Schizophrenia is a highly disabling psychiatric disorder characterized by a range of positive “psychosis” symptoms. However, the neurobiology of psychosis and associated systems-level disruptions in ...the brain remain poorly understood. Here, we test an aberrant saliency model of psychosis, which posits that dysregulated dynamic cross-network interactions among the salience network (SN), central executive network, and default mode network contribute to positive symptoms in patients with schizophrenia.
Using task-free functional magnetic resonance imaging data from two independent cohorts, we examined 1) dynamic time-varying cross-network interactions among the SN, central executive network, and default mode network in 130 patients with schizophrenia versus well-matched control subjects; 2) accuracy of a saliency model–based classifier for distinguishing dynamic brain network interactions in patients versus control subjects; and 3) the relation between SN-centered network dynamics and clinical symptoms.
In both cohorts, we found that dynamic SN-centered cross-network interactions were significantly reduced, less persistent, and more variable in patients with schizophrenia compared with control subjects. Multivariate classification analysis identified dynamic SN-centered cross-network interaction patterns as factors that distinguish patients from control subjects, with accuracies of 78% and 80% in the two cohorts, respectively. Crucially, in both cohorts, dynamic time-varying measures of SN-centered cross-network interactions were correlated with positive, but not negative, symptoms.
Aberrations in time-varying engagement of the SN with the central executive network and default mode network is a clinically relevant neurobiological signature of psychosis in schizophrenia. Our findings provide strong evidence for dysregulated brain dynamics in a triple-network saliency model of schizophrenia and inform theoretically motivated systems neuroscience approaches for characterizing aberrant brain dynamics associated with psychosis.
This study aimed to examine whether 40-Hz auditory steady-state responses (ASSRs) are impaired in participants at clinical high-risk for psychosis (CHR-P) and predict clinical outcomes.
...Magnetoencephalography data were collected during a 40-Hz ASSR paradigm for a group of 116 CHR-P participants, 33 patients with first-episode psychosis (15 antipsychotic-naïve), a psychosis risk–negative group (n = 38), and 49 healthy control subjects. Analysis of group differences of 40-Hz intertrial phase coherence and 40-Hz amplitude focused on right Heschl’s gyrus, superior temporal gyrus, hippocampus, and thalamus after establishing significant activations during 40-Hz ASSR stimulation. Linear regression and linear discriminant analyses were used to predict clinical outcomes in CHR-P participants, including transition to psychosis and persistence of attenuated psychotic symptoms (APSs).
CHR-P participants and patients with first-episode psychosis were impaired in 40-Hz amplitude in the right thalamus and hippocampus. In addition, patients with first-episode psychosis were impaired in 40-Hz amplitude in the right Heschl’s gyrus, and CHR-P participants in 40-Hz intertrial phase coherence in the right Heschl’s gyrus. The 40-Hz ASSR deficits were pronounced in CHR-P participants who later transitioned to psychosis (n = 13) or showed persistent APSs (n = 34). Importantly, both APS persistence and transition to psychosis were predicted by 40-Hz ASSR impairments, with ASSR activity in the right hippocampus, superior temporal gyrus, and middle temporal gyrus correctly classifying 69.2% individuals with nonpersistent APSs and 73.5% individuals with persistent APSs (area under the curve = 0.842), and right thalamus 40-Hz activity correctly classifying 76.9% transitioned and 53.6% nontransitioned CHR-P participants (area under the curve = 0.695).
Our data indicate that deficits in gamma-band entrainment in the primary auditory cortex and subcortical areas constitute a potential biomarker for predicting clinical outcomes in CHR-P participants.
Reasons for the increased prevalence of cigarette smoking in schizophrenia are unclear. Studies assessing clinical symptoms have sampled heterogeneous populations, with discrepant findings.
To ...examine the relationship between clinical features, social adjustment and nicotine dependence in a geographically defined population of people with schizophrenia.
Cross-sectional clinical study of 131 people with schizophrenia in Nithsdale, Scotland.
Smokers were younger, mostly males and three times more likely to be unemployed. Those with severe nicotine dependence had greater scores on the positive subscale of the Positive and Negative Syndrome Scale (PANSS), and were prescribed higher doses of antipsychotic. Those with mild-moderate dependence had greater scores on the PANSS negative subscale. Greater symptom severity was associated with poorer social adjustment. Psychopathology and social adjustment were similar in quitters and never-smokers.
Our findings indicate an association between nicotine dependence, clinical symptoms and social adjustment in schizophrenia. Although causal links cannot be inferred, identifying the relationship between nicotine dependence and psychopathology may have some value in the management of smoking in schizophrenia. Further longitudinal studies are required to explore this relationship.
Stigma and discrimination associated with mental illness are strongly linked to suffering, disability and poverty. In order to protect the rights of those with mental disorders and to sensitively ...develop services, it is vital to gain a more accurate understanding of the frequency and nature of stigma against people with mental illness. Little research about this issue has been conducted in Sub- Saharan Africa. Our study aimed to describe levels of stigma in Malawi.
