Publications
756 results found
Schmierer K, Campion T, Sinclair A, et al., 2019, Towards a standard MRI protocol for multiple sclerosis across the UK., Br J Radiol, Pages: 20180926-20180926
Multiple sclerosis is a chronic inflammatory demyelinating and degenerative disease of the central nervous system. It is the most common non-traumatic cause of chronic disability in young adults. An early and accurate diagnosis, and effective disease modifying treatment are key elements of optimum care for people with MS (pwMS). MRI has become a critical tool to confirm the presence of dissemination in space and time of lesions characteristic of inflammatory demyelination, a cornerstone of MS diagnosis, over and above exclusion of numerous differential diagnoses. In the modern era of early and highly effective DMT, follow-up of pwMS also relies heavily on MRI, to both confirm efficacy and for pharmacovigilance. Since criteria for MS rely heavily on MRI, an agreed standardized acquisition and reporting protocol enabling efficient and equitable application across the UK is desirable. Following a recent meeting of MS experts in London (UK), we make recommendations for a standardized UK MRI protocol that captures the diagnostic phase as well as monitoring for safety and treatment efficacy once the diagnosis is established. Our views take into account issues arising from the (repeated) use of contrast agents as well as the advent of (semi-) automated tools to further optimize disease monitoring in pwMS.
Gafson AR, Savva C, Thorne T, et al., 2019, Breaking the cycle: reversal of flux in the tricarboxylic acid cycle by dimethyl fumarate, Neurology, Neuroimmunology and Neuroinflammation, Vol: 6, ISSN: 2332-7812
ObjectiveTo infer possible molecular effectors of therapeutic effects and adverse events for the pro-drug dimethyl fumarate (DMF, Tecfidera) in the plasma of relapsing-remitting MS patients (RRMS) based on untargeted blood plasma metabolomics. MethodsBlood samples were collected from 27 RRMS patients at baseline and six weeks after initiation of treatment with DMF (BG-12; Tecfidera). Patients were separated into a discovery (n=15) and a validation cohort (n=12). Ten healthy controls were also recruited and blood samples were collected over the same time intervals. Untargeted metabolomic profiling using ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS) was performed on plasma samples from the discovery cohort and healthy controls at Metabolon Inc. (Durham, NC). UPLC-MS was then performed on samples from the validation cohort at the National Phenome Centre (Imperial College, UK). Plasma neurofilament concentration (NfL) was also assayed for all subjects using the Simoa platform (Quanterix, Lexington, MA). Time course and cross-sectional statistical analyses were performed to identify pharmacodynamic changes in the metabolome secondary to DMF and relate these to adverse events. Results In the discovery cohort, tricarboxylic acid (TCA) cycle intermediates fumarate and succinate and TCA cycle metabolites succinyl-carnitine and methyl succinyl-carnitine were increased 6-weeks after the start of treatment (q < 0.05). We confirmed that methyl succinyl carnitine was also increased in the validation cohort 6-weeks after the start of treatment (q < 0.05). Changes in concentrations of these metabolites were not seen over a similar time period in blood from the untreated healthy control population. Increased succinyl-carnitine and methyl succinyl-carnitine were associated with adverse events from DMF (flushing, abdominal symptoms. The mean plasma NfL concentration before treatment was higher in the RRMS patients than in the healthy contro
Tarroni G, Oktay O, Bai W, et al., 2019, Learning-based quality control for cardiac MR images, IEEE Transactions on Medical Imaging, Vol: 38, Pages: 1127-1138, ISSN: 0278-0062
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artefacts such as cardiac and respiratory motion. In the clinical practice, a quality control step is performed by visual assessment of the acquired images: however, this procedure is strongly operatordependent, cumbersome and sometimes incompatible with the time constraints in clinical settings and large-scale studies. We propose a fast, fully-automated, learning-based quality control pipeline for CMR images, specifically for short-axis image stacks. Our pipeline performs three important quality checks: 1) heart coverage estimation, 2) inter-slice motion detection, 3) image contrast estimation in the cardiac region. The pipeline uses a hybrid decision forest method - integrating both regression and structured classification models - to extract landmarks as well as probabilistic segmentation maps from both long- and short-axis images as a basis to perform the quality checks. The technique was tested on up to 3000 cases from the UK Biobank as well as on 100 cases from the UK Digital Heart Project, and validated against manual annotations and visual inspections performed by expert interpreters. The results show the capability of the proposed pipeline to correctly detect incomplete or corrupted scans (e.g. on UK Biobank, sensitivity and specificity respectively 88% and 99% for heart coverage estimation, 85% and 95% for motion detection), allowing their exclusion from the analysed dataset or the triggering of a new acquisition.
