Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles' (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and plasma-derived EVs from 343 participants, including 100 individuals with chronic schizophrenia, 34 first-episode and drug-naïve patients, 35 individuals with bipolar disorder, 25 individuals with major depressive disorder and 149 age- and sex-matched healthy controls. Our innovative approach uncovered EVs-based complement changes in patients, specific to their disease-type and status. The EV-based biomarkers outperformed their plasma counterparts, accurately distinguishing schizophrenia individuals from healthy controls with an area under curve (AUC) of 0.895, 83.5% accuracy, 85.3% sensitivity and 82.0% specificity. Moreover, they effectively differentiated schizophrenia from bipolar disorder and major depressive disorder, with AUCs of 0.966 and 0.893, respectively. The personalized discrimination scores provided a personalized diagnostic index for schizophrenia and exhibited a significant association with patients' antipsychotic treatment response in the follow-up cohort. Overall, our study represents a significant advancement in the field of neuropsychiatric disorders, demonstrating the potential of EV-based biomarkers in guiding personalized diagnosis and treatment of schizophrenia.

The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia: Data from the STRATA collaboration.

Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment.

Brain Structure Measurements Predict Individualized Treatment Outcome of 12-Week Antipsychotic Monotherapies in First-episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Early prediction of treatment response to antipsychotics in schizophrenia remains a challenge in clinical practice. This study aimed to investigate if brain morphometries including gray matter volume and cortical thickness could serve as potential predictive biomarkers in first-episode schizophrenia. STUDY DESIGN: Sixty-eight drug-naïve first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single antipsychotic throughout the first 12 weeks. Assessments for symptoms and social functioning were conducted by eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8) and the Personal and Social performance scale (PSP) multiple times during follow-ups. Treatment outcome was evaluated as subject-specific slope coefficients for PANSS-8 and PSP scores using linear mixed model. LASSO regression model were conducted to examine the performance of baseline gray matter volume and cortical thickness in prediction of individualized treatment outcome. STUDY RESULTS: The study showed that individual brain morphometries at baseline, especially the orbitofrontal, temporal and parietal cortex, pallidum and amygdala, significantly predicted 12-week treatment outcome of PANSS-8 (r[predicted vs observed] = 0.49, P = .001) and PSP (r[predicted vs observed] = 0.40, P = .003) in first-episode schizophrenia. Moreover, the gray matter volume performed better than cortical thickness in the prediction the symptom changes (P = .034), while cortical thickness outperformed gray matter volume in the prediction of outcome of social functioning (P = .029). CONCLUSIONS: These findings provide initial evidence that brain morphometry have potential to be used as prognostic predictors for antipsychotic response in patients, encouraging the future investigation of the translational value of these measures in precision psychiatry.

fMRI connectivity as a biomarker of antipsychotic treatment response: A systematic review.

BACKGROUND: Antipsychotic drugs are the first-choice therapy for psychotic episodes, but antipsychotic treatment response (AP-R) is unpredictable and only becomes clear after weeks of therapy. A biomarker for AP-R is currently unavailable. We reviewed the evidence for the hypothesis that functional magnetic resonance imaging functional connectivity (fMRI-FC) is a predictor of AP-R or could serve as a biomarker for AP-R in psychosis. METHOD: A systematic review of longitudinal fMRI studies examining the predictive performance and relationship between FC and AP-R was performed following PRISMA guidelines. Technical and clinical aspects were critically assessed for the retrieved studies. We addressed three questions: Q1) is baseline fMRI-FC related to subsequent AP-R; Q2) is AP-R related to a change in fMRI-FC; and Q3) can baseline fMRI-FC predict subsequent AP-R? RESULTS: In total, 28 articles were included. Most studies were of good quality. fMRI-FC analysis pipelines included seed-based-, independent component- / canonical correlation analysis, network-based statistics, and graph-theoretical approaches. We found high heterogeneity in methodological approaches and results. For Q1 (N = 17) and Q2 (N = 18), the most consistent evidence was found for FC between the striatum and ventral attention network as a potential biomarker of AP-R. For Q3 (N = 9) accuracy's varied form 50 till 93%, and prediction models were based on FC between various brain regions. CONCLUSION: The current fMRI-FC literature on AP-R is hampered by heterogeneity of methodological approaches. Methodological uniformity and further improvement of the reliability and validity of fMRI connectivity analysis is needed before fMRI-FC analysis can have a place in clinical applications of antipsychotic treatment.

