Publications
612 results found
Graham NSN, Jolly A, Zimmerman K, et al., 2020, Diffuse axonal injury predicts neurodegeneration after moderate-severe traumatic brain injury, Brain: a journal of neurology, Vol: 143, Pages: 3685-3698, ISSN: 0006-8950
Traumatic brain injury is associated with elevated rates of neurodegenerative diseases such as Alzheimer's disease and chronic traumatic encephalopathy. In experimental models, diffuse axonal injury triggers post-traumatic neurodegeneration, with axonal damage leading to Wallerian degeneration and toxic proteinopathies of amyloid and hyperphosphorylated tau. However, in humans the link between diffuse axonal injury and subsequent neurodegeneration has yet to be established. Here we test the hypothesis that the severity and location of diffuse axonal injury predicts the degree of progressive post-traumatic neurodegeneration. We investigated longitudinal changes in 55 patients in the chronic phase after moderate-severe traumatic brain injury and 19 healthy control subjects. Fractional anisotropy was calculated from diffusion tensor imaging as a measure of diffuse axonal injury. Jacobian determinant atrophy rates were calculated from serial volumetric T1 scans as a measure of measure post-traumatic neurodegeneration. We explored a range of potential predictors of longitudinal post-traumatic neurodegeneration and compared the variance in brain atrophy that they explained. Patients showed widespread evidence of diffuse axonal injury, with reductions of fractional anisotropy at baseline and follow-up in large parts of the white matter. No significant changes in fractional anisotropy over time were observed. In contrast, abnormally high rates of brain atrophy were seen in both the grey and white matter. The location and extent of diffuse axonal injury predicted the degree of brain atrophy: fractional anisotropy predicted progressive atrophy in both whole-brain and voxelwise analyses. The strongest relationships were seen in central white matter tracts, including the body of the corpus callosum, which are most commonly affected by diffuse axonal injury. Diffuse axonal injury predicted substantially more variability in white matter atrophy than other putative clinical or ima
Jolly A, Sharp D, Balaet M, et al., 2020, Detecting axonal injury in individual patients after traumatic brain injury, Brain
Li H, Barnaghi P, Skillman S, et al., 2020, Machine learning for risk analysis of Urinary Tract Infection in people with dementia, Publisher: arXiv
The Urinary Tract Infections (UTIs) are one of the top reasons for unplannedhospital admissions in people with dementia, and if detected early, they can betimely treated. However, the standard UTI diagnosis tests, e.g. urine tests,will be only taken if the patients are clinically suspected of having UTIs.This causes a delay in diagnosis and treatment of the conditions and in somecases like people with dementia, the symptoms can be difficult to observe.Delay in detection and treatment of dementia is one of the key reasons forunplanned hospital admissions in people with dementia. To address these issues,we have developed a technology-assisted monitoring system, which is a Class 1medical device. The system uses off-the-shelf and low-cost in-home sensorydevices to monitor environmental and physiological data of people with dementiawithin their own homes. We have designed a machine learning model to use thedata and provide risk analysis for UTIs. We use a semi-supervised learningmodel which leverage the environmental data, i.e. the data collected from themotion sensors, smart plugs and network-connected body temperature monitoringdevices in the home, to detect patterns that can show the risk of UTIs. Sincethe data is noisy and partially labelled, we combine the neural networks andprobabilistic neural networks to train an auto-encoder, which is to extract thegeneral representation of the data. We will demonstrate our smart homemanagement by videos/online, and show how our model can pick up the UTI relatedpatterns.
Graham NSN, Zimmerman KA, Bertolini G, et al., 2020, Multicentre longitudinal study of fluid and neuroimaging BIOmarkers of AXonal injury after traumatic brain injury: the BIO-AX-TBI study protocol., BMJ Open, Vol: 10, Pages: 1-9, ISSN: 2044-6055
INTRODUCTION AND AIMS: Traumatic brain injury (TBI) often results in persistent disability, due particularly to cognitive impairments. Outcomes remain difficult to predict but appear to relate to axonal injury. Several new approaches involving fluid and neuroimaging biomarkers show promise to sensitively quantify axonal injury. By assessing these longitudinally in a large cohort, we aim both to improve our understanding of the pathophysiology of TBI, and provide better tools to predict clinical outcome. METHODS AND ANALYSIS: BIOmarkers of AXonal injury after TBI is a prospective longitudinal study of fluid and neuroimaging biomarkers of axonal injury after moderate-to-severe TBI, currently being conducted across multiple European centres. We will provide a detailed characterisation of axonal injury after TBI, using fluid (such as plasma/microdialysate neurofilament light) and neuroimaging biomarkers (including diffusion tensor MRI), which will then be related to detailed clinical, cognitive and functional outcome measures. We aim to recruit at least 250 patients, including 40 with cerebral microdialysis performed, with serial assessments performed twice in the first 10 days after injury, subacutely at 10 days to 6 weeks, at 6 and 12 months after injury. ETHICS AND DISSEMINATION: The relevant ethical approvals have been granted by the following ethics committees: in London, by the Camberwell St Giles Research Ethics Committee; in Policlinico (Milan), by the Comitato Etico Milano Area 2; in Niguarda (Milan), by the Comitato Etico Milano Area 3; in Careggi (Florence), by the Comitato Etico Regionale per la Sperimentazione Clinica della Regione Toscana, Sezione area vasta centro; in Trento, by the Trento Comitato Etico per le Sperimentazioni Cliniche, Azienda Provinciale per i Servizi Sanitari della Provincia autonoma di Trento; in Lausanne, by the Commission cantonale d'éthique de la recherche sur l'être humain; in Ljubljana, by the National Medical
Li B, Tan H, Jenkins D, et al., 2020, Clinical detection of neurodegenerative blood biomarkers using graphene immunosensor, Carbon, Vol: 168, Pages: 144-162, ISSN: 0008-6223
Accurate detection of blood biomarkers related to neurodegenerative diseases could provide a shortcut to identifying early stage patients before the onset of symptoms. The specificity, selectivity and operational requirements of the current technologies, however, preclude their use in the primary clinical setting for early detection. Graphene, an emerging 2D nanomaterial, is a promising candidate for biosensing which has the potential to meet the performance requirements and enable cost-effective, portable and rapid diagnosis. In this review, we compare graphene-based immunosensing technologies with conventional enzyme-linked immunosorbent assays and cutting-edge single molecule array techniques for the detection of blood-based neurodegenerative biomarkers. We cover the progress in electrical, electrochemical and optical graphene-based immunosensors and outline the barriers that slow or prevent the adoption of this emerging technology in primary clinical settings. We also highlight the possible solutions to overcome these barriers with an outlook on the future of the promising, graphene immunosensor technology.
