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Led by Professor Andrea Cipriani, this course is specifically designed for psychiatrists, psychologists, mental health professionals, pharmacists and researchers in neuroscience and related disciplines.
LGI1-antibody encephalitis: how to approach this highly treatable dementia mimic in memory and mental health services.
Leucine-rich glioma-inactivated 1-antibody-encephalitis is a treatable and potentially reversible cause of cognitive and psychiatric presentations, and may mimic cognitive decline, rapidly progressive dementia and complex psychosis in older patients. This aetiology is of immediate relevance given the alternative treatment pathway required, compared with other conditions presenting with cognitive deficits.
Feasibility and usability of remote monitoring in Alzheimer's disease.
INTRODUCTION: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants. METHODS: For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews. RESULTS: Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible. CONCLUSIONS: This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.
The past, present, and future of the brain imaging data structure (BIDS)
Abstract The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Dissecting unique and common variance across body and brain health indicators using age prediction.
Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.
Exploring the incidence of inadequate response to antidepressants in the primary care of depression.
Data from the UK suggests 13-55 % of depression patients experience some level of treatment resistance. However, little is known about how physicians manage inadequate response to antidepressants in primary care. This study aimed to explore the incidence of inadequate response to antidepressants in UK primary care. One-hundred-eighty-four medication-free patients with low mood initiated antidepressant treatment and monitored severity of depression symptoms, using the QIDS-SR16, for 48 weeks. Medication changes, visits to healthcare providers, and health-related quality of life were also recorded. Patients were classified into one of four response types based on their QIDS scores at three study timepoints: persistent inadequate responders (<50 % reduction in baseline QIDS at all timepoints), successful responders (≥50 % reduction in baseline QIDS at all timepoints), slow responders (≥50 % reduction in QIDS at week 48, despite earlier inadequate responses), and relapse (initial ≥50 % reduction in baseline QIDS, but inadequate response by week 48). Forty-eight weeks after initiating treatment 47 % of patients continued to experience symptoms of depression (QIDS >5), and 20 % of patients had a persistent inadequate response. Regardless of treatment response, 96 % (n = 176) of patients did not visit their primary care physician over the 40-week follow-up period. These results suggest that despite receiving treatment, a considerable proportion of patients with low mood remain unwell and fail to recover. Monitoring depression symptoms remotely can enable physicians to identify inadequate responders, allowing patients to be reassessed or referred to secondary services, likely improving patients' quality of life and reducing the socioeconomic impacts of chronic mental illness.
Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries.
We develop a method, SBayesRC, that integrates genome-wide association study (GWAS) summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyze 50 complex traits and diseases using ∼7 million common single-nucleotide polymorphisms (SNPs) and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and up to 34% in cross-ancestry prediction compared to the baseline method SBayesR, which does not use annotations, and outperforms other methods, including LDpred2, LDpred-funct, MegaPRS, PolyPred-S and PRS-CSx. Investigation of factors affecting prediction accuracy identifies a significant interaction between SNP density and annotation information, suggesting whole-genome sequence variants with annotations may further improve prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from nonsynonymous SNPs.
Phenomewide Association Study of Health Outcomes Associated With the Genetic Correlates of 25 Hydroxyvitamin D Concentration and Vitamin D Binding Protein Concentration.
While it is known that vitamin D deficiency is associated with adverse bone outcomes, it remains unclear whether low vitamin D status may increase the risk of a wider range of health outcomes. We had the opportunity to explore the association between common genetic variants associated with both 25 hydroxyvitamin D (25OHD) and the vitamin D binding protein (DBP, encoded by the GC gene) with a comprehensive range of health disorders and laboratory tests in a large academic medical center. We used summary statistics for 25OHD and DBP to generate polygenic scores (PGS) for 66,482 participants with primarily European ancestry and 13,285 participants with primarily African ancestry from the Vanderbilt University Medical Center Biobank (BioVU). We examined the predictive properties of PGS25OHD, and two scores related to DBP concentration with respect to 1322 health-related phenotypes and 315 laboratory-measured phenotypes from electronic health records. In those with European ancestry: (a) the PGS25OHD and PGSDBP scores, and individual SNPs rs4588 and rs7041 were associated with both 25OHD concentration and 1,25 dihydroxyvitamin D concentrations; (b) higher PGS25OHD was associated with decreased concentrations of triglycerides and cholesterol, and reduced risks of vitamin D deficiency, disorders of lipid metabolism, and diabetes. In general, the findings for the African ancestry group were consistent with findings from the European ancestry analyses. Our study confirms the utility of PGS and two key variants within the GC gene (rs4588 and rs7041) to predict the risk of vitamin D deficiency in clinical settings and highlights the shared biology between vitamin D-related genetic pathways a range of health outcomes.
