45 research outputs found
Assessment and optimisation of MRI measures of atrophy as potential markers of disease progression in multiple sclerosis
No full textThere is a need for sensitive measures of disease progression in multiple sclerosis (MS) to
monitor treatment effects and understand disease evolution. MRI measures of brain
atrophy have been proposed for this purpose. This thesis investigates a number of
measurement techniques to assess their relative ability to monitor disease progression in
clinically isolated syndromes (CIS) and early relapsing remitting MS (RRMS).
Presented, is work demonstrating that measurement techniques and MR acquisitions can
be optimised to give small but significant improvements in measurement sensitivity and
precision, which provided greater statistical power. Direct comparison of numerous
techniques demonstrated significant differences between them. Atrophy measurements
from SIENA and the BBSI (registration-based techniques) were significantly more
precise than segmentation and subtraction of brain volumes, although larger percentage
losses were observed in grey matter fraction. Ventricular enlargement (VE) gave similar
statistical power and these techniques were robust and reliable; scan-rescan measurement
error was <0.01% of brain volume for BBSI and SIENA and <0.04ml for VE.
Annual atrophy rates (using SIENA) were -0.78% in RRMS and -0.52% in CIS patients
who progressed to MS, which were significantly greater than the rate observed in controls
(-0.07%). Sample size calculations for future trials of disease-modifying treatments in
RRMS, using brain atrophy as an outcome measure, are described. For SIENA, the BBSI
and VE respectively, an estimated 123, 157 and 140 patients per treatment arm
respectively would be required to show a 30% slowing of atrophy rate over two years. In
CIS subjects brain atrophy rate was a significant prognostic factor, independent of T2
MRI lesions at baseline, for development of MS by five year follow-up. It was also the
most significant MR predictor of disability in RRMS subjects. Cognitive assessment of
RRMS patients at five year follow-up is described, and brain atrophy rate was a
significant predictor of overall cognitive performance, and more specifically, of
performance in tests of memory.
The work in this thesis has identified methods for sensitively measuring progressive brain
atrophy in MS. It has shown that brain atrophy changes in early MS are related to early
clinical evolution, providing complementary information to clinical assessment that could
be utilised to monitor disease progression
A genome-wide association study in multiple system atrophy
No full textOBJECTIVE: To identify genetic variants that play a role in the pathogenesis of multiple system atrophy (MSA), we undertook a genome-wide association study (GWAS). METHODS: We performed a GWAS with >5 million genotyped and imputed single nucleotide polymorphisms (SNPs) in 918 patients with MSA of European ancestry and 3,864 controls. MSA cases were collected from North American and European centers, one third of which were neuropathologically confirmed. RESULTS: We found no significant loci after stringent multiple testing correction. A number of regions emerged as potentially interesting for follow-up at p < 1 × 10(-6), including SNPs in the genes FBXO47, ELOVL7, EDN1, and MAPT. Contrary to previous reports, we found no association of the genes SNCA and COQ2 with MSA. CONCLUSIONS: We present a GWAS in MSA. We have identified several potentially interesting gene loci, including the MAPT locus, whose significance will have to be evaluated in a larger sample set. Common genetic variation in SNCA and COQ2 does not seem to be associated with MSA. In the future, additional samples of well-characterized patients with MSA will need to be collected to perform a larger MSA GWAS, but this initial study forms the basis for these next steps
A genome-wide association study in multiple system atrophy
No full textObjective: To identify genetic variants that play a role in the pathogenesis of multiple system atrophy (MSA), we undertook a genome-wide association study (GWAS). Methods: We performed a GWAS with >5 million genotyped and imputed single nucleotide polymorphisms (SNPs) in 918 patients with MSA of European ancestry and 3,864 controls. MSA cases were collected from North American and European centers, one third of which were neuropathologically confirmed. Results: We found no significant loci after stringent multiple testing correction. A number of regions emerged as potentially interesting for follow-up at p < 1 × 10-6, including SNPs in the genes FBXO47, ELOVL7, EDN1, and MAPT. Contrary to previous reports, we found no association of the genes SNCA and COQ2 with MSA. Conclusions: We present a GWAS in MSA. We have identified several potentially interesting gene loci, including the MAPT locus, whose significance will have to be evaluated in a larger sample set. Common genetic variation in SNCA and COQ2 does not seem to be associated with MSA. In the future, additional samples of well-characterized patients with MSA will need to be collected to perform a larger MSA GWAS, but this initial study forms the basis for these next steps.</p
Short-interval observational data to inform clinical trial design in Huntington's disease.
