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Mindfulness-based cognitive therapy (MBCT), an intervention that integrates mindfulness with cognitive-behavioral therapy, is an 8-week program originally developed to prevent relapses in patients with depression. Previous studies have demonstrated the efficacy of MBCT for preventing relapse, but few studies have evaluated MBCT in naturalistic conditions with real-world samples. Therefore, we sought to explore the characteristics and experiences of individuals receiving MBCT in primary care. Mixed-methods approach combining descriptive and qualitative data. Quantitative data were obtained from 269 individuals from different socioeconomic backgrounds who participated in an MBCT program in our healthcare area during the years 2017 and 2018. Qualitative data were obtained from a subsample of participants who agree to participate in semi-structured individual interviews. An interpretative phenomenological analysis (IPA) approach was used to analyze the qualitative data. In the whole sample (n = 269), the most commonly diagnosed disorders were adjustment (41.6%), mood (22.7%), and anxiety (14.1%). Most participants (60%) were taking psychotropic medications (mainly antidepressants). Overall, mindfulness training improved depressive and anxiety symptoms, regardless of the specific diagnosis. A subsample of 14 individuals participated in the qualitative study. Four overarching themes emerged from the IPA analysis in this subsample: (1) effects of mindfulness practice, (2) learning process, (3) group experience, and (4) mindfulness in the healthcare system. The findings of this naturalistic, mixed-methods study suggest that MBCT could be an effective approach to treating the symptoms of common mental disorders in the primary care setting.

Background: The main objective of this study was to assess the safety and efficacy of deep brain stimulation (DBS) in patients with severe anorexia nervosa (AN). Methods: Eight participants received active DBS to the subcallosal cingulate (SCC) or nucleus accumbens (NAcc) depending on comorbidities (affective or anxiety disorders, respectively) and type of AN. The primary outcome measure was body mass index (BMI). Results: Overall, we found no significant difference (p = 0.84) between mean preoperative and postoperative (month 6) BMI. A BMI reference value (BMI-RV) was calculated. In patients that received preoperative inpatient care to raise the BMI, the BMI-RV was defined as the mean BMI value in the 12 months prior to surgery. In patients that did not require inpatient care, the BMI-RV was defined as the mean BMI in the 3-month period before surgery. This value was compared to the postoperative BMI (month 6), revealing a significant increase (p = 0.02). After 6 months of DBS, five participants showed an increase of ≥10% in the BMI-RV. Quality of life was improved (p = 0.03). Three cases presented cutaneous complications. Conclusion: DBS may be effective for some patients with severe AN. Cutaneous complications were observed. Longer term data are needed.

Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modeling has provided evidence that patients with chronic schizophrenia jump to conclusions because of noisy decision-making. We developed a novel version of the classical beads task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of “draws to decision” when information sampling had no, a fixed, or an escalating cost. Computational modeling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall, patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block, participants sampled more information than an ideal Bayesian agent. Computational modeling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls did, Mann–Whitney U = 289, p = 0.007, with marginal evidence of differences in noise parameter estimates, t(60) = 1.86, p = 0.07. In patients, individual differences in severity of psychotic symptoms were statistically significantly associated with higher cost of information sampling, ρ = 0.6, p = 0.001, but not with more cognitive noise, ρ = 0.27, p = 0.14; in controls, cognitive noise predicted aspects of schizotypy (preoccupation and distress associated with delusion-like ideation on the Peters Delusion Inventory). Using a psychological manipulation and computational modeling, we provide evidence that early-psychosis patients jump to conclusions because of attributing higher costs to sampling information, not because of being primarily noisy decision makers.

Abnormal salience processing has been suggested to contribute to the formation of positive psychotic symptoms in schizophrenia and related conditions. Previous research utilising reward learning or anticipation paradigms has demonstrated cortical and subcortical abnormalities in people with psychosis, specifically in the prefrontal cortex, the dopaminergic midbrain and the striatum. In these paradigms, reward prediction errors attribute motivational salience to stimuli. However, little is known about possible abnormalities across different forms of salience processing in psychosis patients, and whether any such abnormalities involve the dopaminergic midbrain. The aim of our study was, therefore, to investigate possible alterations in psychosis in neural activity in response to various forms of salience: novelty, negative emotion, targetness (task-driven salience) and rareness/deviance. We studied 14 antipsychotic naïve participants with first episode psychosis, and 37 healthy volunteers. During fMRI scanning, participants performed a visual oddball task containing these four forms of salience. Psychosis patients showed abnormally reduced signalling in the substantia nigra/ventral tegmental area (SN/VTA) for novelty, negative emotional salience and targetness; reduced striatal and occipital (lingual gyrus) signalling to novelty and negative emotional salience, reduced signalling in the amygdala, anterior cingulate cortex and parahippocamal gyrus to negative emotional salience, and reduced cerebellar signalling to novelty and negative emotional salience. Our results indicate alterations of several forms of salience processing in patients with psychosis in the midbrain SN/VTA, with additional subcortical and cortical regions also showing alterations in salience signalling, the exact pattern of alterations depending on the form of salience in question.

Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis, and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modelling has provided evidence that patients with chronic schizophrenia jump to conclusion because of noisy decision making. We developed a novel version of the classical beads-task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of ‘draws to decision’ when information sampling had no, a fixed, or an escalating cost. Computational modelling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block participants sampled more information than an ideal Bayesian agent. Computational modelling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls (Mann-Whiney U=289, p=0.007), with marginal evidence of differences in noise parameter estimates (t=1.86 df=60, p=0.07). In patients, individual differences in severity of psychotic symptoms were statistically significantly associated with higher cost of information sampling (rho=0.6, p=0.001) but not with more cognitive noise (rho=0.27, p=0.14); in controls cognitive noise predicted aspects of schizotypy (preoccupation and distress associated with delusion-like ideation on the Peters Delusion Inventory). Using a psychological manipulation and computational modelling, we provide evidence that early psychosis patients jump to conclusions because of attributing higher costs to sampling information, not because of being primarily noisy decision makers.

Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is unknown at what stage in the pathogenesis of psychosis these impairments in prediction-error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction-error signalling in earliest stages of psychosis. We studied patients with first-episode psychosis (FEP) and help-seeking individuals at-risk for psychosis due to sub-threshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n = 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p 0.05 family-wise error corrected) prediction-error signalling differences between groups in the dopaminergic midbrain and right middle frontal gyrus (dorsolateral prefrontal cortex, DLPFC). FEP patients showed disrupted reward prediction-error signalling compared to controls in both regions. At-risk patients showed intermediate activation in the midbrain that significantly differed from controls and from FEP patients, but DLPFC activation that did not differ from controls. Our study confirms that FEP patients have abnormal meso-cortical signalling of reward-prediction errors, whereas reward-prediction-error dysfunction in the at-risk patients appears to show a more nuanced pattern of activation with a degree of midbrain impairment but preserved cortical function.

Ongoing research suggests preliminary, though not entirely consistent, evidence of neural abnormalities in signalling prediction errors in schizophrenia. Supporting theories suggest mechanistic links between the disruption of these processes and the generation of psychotic symptoms. However, it is not known at what stage in psychosis these impairments in prediction error signalling develop. One major confound in prior studies is the use of medicated patients with strongly varying disease durations. Our study aims to investigate the involvement of the meso-cortico-striatal circuitry during reward prediction error signalling in the earliest stages of psychosis. We studied patients with first episode psychosis (FEP) and help-seeking individuals at risk for psychosis due to subthreshold prodromal psychotic symptoms. Patients with either FEP (n = 14), or at-risk for developing psychosis (n= 30), and healthy volunteers (n = 39) performed a reinforcement learning task during fMRI scanning. ANOVA revealed significant (p

Chronic mood disorders have been associated with a shortened telomere, a marker of increased mortality rate and ageing, and impaired cellular immunity. However, treatment may confound these relationships. We examined the relationship of glucose tolerance, white blood cell count and telomere length to depression in newly diagnosed, antidepressant-naïve patients. Subjects with major depression (n=15), and matched healthy control subjects (n=70) underwent a two-hour oral glucose tolerance test and evaluation of blood cell count and telomere content. The depression group had significantly higher two-hour glucose concentrations and a lower lymphocyte count than control subjects (respective means [SD] for two-hour glucose were 125.0 mg/dL [67.9] vs 84.6 [25.6] (p