Tracing Tomorrow: young people's preferences and values related to use of personal sensing to predict mental health, using a digital game methodology.
BACKGROUND: Use of personal sensing to predict mental health risk has sparked interest in adolescent psychiatry, offering a potential tool for targeted early intervention. OBJECTIVES: We investigated the preferences and values of UK adolescents with regard to use of digital sensing information, including social media and internet searching behaviour. We also investigated the impact of risk information on adolescents' self-understanding. METHODS: Following a Design Bioethics approach, we created and disseminated a purpose-built digital game (www.tracingtomorrow.org) that immersed the player-character in a fictional scenario in which they received a risk assessment for depression Data were collected through game choices across relevant scenarios, with decision-making supported through clickable information points. FINDINGS: The game was played by 7337 UK adolescents aged 16-18 years. Most participants were willing to personally communicate mental health risk information to their parents or best friend. The acceptability of school involvement in risk predictions based on digital traces was mixed, due mainly to privacy concerns. Most participants indicated that risk information could negatively impact their academic self-understanding. Participants overwhelmingly preferred individual face-to-face over digital options for support. CONCLUSIONS: The potential of digital phenotyping in supporting early intervention in mental health can only be fulfilled if data are collected, communicated and actioned in ways that are trustworthy, relevant and acceptable to young people. CLINICAL IMPLICATIONS: To minimise the risk of ethical harms in real-world applications of preventive psychiatric technologies, it is essential to investigate young people's values and preferences as part of design and implementation processes.
Association of symptom severity and cerebrospinal fluid alterations in recent onset psychosis in schizophrenia-spectrum disorders - An individual patient data meta-analysis.
Neuroinflammation and blood-cerebrospinal fluid barrier (BCB) disruption could be key elements in schizophrenia-spectrum disorderś(SSDs) etiology and symptom modulation. We present the largest two-stage individual patient data (IPD) meta-analysis, investigating the association of BCB disruption and cerebrospinal fluid (CSF) alterations with symptom severity in first-episode psychosis (FEP) and recent onset psychotic disorder (ROP) individuals, with a focus on sex-related differences. Data was collected from PubMed and EMBASE databases. FEP, ROP and high-risk syndromes for psychosis IPD were included if routine basic CSF-diagnostics were reported. Risk of bias of the included studies was evaluated. Random-effects meta-analyses and mixed-effects linear regression models were employed to assess the impact of BCB alterations on symptom severity. Published (6 studies) and unpublished IPD from n = 531 individuals was included in the analyses. CSF was altered in 38.8 % of individuals. No significant differences in symptom severity were found between individuals with and without CSF alterations (SMD = -0.17, 95 %CI -0.55-0.22, p = 0.341). However, males with elevated CSF/serum albumin ratios or any CSF alteration had significantly higher positive symptom scores than those without alterations (SMD = 0.34, 95 %CI 0.05-0.64, p = 0.037 and SMD = 0.29, 95 %CI 0.17-0.41p = 0.005, respectively). Mixed-effects and simple regression models showed no association (p > 0.1) between CSF parameters and symptomatic outcomes. No interaction between sex and CSF parameters was found (p > 0.1). BCB disruption appears highly prevalent in early psychosis and could be involved in positive symptomś severity in males, indicating potential difficult-to-treat states. This work highlights the need for considering BCB breakdownand sex-related differences in SSDs clinical trials and treatment strategies.
