Publications
756 results found
Saba Y, Hofer E, Sargurupremraj M, et al., 2020, GENETICS OF WHITE MATTER HYPERINTENSITY STRATIFIED BY HYPERTENSION STATUS-THE CHARGE CONSORTIUM, Publisher: SAGE PUBLICATIONS LTD, Pages: 95-95, ISSN: 1747-4930
Huang J, Zuber V, Matthews P, et al., 2020, Sleep, major depressive disorder and Alzheimer’s disease: a Mendelian randomisation study, Neurology, Vol: 95, ISSN: 0028-3878
ObjectiveTo explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer’s disease (AD).MethodsWe conducted bi-directional two-sample Mendelian randomisation analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (N=446,118), the Psychiatric Genomics Consortium (N=18,759), and the International Genomics of Alzheimer’s Project (N=63,926). We used the inverse variance weighted Mendelian randomisation method to estimate causal effects, and weighted median and MR-Egger for sensitivity analyses to test for pleiotropic effects. ResultsWe found that higher risk of AD was significantly associated with being a “morning person” (odds ratio (OR)=1.01, P=0.001), shorter sleep duration (self-reported: β=-0.006, P=1.9×10-4; accelerometer-based: β=-0.015, P=6.9×10-5), less likely to report long sleep (β=-0.003, P=7.3×10-7), earlier timing of the least active 5 hours (β=-0.024, P=1.7×10-13), and a smaller number of sleep episodes (β=-0.025, P=5.7×10-14) after adjusting for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR=0.99, P=7×10-13). However, we did not find evidence either that these abnormal sleep patterns were causally related to AD or for a significant causal relationship between MDD and risk of AD. ConclusionWe found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns for AD or evidence for a causal relationship between MDD and AD.
Bai W, Suzuki H, Huang J, et al., 2020, A population-based phenome-wide association study of cardiac and aortic structure and function, Nature Medicine, Vol: 26, Pages: 1654-1662, ISSN: 1078-8956
Differences in cardiac and aortic structure and function are associated with cardiovascular diseases and a wide range of other types of disease. Here we analyzed cardiovascular magnetic resonance images from a population-based study, the UK Biobank, using an automated machine-learning-based analysis pipeline. We report a comprehensive range of structural and functional phenotypes for the heart and aorta across 26,893 participants, and explore how these phenotypes vary according to sex, age and major cardiovascular risk factors. We extended this analysis with a phenome-wide association study, in which we tested for correlations of a wide range of non-imaging phenotypes of the participants with imaging phenotypes. We further explored the associations of imaging phenotypes with early-life factors, mental health and cognitive function using both observational analysis and Mendelian randomization. Our study illustrates how population-based cardiac and aortic imaging phenotypes can be used to better define cardiovascular disease risks as well as heart–brain health interactions, highlighting new opportunities for studying disease mechanisms and developing image-based biomarkers.
Thrupp N, Frigerio CS, Wolfs L, et al., 2020, Single-nucleus RNA-seq is not suitable for detection of microglial activation genes in humans, Cell Reports, Vol: 32, Pages: 1-13, ISSN: 2211-1247
Single-nucleus RNA sequencing (snRNA-seq) is used as an alternative to single-cell RNA-seq, as it allows transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-seq is able to detect cellular state in human tissue. Indeed, snRNA-seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer’s disease. Our comparison of microglia from single cells and single nuclei of four human subjects reveals that, although most genes show similar relative abundances in cells and nuclei, a small population of genes (∼1%) is depleted in nuclei compared to whole cells. This population is enriched for genes previously implicated in microglial activation, including APOE, CST3, SPP1, and CD74, comprising 18% of previously identified microglial-disease-associated genes. Given the low sensitivity of snRNA-seq to detect many activation genes, we conclude that snRNA-seq is not suited for detecting cellular activation in microglia in human disease.