A pilot-study to examine motor cortical plasticity as a neuro-marker of antipsychotic treatment response in schizophrenia.

In a pilot study on 15 untreated first-episode schizophrenia participants, we examined how pre-treatment motor cortical plasticity - the brain's ability to change in response to an external perturbation - induced with intermittent theta burst stimulation, predicted prospectively ascertained (in 4-to-6 weeks) response to antipsychotic medications. We observed that participants with cortical plasticity in the opposite direction (possibly compensatory) had significantly greater improvements in their positive symptoms. This association persisted after correcting for multiple comparisons and controlling for potential confounders via linear regression. Inter-individual variability in cortical plasticity is a potential predictive biomarker in schizophrenia requiring further investigation and replication.

Trauma and resistance to antipsychotic treatment in schizophrenia: A narrative review.

This review explored whether trauma exposure is associated with poorer response to antipsychotic treatment in schizophrenia patients. A systematic search identified eight studies, of which five reported an association between trauma and non-remission of psychotic symptoms (n = 4) or treatment-resistant schizophrenia (TRS, n = 1). Although evidence supporting the link between trauma and resistance to antipsychotic treatment is scarce, trauma history should be systematically investigated in all persons with TRS, as there is a growing body of evidence showing that schizophrenia patients benefit from therapies for post-traumatic symptoms.

Methylome-wide association study of different responses to risperidone in schizophrenia.

Background: Accumulating evidence shows that DNA methylation plays a role in antipsychotic response. However, the mechanisms by which DNA methylation changes are associated with antipsychotic responses remain largely unknown. Methods: We performed a methylome-wide association study (MWAS) to evaluate the association between DNA methylation and the response to risperidone in schizophrenia. Genomic DNA methylation patterns were assessed using the Agilent Human DNA Methylation Microarray. Results: We identified numerous differentially methylated positions (DMPs) and regions (DMRs) associated with antipsychotic response. CYP46A1, SPATS2, and ATP6V1E1 had the most significant DMPs, with p values of 2.50 × 10-6, 3.53 × 10-6, and 5.71 × 10-6, respectively. The top-ranked DMR was located on chromosome 7, corresponding to the PTPRN2 gene with a Sidák-corrected p-value of 9.04 × 10-13. Additionally, a significant enrichment of synaptic function and neurotransmitters was found in the differentially methylated genes after gene ontology and pathway analysis. Conclusion: The identified DMP- and DMR-overlapping genes associated with antipsychotic response are related to synaptic function and neurotransmitters. These findings may improve understanding of the mechanisms underlying antipsychotic response and guide the choice of antipsychotic in schizophrenia.

Systems-Level Analysis of Genetic Variants Reveals Functional and Spatiotemporal Context in Treatment-resistant Schizophrenia.

Treatment-resistant schizophrenia (TRS) occurs in one-third of the patients, but the molecular determinants of poor antipsychotic response remain unclear. We compared genetic data of patients with TRS (n = 63) with non-TRS (n = 111) by polygenic risk scores (PRS) calculated by PRSice software using PGC2_SCZ (Psychiatric Genomics Consortium - Schizophrenia) data. TRS criteria followed the International Psychopharmacology Algorithm Project SCZ algorithm. Statistical clustering and functional enrichment analyses of genes harboring TRS-linked variants were performed. Individuals on the top three deciles of schizophrenia PRS distribution exhibited higher odds of being refractory to antipsychotics than those on the bottom three deciles. Clusters of interacting variant-harboring genes were identified among the association signals. They are upregulated in the dorsolateral prefrontal, orbitofrontal, temporal, and inferior parietal areas during adolescence and early adulthood. Similar gene modules were found using transcriptional data from the same brain regions in individuals with schizophrenia. Genes were enriched among markers of cortical interneurons and somatosensory pyramidal cells. Finally, the enrichment of the clustered genes in drug-response expression signatures revealed compounds that could be employed to identify novel antipsychotic targets. In conclusion, we identified variant-harboring genes that may predispose SCZ patients to poor antipsychotic response and found statistically enriched clusters which provided functional and spatiotemporal context for TRS, suggesting that genotypic variation may converge to biological alterations at the interplay between actin dynamics and synaptic organization.

