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Led by Professor Andrea Cipriani, the course is designed to enhance understanding and expertise in carrying out systematic reviews and meta-analysis. It is aimed at psychiatrists, psychologists, mental health professionals, pharmacists and researchers in neuroscience and related disciplines.
Artificial intelligence for dementia genetics and omics.
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data
Background Trace amine-associated receptor 1 (TAAR1) agonism shows promise for treating psychosis, prompting us to synthesise data from human and non-human studies. Methods We co-produced a living systematic review of controlled studies examining TAAR1 agonists in individuals (with or without psychosis/schizophrenia) and relevant animal models. Two independent reviewers identified studies in multiple electronic databases (until 17.11.2023), extracted data, and assessed risk of bias. Primary outcomes were standardised mean differences (SMD) for overall symptoms in human studies and hyperlocomotion in animal models. We also examined adverse events and neurotransmitter signalling. We synthesised data with random-effects meta-analyses. Results Nine randomised trials provided data for two TAAR1 agonists (ulotaront and ralmitaront), and 15 animal studies for 10 TAAR1 agonists. Ulotaront and ralmitaront demonstrated few differences compared to placebo in improving overall symptoms in adults with acute schizophrenia (N=4 studies, n=1291 participants; SMD=0.15, 95%CI: -0.05, 0.34), and ralmitaront was less efficacious than risperidone (N=1, n=156, SMD=-0.53, 95%CI: -0.86, -0.20). Large placebo response was observed in ulotaront phase-III trials. Limited evidence suggested a relatively benign side-effect profile for TAAR1 agonists, although nausea and sedation were common after a single dose of ulotaront. In animal studies, TAAR1 agonists improved hyperlocomotion compared to control (N=13 studies, k=41 experiments, SMD=1.01, 95%CI: 0.74, 1.27), but seemed less efficacious compared to dopamine D2 receptor antagonists (N=4, k=7, SMD=-0.62, 95%CI: -1.32, 0.08). Limited human and animal data indicated that TAAR1 agonists may regulate presynaptic dopaminergic signalling. Conclusions TAAR1 agonists may be less efficacious than dopamine D2 receptor antagonists already licensed for schizophrenia. The results are preliminary due to the limited number of drugs examined, lack of longer-term data, publication bias, and assay sensitivity concerns in trials associated with large placebo response. Considering their unique mechanism of action, relatively benign side-effect profile and ongoing drug development, further research is warranted. Registration PROSPERO-ID:CRD42023451628.
osl-dynamics, a toolbox for modeling fast dynamic brain activity
Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.
The GLM-spectrum: A multilevel framework for spectrum analysis with covariate and confound modelling
Abstract The frequency spectrum is a central method for representing the dynamics within electrophysiological data. Some widely used spectrum estimators make use of averaging across time segments to reduce noise in the final spectrum. The core of this approach has not changed substantially since the 1960s, though many advances in the field of regression modelling and statistics have been made during this time. Here, we propose a new approach, the General Linear Model (GLM) Spectrum, which reframes time averaged spectral estimation as multiple regression. This brings several benefits, including the ability to do confound modelling, hierarchical modelling, and significance testing via non-parametric statistics. We apply the approach to a dataset of EEG recordings of participants who alternate between eyes-open and eyes-closed resting state. The GLM-Spectrum can model both conditions, quantify their differences, and perform denoising through confound regression in a single step. This application is scaled up from a single channel to a whole head recording and, finally, applied to quantify age differences across a large group-level dataset. We show that the GLM-Spectrum lends itself to rigorous modelling of within- and between-subject contrasts as well as their interactions, and that the use of model-projected spectra provides an intuitive visualisation. The GLM-Spectrum is a flexible framework for robust multilevel analysis of power spectra, with adaptive covariate and confound modelling.
Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity.