Popescu S, Sharp D, Cole J, et al., 2020, Hierarchical Gaussian processes with Wasserstein-2 kernels, Publisher: arXiv
We investigate the usefulness of Wasserstein-2 kernels in the context ofhierarchical Gaussian Processes. Stemming from an observation that stackingGaussian Processes severely diminishes the model's ability to detect outliers,which when combined with non-zero mean functions, further extrapolates lowvariance to regions with low training data density, we posit that directlytaking into account the variance in the computation of Wasserstein-2 kernels isof key importance towards maintaining outlier status as we progress through thehierarchy. We propose two new models operating in Wasserstein space which canbe seen as equivalents to Deep Kernel Learning and Deep GPs. Through extensiveexperiments, we show improved performance on large scale datasets and improvedout-of-distribution detection on both toy and real data.
Crone MA, Priestman M, Ciechonska M, et al., 2020, A role for Biofoundries in rapid development and validation of automated SARS-CoV-2 clinical diagnostics (vol 11, 4464, 2020), NATURE COMMUNICATIONS, Vol: 11, ISSN: 2041-1723
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Deb S, Crawford M, Sharp D, et al., 2020, Risperidone versus placebo for aggression following traumatic brain injury: a feasibility randomised controlled trial, BMJ Open, Vol: 10, ISSN: 2044-6055
Objectives: To conduct a feasibility randomised controlled trial of risperidone for the treatment of aggression in adults with traumatic brain injury (TBI).Design: Multi-centre, parallel design, placebo controlled (1:1 ratio) double-blind feasibility trial with an embedded process evaluation. No statistical comparison was performed between the two study groups.Setting Four neuropsychiatric and neurology outpatient clinics in London and Kent, UK. Participants Our aim was to recruit 50 TBI patients over 18 months. Follow up participants at 12 weeks using a battery of assessment scales to measure changes in aggressive behaviour (MOAS-primary outcome, IRQ) as well as global functioning (GOS-E, CGI) and quality of life (EQ-5D-5L, SF-12), mental health (HADS) and medication adverse effects (UKU).Results: Six participants were randomised to the active arm of the trial and eight to the placebo arm over a 10-month period (28% of our target). Two participants withdrew because of adverse events. Twelve out of 14 (85.7%) patients completed a follow up assessment at 12 weeks. At follow up, the scores of all outcome measures improved in both groups. Placebo group showed numerically better score change according to the primary outcome MOAS. No severe adverse events were reported. The overall rate of adverse events remained low. Data from the process evaluation suggest that existence of specialised TBI Follow-up clinics, availability of a dedicated database of TBI patients’ clinical details, simple study procedures and regular support to participants would enhance recruitment and retention in the trial. Feedback from participants showed that once in the study, they did not find the trial procedure onerous.Conclusions: It was not feasible to conduct a successful randomised trial of risperidone versus placebo for post-TBI aggression using the methods we deployed in this study. It is not possible to draw any definitive conclusion about risperidone’s efficacy from such a s
Crone M, Priestman M, Ciechonska M, et al., 2020, A role for Biofoundries in rapid development and validation of automated SARS-CoV-2 clinical diagnostics, Nature Communications, Vol: 11, Pages: 1-11, ISSN: 2041-1723
The SARS-CoV-2 pandemic has shown how a rapid rise in demand for patient and community sample testing can quickly overwhelm testing capability globally. With most diagnostic infrastructure dependent on specialized instruments, their exclusive reagent supplies quickly become bottlenecks, creating an urgent need for approaches to boost testing capacity. We address this challenge by refocusing the London Biofoundry onto the development of alternative testing pipelines. Here, we present a reagent-agnostic automated SARS-CoV-2 testing platform that can be quickly deployed and scaled. Using an in-house-generated, open-source, MS2-virus-like particle (VLP) SARS-CoV-2 standard, we validate RNA extraction and RT-qPCR workflows as well as two detection assays based on CRISPR-Cas13a and RT-loop-mediated isothermal amplification (RT-LAMP). In collaboration with an NHS diagnostic testing lab, we report the performance of the overall workflow and detection of SARS-CoV-2 in patient samples using RT-qPCR, CRISPR-Cas13a, and RT-LAMP. The validated RNA extraction and RT-qPCR platform has been installed in NHS diagnostic labs, increasing testing capacity by 1000 samples per day.