Robinson R, Valindria VV, Bai W, et al., 2019, Automated quality control in image segmentation: application to the UK Biobank cardiac MR imaging study, Journal of Cardiovascular Magnetic Resonance, Vol: 21, ISSN: 1097-6647
Background: The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools, e.g. image segmentation methods, are employed to derive quantitative measures or biomarkers for later analyses. Manual inspection and visual QC of each segmentation isn't feasible at large scale. However, it's important to be able to automatically detect when a segmentation method fails so as to avoid inclusion of wrong measurements into subsequent analyses which could lead to incorrect conclusions. Methods: To overcome this challenge, we explore an approach for predicting segmentation quality based on Reverse Classification Accuracy, which enables us to discriminate between successful and failed segmentations on a per-cases basis. We validate this approach on a new, large-scale manually-annotated set of 4,800 cardiac magnetic resonance scans. We then apply our method to a large cohort of 7,250 cardiac MRI on which we have performed manual QC. Results: We report results used for predicting segmentation quality metrics including Dice Similarity Coefficient (DSC) and surface-distance measures. As initial validation, we present data for 400 scans demonstrating 99% accuracy for classifying low and high quality segmentations using predicted DSC scores. As further validation we show high correlation between real and predicted scores and 95% classification accuracy on 4,800 scans for which manual segmentations were available. We mimic real-world application of the method on 7,250 cardiac MRI where we show good agreement between predicted quality metrics and manual visual QC scores. Conclusions: We show that RCA has the potential for accurate and fully automatic segmentation QC on a per-case basis in the context of large-scale population imaging as in the UK Biobank Imaging Study.
Meyer HV, Dawes TJW, Serrani M, et al., 2019, Genomic analysis reveals a functional role for myocardial trabeculae in adults
<jats:title>ABSTRACT</jats:title><jats:p>Since being first described by Leonardo da Vinci in 1513 it has remained an enigma why the endocardial surfaces of the adult heart retain a complex network of muscular trabeculae – with their persistence thought to be a vestige of embryonic development. For causative physiological inference we harness population genomics, image-based intermediate phenotyping and <jats:italic>in silico</jats:italic> modelling to determine the effect of this complex cardiovascular trait on function. Using deep learning-based image analysis we identified genetic associations with trabecular complexity in 18,097 UK Biobank participants which were replicated in an independently measured cohort of 1,129 healthy adults. Genes in these associated regions are enriched for expression in the fetal heart or vasculature and implicate loci associated with haemodynamic phenotypes and developmental pathways. A causal relationship between increasing trabecular complexity and both ventricular performance and electrical activity are supported by complementary biomechanical simulations and Mendelian randomisation studies. These findings show that myocardial trabeculae are a previously-unrecognised determinant of cardiovascular physiology in adult humans.</jats:p>
Ntusi NAB, Francis JM, Gumedze F, et al., 2019, Cardiovascular magnetic resonance characterization of myocardial and vascular function in rheumatoid arthritis patients, Hellenic Journal of Cardiology, Vol: 60, Pages: 28-35, ISSN: 1109-9666
