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Meijboom R, Wiseman SJ, York EN, Bastin ME, Valdés Hernández MDC, Thrippleton MJ, Mollison D, White N, Kampaite A, Ng Kee Kwong K, Rodriguez Gonzalez D, Job D, Weaver C, Kearns PKA, Connick P, Chandran S, Waldman AD. Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland. Wellcome Open Res 2022; 7:94. [PMID: 36865371 PMCID: PMC9971644 DOI: 10.12688/wellcomeopenres.17731.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2022] [Indexed: 12/22/2022] Open
Abstract
Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Stewart J. Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Maria del C. Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Koy Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - David Rodriguez Gonzalez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Christine Weaver
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Patrick K. A. Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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Kharati M, Foroutanparsa S, Rabiee M, Salarian R, Rabiee N, Rabiee G. Early Diagnosis of Multiple Sclerosis Based on Optical and Electrochemical Biosensors: Comprehensive Perspective. CURR ANAL CHEM 2020. [DOI: 10.2174/1573411014666180829111004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background:
Multiple Sclerosis (MS) involves an immune-mediated response in which
body’s immune system destructs the protective sheath (myelin). Part of the known MS biomarkers are
discovered in cerebrospinal fluid like oligoclonal lgG (OCGB), and also in blood like myelin Oligodendrocyte
Glycoprotein (MOG). The conventional MS diagnostic methods often fail to detect the
disease in early stages such as Clinically Isolated Syndrome (CIS), which considered as a concerning
issue since CIS highlighted as a prognostic factor of MS development in most cases.
Methods:
MS diagnostic techniques include Magnetic Resonance Imaging (MRI) of the brain and spinal
cord, lumbar puncture (or spinal tap) that evaluate cerebrospinal fluid, evoked potential testing revealing
abnormalities in the brain and spinal cord. These conventional diagnostic methods have some
negative points such as extensive processing time as well as restriction in the quantity of samples that
can be analyzed concurrently. Scientists have focused on developing the detection methods especially
early detection which belongs to ultra-sensitive, non-invasive and needed for the Point of Care (POC)
diagnosis because the situation was complicated by false positive or negative results.
Results:
As a result, biosensors are utilized and investigated since they could be ultra-sensitive to specific
compounds, cost effective devices, body-friendly and easy to implement. In addition, it has been
proved that the biosensors on physiological fluids (blood, serum, urine, saliva, milk etc.) have quick
response in a non-invasive rout. In general form, a biosensor system for diagnosis and early detection
process usually involves; biomarker (target molecule), bio receptor (recognition element) and compatible
bio transducer.
Conclusion:
Studies underlined that early treatment of patients with high possibility of MS can be advantageous
by postponing further abnormalities on MRI and subsequent attacks.
:
This Review highlights variable disease diagnosis approaches such as Surface Plasmon Resonance
(SPR), electrochemical biosensors, Microarrays and microbeads based Microarrays, which are considered
as promising methods for detection and early detection of MS.
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Affiliation(s)
- Maryam Kharati
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Sanam Foroutanparsa
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Mohammad Rabiee
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Reza Salarian
- Biomedical Engineering Department, Maziar University, Noor, Royan, Iran
| | - Navid Rabiee
- Department of Chemistry, Shahid Beheshti University, Tehran, Iran
| | - Ghazal Rabiee
- Department of Chemistry, Shahid Beheshti University, Tehran, Iran
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Abdel Naseer M, Fathi S, Roshdy NK, Labib DM, Khalil DH, Ibrahim W, Magdy R. Cognitive and physical disability in Egyptian patients with multiple sclerosis: genetic and optical coherence tomography study. Neurol Res 2019; 41:644-651. [PMID: 31025605 DOI: 10.1080/01616412.2019.1609203] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Objectives: The aim of this study was to explore the relationship between cognitive dysfunction, neurodegeneration, and genetic factors among multiple sclerosis (MS) patients. Methods: Fifty patients of definite MS were included. Physical disability was assessed by expanded disability status scale (EDSS). Cognitive functions were assessed by using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). For each eye, optical coherence tomography (OCT) was used to track thickness of retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC), respecting the previous history of optic neuritis (ON). All patients were genotyped for glutamate N-methyl-D-aspartate receptors (NMDARs). Results: A statistically significant negative correlation was found between scores of EDSS and each of neuropsychological tests scores and thickness of both RNFL and GCC. The predictor for progressive disability assessed by EDSS was Symbol Digit Modalities Test (SDMT) (P = 0.021), that is dependent on the educational level of the patients (P = 0.016). A statistically significant positive correlation was found between scores of all neuropsychological tests and the thickness of both RNFL and GCC. Eighty-three percent of MS patients with CC genotype reported previous attacks of ON with significant thinning in RNFL and GCC despite their higher cognitive performance in comparison to other genotypes. Discussion: Deficit in information processing speed measured by SDMT is a predictor of early progressive disability in MS patients. Thinning of RNFL and GCC is a potential biomarker for cognitive and physical disability in MS. The CC genotype of glutamate NMDAR gene has a divergent effect on visual and cognitive functions.
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Affiliation(s)
- Maged Abdel Naseer
- a Department of Neurology, Faculty of Medicine , Cairo University , Cairo , Egypt
| | - Shereen Fathi
- a Department of Neurology, Faculty of Medicine , Cairo University , Cairo , Egypt
| | - Nagwa K Roshdy
- b Department of Medical Biochemistry and Molecular Biology , Future University , Khartoum , Egypt
| | - Dalia M Labib
- a Department of Neurology, Faculty of Medicine , Cairo University , Cairo , Egypt
| | - Dalia H Khalil
- c Department of Ophthalmology, Faculty of Medicine , Cairo University , Cairo , Egypt
| | - Walaa Ibrahim
- d Department of Medical Biochemistry, Faculty of Medicine , Cairo University , Cairo , Egypt
| | - Rehab Magdy
- a Department of Neurology, Faculty of Medicine , Cairo University , Cairo , Egypt
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