No full textOBJECTIVES: To evaluate candidate outcomes for disease-modifying trials in Huntington's disease (HD) over 6-month, 9-month and 15-month intervals, across multiple domains. To present guidelines on rapid efficacy readouts for disease-modifying trials. METHODS: 40 controls and 61 patients with HD, recruited from four EU sites, underwent 3 T MRI and standard clinical and cognitive assessments at baseline, 6 and 15 months. Neuroimaging analysis included global and regional change in macrostructure (atrophy and cortical thinning), and microstructure (diffusion metrics). The main outcome was longitudinal effect size (ES) for each outcome. Such ESs can be used to calculate sample-size requirements for clinical trials for hypothesised treatment efficacies. RESULTS: Longitudinal changes in macrostructural neuroimaging measures such as caudate atrophy and ventricular expansion were significantly larger in HD than controls, giving rise to consistently large ES over the 6-month, 9-month and 15-month intervals. Analogous ESs for cortical metrics were smaller with wide CIs. Microstructural (diffusion) neuroimaging metrics ESs were also typically smaller over the shorter intervals, although caudate diffusivity metrics performed strongly over 9 and 15 months. Clinical and cognitive outcomes exhibited small longitudinal ESs, particularly over 6-month and 9-month intervals, with wide CIs, indicating a lack of precision. CONCLUSIONS: To exploit the potential power of specific neuroimaging measures such as caudate atrophy in disease-modifying trials, we propose their use as (1) initial short-term readouts in early phase/proof-of-concept studies over 6 or 9 months, and (2) secondary end points in efficacy studies over longer periods such as 15 months
Using support vector machines with multiple indices of diffusion for automated classification of mild cognitive impairment
No full textFew studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer’s disease where the early identification of subjects with MCI is critical
The role of mitochondrial DNA in the tumor biology of glioblastoma multiforme and multiple myeloma
No full textCancer cells preferentially metabolise glucose via aerobic glycolysis (the Warburg effect), which is less energy efficient in teens of ATP production compared to oxidative phosphorylation (OXPHOS). Mitochondrial DNA (mtDNA) encodes proteins of the electron transfer chain and is crucial for functional OXPHOS. MtDNA exists as multiple copies in cells and, often in cancer, there is co-existence of mutant and wild-type mtDNA. There is evidence for mitochondria to contribute towards the tumor biology of multiple myeloma (MM) and glioblastoma multiforme (GBM). The mtDNA from both these cancer types were explored to determine its role in tumor biology.
Sequencing of MM cells and tumor samples using the Ion Torrent next generation sequencer identified Cytochrome C Oxidase and ATP 6 to contain critical variants that are capable of disrupting protein function. Gene expression analysis determined that glycolysis is essential to maintaining MM cell proliferation. Without glycolysis, there was up-regulation in the expression of tumor survival genes, which was only effective in MM cells that had sufficient mtDNA copy numbers above the mtDNA set point.
Sequencing of GBM cell lines, tumor and normal patient samples suggested that there is a predisposition of GBM tumors to acquire a set of GBM-specific mtDNA variants during tumor development. Conserved mtDNA regions, such as Cytochrome C Oxidase I, tend to be least susceptible to mutations. The presence of variants in these conserved regions carry more detrimental effects at the protein-level than at other mtDNA regions. Differentiation of GBM cells decreased the tumor phenotype, as assessed by gene expression analysis.
Altogether, this thesis provides support for the importance of mtDNA in tumor biology. The implications are that the variants identified could be used to screen MM and GBM tumors in a clinical diagnostic lab for the treatment of both these cancer types
Measuring disability in neurological rehabilitation : psychometric evaluation of two outcome measures.