Laverse E, Guo T, Zimmerman K, et al., 2020, Plasma glial fibrillary acidic protein and neurofilament light chain, but not tau, are biomarkers of sports-related mild traumatic brain injury, Brain Communications, Vol: 2, Pages: 1-10, ISSN: 2632-1297
Mild traumatic brain injury is a relatively common event in contact sports and there is increasing interest in the long-term neurocognitive effects. The diagnosis largely relies on symptom reporting and there is a need for objective tools to aid diagnosis and prognosis. There are recent reports that blood biomarkers could potentially help triage patients with suspected injury and normal CT findings. We have measured plasma concentrations of glial and neuronal proteins and explored their potential in the assessment of mild traumatic brain injury in contact sport.We recruited a prospective cohort of active male rugby players, who had pre-season baseline plasma sampling. From this prospective cohort, we recruited 25 players diagnosed with mild traumatic brain injury. We sampled post-match rugby players without head injuries as post-match controls. We measured plasma neurofilament light chain, tau and glial fibrillary acidic protein levels using ultrasensitive single molecule array technology. The data was analysed at the group and individual player level.Plasma glial fibrillary acidic protein concentration was significantly increased 1-hour post-injury in mild traumatic brain injury cases compared to the non-injured group (p = 0.017). Pairwise comparison also showed that glial fibrillary acidic protein levels were higher in players after a head injury in comparison to their pre-season levels at both 1-hour and 3 to 10-days post-injury time points (p = 0.039 and 0.040, respectively). There was also an increase in neurofilament light chain concentration in brain injury cases compared to the pre-season levels within the same individual at both time points (p = 0.023 and 0.002, respectively). Tau was elevated in both the non-injured control group and the 1-hour post-injury group compared to pre-season levels (p = 0.007 and 0.015, respectively). Furthermore, receiver operating characteristic analysis showed that glial
Graham N, Junghans C, Downes R, et al., 2020, SARS-CoV-2 infection, clinical features and outcome of COVID-19 in United Kingdom nursing homes, Journal of Infection, Vol: 81, Pages: 411-419, ISSN: 0163-4453
OBJECTIVES: To understand SARS-Co-V-2 infection and transmission in UK nursing homes in order to develop preventive strategies for protecting the frail elderly residents. METHODS: An outbreak investigation involving 394 residents and 70 staff, was carried out in 4 nursing homes affected by COVID-19 outbreaks in central London. Two point-prevalence surveys were performed one week apart where residents underwent SARS-CoV-2 testing and had relevant symptoms documented. Asymptomatic staff from three of the four homes were also offered SARS-CoV-2 testing. RESULTS: Overall, 26% (95% CI 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336) compared with previous years. Systematic testing identified 40% (95% CI 35 to 46) of residents as positive for SARS-CoV-2, and of these 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had only atypical symptoms; 4% (95% CI -1 to 9) of asymptomatic staff also tested positive. CONCLUSIONS: The SARS-CoV-2 outbreak in four UK nursing homes was associated with very high infection and mortality rates. Many residents developed either atypical or no discernible symptoms. A number of asymptomatic staff members also tested positive, suggesting a role for regular screening of both residents and staff in mitigating future outbreaks.
Foss L, Belli A, Brody D, et al., 2020, Setting a national consensus for managing mild and blast traumatic brain injury: post-meeting consensus report
A meeting was held on Wednesday 15 January 2020 to examine the current evidence for non-routine imaging and for neuroendocrine screening in the management of military personnel with brain injury and overlapping symptom domains. The Summit aimed to specifically address the relative utility of magnetoencephalography (MEG), diffusion tensor imaging (DTI) and susceptibility weighted imaging (SWI) in the UK context. This Consensus Report discusses points of consensus, points for further discussion/points of equipoise and recommendations that arose during, and following, the meeting.
