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Jacobs BM, Tank P, Bestwick JP, Noyce AJ, Marshall CR, Mathur R, Giovannoni G, Dobson R. Modifiable risk factors for multiple sclerosis have consistent directions of effect across diverse ethnic backgrounds: a nested case-control study in an English population-based cohort. J Neurol 2024; 271:241-253. [PMID: 37676298 PMCID: PMC10769990 DOI: 10.1007/s00415-023-11971-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND Multiple sclerosis is a leading cause of non-traumatic neurological disability among young adults worldwide. Prior studies have identified modifiable risk factors for multiple sclerosis in cohorts of White ethnicity, such as infectious mononucleosis, smoking, and obesity during adolescence/early adulthood. It is unknown whether modifiable exposures for multiple sclerosis have a consistent impact on risk across ethnic groups. AIM To determine whether modifiable risk factors for multiple sclerosis have similar effects across diverse ethnic backgrounds. METHODS We conducted a nested case-control study using data from the UK Clinical Practice Research Datalink. Multiple sclerosis cases diagnosed from 2001 until 2022 were identified from electronic healthcare records and matched to unaffected controls based on year of birth. We used stratified logistic regression models and formal statistical interaction tests to determine whether the effect of modifiable risk factors for multiple sclerosis differed by ethnicity. RESULTS We included 9662 multiple sclerosis cases and 118,914 age-matched controls. The cohort was ethnically diverse (MS: 277 South Asian [2.9%], 251 Black [2.6%]; Controls: 5043 South Asian [5.7%], 4019 Black [4.5%]). The age at MS diagnosis was earlier in the Black (40.5 [SD 10.9]) and Asian (37.2 [SD 10.0]) groups compared with White cohort (46.1 [SD 12.2]). There was a female predominance in all ethnic groups; however, the relative proportion of males was higher in the South Asian population (proportion of women 60.3% vs 71% [White] and 75.7% [Black]). Established modifiable risk factors for multiple sclerosis-smoking, obesity, infectious mononucleosis, low vitamin D, and head injury-were consistently associated with multiple sclerosis in the Black and South Asian cohorts. The magnitude and direction of these effects were broadly similar across all ethnic groups examined. There was no evidence of statistical interaction between ethnicity and any tested exposure, and no evidence to suggest that differences in area-level deprivation modifies these risk factor-disease associations. These findings were robust to a range of sensitivity analyses. CONCLUSIONS AND RELEVANCE Established modifiable risk factors for multiple sclerosis are applicable across diverse ethnic backgrounds. Efforts to reduce the population incidence of multiple sclerosis by tackling these risk factors need to be inclusive of people from diverse ethnicities.
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Affiliation(s)
- Benjamin M Jacobs
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
- Department of Neurology, Royal London Hospital, London, UK
| | - Pooja Tank
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
| | - Jonathan P Bestwick
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
| | - Alastair J Noyce
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
- Department of Neurology, Royal London Hospital, London, UK
| | - Charles R Marshall
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
- Department of Neurology, Royal London Hospital, London, UK
| | - Rohini Mathur
- Centre for Primary Care, Wolfson Institute of Population Health, Queen Mary University London, London, UK
| | - Gavin Giovannoni
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK
- Department of Neurology, Royal London Hospital, London, UK
- Blizard Institute, Queen Mary University London, London, UK
| | - Ruth Dobson
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, UK.
- Department of Neurology, Royal London Hospital, London, UK.
