Cambridgeshire and Peterborough NHS Foundation Trust

Promotion of good mental health, prevention, and early intervention before/at the onset of mental disorders improve outcomes. However, the range and peak ages at onset for mental disorders are not fully established. To provide robust, global epidemiological estimates of age at onset for mental disorders, we conducted a PRISMA/MOOSE-compliant systematic review with meta-analysis of birth cohort/cross-sectional/cohort studies, representative of the general population, reporting age at onset for any ICD/DSM-mental disorders, identified in PubMed/Web of Science (up to 16/05/2020) (PROSPERO:CRD42019143015). Co-primary outcomes were the proportion of individuals with onset of mental disorders before age 14, 18, 25, and peak age at onset, for any mental disorder and across International Classification of Diseases 11 diagnostic blocks. Median age at onset of specific disorders was additionally investigated. Across 192 studies (n = 708,561) included, the proportion of individuals with onset of any mental disorders before the ages of 14, 18, 25 were 34.6%, 48.4%, 62.5%, and peak age was 14.5 years (k = 14, median = 18, interquartile range (IQR) = 11-34). For diagnostic blocks, the proportion of individuals with onset of disorder before the age of 14, 18, 25 and peak age were as follows: neurodevelopmental disorders: 61.5%, 83.2%, 95.8%, 5.5 years (k = 21, median=12, IQR = 7-16), anxiety/fear-related disorders: 38.1%, 51.8%, 73.3%, 5.5 years (k = 73, median = 17, IQR = 9-25), obsessive-compulsive/related disorders: 24.6%, 45.1%, 64.0%, 14.5 years (k = 20, median = 19, IQR = 14-29), feeding/eating disorders/problems: 15.8%, 48.1%, 82.4%, 15.5 years (k = 11, median = 18, IQR = 15-23), conditions specifically associated with stress disorders: 16.9%, 27.6%, 43.1%, 15.5 years (k = 16, median = 30, IQR = 17-48), substance use disorders/addictive behaviours: 2.9%, 15.2%, 48.8%, 19.5 years (k = 58, median = 25, IQR = 20-41), schizophrenia-spectrum disorders/primary psychotic states: 3%, 12.3%, 47.8%, 20.5 years (k = 36, median = 25, IQR = 20-34), personality disorders/related traits: 1.9%, 9.6%, 47.7%, 20.5 years (k = 6, median = 25, IQR = 20-33), and mood disorders: 2.5%, 11.5%, 34.5%, 20.5 years (k = 79, median = 31, IQR = 21-46). No significant difference emerged by sex, or definition of age of onset. Median age at onset for specific mental disorders mapped on a time continuum, from phobias/separation anxiety/autism spectrum disorder/attention deficit hyperactivity disorder/social anxiety (8-13 years) to anorexia nervosa/bulimia nervosa/obsessive-compulsive/binge eating/cannabis use disorders (17-22 years), followed by schizophrenia, personality, panic and alcohol use disorders (25-27 years), and finally post-traumatic/depressive/generalized anxiety/bipolar/acute and transient psychotic disorders (30-35 years), with overlap among groups and no significant clustering. These results inform the timing of good mental health promotion/preventive/early intervention, updating the current mental health system structured around a child/adult service schism at age 18.

Abstract Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

The prevalence, age of onset, and symptomatology of many neuropsychiatric conditions differ between males and females. To understand the causes and consequences of sex differences it is important to establish where they occur in the human brain. We report the first meta-analysis of typical sex differences on global brain volume, a descriptive account of the breakdown of studies of each compartmental volume by six age categories, and whole-brain voxel-wise meta-analyses on brain volume and density. Gaussian-process regression coordinate-based meta-analysis was used to examine sex differences in voxel-based regional volume and density. On average, males have larger total brain volumes than females. Examination of the breakdown of studies providing total volumes by age categories indicated a bias towards the 18-59 year-old category. Regional sex differences in volume and tissue density include the amygdala, hippocampus and insula, areas known to be implicated in sex-biased neuropsychiatric conditions. Together, these results suggest candidate regions for investigating the asymmetric effect that sex has on the developing brain, and for understanding sex-biased neurological and psychiatric conditions.