Popescu SG, Whittington A, Gunn RN, et al., 2020, Nonlinear biomarker interactions in conversion from mild cognitive impairment to Alzheimer's disease, Human Brain Mapping, Vol: 41, Pages: 4406-4418, ISSN: 1065-9471
Multiple biomarkers can capture different facets of Alzheimer's disease. However, statistical models of biomarkers to predict outcomes in Alzheimer's rarely model nonlinear interactions between these measures. Here, we used Gaussian Processes to address this, modelling nonlinear interactions to predict progression from mild cognitive impairment (MCI) to Alzheimer's over 3 years, using Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Measures included: demographics, APOE4 genotype, CSF (amyloid‐β42, total tau, phosphorylated tau), [18F]florbetapir, hippocampal volume and brain‐age. We examined: (a) the independent value of each biomarker; and (b) whether modelling nonlinear interactions between biomarkers improved predictions. Each measured added complementary information when predicting conversion to Alzheimer's. A linear model classifying stable from progressive MCI explained over half the variance (R2 = 0.51, p < .001); the strongest independently contributing biomarker was hippocampal volume (R2 = 0.13). When comparing sensitivity of different models to progressive MCI (independent biomarker models, additive models, nonlinear interaction models), we observed a significant improvement (p < .001) for various two‐way interaction models. The best performing model included an interaction between amyloid‐β‐PET and P‐tau, while accounting for hippocampal volume (sensitivity = 0.77, AUC = 0.826). Closely related biomarkers contributed uniquely to predict conversion to Alzheimer's. Nonlinear biomarker interactions were also implicated, and results showed that although for some patients adding additional biomarkers may add little value (i.e., when hippocampal volume is high), for others (i.e., with low hippocampal volume) further invasive and expensive examination may be warranted. Our framework enables visualisation of these interactions, in individual patient biomarker ‘space', providing information for per
Yu X, Azor A, Sharp DJ, et al., 2020, Mechanisms of tensile failure of cerebrospinal fluid in blast traumatic brain injury, Extreme Mechanics Letters, Vol: 38, Pages: 1-9, ISSN: 2352-4316
Mechanisms of blast-induced Traumatic Brain Injury (BTBI), particularly those linked to the primary pressure wave, are still not fully understood. One possible BTBI mechanism is cavitation in the cerebrospinal fluid (CSF) caused by CSF tensile failure, which is likely to increase strain and strain rate in the brain tissue near the CSF. Blast loading of the head can generate rarefaction (expansion) waves and rapid head motion, which both can produce tensile forces in the CSF. However, it is not clear which of these mechanisms is more likely to cause CSF tensile failure. In this study, we used a high-fidelity 3-dimensional computational model of the human head to test whether the CSF tensile failure increases brain deformation near the brain/CSF boundary and to determine the key failure mechanisms. We exposed the head model to a frontal blast wave and predicted strain and strain rate distribution in the cortex. We found that CSF tensile failure significantly increased strain and strain rate in the cortex. We then studied whether the rapid head motion or the rarefaction wave causes strain and strain rate concentration in cortex. We isolated these two effects by conducting simulations with pure head motion loading (i.e. prescribing the skull velocity but eliminating the pressure wave) and pure blast wave loading (i.e. eliminating head motion by fixing the skull base). Our results showed that the strain increase in the cortex was mainly caused by head motion. In contrast, strain rate increase was caused by both rapid head motion and rarefaction waves, but head motion had a stronger effect on elevating strain rate. Our results show that rapid motion of the head produced by blast wave is the key mechanism for CSF tensile failure and subsequent concentration of strain and strain rate in cortex. This finding suggests that mitigation of rapid head motion caused by blast loading needs to be addressed in the design of protective equipment in order to prevent the tensile failure
Hughes SW, Hellyer PJ, Sharp DJ, et al., 2020, Diffusion tensor imaging of lumbar spinal nerves reveals changes in microstructural integrity following decompression surgery associated with improvements in clinical symptoms: A case report, Magnetic Resonance Imaging, Vol: 69, Pages: 65-70, ISSN: 0730-725X
The outcomes from spinal nerve decompression surgery are highly variable with a sizable proportion of elderly foraminal stenosis patients not regaining good pain relief. A better understanding of nerve root compression before and following decompression surgery and whether these changes are mirrored by improvements in symptoms may help to improve clinical decision-making processes. This case study used a combination of diffusion tensor imaging (DTI), clinical questionnaires and motor neurophysiology assessments before and up to 3 months following spinal decompression surgery. In this case report, a 70-year-old women with compression of the left L5 spinal nerve root in the L5-S1 exit foramina was recruited to the study. At 3 months following surgery, DTI revealed marked improvements in left L5 microstructural integrity to a similar level to that seen in the intact right L5 nerve root. This was accompanied by a gradual improvement in pain-related symptoms, mood and disability score by 3 months. Using this novel multimodal approach, it may be possible to track concurrent improvements in pain-related symptoms, function and microstructural integrity of compressed nerves in elderly foraminal stenosis patients undergoing decompression surgery.