BACKGROUND: Rheumatoid arthritis (RA) is a multisystem, autoimmune disorder and confers one of the strongest risks for cardiovascular disease (CVD) morbidity and mortality. OBJECTIVE: To assess myocardial function and vascular stiffness in RA patients with and without cardiovascular risk factors (CVRFs) using cardiovascular magnetic resonance (CMR). METHODS: Twenty-three RA patients with no CVRFs (17 female, mean age 52 ± 13 years), 46 RA patients with CVRFs (32 female, mean age 53 ± 12), 50 normal controls (32 female, mean age 50 ± 11 years), and 13 controls with CVRFs (7 female, mean age 55 ± 7 years), underwent CMR at 1.5 Tesla, including evaluation of left ventricular (LV) ejection fraction, strain, and vascular elasticity (aortic distensibility [AD] and pulse wave velocity [PWV]). Disease activity and duration were recorded for each patient. Subjects with known symptomatic CVD were excluded. RESULTS: LV volumes, mass, and ejection fraction were similar in the four groups. RA patients with CVRFs showed the greatest abnormality in mid short-axis circumferential systolic strain, peak diastolic strain rate, and vascular indices. RA patients without CVRFs showed a similar degree of vascular dysfunction and deformational abnormality as controls with CVRFs. AD and total PWV correlated with myocardial strain and RA disease activity. On multivariate regression analysis, strain was related to age, RA disease activity, AD, and PWV. CONCLUSION: CMR demonstrates impaired myocardial deformation and vascular function in asymptomatic RA patients, worse in those with CVRFs. Subclinical cardiovascular abnormalities are frequent and appear to be incremental to those due to traditional CVRFs and likely contribute to the excess CVD in RA.
Nalbantian S, Matthews PM, 2019, Secrets of Creativity What Neuroscience, the Arts, and Our Minds Reveal, Publisher: Oxford University Press, USA, ISBN: 9780190462321
Authors in this volume take on the challenge of showing how creativity can be characterized behaviorally, cognitively, and neurophysiologically. The complementary perspectives of the authors add to the richness of these findings.
Gafson AR, Thorne T, McKechnie CIJ, et al., 2018, Lipoprotein markers associated with disability from multiple sclerosis, Scientific Reports, Vol: 8, ISSN: 2045-2322
Altered lipid metabolism is a feature of chronic infammatory disorders. Increased plasma lipids andlipoproteins have been associated with multiple sclerosis (MS) disease activity. Our objective was tocharacterise the specifc lipids and associated plasma lipoproteins increased in MS and to test for anassociation with disability. Plasma samples were collected from 27 RRMS patients (median EDSS,1.5, range 1–7) and 31 healthy controls. Concentrations of lipids within lipoprotein sub-classes weredetermined from NMR spectra. Plasma cytokines were measured using the MesoScale DiscoveryV-PLEX kit. Associations were tested using multivariate linear regression. Diferences between thepatient and volunteer groups were found for lipids within VLDL and HDL lipoprotein sub-fractions(p<0.05). Multivariate regression demonstrated a high correlation between lipids within VLDLsub-classes and the Expanded Disability Status Scale (EDSS) (p<0.05). An optimal model for EDSSincluded free cholesterol carried by VLDL-2, gender and age (R2=0.38, p<0.05). Free cholesterolcarried by VLDL-2 was highly correlated with plasma cytokines CCL-17 and IL-7 (R2=0.78, p<0.0001).These results highlight relationships between disability, infammatory responses and systemic lipidmetabolism in RRMS. Altered lipid metabolism with systemic infammation may contribute to immuneactivation.