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Sahi N, Haider L, Chung K, Prados Carrasco F, Kanber B, Samson R, Thompson AJ, Gandini Wheeler-Kingshott CAM, Trip SA, Brownlee W, Ciccarelli O, Barkhof F, Tur C, Houlden H, Chard D. Genetic influences on disease course and severity, 30 years after a clinically isolated syndrome. Brain Commun 2023; 5:fcad255. [PMID: 37841069 PMCID: PMC10576246 DOI: 10.1093/braincomms/fcad255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/31/2023] [Accepted: 10/02/2023] [Indexed: 10/17/2023] Open
Abstract
Multiple sclerosis risk has a well-established polygenic component, yet the genetic contribution to disease course and severity remains unclear and difficult to examine. Accurately measuring disease progression requires long-term study of clinical and radiological outcomes with sufficient follow-up duration to confidently confirm disability accrual and multiple sclerosis phenotypes. In this retrospective study, we explore genetic influences on long-term disease course and severity; in a unique cohort of clinically isolated syndrome patients with homogenous 30-year disease duration, deep clinical phenotyping and advanced MRI metrics. Sixty-one clinically isolated syndrome patients [41 female (67%): 20 male (33%)] underwent clinical and MRI assessment at baseline, 1-, 5-, 10-, 14-, 20- and 30-year follow-up (mean age ± standard deviation: 60.9 ± 6.5 years). After 30 years, 29 patients developed relapsing-remitting multiple sclerosis, 15 developed secondary progressive multiple sclerosis and 17 still had a clinically isolated syndrome. Twenty-seven genes were investigated for associations with clinical outcomes [including disease course and Expanded Disability Status Scale (EDSS)] and brain MRI (including white matter lesions, cortical lesions, and brain tissue volumes) at the 30-year follow-up. Genetic associations with changes in EDSS, relapses, white matter lesions and brain atrophy (third ventricular and medullary measurements) over 30 years were assessed using mixed-effects models. HLA-DRB1*1501-positive (n = 26) patients showed faster white matter lesion accrual [+1.96 lesions/year (0.64-3.29), P = 3.8 × 10-3], greater 30-year white matter lesion volumes [+11.60 ml, (5.49-18.29), P = 1.27 × 10-3] and higher annualized relapse rates [+0.06 relapses/year (0.005-0.11), P = 0.031] compared with HLA-DRB1*1501-negative patients (n = 35). PVRL2-positive patients (n = 41) had more cortical lesions (+0.83 [0.08-1.66], P = 0.042), faster EDSS worsening [+0.06 points/year (0.02-0.11), P = 0.010], greater 30-year EDSS [+1.72 (0.49-2.93), P = 0.013; multiple sclerosis cases: +2.60 (1.30-3.87), P = 2.02 × 10-3], and greater risk of secondary progressive multiple sclerosis [odds ratio (OR) = 12.25 (1.15-23.10), P = 0.031] than PVRL2-negative patients (n = 18). In contrast, IRX1-positive (n = 30) patients had preserved 30-year grey matter fraction [+0.76% (0.28-1.29), P = 8.4 × 10-3], lower risk of cortical lesions [OR = 0.22 (0.05-0.99), P = 0.049] and lower 30-year EDSS [-1.35 (-0.87,-3.44), P = 0.026; multiple sclerosis cases: -2.12 (-0.87, -3.44), P = 5.02 × 10-3] than IRX1-negative patients (n = 30). In multiple sclerosis cases, IRX1-positive patients also had slower EDSS worsening [-0.07 points/year (-0.01,-0.13), P = 0.015] and lower risk of secondary progressive multiple sclerosis [OR = 0.19 (0.04-0.92), P = 0.042]. These exploratory findings support diverse genetic influences on pathological mechanisms associated with multiple sclerosis disease course. HLA-DRB1*1501 influenced white matter inflammation and relapses, while IRX1 (protective) and PVRL2 (adverse) were associated with grey matter pathology (cortical lesions and atrophy), long-term disability worsening and the risk of developing secondary progressive multiple sclerosis.