Graham NSN, Junghans C, Downes R, et al., 2020, SARS-CoV-2 infection, clinical features and outcome of COVID-19 in United Kingdom nursing homes
<jats:title>ABSTRACT</jats:title><jats:sec><jats:title>Objectives</jats:title><jats:p>To understand SARS-Co-V-2 infection and transmission in UK nursing homes in order to develop preventive strategies for protecting the frail elderly residents.</jats:p></jats:sec><jats:sec><jats:title>Design</jats:title><jats:p>An outbreak investigation.</jats:p></jats:sec><jats:sec><jats:title>Setting</jats:title><jats:p>4 nursing homes affected by COVID-19 outbreaks in central London.</jats:p></jats:sec><jats:sec><jats:title>Participants</jats:title><jats:p>394 residents and 70 staff in nursing homes.</jats:p></jats:sec><jats:sec><jats:title>Interventions</jats:title><jats:p>Two point-prevalence surveys one week apart where residents underwent SARS-CoV-2 testing and had relevant symptoms documented. Asymptomatic staff from three of the four homes were also offered SARS-CoV-2 testing.</jats:p></jats:sec><jats:sec><jats:title>Main outcome measures</jats:title><jats:p>All-cause mortality, and mortality attributed to COVID-19 on death certificates. Prevalence of SARS-CoV-2 infection and symptoms in residents and staff.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Overall, 26% (95% confidence interval 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336). Systematic testing identified 40% (95% CI 35 to 46) of residents, of whom 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had atypical symptoms, as well as 4% (95% CI -1 to 9) of asymptomatic staff who tested positive for SARS-CoV-2.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The SARS-CoV-2 outbreak was associated with a ver
Jenkins P, Roussakis A-A, De Simoni S, et al., 2020, Distinct dopaminergic abnormalities in traumatic brain injury and Parkinson’s disease, Journal of Neurology, Neurosurgery and Psychiatry, Vol: 91, Pages: 631-637, ISSN: 0022-3050
Objective: Traumatic brain injury (TBI) and REM behavioural disorder (RBD) are risk factors for Parkinson’s disease (PD). Dopaminergic abnormalities are often seen after TBI, but patients usually lack parkinsonian features. We test whether TBI, PD and RBD have distinct striatal dopamine abnormalities using dopamine transporter imaging. Methods: 123I-ioflupane SPECT scans were used in a cross-sectional study to measure dopamine transporter (DaT) levels in moderate/severe TBI, healthy controls, early PD and RBD patients. Caudate and putamen DaT, putamen-to-caudate ratios and left-right symmetry of DaT were compared.Results: 108 participants (43 TBI, 26 PD, 8 RBD, 31 controls) were assessed. Early PD patients scored significantly higher on the UPDRS motor subscale than other groups. TBI and PD patients had reduced DaT levels in the caudate (12.2% and 18.7% respectively) and putamen (9.0% and 42.6% respectively) compared to controls. RBD patients had reduced DaT levels in the putamen (12.8%) but not in the caudate compared to controls. PD and TBI patients showed distinct patterns of DaT reduction, with PD patients showing a lower putamen-to-caudate ratio. DaT asymmetry was greater in the PD group than other groups. Conclusions: The results show that early PD and TBI patients have distinct patterns of striatal dopamine abnormalities. Early PD and moderate/severe TBI patients showed similar reductions in caudate DaT binding, but PD patients showed a greater reduction in putamen DaT and a lower putamen-to-caudate ratio. The results suggest that parkinsonian motor signs are absent in these TBI patients because of relatively intact putaminal dopamine levels.
Crone MA, Priestman M, Ciechonska M, et al., 2020, A new role for Biofoundries in rapid prototyping, development, and validation of automated clinical diagnostic tests for SARS-CoV-2
<jats:title>Abstract</jats:title><jats:p>The SARS-CoV-2 pandemic has shown how the rapid rise in demand for patient and community sample testing, required for tracing and containing a highly infectious disease, has quickly overwhelmed testing capability globally. With most diagnostic infrastructure dependent on specialised instruments, their exclusive reagent supplies quickly become bottlenecks in times of peak demand, creating an urgent need for novel approaches to boost testing capacity. We address this challenge by refocusing the full synthetic biology stack available at the London Biofoundry onto the development of alternative patient sample testing pipelines. We present a reagent-agnostic automated SARS-CoV-2 testing platform that can be quickly deployed and scaled, and that accepts a diverse range of reagents. Using an in-house-generated, open-source, MS2-virus-like-particle-SARS-CoV-2 standard, we validate RNA extraction and RT-qPCR workflows as well as two novel detection assays based on CRISPR-Cas and Loop-mediated isothermal Amplification (LAMP) approaches. In collaboration with an NHS diagnostic testing lab, we report the performance of the overall workflow and benchmark SARS-CoV-2 detection in patient samples via RT-qPCR, CRISPR-Cas, and LAMP against clinical test sets. The validated RNA extraction and RT-qPCR platform has been installed in NHS diagnostic labs and now contributes to increased patient sample processing in the UK while we continue to refine and develop novel high-throughput diagnostic methods. Finally, our workflows and protocols can be quickly implemented and adapted by members of the Global Biofoundry Alliance and the wider scientific and medical diagnostics community.</jats:p>
Jolly A, Scott G, Sharp D, et al., 2020, Distinct patterns of structural damage underlie working memory and reasoning deficits after traumatic brain injury, Brain: a journal of neurology, Vol: 143, Pages: 1158-1176, ISSN: 0006-8950