Motor recovery is still limited for people with stroke especially those with greater functional impairments. In order to improve outcome, we need to understand more about the mechanisms underpinning recovery. Task-unbiased, blood flow-independent post-stroke neural activity can be acquired from resting brain electrophysiological recordings and offers substantial promise to investigate physiological mechanisms, but behaviourally relevant features of resting-state sensorimotor network dynamics have not yet been identified. Thirty-seven people with subcortical ischaemic stroke and unilateral hand paresis of any degree were longitudinally evaluated at 3 weeks (early subacute) and 12 weeks (late subacute) after stroke. Resting-state magnetoencephalography and clinical scores of motor function were recorded and compared with matched controls. Magnetoencephalography data were decomposed using a data-driven hidden Markov model into 10 time-varying resting-state networks. People with stroke showed statistically significantly improved Action Research Arm Test and Fugl-Meyer upper extremity scores between 3 weeks and 12 weeks after stroke (both P < 0.001). Hidden Markov model analysis revealed a primarily alpha-band ipsilesional resting-state sensorimotor network which had a significantly increased life-time (the average time elapsed between entering and exiting the network) and fractional occupancy (the occupied percentage among all networks) at 3 weeks after stroke when compared with controls. The life-time of the ipsilesional resting-state sensorimotor network positively correlated with concurrent motor scores in people with stroke who had not fully recovered. Specifically, this relationship was observed only in ipsilesional rather in contralesional sensorimotor network, default mode network or visual network. The ipsilesional sensorimotor network metrics were not significantly different from controls at 12 weeks after stroke. The increased recruitment of alpha-band ipsilesional resting-state sensorimotor network at subacute stroke served as functionally correlated biomarkers exclusively in people with stroke with not fully recovered hand paresis, plausibly reflecting functional motor recovery processes.
Evaluating functional brain organization in individuals and identifying contributions to network overlap
Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.
Towards agreement amongst parents, teachers and children on perceived psychopathology in children in a Kenyan socio-cultural context: a cross-sectional study.
BACKGROUND: Our objective was to determine levels of agreement between parents, teachers and children on mental symptoms in the children. Teachers, children and parents constitute the TRIAD in the perception of psychopathology in children. Analyzing the perceptions of psychopathology from the perspectives of parents, teachers, and children is essential for a comprehensive understanding of a child's mental health. METHODS: We identified 195 participants across ten randomly sampled primary schools in South East Kenya. Potential participants were randomly selected and a sampling interval calculated to determine the study participants. The children (Class 5-8; aged 11-14) completed the Youth Self-Report (YSR) scale, the parents the Child Behavior Check List (CBCL) on their children and the teachers completed the Teachers Rating Form (TRF) on the children. Only parents and teachers who gave consent as well as children who gave assent were included in the study. Analysis was conducted using Stata 14.1 and Pearson correlation coefficients used to calculate the correlations between CBCL, YSR and TRF. RESULTS: The children agreed least with the parents and more with the teachers. There was a greater agreement between the children and their teachers in 5 (2 internalizing disorders and 3 externalizing disorders) out of the 8 conditions. Children and parents agreed only on somatic disorders and conduct disorders. YSR mean scores were significantly lower than those for CBCL for all problem scales. Mean scores of TRF and YSR were comparable in the majority of the problems measured. CONCLUSION: We suggest broad-based psychoeducation to include children, parents/guardians and teachers to enhance shared awareness of psychopathology and uptake of treatment and for the consideration of an integrated mental health system.
Study protocol for a pragmatic randomised controlled trial of comparing enhanced acceptance and commitment therapy plus (+) added to usual aftercare versus usual aftercare only, in patients living with or beyond cancer: SUrvivors' Rehabilitation Evaluation after CANcer (SURECAN) trial.