A cross-sectional survey of patients and carers attending mental health and non-mental health related clinics in a general hospital in Blantyre, Malawi. Participants were interviewed using an adapted version of the questionnaire developed for the "World Psychiatric Association Program to Reduce Stigma and Discrimination Because of Schizophrenia".
210 participants participated in our study. Most attributed mental disorder to alcohol and illicit drug abuse (95.7%). This was closely followed by brain disease (92.8%), spirit possession (82.8%) and psychological trauma (76.1%). There were some associations found between demographic variables and single question responses, however no consistent trends were observed in stigmatising beliefs. These results should be interpreted with caution and in the context of existing research. Contrary to the international literature, having direct personal experience of mental illness seemed to have no positive effect on stigmatising beliefs in our sample.
Our study contributes to an emerging picture that individuals in Sub-Saharan Africa most commonly attribute mental illness to alcohol/ illicit drug use and spirit possession. Our work adds weight to the argument that stigma towards mental illness is an important global health and human rights issue.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Depression: an inflammatory illness? Krishnadas, Rajeev; Cavanagh, Jonathan
Journal of neurology, neurosurgery and psychiatry,
05/2012, Letnik:
83, Številka:
5
Journal Article
Recenzirano
Odprti dostop
Major depressive disorder (MDD) is associated with significant morbidity and mortality. Findings from preclinical and clinical studies suggest that psychiatric illnesses, particularly MDD, are ...associated with inflammatory processes. While it is unlikely that MDD is a primary 'inflammatory' disorder, there is now evidence to suggest that inflammation may play a subtle role in the pathophysiology of MDD. Most of the evidence that links inflammation to MDD comes from three observations: (a) one-third of those with major depression show elevated peripheral inflammatory biomarkers, even in the absence of a medical illness; (b) inflammatory illnesses are associated with greater rates of MDD; and (c) patients treated with cytokines are at greater risk of developing major depressive illness. We now know that the brain is not an immune privileged organ. Inflammatory mediators have been found to affect various substrates thought to be important in the aetiopathogenesis of MDD, including altered monoamine and glutamate neurotransmission, glucocorticoid receptor resistance and adult hippocampal neurogenesis. At a higher level, inflammation is thought to affect brain signalling patterns, cognition and the production of a constellation of symptoms, termed 'sickness behaviour'. Inflammation may therefore play a role in the aetiology of depression, at least in a 'cohort' of vulnerable individuals. Inflammation may not only act as a precipitating factor that pushes a person into depression but also a perpetuating factor that may pose an obstacle to recovery. More importantly, inflammatory markers may aid in the diagnosis and prediction of treatment response, leading to the possibility of tailored treatments, thereby allowing stratification of what remains a heterogenous disorder.
Early illness course correlates with long-term outcome in psychosis. Accurate prediction could allow more focused intervention. Earlier intervention corresponds to significantly better symptomatic ...and functional outcomes. Our study objective is to use routinely collected baseline demographic and clinical characteristics to predict employment, education or training (EET) status, and symptom remission in patients with first episode psychosis (FEP) at one-year.
83 FEP patients were recruited from National Health Service (NHS) Glasgow between 2011 and 2014 to a 24-month prospective cohort study with regular assessment of demographic and psychometric measures. An external independent cohort of 79 FEP patients were recruited from NHS Glasgow and Edinburgh during a 12-month study between 2006 and 2009. Elastic net regularised logistic regression models were built to predict binary EET status, period and point remission outcomes at one-year on 83 Glasgow patients (training dataset). Models were externally validated on an independent dataset of 79 patients from Glasgow and Edinburgh (validation dataset). Only baseline predictors shared across both cohorts were made available for model training and validation. After excluding participants with missing outcomes, models were built on the training dataset for EET status, period and point remission outcomes and externally validated on the validation dataset. Models predicted EET status, period and point remission with receiver operating curve (ROC) area under the curve (AUC) performances of 0.876 (95%CI: 0.864, 0.887), 0.630 (95%CI: 0.612, 0.647) and 0.652 (95%CI: 0.635, 0.670) respectively. Positive predictors of EET included baseline EET and living with spouse/children. Negative predictors included higher PANSS suspiciousness, hostility and delusions scores. Positive predictors for symptom remission included living with spouse/children, and affective symptoms on the Positive and Negative Syndrome Scale (PANSS). Negative predictors of remission included passive social withdrawal symptoms on PANSS. A key limitation of this study is the small sample size (n) relative to the number of predictors (p), whereby p approaches n. The use of elastic net regularised regression rather than ordinary least squares regression helped circumvent this difficulty. Further, we did not have information for biological and additional social variables, such as nicotine dependence, which observational studies have linked to outcomes in psychosis.
Using advanced statistical machine learning techniques, we provide the first externally validated evidence, in a temporally and geographically independent cohort, for the ability to predict one-year EET status and symptom remission in individual FEP patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Machine-learning techniques are used in this BJPsych special issue on precision medicine in attempts to create statistical models that make clinically relevant predictions for individual patients. In ...this primer, we outline five key points that are helpful for a new reader to consider in order to engage with the field and evaluate the literature. These points include the consideration of why we are interested in new statistical approaches, how they may produce individualised predictions, what caveats need to be kept in-mind and why the interest and engagment of clinicians and clinical researchers is critical to successful model development and implementation. We hope that the following primer will provide shared understanding to encourage dialogue between clinical and methodological fields.