Meyer H, Dawes T, Serrani M, et al., 2020, Genetic and functional insights into the fractal structure of the heart, Nature, Vol: 584, Pages: 589-594, ISSN: 0028-0836
The inner surfaces of the human heart are covered by a complex network of muscular strands that is thought to be a vestigeof embryonic development.1,2 The function of these trabeculae in adults and their genetic architecture are unknown. Toinvestigate this we performed a genome-wide association study using fractal analysis of trabecular morphology as animage-derived phenotype in 18,096 UK Biobank participants. We identified 16 significant loci containing genes associatedwith haemodynamic phenotypes and regulation of cytoskeletal arborisation.3,4 Using biomechanical simulations and humanobservational data, we demonstrate that trabecular morphology is an important determinant of cardiac performance. Throughgenetic association studies with cardiac disease phenotypes and Mendelian randomisation, we find a causal relationshipbetween trabecular morphology and cardiovascular disease risk. These findings suggest an unexpected role for myocardialtrabeculae in the function of the adult heart, identify conserved pathways that regulate structural complexity, and reveal theirinfluence on susceptibility to disease
Waddingham E, Matthews PM, Ashby D, 2020, Exploiting relationships between outcomes in Bayesian multivariate network meta-analysis with an application to relapsing-remitting multiple sclerosis, Statistics in Medicine, Vol: 39, Pages: 3329-3346, ISSN: 0277-6715
In multivariate network meta‐analysis (NMA), the piecemeal nature of the evidence base means that there may be treatment‐outcome combinations for which no data is available.Most existing multivariate evidence synthesis models are either unable to estimate the missing treatment‐outcome combinations, or can only do so under particularly strong assumptions, such as perfect between‐study correlations between outcomes or constant effect size across outcomes. Many existing implementations are also limited to two treatments or two outcomes, or rely on model specification that is heavily tailored to the dimensions of the dataset. We present a Bayesian multivariate NMA model that estimates the missing treatment‐outcome combinations via mappings between the population mean effects, while allowing the study‐specific effects to be imperfectly correlated. The method is designed for aggregate‐level data (rather than individual patient data) and is likely to be useful when modeling multiple sparsely reported outcomes, or when varying definitions of the same underlying outcome are adopted by different studies. We implement the model via a novel decomposition of the treatment effect variance, which can be specified efficiently for an arbitrary dataset given some basic assumptions regarding the correlation structure. The method is illustrated using data concerning the efficacy and liver‐related safety of eight active treatments for relapsing‐remitting multiple sclerosis. The results indicate that fingolimod and interferon beta‐1b are the most efficacious treatments but also have some of the worst effects on liver safety. Dimethyl fumarate and glatiramer acetate perform reasonably on all of the efficacy and safety outcomes in the model.
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
Gafson AR, Barthelemy NR, Bomont P, et al., 2020, Neurofilaments: neurobiological foundations for biomarker applications, BRAIN, Vol: 143, Pages: 1975-1998, ISSN: 0006-8950
- Author Web Link
- Cite
- Citations: 114
Littlejohns TJ, Holliday J, Gibson LM, et al., 2020, The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions, Nature Communications, Vol: 11, ISSN: 2041-1723
UK Biobank is a population-based cohort of half a million participants aged 40-69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world's largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future directions.
Faergeman SL, Evans H, Attfield KE, et al., 2020, A novel neurodegenerative spectrum disorder in patients with MLKL deficiency, Cell Death and Disease, Vol: 11, ISSN: 2041-4889
Mixed lineage kinase domain-like (MLKL) is the main executor of necroptosis, an inflammatory form of programmed cell death. Necroptosis is implicated in combating infections, but also in contributing to numerous other clinical conditions, including cardiovascular diseases and neurodegenerative disorders. Inhibition of necroptosis is therefore of therapeutic interest. Here we report two siblings both of whom over the course of 35 years developed a similar progressive, neurodegenerative spectrum disorder characterized by paresis, ataxia and dysarthria. Magnetic resonance imaging of their central nervous system (CNS) revealed severe global cerebral volume loss and atrophy of the cerebellum and brainstem. These brothers are homozygous for a rare haplotype identified by whole genome sequencing carrying a frameshift variant in MLKL, as well as an in-frame deletion of one amino acid in the adjacent fatty acid 2-hydroxylase (FA2H) gene. Functional studies of patient-derived primary cells demonstrated that the variant in MLKL leads to a deficiency of MLKL protein resulting in impairment of necroptosis. Conversely, shotgun lipidomic analysis of the variant in FA2H shows no impact on either the abundance or the enzymatic activity of the encoded hydroxylase. To our knowledge, this is the first report of complete necroptosis deficiency in humans. The findings may suggest that impaired necroptosis is a novel mechanism of neurodegeneration, promoting a disorder that shares some clinical features with primary progressive multiple sclerosis (PPMS) and other neurodegenerative diseases. Importantly, the necroptotic deficiency does not cause symptoms outside the nervous system, nor does it confer susceptibility to infections. Given the current interest in pharmacological inhibition of necroptosis by targeting MLKL and its associated pathways, this strategy should be developed with caution, with careful consideration of the possible development of adverse neurological effects.