BACKGROUND: Two million people in the UK are living with or beyond cancer and a third of them report poor quality of life (QoL) due to problems such as fatigue, fear of cancer recurrence, and concerns about returning to work. We aimed to develop and evaluate an intervention based on acceptance and commitment therapy (ACT), suited to address the concerns of cancer survivors and in improving their QoL. We also recognise the importance of exercise and vocational activity on QoL and therefore will integrate options for physical activity and return to work/vocational support, thus ACT Plus (+). METHODS: We will conduct a multi-centre, pragmatic, theory driven, randomised controlled trial. We will assess whether ACT+ including usual aftercare (intervention) is more effective and cost-effective than usual aftercare alone (control). The primary outcome is QoL of participants living with or beyond cancer measured using the Functional Assessment of Cancer Therapy: General scale (FACT-G) at 52 weeks. We will recruit 344 participants identified from secondary care sites who have completed hospital-based treatment for cancer with curative intent, with low QoL (determined by the FACT-G) and randomise with an allocation ratio of 1:1 to the intervention or control. The intervention (ACT+) will be delivered by NHS Talking Therapies, specialist services, and cancer charities. The intervention consists of up to eight sessions at weekly or fortnightly intervals using different modalities of delivery to suit individual needs, i.e. face-to-face sessions, over the phone or skype. DISCUSSION: To date, there have been no robust trials reporting both clinical and cost-effectiveness of an ACT based intervention for people with low QoL after curative cancer treatment in the UK. We will provide high quality evidence of the effectiveness and cost-effectiveness of adding ACT+ to usual aftercare provided by the NHS. If shown to be effective and cost-effective then commissioners, providers and cancer charities will know how to improve QoL in cancer survivors and their families. TRIAL REGISTRATION: ISRCTN: ISRCTN67900293 . Registered on 09 December 2019. All items from the World Health Organization Trial Registration Data Set for this protocol can be found in Additional file 2 Table S1.
How to support adults with anorexia nervosa and autism: Qualitative study of clinical pathway case series.
INTRODUCTION: Previous research has explored the overlapping presentation between autism and eating disorders (ED). This study aims to summarize the clinical challenges associated with co-occurring autism and anorexia nervosa (AN) based on clinicians' case notes and minutes from case discussions, to understand how to better support people with the comorbidity. METHOD: Thematic analysis was conducted on de-identified notes on 20 cases with AN and autistic characteristics and minutes from case discussions. Themes relevant to clinical challenges in supporting those with the comorbidity were identified, and a thematic map was produced to visually represent the results. RESULTS: The key challenges faced by clinicians when treating patients with AN and autism included: communication difficulties, maintaining boundaries, autism screening, presence of other comorbidities, sensory difficulties, atypical presentation of eating difficulties, cognitive rigidity, and emotional difficulties. Adaptations to resolve some of these difficulties included exposure-based food experiments, keeping a record of patients' self-reported communication preferences, individual-level modification of communication style, and providing tools for patients to identify emotions. CONCLUSIONS AND IMPLICATIONS: Further exploration to establish the effectiveness of the adaptations is warranted. Furthermore, tools for differentiating between ED, autism and other comorbidities are needed to help clinicians clarify the cause of a presenting symptom, and help them to best support and maintain boundaries with patients.
Measuring Clinical Efficacy Through the Lens of Audit Data in Different Adult Eating Disorder Treatment Programmes.
Background: Audit data is important in creating a clear picture of clinical reality in clinical services, and evaluating treatment outcomes. This paper explored the data from an audit of a large national eating disorder (ED) service and evaluated the outcome of inpatient and day treatment programmes for patients with anorexia nervosa (AN) with and without autistic traits. Methods: Four hundred and seventy-six patients receiving treatment for AN at inpatient (IP), day-care (DC) and step-up (SU) programmes were assessed at admission and at discharge on the following measures: autistic traits, body-mass-index (BMI), ED symptoms, depression and anxiety symptoms, work and social functioning, and motivation for change. Outcomes were analyzed first at a within-group level based on change in mean scores and then at an individual level based on the clinical significance of improvement in eating disorder symptoms. Outcomes were compared between patients with high autistic traits (HAT) and low autistic traits (LAT) in each programme. Results: The findings suggest that 45.5% of DC and 35.1% of IP patients showed clinically significant changes in ED symptoms following treatment. Co-occurring high autistic traits positively predicted improvement in ED symptoms in IP setting, but was a negative predictor in DC. In IP, more HAT inpatients no longer met the BMI cut-off for AN compared to LAT peers. In terms of general psychopathology, patients with AN and HAT exhibited more severe depression symptoms, anxiety symptoms and social functioning impairment than their LAT peers, and these symptoms stayed clinically severe after treatment. Conclusions: Patients with AN and hight autistic traits are more likely than their peers with low autistic traits to show weight restoration and improvement in ED systems after inpatient treatment. This reverses in DC, with high autistic trait patients less likely to improve after treatment compared to low autistic trait patients. Our results suggest that inpatient treatment with individualized and structured routine care may be an effective model of treatment for patients with AN and high autistic traits.