Brain networks or 'connectomes' include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, we first identified the hubs of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n = 56), and showed that computational attacks targeted on hubs disproportionally degraded the efficiency of brain networks compared to random attacks. We then prepared grey matter lesion maps, based on meta-analyses of published magnetic resonance imaging data on more than 20 000 subjects and 26 different brain disorders. Magnetic resonance imaging lesions that were common across all brain disorders were more likely to be located in hubs of the normal brain connectome (P < 10(-4), permutation test). Specifically, nine brain disorders had lesions that were significantly more likely to be located in hubs (P < 0.05, permutation test), including schizophrenia and Alzheimer's disease. Both these disorders had significantly hub-concentrated lesion distributions, although (almost completely) distinct subsets of cortical hubs were lesioned in each disorder: temporal lobe hubs specifically were associated with higher lesion probability in Alzheimer's disease, whereas in schizophrenia lesions were concentrated in both frontal and temporal cortical hubs. These results linking pathological lesions to the topological centrality of nodes in the normal diffusion tensor imaging connectome were generally replicated when hubs were defined instead by the meta-analysis of more than 1500 task-related functional neuroimaging studies of healthy volunteers to create a normative functional co-activation network. We conclude that the high cost/high value hubs of human brain networks are more likely to be anatomically abnormal than non-hubs in many (if not all) brain disorders.

CONTEXT: Second-generation (atypical) antipsychotics (SGAs) are more expensive than first-generation (typical) antipsychotics (FGAs) but are perceived to be more effective, with fewer adverse effects, and preferable to patients. Most evidence comes from short-term efficacy trials of symptoms. OBJECTIVE: To test the hypothesis that in people with schizophrenia requiring a change in treatment, SGAs other than clozapine are associated with improved quality of life across 1 year compared with FGAs. DESIGN: A noncommercially funded, pragmatic, multisite, randomized controlled trial of antipsychotic drug classes, with blind assessments at 12, 26, and 56 weeks using intention-to-treat analysis. SETTING: Fourteen community psychiatric services in the English National Health Service. PARTICIPANTS: Two hundred twenty-seven people aged 18 to 65 years with DSM-IV schizophrenia and related disorders assessed for medication review because of inadequate response or adverse effects. INTERVENTIONS: Randomized prescription of either FGAs or SGAs (other than clozapine), with the choice of individual drug made by the managing psychiatrist. MAIN OUTCOME MEASURES: Quality of Life Scale scores, symptoms, adverse effects, participant satisfaction, and costs of care. RESULTS: The primary hypothesis of significant improvement in Quality of Life Scale scores during the year after commencement of SGAs vs FGAs was excluded. Participants in the FGA arm showed a trend toward greater improvements in Quality of Life Scale and symptom scores. Participants reported no clear preference for either drug group; costs were similar. CONCLUSIONS: In people with schizophrenia whose medication is changed for clinical reasons, there is no disadvantage across 1 year in terms of quality of life, symptoms, or associated costs of care in using FGAs rather than nonclozapine SGAs. Neither inadequate power nor patterns of drug discontinuation accounted for the result.