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Affiliation(s)
- Nitin Sahi
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Lukas Haider
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, 1090 Vienna, Austria
| | - Karen Chung
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Ferran Prados Carrasco
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
- Universitat Oberta de Catalunya, 08018 Barcelona, Spain
| | - Baris Kanber
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
- Department of Clinical and Experimental Epilepsy, University College London, London WC1N 3BG, UK
| | - Rebecca Samson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Alan J Thompson
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Brain and Behavioural Sciences, University of Pavia, 27100 Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, 27100 Pavia, Italy
| | - S Anand Trip
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Wallace Brownlee
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Institute for Health and Care Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London W1T 7DN, UK
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Institute for Health and Care Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London W1T 7DN, UK
| | - Frederik Barkhof
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
- National Institute for Health and Care Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London W1T 7DN, UK
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, 1081 HV Amsterdam, The Netherlands
| | - Carmen Tur
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- MS Centre of Catalonia (Cemcat), Vall d'Hebron Institute of Research, Vall d'Hebron Barcelona Hospital Campus, 08035 Barcelona, Spain
| | - Henry Houlden
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen’s Square House, Queen’s Square, London, WC1N 3BG, UK
| | - Declan Chard
- NMR Research Unit, Queen Square Multiple Sclerosis Centre, University College London Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Institute for Health and Care Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London W1T 7DN, UK
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Fuh-Ngwa V, Charlesworth JC, Zhou Y, van der Mei I, Melton PE, Broadley SA, Ponsonby AL, Simpson-Yap S, Lechner-Scott J, Taylor BV. The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study. Sci Rep 2023; 13:11584. [PMID: 37463930 DOI: 10.1038/s41598-023-38415-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023] Open
Abstract
The indirect contribution of multiple sclerosis (MS) relapses to disability worsening outcomes, and vice-versa, remains unclear. Disease modifying therapies (DMTs) are potential modulators of this association. Understanding how these endo-phenotypes interact may provide insights into disease pathogenesis and treatment practice in relapse-onset MS (ROMS). Utilising a unique, prospectively collected clinical data from a longitudinal cohort of 279 first demyelinating event cases followed for up to 15 years post-onset, we examined indirect associations between relapses and treatment and the risk of disability worsening, and vice-versa. Indirect association parameters were estimated using joint models for longitudinal and survival data. Early relapses within 2.5 years of MS onset predicted early disability worsening outcomes (HR = 3.45, C.I 2.29-3.61) per relapse, but did not contribute to long-term disability worsening thereinafter (HR = 0.21, C.I 0.15-0.28). Conversely, disability worsening outcomes significantly contributed to relapse risk each year (HR = 2.96, C.I 2.91-3.02), and persisted over time (HR = 3.34, C.I 2.90-3.86), regardless of DMT treatments. The duration of DMTs significantly reduced the hazards of relapses (1st-line DMTs: HR = 0.68, C.I 0.58-0.79; 3rd-line DMTs: HR = 0.37, C.I 0.32-0.44) and disability worsening events (1st-line DMTs: HR = 0.74, C.I 0.69-0.79; 3rd-line DMTs: HR = 0.90, C.I 0.85-0.95), respectively. Results from time-dynamic survival probabilities further revealed individuals having higher risk of future relapses and disability worsening outcomes, respectively. The study provided evidence that in ROMS, relapses accrued within 2.5 years of MS onset are strong indicators of disability worsening outcomes, but late relapses accrued 2.5 years post onset are not overt risk factors for further disability worsening. In contrast, disability worsening outcomes are strong positive predictors of current and subsequent relapse risk. Long-term DMT use and older age strongly influence the individual outcomes and their associations.
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Affiliation(s)
- Valery Fuh-Ngwa
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia.
| | - Jac C Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Yuan Zhou
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Ingrid van der Mei
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Phillip E Melton
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - Simon A Broadley
- Menzies Health Institute Queensland and School of Medicine, Griffith University, Gold Coast, QLD, 4222, Australia
| | - Anne-Louise Ponsonby
- Florey Institute for Neuroscience and Mental Health, Parkville, VIC, 3052, Australia
| | - Steve Simpson-Yap
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
- Neuroepidemiology Unit, Center for Epidemiology and Biostatistics, The University of Melbourne School of Population & Global Health, Melbourne, VIC, 3053, Australia
| | - Jeannette Lechner-Scott
- School of Medicine and Public Health New Lambton, Hunter New England Health, New Lambton Heights, NSW, Australia
- Department of Neurology, The University of Newcastle Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Bruce V Taylor
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia.
