopamine synthesis capacity measured using [18F]-DOPA PET in healthy controls. 92 healthy volunteers underwent [18F]-DOPA PET scans to measure striatal dopamine synthesis capacity (indexed as Kicer) and were genotyped for the SNP rs7085104. We found a significant association between rs7085104 genotype and striatal Kicer. Our findings indicate that the mechanism mediating the 10q24.32 risk locus for schizophrenia could involve altered dopaminergic function. Future studies are needed to clarify the neurobiological pathway implicated in this association.

Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models.

People with psychotic disorders show abnormalities in several organ systems in addition to the central nervous system (CNS); and this contributes to excess mortality. However, it is unclear how strong the evidence is for alterations in non-CNS systems at the onset of psychosis, how the alterations in non-CNS systems compare to those in the CNS, or how they relate to symptoms. Here, we consider these questions, and suggest potential models to account for findings. We conducted a systematic meta-review to summarize effect sizes for both CNS (focusing on brain structural, neurophysiological, and neurochemical parameters) and non-CNS dysfunction (focusing on immune, cardiometabolic, and hypothalamic-pituitary-adrenal (HPA) systems) in first-episode psychosis (FEP). Relevant meta-analyses were identified in a systematic search of Pubmed and the methodological quality of these was assessed using the AMSTAR checklist (A Measurement Tool to Assess Systematic Reviews). Case-control data were extracted from studies included in these meta-analyses. Random effects meta-analyses were re-run and effect size magnitudes for individual parameters were calculated, as were summary effect sizes for each CNS and non-CNS system. We also grouped studies to obtain overall effect sizes for non-CNS and CNS alterations. Robustness of data for non-CNS and CNS parameters was assessed using Rosenthal's fail-safe N. We next statistically compared summary effect size for overall CNSand overall non-CNS alterations, as well as for each organ system separately. We also examined how non-CNS alterations correlate CNS alterations, and with psychopathological symptoms. Case-control data were extracted for 165 studies comprising a total sample size of 13,440. For people with first episode psychosis compared with healthy controls, we observed alterations in immune parameters (summary effect size: g = 1.19), cardiometabolic parameters (g = 0.23); HPA parameters (g = 0.68); brain structure (g = 0.40); neurophysiology (g = 0.80); and neurochemistry (g = 0.43). Grouping non-CNS organ systems together provided an effect size for overall non-CNS alterations in patients compared with controls (g = 0.58), which was not significantly different from the overall CNS alterations effect size (g = 0.50). However, the summary effect size for immune alterations was significantly greater than that for brain structural (P < 0.001) and neurochemical alterations (P < 0.001), while the summary effect size for cardiometabolic alterations was significantly lower than neurochemical (P = 0.04), neurophysiological (P < 0.001), and brain structural alterations (P = 0.001). The summary effect size for HPA alterations was not significantly different from brain structural (P = 0.14), neurophysiological (P = 0.54), or neurochemical alterations (P = 0.22). These outcomes remained similar in antipsychotic naive sensitivity analyses. We found some, but limited and inconsistent, evidence that non-CNS alterations were associated with CNS changes and symptoms in first episode psychosis. Our findings indicate that there are robust alterations in non-CNS systems in psychosis, and that these are broadly similar in magnitude to a range of CNS alterations. We consider models that could account for these findings and discuss implications for future research and treatment.

Correction to: Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models.

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