MicroRNA-195 predicts olanzapine response in drug-free patients with schizophrenia: A prospective cohort study.

BACKGROUND: Disturbances of microRNA-195 have been implicated in the pathogenesis of schizophrenia. However, microRNA-195 levels in schizophrenia are controversial. AIMS: To the best of our knowledge, this is the first study to examine microRNA-195 levels in untreated schizophrenia patients and their relationship to olanzapine response. METHODS: We recruited 81 untreated schizophrenia patients and 96 healthy controls. The patients received 2 months olanzapine treatment. MicroRNA-195 levels in peripheral blood mononuclear cells were measured using quantitative real-time polymerase chain reaction testing. Psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale. RESULTS: No significant differences in microRNA-195 levels were found between patients and healthy controls (p > 0.05). Olanzapine significantly reduced microRNA-195 levels after 2 months treatment (p = 0.003). Interestingly, microRNA-195 levels decreased significantly in responders (p = 0.010), but not in non-responders (p > 0.05). Both baseline microRNA-195 levels (p = 0.027, p = 0.030) and the reduction rate of microRNA-195 levels (p = 0.034, p = 0.044) were positively associated with the reduction rate of Positive and Negative Syndrome Scale total score and general psychopathological subscale score. Multiple stepwise regression analysis revealed that baseline microRNA-195 level was an independent contributor to the reduction in Positive and Negative Syndrome Scale total score and the general psychopathological subscale score (p = 0.018, p = 0.030). Finally, logistic regression analysis suggested that baseline microRNA-195 level can serve as a biomarker for response to olanzapine (p = 0.037). CONCLUSIONS: Our data indicate that microRNA-195 level may predict symptomatic improvement and olanzapine response in schizophrenia patients, suggesting that microRNA-195 should be considered as a potential therapeutic target for antipsychotics.

Peripheral immune markers and antipsychotic non-response in psychosis.

BACKGROUND: Peripheral immune markers have previously been linked to a poor response to antipsychotic medication and more severe negative symptoms at the onset of psychosis. The present study investigated the association of blood cytokines and complement markers with the presence of antipsychotic non-response and symptom severity in patients with psychosis. METHODS: This cross-sectional study recruited 94 patients with schizophrenia and other psychoses, of whom 47 were defined as antipsychotic responders and 47 as antipsychotic non-responders. In all subjects we measured plasma levels of cytokines (IL-1ß, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, and IFN-γ), complement markers (C1-inhibitor, C3, C4, C3a, C3b, Bb, factor D, C5a, terminal complement complex) and high sensitivity C-reactive protein (hsCRP). Symptom severity was recorded using the Positive and Negative Syndrome scale for Schizophrenia (PANSS). Binary logistic regression tested each immune marker as predictor of response status while covarying for relevant socio-demographic variables. Correlation analyses tested the association between immune markers and the severity of symptoms. RESULTS: Interleukin (IL)-8 significantly predicted antipsychotic non-response (OR=24.70, 95% CI, 1.35-453.23, p = 0.03). Other immune markers were not associated with antipsychotic response. IL-6, IL-8, IL-10 and TNF-α significantly positively correlated with negative psychotic symptoms. CONCLUSIONS: Higher levels of IL-8 are associated with a poor response to antipsychotic treatment. Increased cytokines levels are specifically associated with more severe negative symptoms in patients with schizophrenia and other psychoses.