UK medical students’ self-reported knowledge and harm assessment of psychedelics and their application in clinical research: a cross-sectional study
ObjectiveTo capture UK medical students’ self-reported knowledge and harm assessment of psychedelics and to explore the factors associated with support for changing the legal status of psychedelics to facilitate further clinical research.DesignCross-sectional, anonymous online survey of UK medical students using a non-random sampling method.SettingUK medical schools recognised by the General Medical Council.Participants132 medical students who had spent an average of 3.8 years (SD=1.4; range: 1–6) in medical school.ResultsMost students (83%) reported that they were aware of psychedelic research and only four participants (3%) said that they were not interested in learning more about this type of research. Although medical students’ harm assessment of psychedelics closely aligned with that of experts, only 17% of students felt well-educated on psychedelic research. Teachings on psychedelics were only rarely encountered in their curriculum (psilocybin: 14.1 (SD=19.9), scale: 0 (never) to 100 (very often)). Time spent at medical schools was not associated with more knowledge about psychedelics (r=0.12, p=0.129). On average, this sample of medical students showed strong support for changing the legal status of psychedelics to facilitate further research into their potential clinical applications (psilocybin: 80.2 (SD=24.8), scale: 0 (strongly oppose) to 100 (strongly support)). Regression modelling indicated that greater knowledge of psychedelics (p<0.001), lower estimated harm scores (p<0.001), more time spent in medical school (p=0.024) and lower perceived effectiveness of non-pharmacological mental health treatments (p=0.044) were associated with greater support for legal status change.ConclusionsOur findings reveal a significant interest among UK medical students to learn more about psychedelic research and a strong support for further psychedelic research. Future studies are needed to examine how medical education could be refined to adequately prepare medical students for a changing healthcare landscape in which psychedelic-assisted therapy could soon be implemented in clinical practice.
The Hopkins-Oxford Psychedelics Ethics (HOPE) Working Group Consensus Statement
The first Hopkins-Oxford Psychedelic Ethics (HOPE) workshop convened to discuss ethical matters relating to psychedelics in August of 2023 at the University of Oxford. The organizers (BDE, DBY, EJ) aimed for a diversity of participant backgrounds and perspectives. The keynotes were given by an Indigenous scholar and a psychiatrist; other attendees included lawyers and ethicists, psychedelic scientists, anthropologists, philosophers, entrepreneurs and harm reduction actors. The workshop was organized out of a recognition that the field of psychedelics is at a pivotal point in its history: research, clinical applications, and policy initiatives are quickly scaling up. The use of psychedelics is expanding, and the development of new systems governing their use is already underway. These changes are happening while substantial uncertainty remains, both about the effects of psychedelics and about the ethical dimensions surrounding their use. We recognize that there is a significant risk of harms as well as potential benefits. Participants at the workshop discussed the ethical aspects of psychedelics, including research methods, clinical practices, history, law and society, spirituality, community, culture and politics that arise in relation to psychedelics. Despite the value of these discussions, the group remains mindful that relatively few voices could be included compared to the scope of those thinking about psychedelics, and those who will be impacted by psychedelics in the coming years. Participants resolved that improving outcomes will require us to make special efforts to further increase the diversity of participant perspectives and backgrounds at future events, including patients and users (not only those who have been benefited by psychedelics, but also those who have been harmed), biopharmaceutical companies, Indigenous communities with established histories of psychedelic use, and law and policy makers. Workshop participants discussed a draft of the current document. This document is intended to summarize our shared understanding of some of the central ethical considerations relating to psychedelics and a few recommendations to the field. Of course, on some points, there is no consensus yet, and there may never be. Further, there are matters on which the group was agnostic, matters which split the room, and matters which we agreed required more evidence and more discussion between the full breadth of stakeholders. Nonetheless, the signatories endorse the sentiments below and believe they are worth conveying to the field at large. More broadly, we hope that this statement is a useful contribution: to those who work with, research, or use psychedelics, as well as anyone interested in the field.
Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury.
A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.