OBJECTIVE: The relationship between sex/gender differences and autism has attracted a variety of research ranging from clinical and neurobiological to etiological, stimulated by the male bias in autism prevalence. Findings are complex and do not always relate to each other in a straightforward manner. Distinct but interlinked questions on the relationship between sex/gender differences and autism remain underaddressed. To better understand the implications from existing research and to help design future studies, we propose a 4-level conceptual framework to clarify the embedded themes. METHOD: We searched PubMed for publications before September 2014 using search terms "'sex OR gender OR females' AND autism." A total of 1,906 articles were screened for relevance, along with publications identified via additional literature reviews, resulting in 329 articles that were reviewed. RESULTS: Level 1, "Nosological and diagnostic challenges," concerns the question, "How should autism be defined and diagnosed in males and females?" Level 2, "Sex/gender-independent and sex/gender-dependent characteristics," addresses the question, "What are the similarities and differences between males and females with autism?" Level 3, "General models of etiology: liability and threshold," asks the question, "How is the liability for developing autism linked to sex/gender?" Level 4, "Specific etiological-developmental mechanisms," focuses on the question, "What etiological-developmental mechanisms of autism are implicated by sex/gender and/or sexual/gender differentiation?" CONCLUSIONS: Using this conceptual framework, findings can be more clearly summarized, and the implications of the links between findings from different levels can become clearer. Based on this 4-level framework, we suggest future research directions, methodology, and specific topics in sex/gender differences and autism.

Most literature pertaining to carbon fibers is of a theoretical nature. Carbon Fibers and their Composites offers a comprehensive look at the specific manufacturing of carbon fibers and graphite fibers into the growing surge of diverse applications that include flameproof materials, protective coatings, biomedical and prosthetics application

People exposed to more unfavourable social circumstances are more vulnerable to poor mental health over their life course, in ways that are often determined by structural factors which generate and perpetuate intergenerational cycles of disadvantage and poor health. Addressing these challenges is an imperative matter of social justice. In this paper we provide a roadmap to address the social determinants that cause mental ill health. Relying as far as possible on high-quality evidence, we first map out the literature that supports a causal link between social determinants and later mental health outcomes. Given the breadth of this topic, we focus on the most pervasive social determinants across the life course, and those that are common across major mental disorders. We draw primarily on the available evidence from the Global North, acknowledging that other global contexts will face both similar and unique sets of social determinants that will require equitable attention. Much of our evidence focuses on mental health in groups who are marginalized, and thus often exposed to a multitude of intersecting social risk factors. These groups include refugees, asylum seekers and displaced persons, as well as ethnoracial minoritized groups; lesbian, gay, bisexual, transgender and queer (LGBTQ+) groups; and those living in poverty. We then introduce a preventive framework for conceptualizing the link between social determinants and mental health and disorder, which can guide much needed primary prevention strategies capable of reducing inequalities and improving population mental health. Following this, we provide a review of the evidence concerning candidate preventive strategies to intervene on social determinants of mental health. These interventions fall broadly within the scope of universal, selected and indicated primary prevention strategies, but we also briefly review important secondary and tertiary strategies to promote recovery in those with existing mental disorders. Finally, we provide seven key recommendations, framed around social justice, which constitute a roadmap for action in research, policy and public health. Adoption of these recommendations would provide an opportunity to advance efforts to intervene on modifiable social determinants that affect population mental health.