Bauermeister S, Orton C, Thompson S, et al., 2020, The Dementias Platform UK (DPUK) data portal, European Journal of Epidemiology, Vol: 35, Pages: 601-611, ISSN: 0393-2990
The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure ‘lab’ using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.
Matthews PM, Block VJ, Leocani L, 2020, E-health and multiple sclerosis., Current Opinion in Neurology, Vol: 33, Pages: 271-276, ISSN: 1080-8248
PURPOSE OF REVIEW: To outline recent applications of e-health data and digital tools for improving the care and management of healthcare for people with multiple sclerosis. RECENT FINDINGS: The digitization of most clinical data, along with developments in communication technologies, miniaturization of sensors and computational advances are enabling aggregation and clinically meaningful analyses of real-world data from patient registries, digital patient-reported outcomes and electronic health records (EHR). These data are allowing more confident descriptions of prognoses for multiple sclerosis patients and the long-term relative benefits and safety of disease-modifying treatments (DMT). Registries allow detailed, multiple sclerosis-specific data to be shared between clinicians more easily, provide data needed to improve the impact of DMT and, with EHR, characterize clinically relevant interactions between multiple sclerosis and other diseases. Wearable sensors provide continuous, long-term measures of performance dynamics in relevant ecological settings. In conjunction with telemedicine and online apps, they promise a major expansion of the scope for patients to manage aspects of their own care. Advances in disease understanding, decision support and self-management using these Big Data are being accelerated by machine learning and artificial intelligence. SUMMARY: Both health professionals and patients can employ e-health approaches and tools for development of a more patient-centred learning health system.
Longbrake E, Mao-Draayer Y, Matthews PM, et al., 2020, Absolute Lymphocyte Counts Are Not a Biomarker of Clinical Response in Patients Treated With Delayed-Release Dimethyl Fumarate, Annual Meeting of the American-Academy-of-Neurology, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0028-3878
Thrupp N, Frigerio CS, Wolfs L, et al., 2020, Single nucleus sequencing fails to detect microglial activation in human tissue
<jats:title>Abstract</jats:title><jats:p>Single nucleus RNA-Seq (snRNA-Seq) methods are used as an alternative to single cell RNA-Seq methods, as they allow transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-Seq is able to detect cellular state in human tissue. Indeed, snRNA-Seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer’s Disease. A comparison of microglia from single cells and single nuclei of four human subjects reveals that ~1% of genes is depleted in nuclei compared to whole cells. This small population contains 18% of genes previously implicated in microglial activation, including <jats:italic>APOE, CST3, FTL, SPP1</jats:italic>, and <jats:italic>CD74</jats:italic>. We confirm our findings across multiple previous single nucleus and single cell studies. Given the low sensitivity of snRNA-Seq to this population of activation genes, we conclude that snRNA-Seq is not suited to detecting cellular activation in microglia in human disease.</jats:p>
Tarroni G, Bai W, Oktay O, et al., 2020, Large-scale quality control of cardiac imaging in population studies: application to UK Biobank, Scientific Reports, Vol: 10, ISSN: 2045-2322
In large population studies such as the UK Biobank (UKBB), quality control of the acquired images by visual assessment isunfeasible. In this paper, we apply a recently developed fully-automated quality control pipeline for cardiac MR (CMR) imagesto the first 19,265 short-axis (SA) cine stacks from the UKBB. We present the results for the three estimated quality metrics(heart coverage, inter-slice motion and image contrast in the cardiac region) as well as their potential associations with factorsincluding acquisition details and subject-related phenotypes. Up to 14.2% of the analysed SA stacks had sub-optimal coverage(i.e. missing basal and/or apical slices), however most of them were limited to the first year of acquisition. Up to 16% of thestacks were affected by noticeable inter-slice motion (i.e. average inter-slice misalignment greater than 3.4 mm). Inter-slicemotion was positively correlated with weight and body surface area. Only 2.1% of the stacks had an average end-diastoliccardiac image contrast below 30% of the dynamic range. These findings will be highly valuable for both the scientists involvedin UKBB CMR acquisition and for the ones who use the dataset for research purposes.