Ntusi NAB, Francis JM, Sever E, et al., 2018, Anti-TNF modulation reduces myocardial inflammation and improves cardiovascular function in systemic rheumatic diseases, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 270, Pages: 253-259, ISSN: 0167-5273
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- Citations: 43
LaRocca NG, Hudson LD, Rudick R, et al., 2018, The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability, Multiple Sclerosis Journal, Vol: 24, Pages: 1469-1484, ISSN: 1352-4585
BACKGROUND: The Multiple Sclerosis Outcome Assessments Consortium (MSOAC) was formed by the National MS Society to develop improved measures of multiple sclerosis (MS)-related disability. OBJECTIVES: (1) To assess the current literature and available data on functional performance outcome measures (PerfOs) and (2) to determine suitability of using PerfOs to quantify MS disability in MS clinical trials. METHODS: (1) Identify disability dimensions common in MS; (2) conduct a comprehensive literature review of measures for those dimensions; (3) develop an MS Clinical Data Interchange Standards Consortium (CDISC) data standard; (4) create a database of standardized, pooled clinical trial data; (5) analyze the pooled data to assess psychometric properties of candidate measures; and (6) work with regulatory agencies to use the measures as primary or secondary outcomes in MS clinical trials. CONCLUSION: Considerable data exist supporting measures of the functional domains ambulation, manual dexterity, vision, and cognition. A CDISC standard for MS ( http://www.cdisc.org/therapeutic#MS ) was published, allowing pooling of clinical trial data. MSOAC member organizations contributed clinical data from 16 trials, including 14,370 subjects. Data from placebo-arm subjects are available to qualified researchers. This integrated, standardized dataset is being analyzed to support qualification of disability endpoints by regulatory agencies.
Inkster B, Simmons A, Cole JH, et al., 2018, Unravelling the GSK3 beta-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder, Psychiatric Genetics, Vol: 28, Pages: 77-84, ISSN: 0955-8829
Objective Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD.Participants and methods We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models.Results The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer’s combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications.Conclusion Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.
Bai W, Suzuki H, Qin C, et al., 2018, Recurrent neural networks for aortic image sequence segmentation with sparse annotations, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), ISSN: 0302-9743
Segmentation of image sequences is an important task in medical image analysis, which enables clinicians to assess the anatomy and function of moving organs. However, direct application of a segmentation algorithm to each time frame of a sequence may ignore the temporal continuity inherent in the sequence. In this work, we propose an image sequence segmentation algorithm by combining a fully convolutional network with a recurrent neural network, which incorporates both spatial and temporal information into the segmentation task. A key challenge in training this network is that the available manual annotations are temporally sparse, which forbids end-to-end training. We address this challenge by performing non-rigid label propagation on the annotations and introducing an exponentially weighted loss function for training. Experiments on aortic MR image sequences demonstrate that the proposed method significantly improves both accuracy and temporal smoothness of segmentation, compared to a baseline method that utilises spatial information only. It achieves an average Dice metric of 0.960 for the ascending aorta and 0.953 for the descending aorta.
Bai W, Sinclair M, Tarroni G, et al., 2018, Automated cardiovascular magnetic resonance image analysis with fully convolutional networks, Journal of Cardiovascular Magnetic Resonance, Vol: 20, Pages: 1-12, ISSN: 1097-6647
Background: Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR imageanalysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images.Methods: Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a large-scale dataset from the UK Biobank, consisting of 4,875 subjects with 93,500 pixelwise annotated images. The performance of the method has been evaluated using a number of technical metrics, including the Dice metric, mean contour distance and Hausdorff distance, as well as clinically relevant measures, including left ventricle (LV)end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolic volume (RVEDV) and end-systolic volume (RVESV).Results: By combining FCN with a large-scale annotated dataset, the proposed automated method achieves a high performance in segmenting the LV and RV on short-axis CMR images and the left atrium (LA) and right atrium (RA) on long-axis CMR images. On a short-axis image test set of 600 subjects, it achieves an average Dice metric of 0.94 for the LV cavity, 0.88 for the LV myocardium and 0.90 for the RV cavity. The meanabsolute difference between automated measurement and manual measurement was 6.1 mL for LVEDV, 5.3 mL for LVESV, 6.9 gram for LVM, 8.5 mL for RVEDV and 7.2 mL for RVESV. On long-ax