IMPORTANCE: The magnitude and variability of cytokine alterations in depression are not clear. OBJECTIVE: To perform an up to date meta-analysis of mean differences of immune markers in depression, and to quantify and test for evidence of heterogeneity in immune markers in depression by conducting a meta-analysis of variability to ascertain whether only a sub-group of patients with depression show evidence of inflammation. DATA SOURCES: Studies that reported immune marker levels in peripheral blood in patients with depression and matched healthy controls in the MEDLINE database from inception to August 29th 2018 were examined. STUDY SELECTION: Case-control studies that reported immune marker levels in peripheral blood in patients with depression and healthy controls were selected. DATA EXTRACTION AND SYNTHESIS: Means and variances (SDs) were extracted for each measure to calculate effect sizes, which were combined using multivariate meta-analysis. MAIN OUTCOMES AND MEASURES: Hedges g was used to quantify mean differences. Relative variability of immune marker measurements in patients compared with control groups as indexed by the coefficient of variation ratio (CVR). RESULTS: A total of 107 studies that reported measurements from 5,166 patients with depression and 5,083 controls were included in the analyses. Levels of CRP (g = 0.71; 95%CI: 0.50-0.92; p < 0.0001); IL-3 (g = 0.60; 95%CI: 0.31-0.89; p < 0.0001); IL-6 (g = 0.61; 95%CI: 0.39-0.82; p < 0.0001); IL-12 (g = 1.18; 95%CI: 0.74-1.62; p < 0.0001); IL-18 (g = 1.97; 95%CI: 1.00-2.95; p < 0.0001); sIL-2R (g = 0.71; 95%CI: 0.44-0.98; p < 0.0001); and TNFα (g = 0.54; 95%CI: 0.32-0.76; p < 0.0001) were significantly higher in patients with depression. These findings were robust to a range of potential confounds and moderators. Mean-scaled variability, measured as CVR, was significantly lower in patients with depression for CRP (CVR = 0.85; 95%CI: 0.75-0.98; p = 0.02); IL-12 (CVR = 0.61; 95%CI: 0.46-0.80; p < 0.01); and sIL-2R (CVR = 0.85; 95%CI: 0.73-0.99; p = 0.04), while it was unchanged for IL-3, IL-6, IL-18, and TNF α. CONCLUSIONS AND RELEVANCE: Depression is confirmed as a pro-inflammatory state. Some of the inflammatory markers elevated in depression, including CRP and IL-12, show reduced variability in patients with depression, therefore supporting greater homogeneity in terms of an inflammatory phenotype in depression. Some inflammatory marker elevations in depression do not appear due to an inflamed sub-group, but rather to a right shift of the immune marker distribution.

Fueled by developments in computational neuroscience, there has been increasing interest in the underlying neurocomputational mechanisms of psychosis. One successful approach involves predictive coding and Bayesian inference. Here, inferences regarding the current state of the world are made by combining prior beliefs with incoming sensory signals. Mismatches between prior beliefs and incoming signals constitute prediction errors that drive new learning. Psychosis has been suggested to result from a decreased precision in the encoding of prior beliefs relative to the sensory data, thereby garnering maladaptive inferences. Here, we review the current evidence for aberrant predictive coding and discuss challenges for this canonical predictive coding account of psychosis. For example, hallucinations and delusions may relate to distinct alterations in predictive coding, despite their common co-occurrence. More broadly, some studies implicate weakened prior beliefs in psychosis, and others find stronger priors. These challenges might be answered with a more nuanced view of predictive coding. Different priors may be specified for different sensory modalities and their integration, and deficits in each modality need not be uniform. Furthermore, hierarchical organization may be critical. Altered processes at lower levels of a hierarchy need not be linearly related to processes at higher levels (and vice versa). Finally, canonical theories do not highlight active inference-the process through which the effects of our actions on our sensations are anticipated and minimized. It is possible that conflicting findings might be reconciled by considering these complexities, portending a framework for psychosis more equipped to deal with its many manifestations.