Mansur A, Rabiner EA, Comley RA, et al., 2020, Characterization of 3 PET tracers for Quantification of Mitochondrial and Synaptic function in Healthy Human Brain: 18F-BCPP-EF, 11C-SA-4503, 11C-UCB-J, Journal of Nuclear Medicine, Vol: 61, Pages: 96-103, ISSN: 1535-5667
Mitochondrial complex 1 (MC1) is involved in maintaining brain bioenergetics, the sigma 1 receptor (σ1R) responds to neuronal stress and synaptic vesicle protein 2A (SV2A) reflects synaptic integrity. Expression of each of these proteins is altered in neurodegenerative diseases. Here we characterise the kinetic behaviour of three positron emission tomography (PET) radioligands 18F-BCPP-EF, 11C-SA-4503 and 11CUCB- J, for the measurement of MC1, σ1R and SV2A, respectively, and determine appropriate analysis workflows for their application in future studies of the in vivo molecular pathology of these diseases. Methods: Twelve human subjects underwent dynamic PET scans including associated arterial blood sampling with each radioligand. A range of kinetic models were investigated to identify an optimal kinetic analysis method for each radioligand and a suitable acquisition duration. Results: All three radioligands readily entered the brain and yielded heterogeneous uptake consistent with the known distribution of the targets. The optimal models determined for the regional estimates of volume of distribution (VT) were multilinear analysis 1 (MA1) and the 2-tissue compartment (2TC) model for 18F-BCPP-EF, MA1 for 11C-SA- 4503, and both MA1 and the 1-tissue compartment (1TC) model for 11C-UCB-J. Acquisition times of 70, 80 and 60 minutes for 18F-BCPP-EF, 11C-SA-4503, 11C-UCB-J, respectively, provided good estimates of regional VT values. An effect of age was observed on 18F-BCPP-EF and 11C-UCB-J signal in the caudate. Conclusion: These ligands can be assessed for their potential to stratify patients or monitor the progression of molecular neuropathology in neurodegenerative diseases.
Suzuki H, Venkataraman AV, Bai W, et al., 2019, Associations of regional brain structural differences with aging, modifiable risk factors for dementia, and cognitive performance, JAMA Network Open, Vol: 2, Pages: 1-19, ISSN: 2574-3805
Importance Identifying brain regions associated with risk factors for dementia could guide mechanistic understanding of risk factors associated with Alzheimer disease (AD).Objectives To characterize volume changes in brain regions associated with aging and modifiable risk factors for dementia (MRFD) and to test whether volume differences in these regions are associated with cognitive performance.Design, Setting, and Participants This cross-sectional study used data from UK Biobank participants who underwent T1-weighted structural brain imaging from August 5, 2014, to October 14, 2016. A voxelwise linear model was applied to test for regional gray matter volume differences associated with aging and MRFD (ie, hypertension, diabetes, obesity, and frequent alcohol use). The potential clinical relevance of these associations was explored by comparing their neuroanatomical distributions with the regional brain atrophy found with AD. Mediation models for risk factors, brain volume differences, and cognitive measures were tested. The primary hypothesis was that common, overlapping regions would be found. Primary analysis was conducted on April 1, 2018.Main Outcomes and Measures Gray matter regions that showed relative atrophy associated with AD, aging, and greater numbers of MRFD.Results Among 8312 participants (mean [SD] age, 62.4 [7.4] years; 3959 [47.1%] men), aging and 4 major MRFD (ie, hypertension, diabetes, obesity, and frequent alcohol use) had independent negative associations with specific gray matter volumes. These regions overlapped neuroanatomically with those showing lower volumes in participants with AD, including the posterior cingulate cortex, the thalamus, the hippocampus, and the orbitofrontal cortex. Associations between these MRFD and spatial memory were mediated by differences in posterior cingulate cortex volume (β = 0.0014; SE = 0.0006; P = .02).Conclusions and Relevance This cross-sectional study
Goldman MD, LaRocca NG, Rudick RA, et al., 2019, Evaluation of multiple sclerosis disability outcome measures using pooled clinical trial data, NEUROLOGY, Vol: 93, Pages: E1921-E1931, ISSN: 0028-3878
- Author Web Link
- Cite
- Citations: 49
Nutma E, Stephenson JA, Gorter RP, et al., 2019, A quantitative neuropathological assessment of translocator protein expression in multiple sclerosis, Brain, Vol: 142, Pages: 3440-3455, ISSN: 1460-2156