Liu Z, Zhang J, Zhang K, et al., 2018, Distinguishable brain networks relate disease susceptibility to symptom expression in schizophrenia, Human Brain Mapping, Vol: 39, Pages: 3503-3515, ISSN: 1065-9471
Disease association studies have characterized altered resting-state functional connectivities describing schizophrenia, but failed to model symptom expression well. We developed a model that could account for symptom severity and meanwhile relate this to disease-related functional pathology. We correlated BOLD signal across brain regions and tested separately for associations with disease (disease edges) and with symptom severity (symptom edges) in a prediction-based scheme. We then integrated them in an "edge bi-color" graph, and adopted mediation analysis to test for causality between the disease and symptom networks and symptom scores. For first-episode schizophrenics (FES, 161 drug-naïve patients and 150 controls), the disease network (with inferior frontal gyrus being the hub) and the symptom-network (posterior occipital-parietal cortex being the hub) were found to overlap in the temporal lobe. For chronic schizophrenis (CS, 69 medicated patients and 62 controls), disease network was dominated by thalamocortical connectivities, and overlapped with symptom network in the middle frontal gyrus. We found that symptom network mediates the relationship between disease network and symptom scores in FEP, but was unable to define a relationship between them for the smaller CS population. Our results suggest that the disease network distinguishing core functional pathology in resting-state brain may be responsible for symptom expression in FES through a wider brain network associated with core symptoms. We hypothesize that top-down control from heteromodal prefrontal cortex to posterior transmodal cortex contributes to positive symptoms of schizophrenia. Our work also suggests differences in mechanisms of symptom expression between FES and CS, highlighting a need to distinguish between these groups.
Gibson L, Littlejohns T, Adamska L, et al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging, Wellcome Open Research
Background : There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods : Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results : Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions : Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of
Suzuki H, Matthews PM, 2018, Heart rate as a novel risk factor for brain health, European-Society-of-Cardiology Congress, Publisher: OXFORD UNIV PRESS, Pages: 230-231, ISSN: 0195-668X
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Calsolaro V, Mayers J, Fan Z, et al., 2018, Evaluation of novel astrocyte marker [11C]BU99008 PET in Alzheimer’s disease: a Dementia Platform U.K. experimental medicine study, Alzheimer's and Dementia, Vol: 14, Pages: P842-P843, ISSN: 1552-5260
Fan Z, Calsolaro V, Mayers J, et al., 2018, Relationship between astrocyte activation using [11C]BU99008 PET, glucose metabolism and amyloid in Alzheimer’s disease: a Dementia Platform UK experimental medicine study, Alzheimer's and Dementia, Vol: 14, Pages: P1640-P1640, ISSN: 1552-5260
Supratak A, Datta G, Gafson AR, et al., 2018, Remote monitoring in the home validates clinical gait measures for multiple sclerosis, Frontiers in Neurology, Vol: 9, Pages: 1-9, ISSN: 1664-2295
Background: The timed 25-foot walk (T25FW) is widely used as a clinic performance measure, but has yet to be directly validated against gait speed in the home environment.Objectives: To develop an accurate method for remote assessment of walking speed and to test how predictive the clinic T25FW is for real-life walking.Methods: An AX3-Axivity tri-axial accelerometer was positioned on 32 MS patients (Expanded Disability Status Scale [EDSS] 0–6) in the clinic, who subsequently wore it at home for up to 7 days. Gait speed was calculated from these data using both a model developed with healthy volunteers and individually personalized models generated from a machine learning algorithm.Results: The healthy volunteer model predicted gait speed poorly for more disabled people with MS. However, the accuracy of individually personalized models was high regardless of disability (R-value = 0.98, p-value = 1.85 × 10−22). With the latter, we confirmed that the clinic T25FW is strongly predictive of the maximum sustained gait speed in the home environment (R-value = 0.89, p-value = 4.34 × 10−8).Conclusion: Remote gait monitoring with individually personalized models is accurate for patients with MS. Using these models, we have directly validated the clinical meaningfulness (i.e., predictiveness) of the clinic T25FW for the first time.
