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Loonstra FC, de Ruiter LRJ, Koel-Simmelink MJA, Schoonheim MM, Strijbis EMM, Moraal B, Barkhof F, Uitdehaag BMJ, Teunissen C, Killestein J. Neuroaxonal and Glial Markers in Patients of the Same Age With Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 10:10/2/e200078. [PMID: 36543540 PMCID: PMC9773420 DOI: 10.1212/nxi.0000000000200078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/01/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND AND OBJECTIVES The specificity of novel blood biomarkers for multiple sclerosis (MS)-related neurodegeneration is unclear because neurodegeneration also occurs during normal aging. To understand which aspects of neurodegeneration the serum biomarkers neurofilament light (sNfL), serum glial fibrillary acidic protein (sGFAP), and serum contactin-1 (sCNTN1) reflect, we here explore their cross-sectional association with disability outcome measures and MRI volumes in a unique cohort of people with MS (PwMS) of the same age. METHODS sNfL, sGFAP (both singe-molecule array technology) and sCNTN1 (Luminex) were measured in serum samples of 288 PwMS and 125 healthy controls (HCs) of the Project Y cohort, a population-based cross-sectional study of PwMS born in the Netherlands in 1966 and age-matched HC. RESULTS sNfL (9.83 pg/mL [interquartile range {IQR}: 7.8-12.0]) and sGFAP (63.7 pg/mL [IQR: 48.5-84.5]) were higher in PwMS compared with HC (sNfL: 8.8 pg/mL [IQR: 7.0-10.5]; sGFAP: 51.7 pg/mL [IQR: 40.1-68.3]) (p < 0.001), whereas contactin-1 (7,461.3 pg/mL [IQR: 5,951.8-9,488.6]) did not significantly differ between PwMS compared with HC (7,891.2 pg/mL [IQR: 6,120.0-10,265.8]) (p = 0.068). sNfL and sGFAP levels were 1.2-fold higher in secondary progressive patients (SPMS) compared with relapsing remitting patients (p = 0.009 and p = 0.043). Stratified by MS subtype, no relations were seen for CNTN1, whereas sNfL and sGFAP correlated with the Expanded Disability Status Scale (ρ = 0.43 and ρ = 0.39), Nine-Hole Peg Test, Timed 25-Foot Walk Test, and Symbol Digit Modalities Test (average ρ = 0.38) only in patients with SPMS. Parallel to these clinical findings, correlations were only found for sNfL and sGFAP with MRI volumes. The strongest correlations were observed between sNfL and thalamic volume (ρ = -0.52) and between sGFAP with deep gray matter volume (ρ = - 0.56) in primary progressive patients. DISCUSSION In our cohort of patients of the same age, we report consistent correlations of sNfL and sGFAP with a range of metrics, especially in progressive MS, whereas contactin-1 was not related to clinical or MRI measures. This demonstrates the potential of sNfL and sGFAP as complementary biomarkers of neurodegeneration, reflected by disability, in progressive MS.
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Affiliation(s)
- Floor C Loonstra
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom.
| | - Lodewijk R J de Ruiter
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Marleen J A Koel-Simmelink
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Menno M Schoonheim
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Eva M M Strijbis
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Bastiaan Moraal
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Frederik Barkhof
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Bernard M J Uitdehaag
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Charlotte Teunissen
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
| | - Joep Killestein
- From the MS Center Amsterdam (F.C.L., L.R.J.R., E.M.M.S., B.M.J.U., J.K.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; Neurochemistry Laboratory (M.J.A.K.-S., C.T.), Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; MS Center Amsterdam (B.M., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, The Netherlands; andQueen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom
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Colato E, Stutters J, Tur C, Narayanan S, Arnold DL, Gandini Wheeler-Kingshott CAM, Barkhof F, Ciccarelli O, Chard DT, Eshaghi A. Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes. J Neurol Neurosurg Psychiatry 2021; 92:995-1006. [PMID: 33879535 PMCID: PMC8372398 DOI: 10.1136/jnnp-2020-325610] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 03/18/2021] [Accepted: 03/20/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVE In multiple sclerosis (MS), MRI measures at the whole brain or regional level are only modestly associated with disability, while network-based measures are emerging as promising prognostic markers. We sought to demonstrate whether data-driven patterns of covarying regional grey matter (GM) volumes predict future disability in secondary progressive MS (SPMS). METHODS We used cross-sectional structural MRI, and baseline and longitudinal data of Expanded Disability Status Scale, Nine-Hole Peg Test (9HPT) and Symbol Digit Modalities Test (SDMT), from a clinical trial in 988 people