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4
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Brownlee WJ, Tur C, Manole A, Eshaghi A, Prados F, Miszkiel KA, Wheeler-Kingshott CAG, Houlden H, Ciccarelli O. HLA-DRB1*1501 influences long-term disability progression and tissue damage on MRI in relapse-onset multiple sclerosis. Mult Scler 2023; 29:333-342. [PMID: 36398585 DOI: 10.1177/13524585221130941] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND Whether genetic factors influence the long-term course of multiple sclerosis (MS) is unresolved. OBJECTIVE To determine the influence of HLA-DRB1*1501 on long-term disease course in a homogeneous cohort of clinically isolated syndrome (CIS) patients. METHODS One hundred seven patients underwent clinical and MRI assessment at the time of CIS and after 1, 3, 5 and 15 years. HLA-DRB1*1501 status was determined using Sanger sequencing and tagging of the rs3135388 polymorphism. Linear/Poisson mixed-effects models were used to investigate rates of change in EDSS and MRI measures based on HLA-DRB1*1501 status. RESULTS HLA-DRB1*1501 -positive (n = 52) patients showed a faster rate of disability worsening compared with the HLA-DRB1*1501 -negative (n = 55) patients (annualised change in EDSS 0.14/year vs. 0.08/year, p < 0.025), and a greater annualised change in T2 lesion volume (adjusted difference 0.45 mL/year, p < 0.025), a higher number of gadolinium-enhancing lesions, and a faster rate of brain (adjusted difference -0.12%/year, p < 0.05) and spinal cord atrophy (adjusted difference -0.22 mm2/year, p < 0.05). INTERPRETATION These findings provide evidence that the HLA-DRB1*1501 allele plays a role in MS severity, as measured by long-term disability worsening and a greater extent of inflammatory disease activity and tissue loss. HLA-DRB1*1501 may provide useful information when considering prognosis and treatment decisions in early relapse-onset MS.
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Affiliation(s)
- Wallace J Brownlee
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Carmen Tur
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK/UK e-Health Center, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Andreea Manole
- Salk Institute for Biological Studies, San Diego, CA, USA
| | - Arman Eshaghi
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK/Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Katherine A Miszkiel
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Claudia Am Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK/Brain Connectivity Center, C. Mondino National Neurological Institute, Pavia, Italy Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Henry Houlden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK/NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, London, UK/NIHR University College London Hospitals Biomedical Research Centre, London
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5
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Moradi N, Sharmin S, Malpas CB, Shaygannejad V, Terzi M, Boz C, Yamout B, Khoury SJ, Turkoglu R, Karabudak R, Shalaby N, Soysal A, Altıntaş A, Inshasi J, Al-Harbi T, Alroughani R, Kalincik T. External validation of a clinical prediction model in multiple sclerosis. Mult Scler 2023; 29:261-269. [PMID: 36448727 DOI: 10.1177/13524585221136036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
BACKGROUND Timely initiation of disease modifying therapy is crucial for managing multiple sclerosis (MS). OBJECTIVE We aimed to validate a previously published predictive model of individual treatment response using a non-overlapping cohort from the Middle East. METHODS We interrogated the MSBase registry for patients who were not included in the initial model development. These patients had relapsing MS or clinically isolated syndrome, a recorded date of disease onset, disability and dates of disease modifying therapy, with sufficient follow-up pre- and post-baseline. Baseline was the visit at which a new disease modifying therapy was initiated, and which served as the start of the predicted period. The original models were used to translate clinical information into three principal components and to predict probability of relapses, disability worsening or improvement, conversion to secondary progressive MS and treatment discontinuation as well as changes in the area under disability-time curve (ΔAUC). Prediction accuracy was assessed using the criteria published previously. RESULTS The models performed well for predicting the risk of disability worsening and improvement (accuracy: 81%-96%) and performed moderately well for predicting the risk of relapses (accuracy: 73%-91%). The predictions for ΔAUC and risk of treatment discontinuation were suboptimal (accuracy < 44%). Accuracy for predicting the risk of conversion to secondary progressive MS ranged from 50% to 98%. CONCLUSION The previously published models are generalisable to patients with a broad range of baseline characteristics in different geographic regions.