The 18kDa translocator protein (TSPO) is increasingly used to study brain and spinal cord inflammation in degenerative diseases of the CNS such as multiple sclerosis. The enhanced TSPO PET signal that arises during disease is widely-considered to reflect activated pathogenicmicroglia, although quantitative neuropathological data to support this interpretation has not been available. With the increasing interest in the role of chronic microglial activation in multiple sclerosis, characterising the cellular neuropathology associated with TSPO expression is of clear importance for understanding the cellular and pathological processes on which TSPO PET imaging is reporting.Here we have studied the cellular expression of TSPO and specific binding of two TSPO targeting radioligands ([3H]PK11195 and [3H]PBR28) in tissue sections from 42 multiple sclerosis cases and 12 age-matched controls. Markers of homeostatic and reactive microglia, astrocytes, and lymphocytes were used to investigate the phenotypes of cells expressing TSPO. There was an approximate 20-fold increase in cells double positive for TSPO and human leukocyte antigen -DR in active lesions and in the rim of chronic active lesion, relative to normal appearing white matter. TSPO was uniformly expressed across myeloid cells irrespective of their phenotype, rather than being preferentially associated with pro-inflammatory microglia or macrophages. TSPO+astrocytes were increased up to 7-fold compared to normal appearing white matter across all lesion sub-types and accounted for 25% of the TSPO+ cells in these lesions. To relate TSPO protein expression to ligand binding, specific binding of the TSPO ligands [3H]PK11195 and [3H]PBR28was determined in the same lesions. TSPO radioligand binding was increased up to seven times for [3H]PBR28 and up to two times for [3H]PK11195 in active lesions and the centre of chronic ac
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.
Evangelou E, Gao H, Blakeley P, et al., 2019, New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders, Nature Human Behaviour, Vol: 3, Pages: 950-961, ISSN: 2397-3374
Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d−1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.
Smith AM, Khozoie C, Fancy N, et al., 2019, Single nucleus RNA sequencing of post-mortem multiple sclerosis cortical grey matter, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 233-233, ISSN: 1352-4585
Longbrake EE, Matthews PM, Mao-Draayer Y, et al., 2019, Change in absolute lymphocyte count is not a biomarker of clinical response and does not correlate with change in serum neurofilament light for patients treated with delayed-release dimethyl fumarate, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 552-553, ISSN: 1352-4585
Weinert M, Cowley SA, Alavian KN, et al., 2019, Exploring the mitochondrial TSPO protein as a possible immunometabolic modulatory target for treatment of multiple sclerosis, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 515-515, ISSN: 1352-4585
- Author Web Link
- Cite
- Citations: 1
Fancy NN, Srivastava P, Matthews PM, et al., 2019, A bioinformatics approach to understand the regulation of TSPO gene expression in myeloid cells, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 222-222, ISSN: 1352-4585
Podmore S, Datta G, Nicholas R, et al., 2019, Association of binding heterogeneity of the TSPO PET ligand [<SUP>11</SUP>C]PBR28 in deep white matter lesions and their longitudinal MRI evolution, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 235-236, ISSN: 1352-4585
Matthews P, 2019, Chronic inflammation in multiple sclerosis — seeing what was always there, Nature Reviews Neurology, Vol: 15, Pages: 582-593, ISSN: 1759-4758
Activation of innate immune cells and other brain compartmentalized inflammatory cellsin the brains and spinal cords of people with relapsing–remitting multiple sclerosis (MS) and progressive MS have been well described histopathologically. However, conventional clinical MRI is largely insensitive to this inflammatory activity. The past two decades have seen the introduction of quantitative dynamic MRI scanning with contrast agents that are sensitive to the reduction in blood–brain barrier integrity associated with inflammation and to the trafficking of inflammatory myeloid cells. New MRI imaging sequences provide improved contrast for better detection of grey matter lesions. Quantitative lesion volume measures and magnetic resonance susceptibility imaging are sensitive to the activity of macrophages in the rims of white matter lesions. PET and magnetic resonance spectroscopy methods also can be used to detect contributions from innate immune activation in the brain and spinal cord. Some of these advanced research imaging methods for visualization of chronic inflammation are practical for relatively routine clinical applications. Observations using these techniques suggest ways of stratifying patients with MS to improve their care. The imaging methods also provide new tools to support the development of therapies for chronic inflammation in MS.