No full textObjectives: To evaluate comprehensively the psychometric properties of
the Functional Independence Measure (FIM) and the Functional
Independence Measure + Functional Assessment Measure (FIM+FAM), and
to compare their performance in stroke and multiple sclerosis (MS) patients
and with the Barthel Index. To evaluate the conceptual models of both
instruments using item analysis, and determine the feasibility of developing
a short-form measure. To compare five methods of evaluating
responsiveness.
Design: Psychometric study.
Subjects: 209 inpatients with a variety of neurological disorders recruited
from three neurorehabilitation units in Southeast England.
Method: Standard methods were used to evaluate the acceptability,
reliability, validity, and responsiveness of the FIM and FIM+FAM. Detailed
item analyses were performed including internal consistency,
intercorrelations between scales and subscales, item convergent and discriminant validity, and principal components analysis. Item reduction
techniques were used to develop a short-form FIM. Five methods were
used to evaluate responsiveness: t - statistics, relative efficiency, effect
size, standardised response mean, and the responsiveness index.
Results: The FIM and FIM+FAM are acceptable, reliable, valid, and responsive measures of disability in neurorehabilitation. However, they
demonstrate no psychometric advantage over the Barthel Index, show item
redundancy, limited item discriminant validity, and inadequate support for
hypothesised subscales. An 8-item short-form FIM is developed that shows
similar psychometric performance to the 18-item FIM and 30-item FIM+FAM.
Five methods of evaluating responsiveness rank order scales similarly, but
generate numerical estimates of different magnitude.
Conclusions: Results demonstrate the need for a more systematic
and rigorous approach to the development and psychometric evaluation of
instruments before their introduction into practice to ensure the accurate
measurement of patient-oriented outcomes in health care. This approach
includes the development of appropriate conceptual and measurement
models, the application of standard item analysis and item reduction
techniques during questionnaire development, and comprehensive
evaluation of the recommended full range of psychometric properties
Identification and evaluation of biomarkers for Huntington’s disease
No full textHuntington’s disease (HD) is a devastating, incurable inherited neurodegenerative disorder that
commonly affects adults in mid-life. Despite encouraging results from in vitro and animal trials,
disease-modifying therapeutic trials in HD are limited by a lack of tools to track disease progression.
HD is clinically heterogeneous, and current clinical rating scales lack sensitivity and specificity,
particularly over relatively short time periods. Improvements in the precision of objective
measurement of disease progression in HD could lead to state markers (biomarkers) better able to
predict onset, detect progression and measure the effects of therapeutic intervention. Biomarkers
capable of detecting disease-related changes in premanifest gene carriers will be essential for
clinical trials of treatments to delay onset. Imaging, clinical and cognitive assessment as well as
laboratory markers have all been proposed as biomarkers, but few measures have been quantified
over short time intervals or shown to be predictive of clinical change over longer periods.
A robust panel of biomarkers from a number of modalities will be necessary to progress to
interventional clinical trials of disease-modifying therapies in HD, using biomarkers to measure the
success or failure of an intervention. Such cross-validation requires simultaneous multimodal
biomarker evaluation within a suitable cohort of subjects studied longitudinally.
This thesis describes a multi-modal approach to the discovery and evaluation of potential
biomarkers for Huntington's disease in a large cohort of human volunteers. After reviewing the
relevant features of Huntington's disease and current state of biomarker research in Huntington's
disease, several approaches to, and outcomes from, biomarker discovery and evaluation are
described, including proteomic profiling, targeted ELISA, multiplex inflammatory profiling and
measurement of whole-brain atrophy by longitudinal magnetic resonance imaging. The thesis draws
together these different approaches and summarises the contributions to both biomarker research
and our understanding of the neurobiology of HD that the work has generated
Noninvasive molecular imaging of neuroinflammation
No full textInflammation is a highly dynamic and complex adaptive process to preserve and restore tissue homeostasis. Originally viewed as an immune-privileged organ, the central nervous system (CNS) is now recognized to have a constant interplay with the innate and the adaptive immune systems, where resident microglia and infiltrating immune cells from the periphery have important roles. Common diseases of the CNS, such as stroke, multiple sclerosis (MS), and neurodegeneration, elicit a neuroinflammatory response with the goal to limit the extent of the disease and to support repair and regeneration. However, various disease mechanisms lead to neuroinflammation (NI) contributing to the disease process itself. Molecular imaging is the method of choice to try to decipher key aspects of the dynamic interplay of various inducers, sensors, transducers, and effectors of the orchestrated inflammatory response in vivo in animal models and patients. Here, we review the basic principles of NI with emphasis on microglia and common neurologic disease mechanisms, the molecular targets which are being used and explored for imaging, and molecular imaging of NI in frequent neurologic diseases, such as stroke, MS, neurodegeneration, epilepsy, encephalitis, and gliomas
Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials
No full textSupplementary data is available online at: https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awad105/7091433#supplementary-data .The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based end point selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA) and related disorders, to compare candidate clinical trial end points.