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Affiliation(s)
- Nahid Moradi
- Clinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Parkville, VIC, Australia
| | - Sifat Sharmin
- Clinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Parkville, VIC, Australia
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Parkville, VIC, Australia/MS Centre, Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | | | - Murat Terzi
- Faculty of Medicine, Ondokuz Mayis University, Samsun, Turkey
| | - Cavit Boz
- KTU Faculty of Medicine, Farabi Hospital, Trabzon, Turkey
| | - Bassem Yamout
- Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon
| | - Samia J Khoury
- Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon
| | - Recai Turkoglu
- Haydarpasa Numune Training and Research Hospital, Istanbul, Turkey
| | - Rana Karabudak
- Department of Neurology, Faculty of Medicine, Hacettepe University, Ankara, Turkey
| | - Nevin Shalaby
- Department of Neurology, Kasr Al-Ainy MS Research Unit (KAMSU), Cairo University, Cairo, Egypt
| | - Aysun Soysal
- Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey
| | - Ayşe Altıntaş
- Department of Neurology, School of Medicine, Koç University, Istanbul, Turkey
| | | | - Talal Al-Harbi
- Department of Neurology, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - Raed Alroughani
- Division of Neurology, Department of Medicine, Amiri Hospital, Sharq, Kuwait
| | - Tomas Kalincik
- Clinical Outcomes Research Unit (CORe), Department of Medicine, University of Melbourne, Parkville, VIC, Australia/MS Centre, Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
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Jacobs BM, Peter M, Giovannoni G, Noyce AJ, Morris HR, Dobson R. Towards a global view of multiple sclerosis genetics. Nat Rev Neurol 2022; 18:613-623. [PMID: 36075979 DOI: 10.1038/s41582-022-00704-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/27/2022] [Indexed: 11/09/2022]
Abstract
Multiple sclerosis (MS) is a neuroimmunological disorder of the CNS with a strong heritable component. The genetic architecture of MS susceptibility is well understood in populations of European ancestry. However, the extent to which this architecture explains MS susceptibility in populations of non-European ancestry remains unclear. In this Perspective article, we outline the scientific arguments for studying MS genetics in ancestrally diverse populations. We argue that this approach is likely to yield insights that could benefit individuals with MS from all ancestral groups. We explore the logistical and theoretical challenges that have held back this field to date and conclude that, despite these challenges, inclusion of participants of non-European ancestry in MS genetics studies will ultimately be of value to all patients with MS worldwide.
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Affiliation(s)
- Benjamin Meir Jacobs
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University London, London, UK. .,Department of Neurology, Royal London Hospital, London, UK.
| | - Michelle Peter
- NHS North Thames Genomic Laboratory Hub, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Gavin Giovannoni
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University London, London, UK.,Department of Neurology, Royal London Hospital, London, UK.,Blizard Institute, Queen Mary University London, London, UK
| | - Alastair J Noyce
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University London, London, UK.,Department of Neurology, Royal London Hospital, London, UK.,Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Huw R Morris
- Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ruth Dobson
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University London, London, UK.,Department of Neurology, Royal London Hospital, London, UK
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7
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Zhang Y, Zhou Y, van der Mei IAF, Simpson S, Ponsonby AL, Lucas RM, Tettey P, Charlesworth J, Kostner K, Taylor BV. Lipid-related genetic polymorphisms significantly modulate the association between lipids and disability progression in multiple sclerosis. J Neurol Neurosurg Psychiatry 2019; 90:636-641. [PMID: 30782980 DOI: 10.1136/jnnp-2018-319870] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 12/14/2018] [Accepted: 12/24/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVE To investigate whether lipid-related or body mass index (BMI)-related common genetic polymorphisms modulate the associations between serum lipid levels, BMI and disability progression in multiple sclerosis (MS). METHODS The association between disability progression (annualised Expanded Disability Status Scale (EDSS) change over 5 years, ΔEDSS) and lipid-related or BMI-related genetic polymorphisms was evaluated in a longitudinal cohort (n=184), diagnosed with MS. We constructed a cumulative genetic risk score (CGRS) of associated polymorphisms (p<0.05) and examined the interactions between the CGRS and lipid levels (measured at baseline) in predicting ΔEDSS. All analyses were conducted using linear regression. RESULTS Five lipid polymorphisms (rs2013208, rs9488822, rs17173637, rs10401969 and rs2277862) and one BMI polymorphism (rs2033529) were nominally associated with ΔEDSS. The constructed lipid CGRS showed a significant, dose-dependent association with ΔEDSS (ptrend=1.4×10-6), such that participants having ≥6 risk alleles progressed 0.38 EDSS points per year faster compared with those having ≤3. This CGRS model explained 16% of the variance in ΔEDSS. We also found significant interactions between the CGRS and lipid levels in modulating ΔEDSS, including high-density lipoprotein (HDL; pinteraction=0.005) and total cholesterol:high-density lipoprotein ratio (TC:HDL; pinteraction=0.030). The combined model (combination of CGRS and the lipid parameter) explained 26% of the disability variance for HDL and 27% for TC:HDL. INTERPRETATION In this prospective cohort study, both lipid levels and lipid-related polymorphisms individually and jointly were associated with significantly increased disability progression in MS. These results indicate that these polymorphisms and tagged genes might be potential points of intervention to moderate disability progression.