BACKGROUND: Cannabis use is associated with increased risk of later psychotic disorder but whether it affects incidence of the disorder remains unclear. We aimed to identify patterns of cannabis use with the strongest effect on odds of psychotic disorder across Europe and explore whether differences in such patterns contribute to variations in the incidence rates of psychotic disorder. METHODS: -tetrahydrocannabinol (THC) in the different types of cannabis available across the sites, we divided the types of cannabis used by participants into two categories: low potency (THC <10%) and high potency (THC ≥10%). Assuming causality, we calculated the population attributable fractions (PAFs) for the patterns of cannabis use associated with the highest odds of psychosis and the correlation between such patterns and the incidence rates for psychotic disorder across the study sites. FINDINGS: Between May 1, 2010, and April 1, 2015, we obtained data from 901 patients with first-episode psychosis across 11 sites and 1237 population controls from those same sites. Daily cannabis use was associated with increased odds of psychotic disorder compared with never users (adjusted odds ratio [OR] 3·2, 95% CI 2·2-4·1), increasing to nearly five-times increased odds for daily use of high-potency types of cannabis (4·8, 2·5-6·3). The PAFs calculated indicated that if high-potency cannabis were no longer available, 12·2% (95% CI 3·0-16·1) of cases of first-episode psychosis could be prevented across the 11 sites, rising to 30·3% (15·2-40·0) in London and 50·3% (27·4-66·0) in Amsterdam. The adjusted incident rates for psychotic disorder were positively correlated with the prevalence in controls across the 11 sites of use of high-potency cannabis (r = 0·7; p=0·0286) and daily use (r = 0·8; p=0·0109). INTERPRETATION: Differences in frequency of daily cannabis use and in use of high-potency cannabis contributed to the striking variation in the incidence of psychotic disorder across the 11 studied sites. Given the increasing availability of high-potency cannabis, this has important implications for public health. FUNDING SOURCE: Medical Research Council, the European Community's Seventh Framework Program grant, São Paulo Research Foundation, National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and King's College London and the NIHR BRC at University College London, Wellcome Trust.

IMPORTANCE: Longitudinal studies have linked the systemic inflammatory markers interleukin 6 (IL-6) and C-reactive protein (CRP) with the risk of developing heart disease and diabetes mellitus, which are common comorbidities for depression and psychosis. Recent meta-analyses of cross-sectional studies have reported increased serum levels of these inflammatory markers in depression, first-episode psychosis, and acute psychotic relapse; however, the direction of the association has been unclear. OBJECTIVE: To test the hypothesis that higher serum levels of IL-6 and CRP in childhood would increase future risks for depression and psychosis. DESIGN, SETTING, AND PARTICIPANTS: The Avon Longitudinal Study of Parents and Children (ALSPAC)is a prospective general population birth cohort study based in Avon County, England. We have studied a subsample of approximately 4500 individuals from the cohort with data on childhood IL-6 and CRP levels and later psychiatric assessments. MEASUREMENT OF EXPOSURE: Levels of IL-6 and CRP were measured in nonfasting blood samples obtained in participants at age 9 years. MAIN OUTCOMES AND MEASURES: Participants were assessed at age 18 years. Depression was measured using the Clinical Interview Schedule-Revised (CIS-R) and Mood and Feelings Questionnaire (MFQ), thus allowing internal replication; psychotic experiences (PEs) and psychotic disorder were measured by a semistructured interview. RESULTS: After adjusting for sex, age, body mass index, ethnicity, social class, past psychological and behavioral problems, and maternal postpartum depression, participants in the top third of IL-6 values compared with the bottom third at age 9 years were more likely to be depressed (CIS-R) at age 18 years (adjusted odds ratio [OR], 1.55; 95% CI, 1.13-2.14). Results using the MFQ were similar. Risks of PEs and of psychotic disorder at age 18 years were also increased with higher IL-6 levels at baseline (adjusted OR, 1.81; 95% CI, 1.01-3.28; and adjusted OR, 2.40; 95% CI, 0.88-6.22, respectively). Higher IL-6 levels in childhood were associated with subsequent risks of depression and PEs in a dose-dependent manner. CONCLUSIONS AND RELEVANCE: Higher levels of the systemic inflammatory marker IL-6 in childhood are associated with an increased risk of developing depression and psychosis in young adulthood. Inflammatory pathways may provide important new intervention and prevention targets for these disorders. Inflammation might explain the high comorbidity between heart disease, diabetes mellitus, depression, and schizophrenia.