In this multicentre UK study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and MRI assessments at baseline, 6 and 12 months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, PSP-subcortical (PSP-parkinsonism and progressive gait freezing subtypes), PSP-cortical (PSP-frontal, PSP-speech and language and PSP-CBS subtypes), MSA-parkinsonism, MSA-cerebellar, CBS with and without evidence of Alzheimer’s disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling and sample sizes for clinical trials of disease-modifying agents, according to group and assessment type.
Two hundred forty-three people were recruited [117 PSP, 68 CBS, 42 MSA and 16 indeterminate; 138 (56.8%) male; age at recruitment 68.7 ± 8.61 years]. One hundred and fifty-nine completed the 6-month assessment (82 PSP, 27 CBS, 40 MSA and 10 indeterminate) and 153 completed the 12-month assessment (80 PSP, 29 CBS, 35 MSA and nine indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N < 100 required for 1-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease-specific.
In conclusion, phenotypic variance within PSP, CBS and MSA is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial end points, from potential functional, cognitive, clinical or neuroimaging measures of disease progression.The Progressive Supranuclear Palsy–Corticobasal Syndrome–Multiple System Atrophy (PROSPECT-M-UK) study is supported by grants for PROSPECT, cerebrospinal fluid biomarker measurements, and PROSPECT magnetic resonance imaging and Sara Koe Fellowship grants from the PSP Association UK, CBD Solutions, the MSA Trust, the Wellcome Trust (103838; 220258); the NIHR Cambridge Biomedical Research Centre and Cambridge Brain Bank (BRC 1215-20014; NIHR203312: The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care); Cambridge Centre for Parkinson-Plus; Medical Research Council (SUAG/092 116768); and the NIHR UCLH Biomedical Research Centre. Queen Square Brain Bank is supported by the Reta Lila Weston Institute for Neurological Studies and the MRC. The fluid biomarker measurements were supported in part by the UK Dementia Research Institute at UCL and a multiuser equipment grant from Wellcome Trust. The Cambridge Brain Bank is part of the Cambridge Human research Tissue Bank funded by the Biomedical Research Council. The Oxford Brain Bank is supported by the MRC, Brains for Dementia Research (Alzheimer’s Society and Alzheimer’s Research UK), and the NIHR Oxford Biomedical Research Centre. In addition, this study was supported by the Medical Research Council (MRC 548211) (Dr Jabbari); the Association of British Neurologists Clinical Research Training Fellowships (Dr Holland, Dr Goh and Dr Chelban); the MSA Trust (Dr Chelban, Dr Goh); Guarantors of Brain (Dr Chelban); CBD Solutions (Dr Revesz, and Dr Morris); the NIHR Oxford Health Clinical Research Facility (Dr Klein); the NIHR Queen Square Biomedical Research Centre based at UCLH (Dr Revesz and Dr Jaunmuktane) a Wallenberg Academy fellowship (Dr Zetterberg); the Monument Trust Discovery Award from Parkinson’s UK (Dr Hu). Dr Bocchetta is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). Dr Bocchetta’s work was also supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. Professor Rohrer is supported by the Miriam Marks Brain Research UK Senior Fellowship and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). Professor Zetterberg is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer's Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C), the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), European Union Joint Program for Neurodegenerative Disorders (JPND2021-00694), and the UK Dementia Research Institute at UCL. Professor Roncaroli’s work is supported by The Manchester Brain Bank, which is part of BDR, jointly funded by Alzheimer’s Society and Alzheimer’s Research UK. For the purpose of open access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission, under a Creative Commons Attribution 4.0 International License