Bai W, Chen C, Tarroni G, et al., 2019, Self-supervised learning for cardiac MR image segmentation by anatomicalposition prediction, International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regression tasks. However, successfully learning these features requires a large amount of manuallyannotated data, which is expensive to acquire and limited by the availableresources of expert image analysts. Therefore, unsupervised, weakly-supervised and self-supervised feature learning techniques receive a lot of attention, which aim to utilise the vast amount of available data, while at the same time avoid or substantially reduce the effort of manual annotation. In this paper, we propose a novel way for training a cardiac MR image segmentation network, in which features are learnt in a self-supervised manner by predicting anatomical positions. The anatomical positions serve as a supervisory signal and do not require extra manual annotation. We demonstrate that this seemingly simple task provides a strong signal for feature learning and with self-supervised learning, we achieve a high segmentation accuracy that is better than or comparable to a U-net trained from scratch, especially at a small data setting. When only five annotated subjects are available, the proposed method improves the mean Dice metric from 0.811 to 0.852 for short-axis image segmentation, compared to the baseline U-net.
Venkataraman A, Mansur A, Lewis Y, et al., 2019, Evaluation of mitochondrial and synaptic function in Alzheimer’s disease (AD): a [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J PET study, Journal of Cerebral Blood Flow and Metabolism, Vol: 39, Pages: 121-122, ISSN: 1559-7016
ObjectivesMitochondrial deficits leading to synaptic dysfunction have been hypothesised in the pathophysiology of neurodegenerative disease, with Aβ/tau impairing mitochondrial function in AD. To date a combined evaluation of human mitochondrial and synaptic function has not been performed directly in vivo. We describe the pilot results of MINDMAPS-AD, a study within the MINDMAPS1 programme aiming to evaluate mitochondrial and synaptic function in the brain of patients with MCI/AD. MINDMAPS-AD uses the novel radioligands [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J, to compare the regional density of mitochondrial complex I (MC1), the sigma 1 receptor (s1R) and synaptic vesicular protein 2A (SV2A) respectively.MethodsSix participants with a range of AD related pathologies, EMCI (n = 2), LMCI (n = 2), and AD (n = 2), were enrolled into the study. Participants fulfilled NIA-AA criteria and were amyloid-beta +ve confirmed by [18F]Florbetaben PET. All participants underwent three PET scans with [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J. Arterial blood samples were collected and a metabolite corrected arterial plasma input function was estimated to derive regional volumes of distribution (VT). These data were compared to six age/sex matched cognitively normal (CN) healthy subjects recruited for ongoing studies within the MINDMAPS programme. Regions of interest (ROIs) were defined on individual subject MR images using an anatomical atlas and included: frontal cortex, hippocampus, amygdala, anterior cingulate, posterior cingulate, thalamus, temporal cortex, parietal cortex, caudate, putamen, and occipital lobe. Regional target density was evaluated using the VT, as well as VT corrected for the plasma free fraction of the radioligand (fP; VT/fp), and the regional VT ratio versus the VT in the centrum semiovale, a white matter region expected to have low levels of the targets evaluated (DVR). Comparison of regional target density and
Venkataraman AV, Mansur A, Huiban M, et al., 2019, Evaluation of mitochondrial and synaptic function in Alzheimer's disease (AD): a [<SUP>18</SUP>F]BCPP-EF, [<SUP>11</SUP>C]SA4503 and [<SUP>11</SUP>C]UCB-J PET study, 29th International Symposium on Cerebral Blood Flow, Metabolism and Function / 14th International Conference on Quantification of Brain Function with PET (BRAIN and BRAIN Pet), Publisher: SAGE PUBLICATIONS INC, Pages: 121-122, ISSN: 0271-678X
- Author Web Link
- Cite
- Citations: 1
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.