, we provide a narrative review of the transdiagnostic literature in order to situate the Special Section articles in context. We begin with a brief history of the diagnostic approach and outline several challenges it currently faces that arguably limit its applicability in current mental health science and practice. We then review several recent transdiagnostic approaches to classification, biopsychosocial processes, and clinical interventions, highlighting promising novel developments. Finally, we present some key challenges facing transdiagnostic science and make suggestions for a way forward. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

As a response to the COVID-19 pandemic, many governments have introduced steps such as spatial distancing and "staying at home" to curb its spread and impact. The fear resulting from the disease, the 'lockdown' situation, high levels of uncertainty regarding the future, and financial insecurity raise the level of stress, anxiety, and depression experienced by people all around the world. Psychoactive substances and other reinforcing behaviors (e.g., gambling, video gaming, watching pornography) are often used to reduce stress and anxiety and/or to alleviate depressed mood. The tendency to use such substances and engage in such behaviors in an excessive manner as putative coping strategies in crises like the COVID-19 pandemic is considerable. Moreover, the importance of information and communications technology (ICT) is even higher in the present crisis than usual. ICT has been crucial in keeping parts of the economy going, allowing large groups of people to work and study from home, enhancing social connectedness, providing greatly needed entertainment, etc. Although for the vast majority ICT use is adaptive and should not be pathologized, a subgroup of vulnerable individuals are at risk of developing problematic usage patterns. The present consensus guidance discusses these risks and makes some practical recommendations that may help diminish them.

IMPORTANCE: Relapse prevention in recurrent depression is a significant public health problem, and antidepressants are the current first-line treatment approach. Identifying an equally efficacious nonpharmacological intervention would be an important development. OBJECTIVE: To conduct a meta-analysis on individual patient data to examine the efficacy of mindfulness-based cognitive therapy (MBCT) compared with usual care and other active treatments, including antidepressants, in treating those with recurrent depression. DATA SOURCES: English-language studies published or accepted for publication in peer-reviewed journals identified from EMBASE, PubMed/Medline, PsycINFO, Web of Science, Scopus, and the Cochrane Controlled Trials Register from the first available year to November 22, 2014. Searches were conducted from November 2010 to November 2014. STUDY SELECTION: Randomized trials of manualized MBCT for relapse prevention in recurrent depression in full or partial remission that compared MBCT with at least 1 non-MBCT treatment, including usual care. DATA EXTRACTION AND SYNTHESIS: This was an update to a previous meta-analysis. We screened 2555 new records after removing duplicates. Abstracts were screened for full-text extraction (S.S.) and checked by another researcher (T.D.). There were no disagreements. Of the original 2555 studies, 766 were evaluated against full study inclusion criteria, and we acquired full text for 8. Of these, 4 studies were excluded, and the remaining 4 were combined with the 6 studies identified from the previous meta-analysis, yielding 10 studies for qualitative synthesis. Full patient data were not available for 1 of these studies, resulting in 9 studies with individual patient data, which were included in the quantitative synthesis. RESULTS: Of the 1258 patients included, the mean (SD) age was 47.1 (11.9) years, and 944 (75.0%) were female. A 2-stage random effects approach showed that patients receiving MBCT had a reduced risk of depressive relapse within a 60-week follow-up period compared with those who did not receive MBCT (hazard ratio, 0.69; 95% CI, 0.58-0.82). Furthermore, comparisons with active treatments suggest a reduced risk of depressive relapse within a 60-week follow-up period (hazard ratio, 0.79; 95% CI, 0.64-0.97). Using a 1-stage approach, sociodemographic (ie, age, sex, education, and relationship status) and psychiatric (ie, age at onset and number of previous episodes of depression) variables showed no statistically significant interaction with MBCT treatment. However, there was some evidence to suggest that a greater severity of depressive symptoms prior to treatment was associated with a larger effect of MBCT compared with other treatments. CONCLUSIONS AND RELEVANCE: Mindfulness-based cognitive therapy appears efficacious as a treatment for relapse prevention for those with recurrent depression, particularly those with more pronounced residual symptoms. Recommendations are made concerning how future trials can address remaining uncertainties and improve the rigor of the field.