It is well established that chronic cognitive problems after traumatic brain injury (TBI) relate to diffuse axonal injury (DAI) and the consequent widespread disruption of brain connectivity. However, the pattern of DAI varies between patients and they have a correspondingly heterogeneous profile of cognitive deficits. This heterogeneity is poorly understood, presenting a non-trivial challenge for prognostication and treatment. Prominent amongst cognitive problems are deficits in working memory and reasoning. Previous functional magnetic resonance imaging (fMRI) in controls has associated these aspects of cognition with distinct, but partially overlapping, networks of brain regions. Based on this, a logical prediction is that differences in the integrity of the white matter tracts that connect these networks should predict variability in the type and severity of cognitive deficits after TBI.We use diffusion-weighted imaging, cognitive testing and network analyses to test this prediction. We define functionally distinct sub-networks of the structural connectome by intersecting previously published fMRI maps of the brain regions that are activated during our working memory and reasoning tasks, with a library of the white-matter tracts that connect them. We examine how graph theoretic measures within these sub-networks relate to the performance of the same tasks in a cohort of 92 moderate-severe TBI patients. Finally, we use machine learning to determine whether cognitive performance in patients can be predicted using graph theoretic measures from each sub-network.Principal component analysis of behavioural scores confirm that reasoning and working memory form distinct components of cognitive ability, both of which are vulnerable to TBI. Critically, impairments in these abilities after TBI correlate in a dissociable manner with the information-processing architecture of the sub-networks that they are associated with. This dissociation is confirmed when examining degree
De Francesco D, Choi J-P, Choi JY, et al., 2020, Cognitive function and drivers of cognitive impairment in a European and a Korean cohort of people living with HIV, INTERNATIONAL JOURNAL OF STD & AIDS, Vol: 31, Pages: 30-37, ISSN: 0956-4624
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Enshaeifar S, Barnaghi P, Skillman S, et al., 2020, A Digital Platform for Remote Healthcare Monitoring, 29th World Wide Web Conference (WWW), Publisher: ASSOC COMPUTING MACHINERY, Pages: 203-206
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Graham NSN, Sharp DJ, 2019, Understanding neurodegeneration after traumatic brain injury: from mechanisms to clinical trials in dementia, Journal of Neurology, Neurosurgery & Psychiatry, Vol: 90, ISSN: 0022-3050
Traumatic brain injury (TBI) leads to increased rates of dementia, including Alzheimer’s disease. The mechanisms by which trauma can trigger neurodegeneration are increasingly understood. For example, diffuse axonal injury is implicated in disrupting microtubule function, providing the potential context for pathologies of tau and amyloid to develop. The neuropathology of post-traumatic dementias is increasingly well characterised, with recent work focusing on chronic traumatic encephalopathy (CTE). However, clinical diagnosis of post-traumatic dementia is problematic. It is often difficult to disentangle the direct effects of TBI from those produced by progressive neurodegeneration or other post-traumatic sequelae such as psychiatric impairment. CTE can only be confidently identified at postmortem and patients are often confused and anxious about the most likely cause of their post-traumatic problems. A new approach to the assessment of the long-term effects of TBI is needed. Accurate methods are available for the investigation of other neurodegenerative conditions. These should be systematically employed in TBI. MRI and positron emission tomography neuroimaging provide biomarkers of neurodegeneration which may be of particular use in the postinjury setting. Brain atrophy is a key measure of disease progression and can be used to accurately quantify neuronal loss. Fluid biomarkers such as neurofilament light can complement neuroimaging, representing sensitive potential methods to track neurodegenerative processes that develop after TBI. These biomarkers could characterise endophenotypes associated with distinct types of post-traumatic neurodegeneration. In addition, they might profitably be used in clinical trials of neuroprotective and disease-modifying treatments, improving trial design by providing precise and sensitive measures of neuronal loss.
Underwood J, De Francesco D, Koostra N, et al., 2019, Higher anti-CMV IgG concentrations are not associated with longitudinal brain injury in virally suppressed people with HIV, Publisher: WILEY, Pages: 139-140, ISSN: 1464-2662
Li L, Violante I, Zimmerman K, et al., 2019, Traumatic axonal injury influences the cognitive effect of non-invasive brain stimulation, Brain, Vol: 142, Pages: 3280-3293, ISSN: 1460-2156
Non-invasive brain stimulation has been widely investigated for as a potentialtreatment for a range of neurological and psychiatric conditions, including braininjury. However, the behavioural effects of brain stimulation are very variable, forreasons that are poorly understood. This is a particular challenge for traumatic braininjury, where patterns of damage and their clinical effects are heterogenous. Here wetest the hypothesis that the response to transcranial direct current stimulationfollowing traumatic brain injury is dependent on white matter damage within thestimulated network. We used a novel simultaneous stimulation-MRI protocolapplying anodal, cathodal and sham stimulation to 24 healthy and 35 moderate/severetraumatic brain injury patients. Stimulation was applied to the right inferior frontalgyrus/anterior insula node of the Salience Network, which was targeted because ourprevious work had shown its importance to executive function. Stimulation wasapplied during performance of the Stop Signal Task, which assesses responseinhibition, a key component of executive function. Structural MRI was used to assessthe extent of brain injury, including diffusion MRI assessment of post-traumaticaxonal injury. Functional MRI, which was simultaneously acquired to delivery ofstimulation, assessed the effects of stimulation on cognitive network function. Anodalstimulation improved response inhibition in control participants, an effect that was notobserved in the patient group. The extent of traumatic axonal injury within theSalience Network strongly influenced the behavioural response to stimulation.Increasing damage to the tract connecting the stimulated right inferior frontalgyrus/anterior insula to the rest of the SN was associated with reduced beneficialeffects of stimulation. In addition, anodal stimulation normalised Default ModeNetwork activation in patients with poor response inhibition, suggesting thatstimulation modulates communication between the networks invo