Dopamine and Glutamate in Antipsychotic-Responsive Compared With Antipsychotic-Nonresponsive Psychosis: A Multicenter Positron Emission Tomography and Magnetic Resonance Spectroscopy Study (STRATA).

The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min-1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity.

Moderators and mediators of antipsychotic response in delusional disorder: Further steps are needed.

Delusional disorder (DD) has been traditionally considered a relatively rare and treatment-resistant psychotic disorder. In the last decade, increasing attention has focused on therapeutic outcomes of individuals affected by this disorder. The aim of this paper is to provide a synthesis of the literature addressing two very important questions arising from DD research: (1) For which patients with DD do antipsychotic medications work best (the moderators of response); and (2) What variables best explain the relationship between such treatments and their effectiveness (the mediators of response). We searched PubMed and Google Scholar databases for English, German, French and Spanish language papers published since 2000. We also included a few classic earlier papers addressing this topic. Variables potentially moderating antipsychotic response in DD are gender, reproductive status, age, duration of illness, the presence of comorbidity (especially psychiatric comorbidity) and its treatment, brain structure, and genetics of neurochemical receptors and drug metabolizing enzymes. Antipsychotic and hormonal blood levels during treatment, as well as functional brain changes, are potential mediating variables. Some, but not all, patients with DD benefit from antipsychotic treatment. Understanding the circumstances under which treatment works best can serve to guide optimal management.

Long Non-Coding RNAs Associated with Heterochromatin Function in Immune Cells in Psychosis.

Psychosis is associated with chronic immune dysregulation. Many long non-coding RNAs (lncRNAs) display abnormal expression during activation of immune responses, and play a role in heterochromatic regulation of gene promoters. We have measured lncRNAs MEG3, PINT and GAS5, selected for their previously described association with heterochromatin. Peripheral blood mononuclear cells (PBMCs) were isolated from blood samples collected from 86 participants with a diagnosis of psychosis and 44 control participants. Expression was assessed in relation to diagnosis, illness acuity status, and treatment with antipsychotic medication. We observed diagnostic differences with MEG3, PINT and GAS5, and symptom acuity effect with MEG3 and GAS5. Medication effects were evident in those currently on treatment with antipsychotics when compared to drug-naïve participants. We observed that clinical diagnosis and symptom acuity predict selected lncRNA expression. Particular noteworthy is the differential expression of MEG3 in drug naïve participants compared to those treated with risperidone. Additionally, an in vitro cell model using M2tol macrophages was used to test the effects of the antipsychotic drug risperidone on the expression of these lncRNAs using quantitative real-time PCR (qRT-PCR). Significant but differential effects of risperidone were observed in M2tol macrophages indicating a clear ability of antipsychotic medications to modify lncRNA expression.

COMT, 5-HTR2A, and SLC6A4 mRNA Expressions in First-Episode Antipsychotic-Naïve Schizophrenia and Association With Treatment Outcomes.

Background: Dopaminergic and serotonergic systems play crucial roles in the pathophysiology of schizophrenia and modulate response to antipsychotic treatment. However, previous studies of dopaminergic and serotonergic genes expression are sparse, and their results have been inconsistent. In this longitudinal study, we aim to investigate the expressions of Catechol-O-methyltransferase (COMT), serotonin 2A receptor (5-HTR2A), and serotonin transporter gene (SLC6A4) mRNA in first-episode antipsychotic-naïve schizophrenia and to test if these mRNA expressions are associated with cognitive deficits and treatment outcomes or not. Method: We measured COMT, 5-HTR2A, and SLC6A4 mRNA expressions in 45 drug-naive first-episode schizophrenia patients and 38 health controls at baseline, and repeated mRNA measurements in all patients at the 8-week follow up. Furthermore, we also assessed antipsychotic response and cognitive improvement after 8 weeks of risperidone monotherapy. Results: Patients were divided into responders (N = 20) and non-responders groups (N = 25) according to the Remission criteria of the Schizophrenia Working Group. Both patient groups have significantly higher COMT mRNA expression and lower SLC6A4 mRNA expression when compared with healthy controls. Interestingly, responder patients have significantly higher levels of COMT and 5-HTR2A mRNA expressions than non-responder patients at baseline. However, antipsychotic treatment has no significant effect on the expressions of COMT, 5-HTR2A, and SLC6A4 mRNA over 8-week follow up. Conclusion: Our findings suggest that dysregulated COMT and SLC6A4 mRNA expressions may implicate in the pathophysiology of schizophrenia, and that COMT and 5-HTR2A mRNA may be potential biomarkers to predict antipsychotic response.