Autistic characteristics in eating disorders: Treatment adaptations and impact on clinical outcomes.
OBJECTIVE: Autistic people with eating disorders (EDs) may have special needs that are not met in standard ED treatment, raising the need for treatment adaptations to accommodate co-existing autism spectrum condition (ASC). Little is currently known about the nature of existing treatment options or adaptations for this population. We conducted a pre-registered systematic review to: (1) identify research articles describing existing interventions for patients with ED and comorbid ASC, and to critically review evidence of their clinical effectiveness and cost-effectiveness (Review 1); (2) review the impact of ASC comorbidity on ED clinical outcomes (Review 2). METHOD: Peer-reviewed studies published until the end of December 2020 were identified through a systematic search of the electronic databases: Medline, Embase, PsycINFO, Web of Science, CINAHL, Scopus and Cochrane Library. RESULTS: Only one clinical pathway of treatment adaptations (the 'PEACE' pathway) was identified in Review 1 with early evidence of cost-savings and favourable treatment outcomes. ASC characteristics were shown in Review 2 to have no direct impact on physical outcomes or ED symptoms, but could be associated with higher rates of comorbidities and greater use of intensive ED treatment. Additionally, patients with ASC characteristics may benefit more from individual sessions, rather than group sessions. CONCLUSIONS: Any new treatments or treatment adaptations may not directly impact on ED symptoms, but may be better able to support the complex needs of the ASC population, thus reducing subsequent need for intensive treatment. Future research is warranted to explore evidence of clinical and cost-effectiveness of interventions for this population.
Analysis of symptom clusters amongst adults with anorexia nervosa: Key severity indicators.
This study used cluster analysis to explore clinically relevant subgroups of adult patients with anorexia nervosa (AN). Patients were clustered based on their body mass index (BMI), eating disorder symptomatology, anxiety and depression symptoms and autistic characteristics. The difference between clusters in work and social functioning, duration of illness, bingeing and purging behaviour, previous hospitalisations and number of comorbidities was also investigated. Two meaningful clusters emerged: a higher symptoms cluster with more severe eating pathology, anxiety, depression, and more autistic traits, and a second cluster with lower symptoms. BMI did not make major contributions to cluster formation. The higher symptoms cluster also reported lower self-efficacy to change, more previous hospitalisations, comorbid diagnoses, binge eating and purging behaviours and use of psychotropic medication. Our findings suggest that weight alone may not be a significant severity indicator amongst inpatients with AN, and targeted treatment of AN should consider a broader range of symptom severity indicators.
Sensory wellbeing workshops for inpatient and day-care patients with anorexia nervosa.
BACKGROUND: The wellbeing of patients with eating disorders is one of the priorities in the "bigger picture" of treatment for eating disorders. Sensory soothing strategies for sensory sensitivities are supportive tools which could be useful in day-care and inpatient clinical programmes. METHODS: Evaluation of multiple separate sensory wellbeing workshops consisting of psychoeducation and experiential components delivered in inpatient and intensive day-care services was performed. Participants' self-report questionnaires were evaluated pre- and post-workshop. Additionally, patients' comments and qualitative feedback was collected after completion of the workshop. RESULTS: There was strong evidence that self-reported awareness of sensory wellbeing, awareness of strategies to enhance sensory wellbeing, and confidence in managing sensory wellbeing increased after the workshops with positive qualitative feedback from participants. The feedback questionnaires highlighted that patients found the sessions useful and were able to use some of the skills and strategies they learned in the workshop. CONCLUSION: This pilot work on sensory wellbeing workshops with a protocol-based format was feasible and beneficial for the patient group. Preliminary evidence suggests that delivery of similar workshops could be sensible in addition to treatment as usual in inpatient and day-care programmes.