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Affiliation(s)
- Yan Zhang
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Yuan Zhou
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Ingrid A F van der Mei
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Steve Simpson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.,Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Anne-Louise Ponsonby
- Murdoch Children's Research Institute, The University of Melbourne, Melbourne, Victoria, Australia
| | - Robyn M Lucas
- National Centre for Epidemiology and Population Health, Research School of Population Health, College of Medicine, Biology and Environment, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Prudence Tettey
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.,School of Public Health, University of Ghana, Accra, Ghana
| | - Jac Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Karam Kostner
- Mater Hospital, University of Queensland, Brisbane, Queensland, Australia
| | - Bruce V Taylor
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
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Manouchehri N, Zhang Y, Salter A, Hussain RZ, Hartung HP, Hemmer B, Linker R, Segal BM, Cutter G, Stüve O. Clinical trials in multiple sclerosis: potential future trial designs. Ther Adv Neurol Disord 2019; 12:1756286419847095. [PMID: 31205492 PMCID: PMC6535717 DOI: 10.1177/1756286419847095] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 03/29/2019] [Indexed: 12/13/2022] Open
Abstract
Clinical trials of new treatments in multiple sclerosis (MS) currently require large sample sizes and long durations in order to yield reliable results. The differential responses of an already heterogeneous population of MS patients to individual disease-modifying therapies (DMTs) will further complicate future trials. MS trials with smaller samples and faster outcomes are conceivable through the substitution of current clinical and MRI outcomes with objectively measureable genomic and proteomic biomarkers. Currently, biomarkers that could be utilized for diagnosis and monitoring of MS disease activity are in the early validation phase. The power of single biomarkers or multiple correlated biomarkers to predict prognosis and response to treatment could initially be compared with currently accepted methods. These prospectively validated disease biomarkers could then be used to subcategorize the spectrum of MS patients into a finite number of endophenotypes with demonstrable different molecular pathogeneses and DMT response profiles. Newly developed DMT could potentially be assessed within specific endophenotypes and compared with pharmacogenomically relevant active comparator DMT. This approach may increase the efficiency of MS trials through homogenization of patient population and minimization of nonresponders in study groups, providing the potential for the development of targeted therapies.
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Affiliation(s)
- Navid Manouchehri
- Department of Neurology and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, TX
| | - Yinan Zhang
- Department of Neurology and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, TX
| | - Amber Salter
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO
| | - Rehana Z Hussain
- Department of Neurology and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, TX
| | - Hans-Peter Hartung
- Department of Neurology, UKD and Center for Neurology and Neuropsychiatry, LVR Klinikum, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Germany
| | - Ralf Linker
- Department of Neurology, University of Regensburg, Germany
| | | | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL
| | - Olaf Stüve
- Neurology Section, VA North Texas Health Care System, Medical Service, 500 South Lancaster Rd., Dallas, TX 75216, USA Department of Neurology and Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, TX Department of Neurology, Klinikum rechts der Isar, Technische Universität München, Germany
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