Sridharan S, Raffel J, Nandoskar A, et al., 2019, Confirmation of specific binding of the 18 kDa translocator protein (TSPO) radioligand [18F]GE-180: a blocking study using XBD173 in multiple sclerosis normal appearing white and grey matter, Molecular Imaging and Biology, Vol: 21, Pages: 935-944, ISSN: 1536-1632
Purpose: Positron emission tomography (PET) ligands exhibit different levels of non-displaceable binding in vivo. In the case of ligands for the 18 kDa translocator protein (TSPO), the component of non-displaceable binding for the most widely used radiotracer, [11C]-(R)-PK11195, is relatively high compared to that for newer TSPO ligands. Non-displaceable binding is not often quantified in humans in vivo, partially due to a lack of available ligands that are known to be safe with which to displace binding to the target receptor. Recently, however, a technique has been developed to quantify the non-displaceable binding of TSPO tracers in vivo, by blocking the receptor with the TSPO ligand XBD173 and comparing the total volume of distribution ( ) pre and post-blockade. Here, we used an occupancy plot to quantify the non-displaceable binding ( ) of the TSPO PET tracers [18F]GE-180 and [11C]PBR28 in cohorts of people with multiple sclerosis (MS). We also compared plots of subjects carrying both high and mixed binding affinity polymorphisms of TSPO to estimate while potentially avoiding the need for receptor blockade.Procedures: Twelve people with multiple sclerosis (MS) and high (HAB) or mixed (MAB) affinity binding for TSPO underwent baseline MRI and 90-minute dynamic [18F]GE-180 PET (n=6; 3 HAB and 3 MAB) or [11C]PBR28 PET (n=6; 3 HAB, 3 MAB). Either one week later ([18F]GE-180) or the same afternoon ([11C]PBR28), participants had repeat PET following a 90mg dose of XBD173. PET images were co-registered with T1 MR volumetric images and regions of interest (ROIs) were defined using the 83-region Hammers atlas. Arterial blood sampling was used to generate plasma input functions for the two-tissue compartment model to quantify . The non-displaceable fraction of the total volume of distribution ( ) was calculated using two independent methods: the occupancy plot (by modelling the differences in signal post XBD173), and the polymorphism plot (by modelling the differences in
Gorgoraptis N, Li LM, Whittington A, et al., 2019, In vivo detection of cerebral tau pathology in long-term survivors of traumatic brain injury, Science Translational Medicine, Vol: 11, Pages: 1-14, ISSN: 1946-6234
Traumatic brain injury (TBI) can trigger progressive neurodegeneration, with tau pathology seen years after a single moderate-severe TBI. Identifying this type of posttraumatic pathology in vivo might help to understand the role of tau pathology in TBI pathophysiology. We used flortaucipir positron emission tomography (PET) to investigate whether tau pathology is present many years after a single TBI in humans. We examined PET data in relation to markers of neurodegeneration in the cerebrospinal fluid (CSF), structural magnetic resonance imaging measures, and cognitive performance. Cerebral flortaucipir binding was variable, with many participants with TBI showing increases in cortical and white matter regions. At the group level, flortaucipir binding was increased in the right occipital cortex in TBI when compared to healthy controls. Flortaucipir binding was associated with increased total tau, phosphorylated tau, and ubiquitin carboxyl-terminal hydrolase L1 CSF concentrations, as well as with reduced fractional anisotropy and white matter tissue density in TBI. Apolipoprotein E (APOE) ε4 genotype affected the relationship between flortaucipir binding and time since injury, CSF β amyloid 1–42 (Aβ42) concentration, white matter tissue density, and longitudinal Mini-Mental State Examination scores in TBI. The results demonstrate that tau PET is a promising approach to investigating progressive neurodegeneration associated with tauopathy after TBI.
Jolly AE, Raymont V, Cole JH, et al., 2019, Dopamine D2/D3 receptor abnormalities after traumatic brain injury and their relationship to post-traumatic depression, NeuroImage: Clinical, Vol: 24, ISSN: 2213-1582
ObjectiveTo investigate dopamine D2/D3 receptor availability following traumatic brain injury (TBI) and their relationship to the presence of DSM-IV Major Depressive Disorder (MDD) and patterns of axonal injury.MethodsTwelve moderate-severe TBI patients and 26 controls were imaged using [11C]PHNO positron emission tomography (PET) and structural magnetic resonance imaging (MRI). TBI patients and a second group of 32 controls also underwent diffusion tensor imaging (DTI) and neuropsychological assessment. Patients included six with post-injury MDD (TBI-MDD) and six without (TBI-NON). Non-displaceable binding potential (BPND) [11C]PHNO values were used to index D2/D3 receptor availability, and were calculated using a reference region procedure. Differences in BPND were examined using voxelwise and region-of-interest analyses. White matter microstructure integrity, quantified by fractional anisotropy (FA), was assessed and correlated with BPND.ResultsLower [11C]PHNO BPND was found in the caudate across all TBI patients when compared to controls. Lower [11C]PHNO BPND was observed in the caudate of TBI-MDD patients and increased [11C]PHNO BPND in the Amygdala of TBI-NON patients compared to controls. There were no significant differences in [11C]PHNO BPND between TBI-MDD and TBI-NON patients. Furthermore, DTI provided evidence of axonal injury following TBI. The uncinate fasciculus and cingulum had abnormally low FA, with the uncinate particularly affected in TBI-MDD patients. Caudate [11C]PHNO BPND correlated with FA within the nigro-caudate tract.Conclusions[11C]PHNO BPND is abnormal following TBI, which indicates post-traumatic changes in D2/D3 receptors. Patterns of [11C]PHNO BPND seen in patients with and without MDD suggest that further research would be beneficial to determine whether the use of dopaminergic treatment might be effective in the treatment of post-traumatic depression.