Therapy outcome of day treatment for people with anorexia nervosa before and during the COVID-19 pandemic.
OBJECTIVE: The current research aimed to compare clinical outcome measures of two National Eating Disorder (ED) Day Services at the Maudsley Hospital from before the COVID-19 lockdown, when treatment was face to face, with after the lockdown when treatment moved online. METHOD: Clinical outcome measures collected as part of the admission and discharge process were compared from the beginning and end of treatment for patients treated either via face-to-face or online delivery. Twenty-nine patients' data were analyzed (89% of them female, 11% male, 89% from White ethnic backgrounds, 11% from BAME ethnic backgrounds and a mean age of 25.99 years). Additionally, the mean change in outcome measures was also compared between the two groups (pre-lockdown face to face and during lockdown online). RESULTS: Treatment delivered face to face led to significant improvements in body mass index (BMI) but not in Eating Disorder Examination Questionnaire (EDEQ) Global and Work and Social Adjustment Scale (WSAS) Total scores. In contrast, treatment delivered online led to significant improvements in EDEQ Global and WSAS Total scores but not in BMI. Neither one of the delivery modalities created significantly larger mean changes in any of the clinical outcome measures than the other. CONCLUSIONS: Both face-to-face and online delivery of eating disorder day treatment show some success. Suggested improvements for using online delivery of treatment include implementing additional support opportunities, adapting the online format to improve communication and commitment and using a hybrid model of specific face-to-face elements with some online treatment.
A novel approach for autism spectrum condition patients with eating disorders: Analysis of treatment cost-savings.
OBJECTIVE: In the current economic context, it is critical to ensure that eating disorder (ED) treatments are both effective and cost-effective. We describe the impact of a novel clinical pathway developed to better meet the needs of autistic patients with EDs on the length and cost of hospital admissions. METHOD: The pathway was based on the Institute for Healthcare's Model of Improvement methodology, using an iterative Plan, Do, Study, Act format to introduce change and to co-produce the work with people with lived experience and with healthcare professionals. We explored the change in length and cost of admissions before and after the pathway was introduced. RESULTS: Preliminary results suggest that the treatment innovations associated with this pathway have led to reduced lengths of admission for patients with the comorbidity, which were not seen for patients without the comorbidity. Estimated cost-savings were approximately £22,837 per patient and approximately £275,000 per year for the service as a whole. CONCLUSION: Going forward, our aim is to continue to evaluate the effectiveness and cost-effectiveness of investment in the pathway to determine whether the pathway improves the quality of care for patients with a comorbid ED and autism and is good value for money.
Pragmatic Sensory Screening in Anorexia Nervosa and Associations with Autistic Traits.
BACKGROUND: Research suggests that people with anorexia nervosa (AN) experience subjective hypersensitivity to external sensations that may require consideration in treatment. These difficulties may be particularly pronounced in people with AN and high autistic traits. The purpose of this pilot study was to explore the use of a brief screening tool to assess sensory sensitivity in individuals receiving treatment for AN, and to assess if self-rated sensitivity in AN is related to autistic traits. METHODS: 47 individuals receiving treatment for AN completed a brief sensory screening tool and self-rated their autistic traits. Individuals were also asked to give qualitative feedback on the screening tool. RESULTS: People with AN and high autistic traits rated themselves as more hypersensitive compared to people with AN and low autistic traits. Feedback surrounding the use of the screener was positive. CONCLUSIONS: The results of this study suggest that the use of this screener may be beneficial in eating disorder settings to help adjust and calibrate treatment to personal needs, although further research and psychometric evaluation around the clinical use of the screener is required. The finding that people with AN and high autistic traits may experience elevated hypersensitivity also warrants further exploration in future research.