BACKGROUND: Peripheral low-grade inflammation in depression is increasingly seen as a therapeutic target. We aimed to establish the prevalence of low-grade inflammation in depression, using different C-reactive protein (CRP) levels, through a systematic literature review and meta-analysis. METHODS: We searched the PubMed database from its inception to July 2018, and selected studies that assessed depression using a validated tool/scale, and allowed the calculation of the proportion of patients with low-grade inflammation (CRP >3 mg/L) or elevated CRP (>1 mg/L). RESULTS: After quality assessment, 37 studies comprising 13 541 depressed patients and 155 728 controls were included. Based on the meta-analysis of 30 studies, the prevalence of low-grade inflammation (CRP >3 mg/L) in depression was 27% (95% CI 21-34%); this prevalence was not associated with sample source (inpatient, outpatient or population-based), antidepressant treatment, participant age, BMI or ethnicity. Based on the meta-analysis of 17 studies of depression and matched healthy controls, the odds ratio for low-grade inflammation in depression was 1.46 (95% CI 1.22-1.75). The prevalence of elevated CRP (>1 mg/L) in depression was 58% (95% CI 47-69%), and the meta-analytic odds ratio for elevated CRP in depression compared with controls was 1.47 (95% CI 1.18-1.82). CONCLUSIONS: About a quarter of patients with depression show evidence of low-grade inflammation, and over half of patients show mildly elevated CRP levels. There are significant differences in the prevalence of low-grade inflammation between patients and matched healthy controls. These findings suggest that inflammation could be relevant to a large number of patients with depression.

The study of age at onset of mental health disorders is technically and conceptually difficult. It is important to consider these age distributions in order to understand causes and mechanisms of illness and to intervene at an appropriate juncture for primary and secondary prevention. This article reviews some of the approaches to studying age at onset, sets out the evidence to support the assertion that adult mental disorders begin in adolescence, and finds that perhaps half of all adult mental health disorders have begun by the teenage years. The paper then discusses whether this fits what is known about the developmental neurobiology of the brain and introduces the implications for mental health services.

Autobiographical descriptions and clinician observations suggest that some individuals with autism, particularly females, 'camouflage' their social communication difficulties, which may require considerable cognitive effort and lead to increased stress, anxiety and depression. Using data from 60 age- and IQ-matched men and women with autism (without intellectual disability), we operationalized camouflaging in adults with autism for the first time as the quantitative discrepancy between the person's 'external' behavioural presentation in social-interpersonal contexts (measured by the Autism Diagnostic Observation Schedule) and the person's 'internal' status (dispositional traits measured by the Autism Spectrum Quotient and social cognitive capability measured by the 'Reading the Mind in the Eyes' Test). We found that the operationalized camouflaging measure was not significantly correlated with age or IQ. On average, women with autism had higher camouflaging scores than men with autism (Cohen's d = 0.98), with substantial variability in both groups. Greater camouflaging was associated with more depressive symptoms in men and better signal-detection sensitivity in women with autism. The neuroanatomical association with camouflaging score was largely sex/gender-dependent and significant only in women: from reverse inference, the most correlated cognitive terms were about emotion and memory. The underlying constructs, measurement, mechanisms, consequences and heterogeneity of camouflaging in autism warrant further investigation.

This revision of the 2005 British Association for Psychopharmacology guidelines for the evidence-based pharmacological treatment of anxiety disorders provides an update on key steps in diagnosis and clinical management, including recognition, acute treatment, longer-term treatment, combination treatment, and further approaches for patients who have not responded to first-line interventions. A consensus meeting involving international experts in anxiety disorders reviewed the main subject areas and considered the strength of supporting evidence and its clinical implications. The guidelines are based on available evidence, were constructed after extensive feedback from participants, and are presented as recommendations to aid clinical decision-making in primary, secondary and tertiary medical care. They may also serve as a source of information for patients, their carers, and medicines management and formulary committees.

Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.