Dawes TJW, Serrani M, Bai W, et al., 2018, Myocardial trabeculae improve left ventricular function: a combined UK Biobank and computational analysis, GAT Annual Scientific Meeting 2018, Publisher: Association of Anaesthetists of Great Britain and Ireland
Gafson A, Kicheol K, Cencioni M, et al., 2018, Mononuclear cell transcriptome changes associated with dimethyl fumarate in multiple sclerosis., Neurology, Neuroimmunology and Neuroinflammation, Vol: 5, ISSN: 2332-7812
Objective To identify short-term changes in gene expression in peripheral blood mononuclear cells (PBMCs) associated with treatment response to dimethyl fumarate (DMF, Tecfidera) in patients with relapsing-remitting MS (RRMS).Methods Blood samples were collected from 24 patients with RRMS (median Expanded Disability Status Scale score, 2.0; range 1–7) at baseline, 6 weeks, and 15 months after the initiation of treatment with DMF (BG-12; Tecfidera). Seven healthy controls were also recruited, and blood samples were collected over the same time intervals. PBMCs were extracted from blood samples and sequenced using next-generation RNA sequencing. Treatment responders were defined using the composite outcome measure “no evidence of disease activity” (NEDA-4). Time-course and cross-sectional differential expression analyses were performed to identify transcriptomic markers of treatment response.Results Treatment responders (NEDA-4 positive, 8/24) over the 15-month period had 478 differentially expressed genes (DEGs) 6 weeks after the start of treatment. These were enriched for nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and inhibition of nuclear factor κB (NFκB) pathway transcripts. For patients who showed signs of disease activity, there were no DEGs at 6 weeks relative to their (untreated) baseline. Contrasting transcriptomes expressed at 6 weeks with those at 15 months of treatment, 0 and 1,264 DEGs were found in the responder and nonresponder groups, respectively. Transcripts in the nonresponder group (NEDA-4 negative, 18/24) were enriched for T-cell signaling genes.Conclusion Short-term PBMC transcriptome changes reflecting activation of the Nrf2 and inhibition of NFκB pathways distinguish patients who subsequently show a medium-term treatment response with DMF. Relative stabilization of gene expression patterns may accompany treatment-associated suppression of disease activity.
Gibson L, Littlejohns T, Adamska L, et al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging
Background : There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods : Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results : Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions : Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of
Bishop CA, Ricotti V, Sinclair CDJ, et al., 2018, Semi-automated analysis of diaphragmatic motion with dynamic magnetic resonance imaging in healthy controls and non-ambulant subjects with duchenne muscular dystrophy, Frontiers in Neurology, Vol: 9, ISSN: 1664-2295
Subjects with Duchenne Muscular Dystrophy (DMD) suffer from progressive muscle damage leading to diaphragmatic weakness that ultimately requires ventilation. Emerging treatments have generated interest in better characterizing the natural history of respiratory impairment in DMD and responses to therapy. Dynamic (cine) Magnetic Resonance Imaging (MRI) may provide a more sensitive measure of diaphragm function in DMD than the commonly used spirometry. This study presents an analysis pipeline for measuring parameters of diaphragmatic motion from dynamic MRI and its application to investigate MRI measures of respiratory function in both healthy controls and non-ambulant DMD boys. We scanned 13 non-ambulant DMD boys and 10 age-matched healthy male volunteers at baseline, with a subset (n = 10, 10, 8) of the DMD subjects also assessed 3, 6, and 12 months later. Spirometry-derived metrics including forced vital capacity were recorded. The MRI-derived measures included the lung cross-sectional area (CSA), the anterior, central, and posterior lung lengths in the sagittal imaging plane, and the diaphragm length over the time-course of the dynamic MRI. Regression analyses demonstrated strong linear correlations between lung CSA and the length measures over the respiratory cycle, with a reduction of these correlations in DMD, and diaphragmatic motions that contribute less efficiently to changing lung capacity in DMD. MRI measures of pulmonary function were reduced in DMD, controlling for height differences between the groups: at maximal inhalation, the maximum CSA and the total distance of motion of the diaphragm were 45% and 37% smaller. MRI measures of pulmonary function were correlated with spirometry data and showed relationships with disease progression surrogates of age and months non-ambulatory, suggesting that they provide clinically meaningful information. Changes in the MRI measures over 12 months were consistent with weakening of diaphragmatic and inter-costal muscl
