Clinical correlates of early onset antipsychotic treatment resistance.

BACKGROUND: There is evidence of heterogeneity within treatment-resistant schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and others becoming treatment-resistant after an initial response period. These groups may have different aetiologies. AIM: This study investigates sociodemographic and clinical correlates of early onset of TRS. METHOD: Employing a retrospective cohort design, we do a secondary analysis of data from a cohort of people with TRS attending the South London and Maudsley. Regression analyses were conducted to identify the correlates of the length of treatment to TRS. Predictors included the following: gender, age, ethnicity, problems with positive symptoms, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics. RESULTS: In a cohort of 164 people with TRS (60% were men), the median length of treatment to TRS was 3 years and 8 months. We observed no cut-off on the length of treatment until TRS presentation differentiating between early and late TRS (i.e. no bimodal distribution). Having mild to very severe problems with hallucinations and delusions at the treatment start was associated with earlier TRS (~19 months earlier). In sensitivity analyses, including only complete cases (subject to selection bias), treatment with a long-acting injectable antipsychotic was additionally associated with later TRS (~15 months later). CONCLUSION: Our findings do not support a clear separation between early and late TRS but rather a continuum of the length of treatment before TRS onset. Having mild to very severe problems with positive symptoms at treatment start predicts earlier onset of TRS.

A predictor model of treatment resistance in schizophrenia using data from electronic health records.

OBJECTIVES: To develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs. METHODS: We used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records. RESULTS: We reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel's C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic. CONCLUSIONS: Routinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS.

Using a statistical learning approach to identify sociodemographic and clinical predictors of response to clozapine.

BACKGROUND: A proportion of people with treatment-resistant schizophrenia fail to show improvement on clozapine treatment. Knowledge of the sociodemographic and clinical factors predicting clozapine response may be useful in developing personalised approaches to treatment. METHODS: This retrospective cohort study used data from the electronic health records of the South London and Maudsley (SLaM) hospital between 2007 and 2011. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression statistical learning approach, we examined 35 sociodemographic and clinical factors' predictive ability of response to clozapine at 3 months of treatment. Response was assessed by the level of change in the severity of the symptoms using the Clinical Global Impression (CGI) scale. RESULTS: We identified 242 service-users with a treatment-resistant psychotic disorder who had their first trial of clozapine and continued the treatment for at least 3 months. The LASSO regression identified three predictors of response to clozapine: higher severity of illness at baseline, female gender and having a comorbid mood disorder. These factors are estimated to explain 18% of the variance in clozapine response. The model's optimism-corrected calibration slope was 1.37, suggesting that the model will underfit when applied to new data. CONCLUSIONS: These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.

Effects of Vortioxetine and Escitalopram on Electroencephalographic Recordings - A Randomized, Crossover Trial in Healthy Males.

The antidepressant drug vortioxetine has a multimodal action modulating neurotransmission through inhibition of the serotonin transporter and modulation of serotonin receptors. Vortioxetine has also been shown to alleviate cognitive symptoms in preclinical studies and in patients with depression. However, it is largely unclear how vortioxetine affects the brain processing in humans. The present study was conducted in 32 healthy males in a randomized, double-blinded, placebo-controlled, active comparator, four-way crossover design. Treatments were 10 and 20 mg/day vortioxetine, 15 mg/day escitalopram, and placebo, administered orally once daily for three days. Results were compared to placebo. Treatment effect was assessed by recording spontaneous electroencephalography (EEG) and 40 Hz auditory steady state responses. For the spontaneous EEG, both vortioxetine and escitalopram decreased the frequency content in the theta band (4-8 Hz) and increased power in the beta (12-32 Hz) and gamma (32-45 Hz) bands. Vortioxetine and escitalopram decreased connectivity during rest in the theta band and increased connectivity in the gamma bands. Finally, both treatments caused decreased power in the evoked gamma band in response to 40 Hz auditory stimulation. Although the global EEG changes were comparable between vortioxetine and escitalopram, subtle differences between treatment effects on the EEG in terms of effect size and regional distribution of the EEG changes were apparent. To our knowledge, the current results are the first data on how vortioxetine affects EEG in humans. The present study calls for further investigations addressing the possible electrophysiological and cognitive effects of vortioxetine.