•Long Range Temporal Correlations do not reflect the clinical trajectory of psychosis.•Reduced Long Range Temporal Correlations may appear at the onset of psychosis.•Antipsychotic medication may ...affect Long Range Temporal Correlations.•Long Range Temporal Correlations do not correlate with symptoms of psychosis.
Long-Range Temporal Correlations (LRTCs) index the capacity of the brain to optimally process information. Previous research has shown that patients with chronic schizophrenia present altered LRTCs at alpha and beta oscillations. However, it is currently unclear at which stage of schizophrenia aberrant LRTCs emerge. To address this question, we investigated LRTCs in resting-state magnetoencephalographic (MEG) recordings obtained from patients with affective disorders and substance abuse (clinically at low-risk of psychosis, CHR-N), patients at clinical high-risk of psychosis (CHR-P) (n = 115), as well as patients with a first episode (FEP) (n = 25). Matched healthy controls (n = 47) served as comparison group. LRTCs were obtained for frequencies from 4 to 40 Hz and correlated with clinical and neuropsychological data. In addition, we examined the relationship between LRTCs and transition to psychosis in CHR-P participants, and the relationship between LRTC and antipsychotic medication in FEP participants. Our results show that participants from the clinical groups have similar LRTCs to controls. In addition, LRTCs did not correlate with clinical and neurocognitive variables across participants nor did LRTCs predict transition to psychosis. Therefore, impaired LRTCs do not reflect a feature in the clinical trajectory of psychosis. Nevertheless, reduced LRTCs in the beta-band over posterior sensors of medicated FEP participants indicate that altered LRTCs may appear at the onset of the illness. Future studies are needed to elucidate the role of anti-psychotic medication in altered LRTCs.
•Individuals with early-stage psychosis show reduced hippocampal volumes.•FEP show bilateral and widespread changes, while left hemisphere is affected in CHR-P.•However, hippocampal changes do not ...show a relationship with clinical outcomes.
Hippocampal dysfunctions are a core feature of schizophrenia, but conflicting evidence exists whether volumetric and morphological changes are present in early-stage psychosis and to what extent these deficits are related to clinical trajectories. In this study, we recruited individuals at clinical high risk for psychosis (CHR-P) (n = 108), patients with a first episode of psychosis (FEP) (n = 37), healthy controls (HC) (n = 70) as well as a psychiatric control group with substance abuse and affective disorders (CHR-N: n = 38). MRI-data at baseline were obtained and volumetric as well as vertex analyses of the hippocampus were carried out. Moreover, volumetric changes were examined in the amygdala, caudate, nucleus accumbens, pallidum, putamen and thalamus. In addition, we obtained follow-up functional and symptomatic assessments in CHR-P individuals to examine the question whether anatomical deficits at baseline predicted clinical trajectories. Our results show that the hippocampus is the only structure showing significant volumetric decrease in early-stage psychosis, with FEPs showing significantly smaller hippocampal volumes bilaterally alongside widespread shape changes in the vertex analysis. For the CHR-P group, volumetric decreases were confined to the left hippocampus. However, hippocampal alterations in the CHR-P group were not robustly associated with clinical outcomes, including the persistence of attenuated psychotic symptoms and functional trajectories. Accordingly, our findings highlight that dysfunctions in hippocampal anatomy are an important feature of early-stage psychosis which may, however, not be related to clinical outcomes in CHR-P participants.
Systemic inflammation has been associated with negative mood states and human sickness behaviour. Previous studies have shown an association between systemic inflammation and changes in task-related ...blood-oxygen-level-dependent activity and functional connectivity within large-scale networks. However, no study has examined the effect of inflammation on the magnitude of blood-oxygen-level-dependent low-frequency fluctuations at rest. We used a double-blind placebo-controlled crossover design to randomise 20 male subjects (aged 20–50 years) to receive either a Salmonella typhi vaccine or a placebo saline injection at two separate sessions. All participants underwent a resting-state functional magnetic resonance scan and a measure of inflammation (interleukin 6) and mood (Profile of Mood States) 3 h after injection. We compared the whole brain amplitude of low-frequency fluctuations between the vaccine and placebo conditions using a repeated measures design. Vaccine condition was associated with greater interleukin 6 levels (p < 0.001). Vaccine condition was also associated with lower amplitude of low-frequency fluctuations in the right and left frontal pole, superior frontal gyrus, paracingulate gyrus (Cluster 1) and the right mid and inferior frontal gyrus (Cluster 2) (p < 0.001, false discovery rate corrected). Lower amplitude of low-frequency fluctuations pertaining to first cluster correlated with greater total Profile of Mood States score (worse mood) (r = −0.38; p = 0.04). These results imply possible excitation/inhibition imbalance mechanisms during inflammation that may be a relevant target in psychiatric disease, especially mood disorders.
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