Gibson LM, Littlejohns TJ, Adamska L, et al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging, Publisher: F1000 Research Ltd
<ns5:p><ns5:bold>Background</ns5:bold>: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images.</ns5:p><ns5:p> <ns5:bold>Methods</ns5:bold>: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts.</ns5:p><ns5:p> <ns5:bold>Results</ns5:bold>: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%).</ns5:p><ns5:p> <ns5:bold>Conclusions</ns5:bold>: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoi
Scott GPT, Zetterberg H, Jolly A, et al., 2017, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, Brain, Vol: 141, Pages: 459-471, ISSN: 1460-2156
Survivors of a traumatic brain injury can deteriorate years later, developing brain atrophy and dementia. Traumatic brain injury triggers chronic microglial activation, but it is unclear whether this is harmful or beneficial. A successful chronic-phase treatment for traumatic brain injury might be to target microglia. In experimental models, the antibiotic minocycline inhibits microglial activation. We investigated the effect of minocycline on microglial activation and neurodegeneration using PET, MRI, and measurement of the axonal protein neurofilament light in plasma. Microglial activation was assessed using 11C-PBR28 PET. The relationships of microglial activation to measures of brain injury, and the effects of minocycline on disease progression, were assessed using structural and diffusion MRI, plasma neurofilament light, and cognitive assessment. Fifteen patients at least 6 months after a moderate-to-severe traumatic brain injury received either minocycline 100 mg orally twice daily or no drug, for 12 weeks. At baseline, 11C-PBR28 binding in patients was increased compared to controls in cerebral white matter and thalamus, and plasma neurofilament light levels were elevated. MRI measures of white matter damage were highest in areas of greater 11C-PBR28 binding. Minocycline reduced 11C-PBR28 binding (mean Δwhite matter binding = −23.30%, 95% confidence interval −40.9 to −5.64%, P = 0.018), but increased plasma neurofilament light levels. Faster rates of brain atrophy were found in patients with higher baseline neurofilament light levels. In this experimental medicine study, minocycline after traumatic brain injury reduced chronic microglial activation while increasing a marker of neurodegeneration. These findings suggest that microglial activation has a reparative effect in the chronic phase of traumatic brain injury.
Stangel M, Kuhlmann T, Matthews PM, et al., 2017, Achievements and obstacles of remyelinating therapies in multiple sclerosis, Nature Reviews Neurology, Vol: 13, Pages: 742-754, ISSN: 1759-4758
Remyelination in the CNS is the natural process of damage repair in demyelinating diseases such as multiple sclerosis (MS). However, remyelination becomes inadequate in many people with MS, which results in axonal degeneration and clinical disability. Enhancement of remyelination is a logical therapeutic goal; nevertheless, all currently licensed therapies for MS are immunomodulatory and do not support remyelination directly. Several molecular pathways have been identified as potential therapeutic targets to induce remyelination, and some of these have now been assessed in proof-of-concept clinical trials. However, trial design faces several obstacles: optimal clinical or paraclinical outcome measures to assess remyelination remain ill-defined, and identification of the ideal timing of therapy is also a crucial issue. In addition, realistic expectations are needed concerning the probable benefits of such therapies. Nevertheless, approaches that enhance remyelination are likely to be protective for axons and so could prevent long-term neurodegeneration. Future MS treatment paradigms, therefore, are likely to comprise a combinatorial approach that involves both immunomodulatory and regenerative treatments.