Event related desynchronisation of mu-wave over right sensorimotor cortex at baseline may predict subsequent response to antipsychotics in Schizophrenia.

Mirror neuron system (MNS) has been demonstrated to be defective in patients with schizophrenia. This paper report findings from a high resolution (192-channel) EEG study conducted on 15 drug free/naïve consenting schizophrenia patients, in which the specific role of right hemispheric MNS has been explored over 4 weeks of antipsychotic treatment. The authors used mu wave suppression paradigm, and found that baseline right MNS mu suppression correlated negatively with and predicted relative improvement in thought disturbance cluster score of PANSS during first 4 weeks of drug treatment.

The promise of biological markers for treatment response in first-episode psychosis: a systematic review.

Successful treatment of first-episode psychosis is one of the major factors that impacts long-term prognosis. Currently, there are no satisfactory biological markers (biomarkers) to predict which patients with a first-episode psychosis will respond to which treatment. In addition, a non-negligible rate of patients does not respond to any treatment or may develop side effects that affect adherence to the treatments as well as negatively impact physical health. Thus, there clearly is a pressing need for defining biomarkers that may be helpful to predict response to treatment and sensitivity to side effects in first-episode psychosis. The present systematic review provides (1) trials that assessed biological markers associated with antipsychotic response or side effects in first-episode psychosis and (2) potential biomarkers associated with biological disturbances that may guide the choice of conventional treatments or the prescription of innovative treatments. Trials including first-episode psychoses are few in number. Most of the available data focused on pharmacogenetics markers with so far only preliminary results. To date, these studies yielded-beside markers for metabolism of antipsychotics-no or only a few biomarkers for response or side effects, none of which have been implemented in daily clinical practice. Other biomarkers exploring immunoinflammatory, oxidative, and hormonal disturbances emerged as biomarkers of first-episode psychoses in the last decades, and some of them have been associated with treatment response. In addition to pharmacogenetics, further efforts should focus on the association of emergent biomarkers with conventional treatments or with innovative therapies efficacy, where some preliminary data suggest promising results.

Replication of SULT4A1-1 as a pharmacogenetic marker of olanzapine response and evidence of lower weight gain in the high response group.

AIM: Antipsychotic efficacy biomarkers have the potential to improve outcomes in psychotic patients. This study examined the effect of SULT4A1-1 haplotype status (rs2285162 [A]-rs2285167 [G]) on olanzapine response. PATIENTS & METHODS: We evaluated 87 olanzapine treated subjects from Phases 1, 1B and 2 of the CATIE trial for the impact of SULT4A1-1 status on change in Positive and Negative Syndrome Scale (PANSS) total score using two models of response. We also examined weight change. RESULTS: SULT4A1-1-positive status correlated with superior olanzapine response in Phase 1 (p = 0.004 for model 1 and p = 0.001 for model 2) and Phases 1B/2 (p = 0.05 for model 1 and p = 0.007 for model 2). SULT4A1-1-positive subjects gained significantly less weight per month on olanzapine, 0.15 lbs, than did SULT4A1-1-negative subjects, 2.27 lbs (p = 0.04). CONCLUSION: This study provides a second replication of superior olanzapine response in SULT4A1-1-positive subjects compared with SULT4A1-1-negative subjects. SULT4A1-1-positive subjects treated with olanzapine also gained less weight than SULT4A1-1-negative subjects.

How antipsychotics impact the different dimensions of Schizophrenia: a test of competing hypotheses.

