Integrating stem cell-based experiments in clinical research

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Detection of risk for future depression among adolescents: Stakeholder views of acceptability and feasibility in the United Kingdom

Aim: Depression is one of the most common mental illnesses globally and a leading cause of disability. It is often established by late adolescence and thus identifying which adolescents are most at risk is crucial to enable early intervention to prevent depression onset. We have previously developed a risk calculator to stratify which adolescents are at high risk of developing depression and in this study explore the views of stakeholders to ascertain the acceptability and feasibility of implementing such a tool in the UK.Methods: Semi-structured interviews were conducted with 60 UK-based stakeholders (12 healthcare workers, 12 social workers, 12 school workers, 12 policymakers, and 12 parents). Interviews were audio-recorded and transcribed verbatim. Transcripts were analysed drawing on framework analysis techniques in NVivo 12.Results: Six overarching themes were identified: facilitators of acceptability; barriers to acceptability; role of stakeholders in implementing risk screening; feasibility of delivering the risk calculator in practice; barriers to implementation; and policy and system implications of using it in the current UK health and social care climate. The implementation of a depression risk calculator in the UK was seen as largely acceptable and feasible by most respondents. There was a strong emphasis on the utility of schools to implement this risk calculator, although it was recognised that training and support would be essential.Conclusions: Stakeholders were generally positive about utilising a tool to screen for risk of future depression among adolescents in the UK but raised important concerns which should be taken into account before implementation

Childhood trauma associated with increased post-awakening cortisol in major depressive disorder

Background: Enhanced post-awakening cortisol may serve as a biological marker for individuals with major depressive disorder. However, studies comparing post-awakening cortisol between patients with major depressive disorder (MDD) and healthy controls have produced conflicting findings. The aim of this study was to investigate whether this inconsistency could be due to the effects of childhood trauma. Methods: A total of N = 112 patients with MDD and healthy controls were divided into four groups according to the presence of childhood trauma. Saliva samples were collected at awakening and 15, 30, 45, and 60 min later. The total cortisol output and the cortisol awakening response (CAR) were calculated. Results: The total post-awakening cortisol output was significantly higher in patients with MDD as compared to healthy controls, but only in those individuals reporting childhood trauma. The four groups did not differ regarding the CAR. Conclusions: Elevated post-awakening cortisol in MDD may be confined to those with a history of early life stress. Tailoring and/or augmenting of currently available treatments may be required to meet the specific needs of this population

Predicting the risk of future depression among school-attending adolescents in Nigeria using a model developed in Brazil

Depression commonly emerges in adolescence and is a major public health issue in low- and middle-income countries where 90% of the world's adolescents live. Thus efforts to prevent depression onset are crucial in countries like Nigeria, where two-thirds of the population are aged under 24. Therefore, we tested the ability of a prediction model developed in Brazil to predict future depression in a Nigerian adolescent sample. Data were obtained from school students aged 14–16 years in Lagos, who were assessed in 2016 and 2019 for depression using a self-completed version of the Mini International Neuropsychiatric Interview for Children and Adolescents. Only the 1,928 students free of depression at baseline were included. Penalized logistic regression was used to predict individualized risk of developing depression at follow-up for each adolescent based on the 7 matching baseline sociodemographic predictors from the Brazilian model. Discrimination between adolescents who did and did not develop depression was better than chance (area under the curve = 0.62 (bootstrap-corrected 95% CI: 0.58–0.66). However, the model was not well-calibrated even after adjustment of the intercept, indicating poorer overall performance compared to the original Brazilian cohort. Updating the model with context-specific factors may improve prediction of depression in this setting

Complement system biomarkers in first episode psychosis

Several lines of evidence implicate immunological/inflammatory factors in development of schizophrenia. Complement is a key driver of inflammation, and complement dysregulation causes pathology in many diseases. Here we exploredwhether complement dysregulation occurred in first episode psychosis (FEP) andwhether this provides a source of biomarkers. Eleven complement analytes (C1q, C3, C4, C5, factor B [FB], terminal complement complex [TCC], factor H [FH], FH-related proteins [FHR125], Properdin, C1 inhibitor [C1inh], soluble complement receptor 1 [CR1]) plus C-reactive protein (CRP) were measured in serum from 136 first episode psychosis (FEP) cases and 42 mentally healthy controls using established in-house or commercial ELISA. The relationship between caseness and variables (analytes measured, sex, age, ethnicity, tobacco/cannabis smoking) was tested by multivariate logistic regression. Whenmeasured individually, only TCC was significantly different between FEP and controls (p=0.01). Stepwise selection demonstrated interdependence between some variables and revealed other variables that significantly and independently contributed to distinguishing cases and controls. The finalmodel included demographics (sex, ethnicity, age, tobacco smoking) and a subset of analytes (C3, C4, C5, TCC, C1inh, FHR125, CR1). A receiver operating curve analysis combining these variables yielded an area under the curve of 0.79 for differentiating FEP from controls. This model was confirmed by multiple replications using randomly selected sample subsets. The data suggest that complement dysregulation occurs in FEP, supporting an underlying immune/inflammatory component to the disorder. Classification of FEP cases according to biological variables rather than symptoms would help stratify cases to identify those that might most benefit from therapeuticmodification of the inflammatory response