Gibson LM, Littlejohns TJ, Adamska L, et al., 2017, Impact of detecting potentially serious incidental findings during multi-modal imaging [version 3; peer review: 2 approved, 1 approved with reservations], Wellcome Open Research, Vol: 2, ISSN: 2398-502X
Background: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank's protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer 'flagging' with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank's responsibility to avoid both unnecessary harm to larger numbers of participants and burdening
Owen DRJ, Fan J, Campioli E, et al., 2017, TSPO mutations in rats and a human polymorphism impair the rate of steroid synthesis, Biochemical Journal, Vol: 474, Pages: 3985-3999, ISSN: 1470-8728
The 18 kDa translocator protein (TSPO) is a ubiquitous conserved outer mitochondrial membrane protein implicated in numerous cell and tissue functions, including steroid hormone biosynthesis, respiration, cell proliferation, and apoptosis. TSPO binds with high affinity to cholesterol and numerous compounds, is expressed at high levels in steroid-synthesizing tissues, and mediates cholesterol import into mitochondria, which is the rate-limiting step in steroid formation. In humans, the rs6971 polymorphism on the TSPO gene leads to an amino acid substitution in the fifth transmembrane loop of the protein, which is where the cholesterol-binding domain of TSPO is located, and this polymorphism has been associated with anxiety-related disorders. However, recent knockout mouse models have provided inconsistent conclusions of whether TSPO is directly involved in steroid synthesis. In this report, we show that TSPO deletion mutations in rat and its corresponding rs6971 polymorphism in humans alter adrenocorticotropic hormone-induced plasma corticosteroid concentrations. Rat tissues examined show increased cholesteryl ester accumulation, and neurosteroid formation was undetectable in homozygous rats. These results also support a role for TSPO ligands in diseases with steroid-dependent stress and anxiety elements.
Suzuki HS, Gao HG, Bai WB, et al., 2017, Abnormal brain white matter microstructure is associated withboth pre-hypertension and hypertension, PLoS ONE, Vol: 12, ISSN: 1932-6203
ObjectivesTo characterize effects of chronically elevated blood pressure on the brain, we tested for brain white matter microstructural differences associated with normotension, pre-hypertension and hypertension in recently available brain magnetic resonance imaging data from 4659 participants without known neurological or psychiatric disease (62.3±7.4 yrs, 47.0% male) in UK Biobank.MethodsFor assessment of white matter microstructure, we used measures derived from neurite orientation dispersion and density imaging (NODDI) including the intracellular volume fraction (an estimate of neurite density) and isotropic volume fraction (an index of the relative extra-cellular water diffusion). To estimate differences associated specifically with blood pressure, we applied propensity score matching based on age, sex, educational level, body mass index, and history of smoking, diabetes mellitus and cardiovascular disease to perform separate contrasts of non-hypertensive (normotensive or pre-hypertensive, N = 2332) and hypertensive (N = 2337) individuals and of normotensive (N = 741) and pre-hypertensive (N = 1581) individuals (p<0.05 after Bonferroni correction).ResultsThe brain white matter intracellular volume fraction was significantly lower, and isotropic volume fraction was higher in hypertensive relative to non-hypertensive individuals (N = 1559, each). The white matter isotropic volume fraction also was higher in pre-hypertensive than in normotensive individuals (N = 694, each) in the right superior longitudinal fasciculus and the right superior thalamic radiation, where the lower intracellular volume fraction was observed in the hypertensives relative to the non-hypertensive group.SignificancePathological processes associated with chronically elevated blood pressure are associated with imaging differences suggesting chronic alterations of white matter axonal structure that may affect cognitive functions even with pre-hypertension.
Alfaro-Almagro F, Jenkinson M, Bangerter NK, et al., 2017, Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank., NeuroImage, Vol: 166, Pages: 400-424, ISSN: 1053-8119
UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.
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