Popescu SG, Whittington A, Gunn RN, et al., 2019, Nonlinear biomarker interactions in conversion from Mild Cognitive Impairment to Alzheimer’s disease
<jats:title>Abstract</jats:title><jats:p>The multi-faceted nature of Alzheimer’s disease means that multiple biomarkers (e.g., amyloid-β, tau, brain atrophy) can contribute to the prediction of clinical outcomes. Machine learning methods are a powerful way to identify the best approach to this prediction. However, it has been difficult previously to model nonlinear interactions between biomarkers in the context of predictive models. This is important as the mechanisms relating these biomarkers to the disease are inter-related and nonlinear interactions occur. Here, we used Gaussian Processes to model nonlinear interactions when combining biomarkers to predict Alzheimer’s disease conversion in 48 mild cognitive impairment participants who progressed to Alzheimer’s disease and 158 stable (over three years) people with mild cognitive impairment. Measures included: demographics, APOE4 genotype, CSF (amyloid-β42, total tau, phosphorylated tau), neuroimaging markers of amyloid-β deposition ([18<jats:sup>F</jats:sup>]florbetapir) or neurodegeneration (hippocampal volume, brain-age). We examined: (i) the independent value each biomarker has in predicting conversion; and (ii) whether modelling nonlinear interactions between biomarkers improved prediction performance.</jats:p><jats:p>Despite relatively high correlations between different biomarkers, our results showed that each measured added complementary information when predicting conversion to Alzheimer’s disease. A linear model predicting MCI group (stable versus progressive) explained over half the variance (R<jats:sup>2</jats:sup> = 0.51, <jats:italic>P</jats:italic> < 0.001); the strongest independently-contributing biomarker was hippocampal volume (R<jats:sup>2</jats:sup> = 0.13). Next, we compared the sensitivity of different models to progressive MCI: independent biomarker models, additive mod
Gorgoraptis N, Zaw-Linn J, Feeney C, et al., 2019, Cognitive impairment and health- related quality of life following traumatic brain injury, Journal of Alzheimer's Disease, Vol: 44, Pages: 321-331, ISSN: 1387-2877
BACKGROUNDCognitive impairment is a common and disabling consequence of traumatic brain injury (TBI) but its impact on health-related quality of life is not well understood.OBJECTIVETo investigate the relationship between cognitive impairment and health-related quality of life (HRQoL) after TBI.METHODSRetrospective, cross-sectional study of a specialist TBI outpatient clinic patient sample. Outcome measures: Addenbrooke's Cognitive Examination Tool - Revised (ACE-R), and SF-36 quality of life, Beck Depression Inventory II (BDI-II), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires.RESULTS240 adults were assessed: n = 172 (71.7% ) moderate-severe, 41 (23.8% ) mild, 27 (11.3% ) symptomatic TBI, 174 (72.5% ) male, median age (range): 44 (22-91) years. TBI patients reported poorer scores on all domains of SF-36 compared to age-matched UK normative data. Cognitively impaired patients reported poorer HRQoL on the physical, social role and emotional role functioning, and mental health domains. Cognitive impairment predicted poorer HRQoL on the social and emotional role functioning domains, independently of depressive symptoms, sleep disturbance, daytime sleepiness and TBI severity. Mediation analysis revealed that the effect of depressive symptoms on the emotional role functioning domain of HRQoL was partially mediated by cognitive dysfunction.CONCLUSIONCognitive impairment is associated with worse health-related quality of life after TBI and partially mediates the effect of depressive symptoms on emotional role functioning.
Jenkins PO, De Simoni S, Bourke NJ, et al., 2019, Stratifying drug treatment of cognitive impairments after traumatic brain injury using neuroimaging, Brain, Vol: 142, Pages: 2367-2379, ISSN: 1460-2156
Cognitive impairment is common following traumatic brain injury. Dopaminergic drugs can enhance cognition after traumatic brain injury, but individual responses are highly variable. This may be due to variability in dopaminergic damage between patients. We investigate whether measuring dopamine transporter levels using 123I-ioflupane single-photon emission computed tomography (SPECT) predicts response to methylphenidate, a stimulant with dopaminergic effects. Forty patients with moderate-severe traumatic brain injury and cognitive impairments completed a randomized, double-blind, placebo-controlled, crossover study. 123I-ioflupane SPECT, MRI and neuropsychological testing were performed. Patients received 0.3 mg/kg of methylphenidate or placebo twice a day in 2-week blocks. Subjects received neuropsychological assessment after each block and completed daily home cognitive testing during the trial. The primary outcome measure was change in choice reaction time produced by methylphenidate and its relationship to stratification of patients into groups with normal and low dopamine transporter binding in the caudate. Overall, traumatic brain injury patients showed slow information processing speed. Patients with low caudate dopamine transporter binding showed improvement in response times with methylphenidate compared to placebo [median change = -16 ms; 95% confidence interval (CI): -28 to -3 ms; P = 0.02]. This represents a 27% improvement in the slowing produced by traumatic brain injury. Patients with normal dopamine transporter binding did not improve. Daily home-based choice reaction time results supported this: the low dopamine transporter group improved (median change -19 ms; 95% CI: -23 to -7 ms; P = 0.002) with no change in the normal dopamine transporter group (P = 0.50). The low dopamine transporter group also improved on self-reported and caregiver apathy assessments (P = 0.03 and P = 0.02, respectively). Both groups reported improvements in fatigue (P = 0.03
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