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Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.
A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15–41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1–2 s.d. below or above HC, respectively) for each cognitive test.
Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.
These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.
Major depressive disorder (MDD) is highly prevalent across Europe. While evidence-based treatments exist, many people with MDD have their condition undetected and/or untreated. This study aimed to assess the cost-effectiveness of reducing treatment gaps using a modeling approach.
A decision-tree model covering a 27-month time horizon was used. This followed a care pathway where MDD could be detected or not, and where different forms of treatment could be provided. Expected costs pertaining to Germany, Hungary, Italy, Portugal, Sweden, and the UK were calculated and quality-adjusted life years (QALYs) were estimated. The incremental costs per QALY of reducing detection and treatment gaps were estimated.
The expected costs with a detection gap of 69% and treatment gap of 50% were €1236 in Germany, €476 in Hungary, €1413 in Italy, €938 in Portugal, €2093 in Sweden, and €1496 in the UK. The incremental costs per QALY of reducing the detection gap to 50% ranged from €2429 in Hungary to €10,686 in Sweden. The figures for reducing the treatment gap to 25% ranged from €3146 in Hungary to €13,843 in Sweden.
Reducing detection and treatment gaps, and maintaining current patterns of care, is likely to increase healthcare costs in the short term. However, outcomes are improved, and reducing these gaps to 50 and 25%, respectively, appears to be a cost-effective use of resources.
Understanding the evolution of negative symptoms in first-episode psychosis (FEP) requires long-term longitudinal study designs that capture the progression of this condition and the associated brain changes.
To explore the factors underlying negative symptoms and their association with long-term abnormal brain trajectories.
We followed up 357 people with FEP over a 10-year period. Factor analyses were conducted to explore negative symptom dimensionality. Latent growth mixture modelling (LGMM) was used to identify the latent classes. Analysis of variance (ANOVA) was conducted to investigate developmental trajectories of cortical thickness. Finally, the resulting ANOVA maps were correlated with a wide set of regional molecular profiles derived from public databases.
Three trajectories (stable, decreasing and increasing) were found in each of the three factors (expressivity, experiential and attention) identified by the factor analyses. Patients with an increasing trajectory in the expressivity factor showed cortical thinning in caudal middle frontal, pars triangularis, rostral middle frontal and superior frontal regions from the third to the tenth year after the onset of the psychotic disorder. The F-statistic map of cortical thickness expressivity differences was associated with a receptor density map derived from positron emission tomography data.
Stable and decreasing were the most common trajectories. Additionally, cortical thickness abnormalities found at relatively late stages of FEP onset could be exploited as a biomarker of poor symptom outcome in the expressivity dimension. Finally, the brain areas with less density of receptors spatially overlap areas that discriminate the trajectories of the expressivity dimension.
Cognitive deficits are prevalent in bipolar disorder even during the euthymic phase, having a negative impact on global functioning and quality of life. As such, more and more mental health professionals agree that neuropsychological assessment should be considered an essential component of the clinical management of bipolar patients. However, no gold standard tool has been established so far. According to bipolar disorder experts targeting cognition, appropriate cognitive tools should be brief, easy to administer, cost-effective and validated in the target population. In this commentary, we critically appraised the strengths and limitations of the tools most commonly used to assess cognitive functioning in bipolar patients, both for screening and diagnostic purposes.
Despite well-established guidelines for managing major depressive disorder, its extensive disability burden persists. This Value of Treatment mission from the European Brain Council aimed to elucidate the nature and extent of “gaps” between best-practice and current-practice care, specifically to:
1. Identify current treatment gaps along the care pathway and determine the extent of these gaps in comparison with the stepped-care model and
After agreement upon a set of relevant treatment gaps, data pertaining to each gap were gathered and synthesized from several sources across six European countries. Subsequently, a modified Delphi approach was undertaken to attain consensus among an expert panel on proposed recommendations for minimizing treatment gaps.
Four recommendations were made to increase the depression diagnosis rate (from ~50% episodes), aiming to both increase the number of patients seeking help, and the likelihood of a practitioner to correctly detect depression. These should reduce time to treatment (from ~1 to ~8 years after illness onset) and increase rates of treatment; nine further recommendations aimed to increase rates of treatment (from ~25 to ~50% of patients currently treated), mainly focused on targeting the best treatment to each patient. To improve follow-up after treatment initiation (from ~30 to ~65% followed up within 3 months), seven recommendations focused on increasing continuity of care. For those not responding, 10 recommendations focused on ensuring access to more specialist care (currently at rates of ~5–25% of patients).
The treatment gaps in depression care are substantial and concerning, from the proportion of people not entering care pathways to those stagnating in primary care with impairing and persistent illness. A wide range of recommendations can be made to enhance care throughout the pathway.
Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.
We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.
Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).
Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.
Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.
Early-life adverse events or childhood adversities (CAs) are stressors and harmful experiences severely impacting on a child's wellbeing and development. Examples of CAs include parental neglect, emotional and physical abuse and bullying. Even though the prevalence of CAs and their psychological effects in both healthy and psychiatric populations is established, only a paucity of studies have investigated the neurobiological firms associated with CAs in bipolar disorder (BD). In particular, the exact neural mechanisms and trajectories of biopsychosocial models integrating both environmental and genetic effects are still debated. Considering the potential impact of CAs on BD, including its clinical manifestations, we reviewed existing literature discussing the association between CAs and brain alterations in BD patients. Results showed that CAs are associated with volume alterations of several grey matter regions including the hippocampus, thalamus, amygdala and frontal cortex. A handful of studies suggest the presence of alterations in the corpus callosum and the pre-fronto-limbic connectivity at rest. Alterations in these regions of the brain of patients with BD are possibly due to the effect of stress produced by CAs, being hippocampus part of the hypothalamus–pituitary–adrenal axis and thalamus together with amygdala filtering sensory information and regulating emotional responses. However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies disentangling between different types of CAs or differentiating between BD sub-types are needed in order to understand the link between CAs and BD.
Personalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.
The European impact of the clinical high risk for psychosis (CHR-P) paradigm is constrained by the lack of critical mass (detection) to power prognostic and preventive interventions.
An ITAlian partnership for psychosis prevention (ITAPP) was created across CHR-P centers, which were surveyed to describe: (a) service, catchment area, and outreach; (b) service users; and (c) interventions and outcomes. Descriptive statistics and Kaplan–Meier failure function complemented the analyses.
The ITAPP included five CHR-P clinical academic centers established from 2007 to 2018, serving about 13 million inhabitants, with a recruitment capacity of 277 CHR-P individuals (mean age: 18.7 years, SD: 4.8, range: 12–39 years; 53.1% females; 85.7% meeting attenuated psychotic symptoms; 85.8% without any substance abuse). All centers were multidisciplinary and included adolescents and young adults (transitional) primarily recruited through healthcare services. The comprehensive assessment of at-risk mental state was the most widely used instrument, while the duration of follow-up, type of outreach, and preventive interventions were heterogeneous. Across 205 CHR-P individuals with follow up (663.7 days ± 551.7), the cumulative risk of psychosis increased from 8.7% (95% CI 5.3–14.1) at 1 year to 15.9% (95% CI 10.6–23.3) at 2 years, 21.8% (95% CI 14.9–31.3) at 3 years, 34.8% (95% CI 24.5–47.9) at 4 years, and 51.9% (95% CI 36.3–69.6) at 5 years.
The ITAPP is one of the few CHR-P clinical research partnerships in Europe for fostering detection, prognosis, and preventive care, as well as for translating research innovations into practice.
Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure.
We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry.
(i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains ‘emotional neglect’ and ‘emotional abuse’ were most predictive for CHR and ROP, while in ROD ‘physical abuse’ and ‘sexual abuse’ were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found.
These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.
According to the social brain hypothesis, the human brain includes a network designed for the processing of social information. This network includes several brain regions that elaborate social cues, interactions and contexts, i.e. prefrontal paracingulate and parietal cortices, amygdala, temporal lobes and the posterior superior temporal sulcus. While current literature suggests the importance of this network from both a psychological and evolutionary perspective, little is known about its neurobiological bases. Specifically, only a paucity of studies explored the neural underpinnings of constructs that are ascribed to the social brain network functioning, i.e. objective social isolation and perceived loneliness. As such, this review aimed to overview neuroimaging studies that investigated social isolation in healthy subjects. Social isolation correlated with both structural and functional alterations within the social brain network and in other regions that seem to support mentalising and social processes (i.e. hippocampus, insula, ventral striatum and cerebellum). However, results are mixed possibly due to the heterogeneity of methods and study design. Future neuroimaging studies with longitudinal designs are needed to measure the effect of social isolation in experimental v. control groups and to explore its relationship with perceived loneliness, ultimately helping to clarify the neural correlates of the social brain.
Diogenes syndrome is a neurobehavioural syndrome characterised by domestic squalor, hoarding and lack of insight. It is an uncommon but high-mortality condition, often associated with dementia.
To describe the clinical features and treatment of Diogenes syndrome secondary to behavioural variant frontotemporal dementia (bvFTD).
We describe a case of bvFTD in a 77-year-old man presenting with Diogenes syndrome.
The patient's medical and psychiatric histories were unremarkable, but in recent years he had begun packing his flat with ‘art pieces’. Mental state examination revealed confabulation and more structured delusions. Neuropsychological evaluation outlined an impairment in selective attention and letter verbal fluency, but no semantic impairment, in the context of an overall preserved mental functioning. Brain magnetic resonance imaging and positron emission tomography (PET) with fluorodeoxyglucose showed mild bilateral temporo-insular atrophy and hypometabolism in the left-superior temporal gyrus respectively. An amyloid PET scan and genetic analysis covering the dementia spectrum were normal. A diagnosis of bvFTD was made.
The clinical framing of behavioural symptoms of dementia such as hoarding poses a diagnostic challenge. This case illustrates the importance of a deeper understanding of Diogenes syndrome, leading to timelier diagnosis and effective therapeutic strategies.
Mood disorders are the most common mental illnesses with a lifetime prevalence of up to 20% worldwide (1). Major depressive disorder (MDD) and bipolar disorder (BD) are significant health problems in the United States and worldwide (2). In the United States alone, the lifetime prevalence of MDD is up to 17%, and that of BD about 2.1% (2) that can go up to 4% of individuals with mood episodes not meeting episodic criteria included. Both are chronic illnesses characterized by recurrent episodes of depression and mania and depression in MDD and BD, respectively. Severe and disabling forms of BD and MDD are associated with increased risk of suicide, decline of physical health, and reduced productivity, and both conditions are associated with high rates of completed suicide of up to 8% (3).
Mood disorders such as depression and bipolar disorder are common mental illnesses, affecting millions of patients worldwide. The application of newly available brain imaging methods to the study of mood disorders holds substantial promise in uncovering the brain mechanisms affected in these illnesses. This comprehensive and authoritative text features contributions from leading international experts, providing easily accessible information on the study of the brain mechanisms involved in the causation of mood disorders and the available treatments. Topics covered include the potential of magnetoencephalography (MEG), neuroimaging brain inflammation in depression, electrophysiology studies in mood disorders, and the applications of machine learning, filling an important gap in available neuropsychiatric literature and highlighting new developments. An invaluable resource for practitioners in the fields of psychiatry, neurology, primary care medicine, and related mental health professions, as well as researchers, students, graduate and post-graduate trainees.