79 research outputs found
Quality control, imputation and analysis of genome-wide genotyping data from the Illumina HumanCoreExome microarray
ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (ART-CARMA): a multi-centre prospective cohort study protocol
Attention deficit hyperactivity disorder; Digital phenotyping; Remote monitoringTrastorno por déficit de atención con hiperactividad; Fenotipado digital; Monitoreo remotoTranstorn per dèficit d'atenció amb hiperactivitat; Fenotipat digital; Monitorització remotaBackground
Emerging evidence points at substantial comorbidity between adult attention deficit hyperactivity disorder (ADHD) and cardiometabolic diseases, but our understanding of the comorbidity and how to manage cardiometabolic disease in adults with ADHD is limited. The ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (ART-CARMA) project uses remote measurement technology to obtain real-world data from daily life to assess the extent to which ADHD medication treatment and physical activity, individually and jointly, may influence cardiometabolic risks in adults with ADHD. Our second main aim is to obtain valuable real-world data on adherence to pharmacological treatment and its predictors and correlates during daily life from adults with ADHD.
Methods
ART-CARMA is a multi-site prospective cohort study within the EU-funded collaboration ‘TIMESPAN’ (Management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients) that will recruit 300 adults from adult ADHD waiting lists. The participants will be monitored remotely over a period of 12 months that starts from pre-treatment initiation. Passive monitoring, which involves the participants wearing a wrist-worn device (EmbracePlus) and downloading the RADAR-base Passive App and the Empatica Care App on their smartphone, provides ongoing data collection on a wide range of variables, such as physical activity, sleep, pulse rate (PR) and pulse rate variability (PRV), systolic peaks, electrodermal activity (EDA), oxygen saturation (SpO2), peripheral temperature, smartphone usage including social connectivity, and the environment (e.g. ambient noise, light levels, relative location). By combining data across these variables measured, processes such as physical activity, sleep, autonomic arousal, and indicators of cardiovascular health can be captured. Active remote monitoring involves the participant completing tasks using a smartphone app (such as completing clinical questionnaires or speech tasks), measuring their blood pressure and weight, or using a PC/laptop (cognitive tasks). The ART system is built on the RADAR-base mobile-health platform.
Discussion
The long-term goal is to use these data to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment.The ART-CARMA study has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 965381. This communication reflects the views of the authors, and the European Commission is not responsible for any use that may be made of the information it contains. HD is supported by the UK Medical Research Council (MR/N013700/1) and King’s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences
Interstitial lung disease:A review of classification, aetiology, epidemiology, clinical diagnosis, pharmacological and non-pharmacological treatment
IInterstitial lung diseases (ILDs) refer to a heterogeneous and complex group of conditions characterized by inflammation, fibrosis, or both, in the interstitium of the lungs. This results in impaired gas exchange, leading to a worsening of respiratory symptoms and a decline in lung function. While the etiology of some ILDs is unclear, most cases can be traced back to factors such as genetic predispositions, environmental exposures (including allergens, toxins, and air pollution), underlying autoimmune diseases, or the use of certain medications. There has been an increase in research and evidence aimed at identifying etiology, understanding epidemiology, improving clinical diagnosis, and developing both pharmacological and non-pharmacological treatments. This review provides a comprehensive overview of the current state of knowledge in the field of interstitial lung diseases
The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions
Ambulatory impairments; Machine learning; Multiple sclerosisDeficiencias ambulatorias; Aprendizaje automático; Esclerosis múltipleDeficiències ambulatòries; Aprenentatge automà tic; Esclerosi múltipleAbstract
Background and objectives
Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute walk test (6MWT) is a widely used objective measure to evaluate the progression of MS. Yet, it has limitations such as the need for a clinical visit and a proper walkway. The widespread use of wearable devices capable of depicting patients’ activity profiles has the potential to assess the level of MS-induced disability in free-living conditions.
Methods
In this work, we extracted 96 features in different temporal granularities (from minute-level to day-level) from wearable data and explored their utility in estimating 6MWT scores in a European (Italy, Spain, and Denmark) MS cohort of 337 participants over an average of 10 months’ duration. We combined these features with participants’ demographics using three regression models including elastic net, gradient boosted trees and random forest. In addition, we quantified the individual feature's contribution using feature importance in these regression models, linear mixed-effects models, generalized estimating equations, and correlation-based feature selection (CFS).
Results
The results showed promising estimation performance with R2 of 0.30, which was derived using random forest after CFS. This model was able to distinguish the participants with low disability from those with high disability. Furthermore, we observed that the minute-level (≤ 8 minutes) step count, particularly those capturing the upper end of the step count distribution, had a stronger association with 6MWT. The use of a walking aid was indicative of ambulatory function measured through 6MWT.