Newly diagnosed, antipsychotic-naive patients with nonaffective psychosis appear to have increases in pro-inflammatory cytokines. Patients characterized by primary, enduring negative symptoms (deficit symptoms) differ from patients without such features with regard to course of illness, treatment response, risk factors and metabolic disturbances. We hypothesized that they would also differ on concentrations of the inflammatory markers interleukin-6 (IL6) and C-reactive protein (CRP). Newly diagnosed, antipsychotic-naive patients with nonaffective psychosis were categorized into deficit ( N = 20) and nondeficit ( N = 42) groups, and were matched on age, gender, body mass index, smoking, cortisol level, socioeconomic status, and the severity of psychotic symptoms. Fasting concentrations of IL6 were significantly higher in deficit (mean [S.D.]) (8.0 pg/ml [12.7]) than nondeficit patients (0.3 pg/ml [1.3]). CRP levels were also significantly higher in the deficit patients (0.3 mg/dl [0.4]) vs. (0.2 mg/dl [0.4]), respectively. In contrast, 2-h glucose concentrations (2HG) in a glucose tolerance test were lower in the deficit than the nondeficit group. Our results show a double dissociation with regard to glucose intolerance and inflammation: the deficit group has greater inflammation, but less severe glucose intolerance. These results provide further evidence for the validity of the deficit/nondeficit categorization.

Background Previous studies have found increased prolactin concentrations in antipsychotic-naive patients with schizophrenia. However, the roles of other hormones, and of potentially confounding variables such as gender and smoking, have not been considered. Methods Blood from newly diagnosed, antipsychotic-naive patients with nonaffective psychosis (13 women and 20 men) and matched controls (12 women and 21 men) was assayed for prolactin, as well as three other hormones that impact prolactin concentrations: thyrotropin-stimulating hormone (TSH), ghrelin, and cortisol. Results Patients had significantly higher prolactin concentrations: female patients had a mean [SD] of 37.1 ng/mL [24.9] vs. 13.5 ng/mL [7.2] for female control subjects (p = .001), while male patients had a mean of 15.3 ng/mL [9.5] vs. 7.6 ng/mL [2.2] for male control subjects (p = .006). Patients and control subjects did not differ on concentrations of TSH, ghrelin, or cortisol. The group differences could not be attributed to differences in age, gender, smoking, body mass index, ethnicity, or the socioeconomic status of the family of origin. Conclusions Increased prolactin concentrations in antipsychotic-naive patients do not appear to be due to important confounding variables, or to the effects of elevated TSH, ghrelin, or cortisol.

Schizophrenia has been associated with age-related abnormalities, including abnormal glucose tolerance, increased pulse pressure, increased inflammation, abnormal stem cell signaling, and shorter telomere length. These metabolic abnormalities and other findings suggest that schizophrenia and related disorders might be associated with accelerated aging. Testosterone activity has a progressive decline with increasing age.We tested the hypothesis that circulating biologically active testosterone is lower in newly diagnosed, antipsychotic-naive male patients with nonaffective psychosis than in matched control subjects.Patients (n = 33) were matched to control subjects (n = 33) for age, sex, body mass index, socioeconomic status of the family of origin, and smoking. The free androgen index, a measure of biologically active testosterone, was significantly lower in the psychosis group (mean [standard deviation] = 57.7% [26.1]) than in control subjects (71.6% [27.0], p = .04), with an effect size of 0.53. Multivariate analysis also supported the findings. In the psychosis group, free androgen index had a significant negative correlation with the conceptual disorganization item (r = -0.35, p = .049) but not with reality distortion (r = -0.21, p = .24), negative symptoms (r = 0.004, p = .98), or depression (r = -0.014, p = .94).Lower testosterone level is consistent with accelerated aging in nonaffective psychosis, but further testing of this hypothesis is needed.

Background Some studies suggest that schizophrenia may be associated with an increased risk of diabetes, independently of antipsychotic medications and other confounding factors. Previous studies have also suggested that there is an increased prevalence of diabetes in the relatives of schizophrenia probands. Method First-degree siblings of schizophrenia probands ( N = 6) and control subjects ( N = 12) were administered a glucose tolerance test. Subjects were matched for gender, age, body mass index, neighborhood of residence, socio-economic status and smoking habits. Results The siblings of schizophrenia probands had a significantly increased two-hour mean glucose concentration compared to the control subjects (respective means [SD] were 100.5 mg/dL [27.7] vs. 78.0 [12.3]; p Conclusions Although confirmation with larger samples is needed, these results and other studies suggest that diabetes may share familial risk factors with schizophrenia.