Sleep stability and transitions in patients with idiopathic REM sleep behavior disorder and patients with Parkinson's disease.

OBJECTIVE: Patients with idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) are at high risk of developing Parkinson's disease (PD). As wake/sleep-regulation is thought to involve neurons located in the brainstem and hypothalamic areas, we hypothesize that the neurodegeneration in iRBD/PD is likely to affect wake/sleep and REM/non-REM (NREM) sleep transitions. METHODS: We determined the frequency of wake/sleep and REM/NREM sleep transitions and the stability of wake (W), REM and NREM sleep as measured by polysomnography (PSG) in 27 patients with PD, 23 patients with iRBD, 25 patients with periodic leg movement disorder (PLMD) and 23 controls. Measures were computed based on manual scorings and data-driven labeled sleep staging. RESULTS: Patients with PD showed significantly lower REM stability than controls and patients with PLMD. Patients with iRBD had significantly lower REM stability compared with controls. Patients with PD and RBD showed significantly lower NREM stability and significantly more REM/NREM transitions than controls. CONCLUSIONS: We conclude that W, NREM and REM stability and transitions are progressively affected in iRBD and PD, probably reflecting the successive involvement of brain stem areas from early on in the disease. SIGNIFICANCE: Sleep stability and transitions determined by a data-driven approach could support the evaluation of iRBD and PD patients.

Discovery and development of 11C-Lu AE92686 as a radioligand for PET imaging of phosphodiesterase10A in the brain.

UNLABELLED: Phosphodiesterase 10A (PDE10A) plays a key role in the regulation of brain striatal signaling, and several pharmaceutical companies currently investigate PDE10A inhibitors in clinical trials for various central nervous system diseases. A PDE10A PET ligand may provide evidence that a clinical drug candidate reaches and binds to the target. Here we describe the successful discovery and initial validation of the novel radiolabeled PDE10A ligand 5,8-dimethyl-2-[2-((1-(11)C-methyl)-4-phenyl-1H-imidazol-2-yl)-ethyl]-[1,2,4]triazolo[1,5-a]pyridine ((11)C-Lu AE92686) and its tritiated analog (3)H-Lu AE92686. METHODS: Initial in vitro experiments suggested Lu AE92686 as a promising radioligand, and the corresponding tritiated and (11)C-labeled compounds were synthesized. (3)H-Lu AE92686 was evaluated as a ligand for in vivo occupancy studies in mice and rats, and (11)C-Lu AE92686 was evaluated as a PET tracer candidate in cynomolgus monkeys and in humans. RESULTS: (11)C-Lu AE92686 displayed high specificity and selectivity for PDE10A-expressing regions in the brain of cynomolgus monkeys and humans. Similar results were found in rodents using (3)H-Lu AE92686. The binding of (11)C-Lu AE92686 and (3)H-Lu AE92686 to striatum was completely and dose-dependently blocked by the structurally different PDE10A inhibitor 2-[4-(1-methyl-4-pyridin-4-yl-1H-pyrazol-3-yl)-phenoxymethyl]-quinoline (MP-10) in rodents and in monkeys. In all species, specific binding of the radioligand was seen in the striatum but not in the cerebellum, supporting the use of the cerebellum as a reference region. The binding potentials (BPND) of (11)C-Lu AE92686 in the striatum of both cynomolgus monkeys and humans were evaluated by the simplified reference tissue model with the cerebellum as the reference tissue, and BPND was found to be high and reproducible-that is, BPNDs were 6.5 ± 0.3 (n = 3) and 7.5 ± 1.0 (n = 12) in monkeys and humans, respectively. CONCLUSION: Rodent, monkey, and human tests of labeled Lu AE92686 suggest that (11)C-Lu AE92686 has great potential as a human PET tracer for the PDE10A enzyme.