Conclusions
This study demonstrates the utility of wearables devices in assessing ambulatory impairments in people with MS in free-living conditions and provides a basis for future investigation into the clinical relevance.The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115902. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA, www.imi.europa.eu. This paper reflects the views of the RADAR-CNS consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. The funding body have not been involved in the design of the study, the collection or analysis of data, or the interpretation of data. RJBD is supported by the following: (1) NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, London, UK; (2) Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome Trust; (3) The BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA; it is chaired by DE Grobbee and SD Anker, partnering with 20 academic and industry partners and ESC; (4) the National Institute for Health Research University College London Hospitals Biomedical Research Centre; (5) the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London; (6) the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare; (7) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust
Home Monitoring to Detect Progression of Interstitial Lung Disease:A Prospective Cohort Study
In this prospective observational cohort study, 20 IPF and non-IPF patients, as diagnosed by a multidisciplinary team were recruited from the University College London Hospital (UCLH) between August 2021 and January 2022 using 2018 ATS criteria. Patients who met the criteria for ILD other than IPF, including those with sarcoidosis, and hypersensitivity pneumonitis, were grouped together as non-IPF. They were monitored over 26 weeks using the RADAR-Base mHealth platform. Data collection tools included: questionnaires, a Garmin wearable device, finger pulse oximeter and a NuvoAir smart-spirometer.7 In addition, participants underwent lung function testing in a hospital setting as part of their usual hospital visits. Patients were divided into two groups: progressed and stable. Progression was defined as a ≥5% decline in forced vital capacity (FVC) at6 months by hospital-based spirometry and/or death
Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer.
Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers-either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions. Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array. Firstly, we performed SNP and gene-level analyses of protein-altering variants on the array to identify novel associations the following ADRs, which were grouped into four phenotypes based on symptoms of diarrhea, mucositis, and neutropenia and hand-and-foot syndrome. Secondly, we performed detailed analyses of the HLA region on the same phenotypes after imputing the HLA alleles and amino acids. No protein-altering variants, or sets of protein-altering variants collapsed into genes, were associated with the main outcomes after Bonferroni correction. We found evidence that the HLA region was enriched for associations with Hand-and-Foot syndrome (p = 0.023), but no specific SNPs or HLA alleles were significant after Bonferroni correction. Larger studies will be required to characterize the genetic contribution to ADRs to 5FU. Future studies that focus on the HLA region are likely to be fruitful
Remote Administration of ADHD-Sensitive Cognitive Tasks: A Pilot Study
Objective: We assessed the feasibility and validity of remote researcher-led administration and self-administration of modified versions of two cognitive tasks sensitive to ADHD, a four-choice reaction time task (Fast task) and a combined Continuous Performance Test/Go No-Go task (CPT/GNG), through a new remote measurement technology system. Method: We compared the cognitive performance measures (mean and variability of reaction times (MRT, RTV), omission errors (OE) and commission errors (CE)) at a remote baseline researcher-led administration and three remote self-administration sessions between participants with and without ADHD (n = 40). Results: The most consistent group differences were found for RTV, MRT and CE at the baseline researcher-led administration and the first self-administration, with 8 of the 10 comparisons statistically significant and all comparisons indicating medium to large effect sizes. Conclusion: Remote administration of cognitive tasks successfully captured the difficulties with response inhibition and regulation of attention, supporting the feasibility and validity of remote assessments
Classifying depression symptom severity: Assessment of speech representations in personalized and generalized machine learning models
There is an urgent need for new methods that improve the management and treatment of Major Depressive Disorder (MDD). Speech has long been regarded as a promising digital marker in this regard, with many works highlighting that speech changes associated with MDD can be captured through machine learning models. Typically, findings are based on cross-sectional data, with little work exploring the advantages of personalization in building more robust and reliable models. This work assesses the strengths of different combinations of speech representations and machine learning models, in personalized and generalized settings in a two-class depression severity classification paradigm. Key results on a longitudinal dataset highlight the benefits of personalization. Our strongest performing model set-up utilized self-supervised learning features and convolutional neural network (CNN) and long short-term memory (LSTM) back-end
EDIFY (Eating disorders: delineating illness and recovery trajectories to inform personalised prevention and early intervention in young people):Project outline
EDIFY (Eating Disorders: Delineating Illness and Recovery Trajectories to Inform Personalised Prevention and Early Intervention in Young People) is an ambitious research project aiming to revolutionise how eating disorders are perceived, prevented and treated. Six integrated workstreams will address key questions, including: What are young people's experiences of eating disorders and recovery? What are the unique and shared risk factors in different groups? What helps or hinders recovery? How do the brain and behaviour change from early- to later-stage illness? How can we intervene earlier, quicker and in a more personalised way? This 4-year project, involving over 1000 participants, integrates arts, design and humanities with advanced neurobiological, psychosocial and bioinformatics approaches. Young people with lived experience of eating disorders are at the heart of EDIFY, serving as advisors and co-producers throughout. Ultimately, this work will expand public and professional perceptions of eating disorders, uplift under-represented voices and stimulate much-needed advances in policy and practice
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