Neighbourhood characteristics and social isolation of people with psychosis: a multi-site cross-sectional study

Purpose: People with psychosis are vulnerable to social isolation, which is associated with worse clinical outcomes. In general populations, people living in areas with higher population density have more social contacts, while those living in more socially deprived and fragmented areas are less satisfied with their relationships. We assessed whether and how neighbourhood factors are associated with social contacts and satisfaction with friendships for people with psychosis. Methods: We carried out a cross-sectional study including people with psychosis aged 18–65 years in urban and rural sites in England. Population density and social deprivation and fragmentation indexes were described within Lower Level Super Output Areas (LSOA). Their associations with participants’ social contacts and satisfaction with friendships were tested with negative binomial and ordinal regression models, respectively. Results: We surveyed 511 participants with psychotic disorders. They had a median of two social contacts in the previous week (interquartile range [IQR] = 1–4), and rated satisfaction with friendships as 5 out of 7 (Manchester Short Assessment of Quality of Life; IQR = 4–6). Higher population density was associated with fewer social contacts (Z-standardised relative risk [RR] = 0.88; 95% CI = 0.79–0.99, p = 0.03), but not with satisfaction with friendships (RR = 1.08; 95% CI = 0.93–1.26, p = 0.31). No associations were found for social contacts or satisfaction with friendships with social deprivation or fragmentation indexes. Conclusions: Clinicians in urban areas should be aware that their patients with psychosis are more socially isolated when more people live around them, and this could impact their clinical outcomes. These findings may inform housing programmes

Cost Evaluation During Decision-Making in Patients at Early Stages of Psychosis

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

Cortical and Striatal Reward Processing in Parkinson's Disease Psychosis

Psychotic symptoms frequently occur in Parkinson's disease (PD), but their pathophysiology is poorly understood. According to the National Institute of Health RDoc programme, the pathophysiological basis of neuropsychiatric symptoms may be better understood in terms of dysfunction of underlying domains of neurocognition in a trans-diagnostic fashion. Abnormal cortico-striatal reward processing has been proposed as a key domain contributing to the pathogenesis of psychotic symptoms in schizophrenia. This theory has received empirical support in the study of schizophrenia spectrum disorders and preclinical models of psychosis, but has not been tested in the psychosis associated with PD. We, therefore, investigated brain responses associated with reward expectation and prediction error signaling during reinforcement learning in PD-associated psychosis. An instrumental learning task with monetary gains and losses was conducted during an fMRI study in PD patients with (n = 12), or without (n = 17), a history of psychotic symptoms, along with a sample of healthy controls (n = 24). We conducted region of interest analyses in the ventral striatum (VS), ventromedial prefrontal and posterior cingulate cortices, and whole-brain analyses. There was reduced activation in PD patients with a history of psychosis, compared to those without, in the posterior cingulate cortex and the VS during reward anticipation (p < 0.05 small volume corrected). The results suggest that cortical and striatal abnormalities in reward processing, a putative pathophysiological mechanism of psychosis in schizophrenia, may also contribute to the pathogenesis of psychotic symptoms in PD. The finding of posterior cingulate dysfunction is in keeping with prior results highlighting cortical dysfunction in the pathogenesis of PD psychosis.This study was supported by a Medical Research Council Clinician Scientist award (G0701911), and an Isaac Newton Trust award to Dr. Murray; by support to Dr. Fletcher from the Wellcome Trust and Bernard Wolfe Health Neuroscience Fund; by a Wellcome Trust strategic award to University of Cambridge (097814/Z/11), by the NIHR Cambridge Biomedical Research Centre and University of Cambridge Behavioural and Clinical Neuroscience Institute, supported by a joint award from the Medical Research Council (G1000183) and Wellcome Trust (093875/Z/10/Z)

Width of Gene Expression Profile Drives Alternative Splicing

Alternative splicing generates an enormous amount of functional and proteomic diversity in metazoan organisms. This process is probably central to the macromolecular and cellular complexity of higher eukaryotes. While most studies have focused on the molecular mechanism triggering and controlling alternative splicing, as well as on its incidence in different species, its maintenance and evolution within populations has been little investigated. Here, we propose to address these questions by comparing the structural characteristics as well as the functional and transcriptional profiles of genes with monomorphic or polymorphic splicing, referred to as MS and PS genes, respectively. We find that MS and PS genes differ particularly in the number of tissues and cell types where they are expressed.We find a striking deficit of PS genes on the sex chromosomes, particularly on the Y chromosome where it is shown not to be due to the observed lower breadth of expression of genes on that chromosome. The development of a simple model of evolution of cis-regulated alternative splicing leads to predictions in agreement with these observations. It further predicts the conditions for the emergence and the maintenance of cis-regulated alternative splicing, which are both favored by the tissue specific expression of splicing variants. We finally propose that the width of the gene expression profile is an essential factor for the acquisition of new transcript isoforms that could later be maintained by a new form of balancing selection