with SPMS. We processed T1-weighted scans to obtain GM probability maps and applied spatial independent component analysis (ICA). We repeated ICA on 400 healthy controls. We used survival models to determine whether baseline patterns of covarying GM volume measures predict cognitive and motor worsening. RESULTS We identified 15 patterns of regionally covarying GM features. Compared with whole brain GM, deep GM and lesion volumes, some ICA components correlated more closely with clinical outcomes. A mainly basal ganglia component had the highest correlations at baseline with the SDMT and was associated with cognitive worsening (HR=1.29, 95% CI 1.09 to 1.52, p<0.005). Two ICA components were associated with 9HPT worsening (HR=1.30, 95% CI 1.06 to 1.60, p<0.01 and HR=1.21, 95% CI 1.01 to 1.45, p<0.05). ICA measures could better predict SDMT and 9HPT worsening (C-index=0.69-0.71) compared with models including only whole and regional MRI measures (C-index=0.65-0.69, p value for all comparison <0.05). CONCLUSIONS The disability progression was better predicted by some of the covarying GM regions patterns, than by single regional or whole-brain measures. ICA, which may represent structural brain networks, can be applied to clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect.
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Affiliation(s)
- Elisa Colato
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Jonathan Stutters
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Carmen Tur
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Douglas L Arnold
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Department of Brain & Behavioural Sciences, University of Pavia, Pavia, Italy.,Brain Connectivity Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.,Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, NL
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Declan T Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre (BRC), London, UK
| | - Arman Eshaghi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.,Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
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Moosavi E, Rafiei A, Yazdani Y, Eslami M, Saeedi M. Association of serum levels and receptor genes BsmI, TaqI and FokI polymorphisms of vitamin D with the severity of multiple sclerosis. J Clin Neurosci 2021; 84:75-81. [PMID: 33485603 DOI: 10.1016/j.jocn.2020.12.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 11/12/2020] [Accepted: 12/06/2020] [Indexed: 11/30/2022]
Abstract
PURPOSE Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease. Vitamin D has a major role in preventing inflammatory disorders. Therefore, any alteration in vitamin D receptor (VDR) might be a genetic risk factor for MS development. This study aimed to evaluate the effect of serum levels and VDR FokI, BsmI, and TaqI gene polymorphisms on the severity of MS. METHODS This case-control study recruited 160 MS patients (71.9% females, mean age of 34.3 ± 8.3 years) and 162 (66.7% females, mean age 35.4 ± 7.9 year) age, sex, and ethnicity matched healthy controls. FokI (rs2228570), BsmI (rs1544410), and TaqI (rs731236) polymorphisms were carried out using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Demographic, clinical parameters, and the levels of vitamin D were compared between groups. RESULTS We found that the frequency of FokI and TaqI polymorphisms significantly differed between the patients and the controls (p = 0.0127 and p = 0.0236, respectively). The MS patients had low levels of vitamin D compared to the controls (p = 0.011). In addition, TaqI T/C polymorphism significantly decreased the levels of vitamin D in the MS patients (p = 0.002). However, there was no significant association between FokI or BsmI SNPs and the levels of vitamin D in MS patients (p > 0.5). CONCLUSION Our results suggest that FokI and TaqI polymorphisms of VDR are associated with MS risk and TaqI polymorphism is associated with Vitamin D levels in MS patients. Meanwhile, no difference was observed between VDR gene polymorphisms and any types of MS.
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Affiliation(s)
- Ensieh Moosavi
- Stem Cell Research Center, Golestan University of Medical Sciences, Gorgan, Iran; Department of Immunology, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, Iran
| | - Alireza Rafiei
- Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran.
| | - Yaghoub Yazdani
- Stem Cell Research Center, Golestan University of Medical Sciences, Gorgan, Iran; Department of Immunology, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, Iran
| | - Mina Eslami
- Department of Immunology, Molecular and Cell Biology Research Center, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Mohsen Saeedi
- Stem Cell Research Center, Golestan University of Medical Sciences, Gorgan, Iran; Department of Immunology, Faculty of Medicine, Golestan University of Medical Sciences, Gorgan, Iran.
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