Neurocognitive impairment is a core feature of schizophrenia and is closely associated with functional outcome. The importance of cognitive assessment is broadly accepted today, and an easy-to-use, internationality validated cognitive assessment tool is needed by researchers and in daily clinical practice. The Brief Assessment of Cognition in Schizophrenia (BACS) has been validated in English, French, Japanese and Italian. It is as sensitive to cognitive dysfunction as a standard test battery, with the advantage of requiring less than 35 minutes to complete. In our study, we tested the psychometric characteristics of a Spanish version of the BACS in 117 patients with schizophrenia-spectrum disorders and 36 healthy controls. All BACS cognitive subtests discriminated between patients and controls (P< .001), and the concurrent validity between the BACS and a traditional neuropsychological test battery was similar to that reported in other languages. We conclude that the BACS can facilitate the comparison of the cognitive performance of patients with schizophrenia in many different countries.

a Schizophrenia Program, Department of Psychiatry, Neuroscience Institute, Hospital Clinic, University of Barcelona, Barcelona, Spain b Department of Psychiatry, University of Cambridge, Addenbrooke's Hospital, CB2 0QQ Cambridge, UK c Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK d Institute of Biomedical Research Agusti Pi i Sunyer (IDIBAPS), Barcelona, Spain e CIBERSAM, Madrid, Spain f Department of Psychiatry, Texas A&M University College of Medicine and Scott & White Healthcare, Temple, TX, USA

BackgroundSome studies suggest individuals with schizophrenia have an increased risk of diabetes prior to antipsychotic use. Small sample sizes and the potential for confounding by hypercortisolaemia have decreased confidence in those results.AimsTo examine diabetes-related factors in newly diagnosed, antipsychotic-naive people with non-affective psychosis.MethodParticipants with psychosis (the psychosis group;n= 50) and matched controls (the control group;n= 50) were given a 2 h oral glucose tolerance test. Fasting concentrations were also determined for adiponectin, interleukin-6 and C-reactive protein.ResultsCompared with the control group, the psychosis group had significant increases in 2 h glucose and interleukin-6 concentrations, and in the prevalence of abnormal glucose tolerance (16% of psychosis groupv.0% of control group). Adiponectin and C-reactive protein concentrations did not differ significantly between the two groups. These findings could not be attributed to differences in cortisol concentrations, smoking, gender, neighbourhood of residence, body mass index, aerobic conditioning, ethnicity, socioeconomic status or age.ConclusionsIndividuals with non-affective psychosis appear to have an increased prevalence of abnormal glucose tolerance prior to antipsychotic treatment, as well as abnormalities in a related inflammatory molecule. These underlying problems may contribute to the metabolic side-effects of antipsychotic medications.

Psychotic symptoms occur in a majority of schizophrenia patients, and in approximately 50% of all Parkinson’s disease (PD) patients. Altered grey matter (GM) structure within several brain areas and networks may contribute to their pathogenesis. Little, however, is known about transdiagnostic similarities when psychotic symptoms occur in different disorders, such as schizophrenia and PD.The present study investigated a large, multicenter sample containing 722 participants: 146 patients with first episode psychosis, FEP; 106 individuals at-risk mental state for developing psychosis, ARMS; 145 healthy controls matching FEP and ARMS, Con-Psy; 92 PD patients with psychotic symptoms, PDP; 145 PD patients without psychotic symptoms, PDN; 88 healthy controls matching PDN and PDP, Con-PD. We applied source-based morphometry in association with receiver operating curves (ROC) analyses to identify common GM structural covariance networks (SCN) and investigated their accuracy in identifying the different patient groups. We assessed group-specific homogeneity and variability across the different networks and potential associations with clinical symptoms.SCN-extracted GM values differed significantly between FEP and Con-Psy, PDP and Con-PD as well as PDN and Con-PD, indicating significant overall grey matter reductions in PD and early schizophrenia. ROC analyses showed that SCN-based classification algorithms allow good classification (AUC∼0.80) of FEP and Con-Psy, and fair performance (AUC∼0.72) when differentiating PDP from Con-PD. Importantly, best performance was found in partly the same networks including the precuneus. Finally, reduced GM volume in SCN with increased variability was linked to increased psychotic symptoms in both FEP and PDP.Alterations within selected SCNs may be related to the presence of psychotic symptoms in both early schizophrenia and PD psychosis, indicating some commonality of underlying mechanisms. Furthermore, results provide first evidence that GM volume within specific SCNs may serve as a biomarker for identifying FEP and PDP.