The clinical expression of schizophrenia is generally reported to be expressed by three to five different factors (i.e. positive, negative, disorganization, excitability, anxiety-depression symptoms). It is often claimed that antipsychotic medications are particularly helpful for positive symptoms, but not for the others, suggesting a differential efficacy for different aspects of the disorder. We formally tested this claim. Using Structural Equation Modeling in two large [1884 patients] clinical trials in schizophrenia, we compared the model of a common general effect of antipsychotics to models whereby the antipsychotics have multiple and differential effects on the different factors of the illness. We validated the generalizability of the model in further trials involving antipsychotics in chronic [1460 patients] and first-episode patients [1053 patients]. Across different populations, different trials and different antipsychotics - the best-fitting model suggests that symptom response in schizophrenia is underpinned by a single general effect with secondary and minor lower-order effects on specific symptom domains. This single-factor model explained nearly 80% of the variance, was superior to the assumption of unique efficacy for specific domains; and replicated across antipsychotics and illness stages. Despite theoretical and pharmacological claims the differential efficacy of antipsychotics on the various dimensions of schizophrenia is not supported in the prevailing data. The implication of this finding for the measurement of treatment response and our understanding of the neurobiology of antipsychotic action, for clinical practice and for future drug development are discussed.

SULT4A1 haplotype: conflicting results on its role as a biomarker of antipsychotic response.

AIM: Based on previous pharmacogenetic findings, we investigated the possible association between SULT4A1-1 haplotype and antipsychotic treatment response. MATERIALS & METHODS: Using Mixed Model Repeated Measures, we tested the relationship between SULT4A1-1 status (+carrier, -noncarrier) and clinical improvement (in Positive and Negative Syndrome Scale total score) among European ancestry patients treated with paliperidone extended release (n=937), paliperidone palmitate (n=990), risperidone (n=507) and olanzapine (n=381) in 12 schizophrenia, two schizoaffective disorder and three bipolar I disorder trials. SULT4A1-1 haplotype was determined using tagging SNP rs763120. RESULTS: There was no significant difference between SULT4A1-1(+) and SULT4A1-1(-) patients for treatment response to paliperidone or olanzapine. SULT4A1-1(-) patients had better treatment response to risperidone in one schizophrenia trial, but not in another schizophrenia trial or bipolar mania trial. CONCLUSION: Across three psychiatric disorders (n=2815 patients), we observed no consistent association between SULT4A1-1 status and atypical antipsychotic effect.

Prominent clinical dimension, duration of illness and treatment response in schizophrenia: a naturalistic study.

OBJECTIVE: Preliminary data indicate that predominant positive symptoms are predictive of subsequent treatment response, while negative and cognitive symptoms are associated with poor outcome. Purpose of the present study was to investigate the relation between the predominant clinical dimension, duration of illness and acute antipsychotic response in a sample of schizophrenic inpatients. METHODS: Fifty-one schizophrenic inpatients, receiving an antipsychotic mono-therapy, were dimensionally assessed at the admission in the Acute Psychiatric Unit of the University of Milan. Treatment response was selected as parameter of outcome and defined as a reduction >50% of baseline total The Positive and Negative Syndrome Scale (PANSS) score. Demographic and clinical variables between responders and non-responders were compared using one-way analysis of variance for continuous variables and χ(2) test for dichotomous ones. Binary logistic regression was performed to find if dimensional scores and duration of illness were associated with acute antipsychotic response. RESULTS: A longer duration of illness was found in non-responders respect to responders (15.61 years vs. 8.28 years)(F=4.98, p=0.03). Higher scores on PANSS positive sub-scale (OR=1.3, p=0.03), lower scores on cognitive PANSS scores (OR=0.75, p=0.05) and shorter duration of illness (OR=0.93, p=0.04) were found to be predictive of acute antipsychotic response. CONCLUSION: These preliminary results show that a long duration of illness as well as a more severe cognitive impairment is predictive of treatment non-response, indicating a worse outcome for chronic patients with predominant cognitive symptoms.